National Academies Press: OpenBook

WIC Nutrition Risk Criteria: A Scientific Assessment (1996)

Chapter: 4 Anthropometric Risk Criteria

« Previous: 3 Principles Underlying the Nutrition Risk Criteria for WIC Eligibility
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 67
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 68
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 69
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 70
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 71
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 72
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 73
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 74
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 75
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 76
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 77
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 78
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 79
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 80
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 81
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 82
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 83
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 84
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 85
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 86
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 87
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 88
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 89
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 90
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 91
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 92
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 93
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 94
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 95
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 96
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 97
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 98
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 99
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 100
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 101
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 102
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 103
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 104
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 105
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 106
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 107
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 108
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 109
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 110
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 111
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 112
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 113
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 114
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 115
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 116
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 117
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 118
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 119
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 120
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 121
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 122
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 123
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 124
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 125
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 126
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 127
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 128
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 129
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 130
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 131
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 132
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 133
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 134
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 135
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 136
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 137
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 138
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 139
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 140
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 141
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 142
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 143
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 144
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 145
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 146
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 147
Suggested Citation:"4 Anthropometric Risk Criteria." Institute of Medicine. 1996. WIC Nutrition Risk Criteria: A Scientific Assessment. Washington, DC: The National Academies Press. doi: 10.17226/5071.
×
Page 148

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

ANTHROPOMETRIC RISK CRITERIA 67 4 Anthropometric Risk Criteria This chapter provides information about anthropometric characteristics of women, infants, and children that are used to place them in Priorities I through III in the WIC program (biochemical and other medical risk criteria in Priorities I through III are in Chapter 5). It begins with a consideration of the use of reference anthropometric measures. Then, it covers anthropometric criteria used for pregnant or postpartum women, followed by risk criteria used for infants and children. For each risk criterion, available information is provided about the prevalence of the condition in the population eligible for participation in the WIC program, use of each criterion as an indicator of risk and a predictor of benefit, and cutoff points in use in WIC programs nationwide. A summary of anthropometric risk criteria used by state WIC agencies appears in Table 4-1. USE OF ANTHROPOMETRIC MEASURES IN THE WIC PROGRAM The major uses of anthropometric measures in the WIC program are twofold: (1) to screen women, infants, and children with nutrition risks for certification to participate in the program and (2) to assess their responses to interventions over time. Their use to assess individuals has several implications for interpreting results and choosing cutoff points. First, a woman or child's position relative to the reference standard for the anthropometric measure being evaluated, whether it is expressed as a percentile or a z-score, represents a statement of the probability that the individual is part of the healthy distribution (also called specificity). It is not a statement about the probability that the mother or child is unhealthy. The farther away a

ANTHROPOMETRIC RISK CRITERIA 68 measurement is from the central part of the distribution of healthy individuals, the greater the likelihood that it indicates health and nutrition disorders. As described in Chapter 3, yield for a given cutoff point increases with prevalence. If the assessed population were exactly the same as the healthy reference population, then one would expect, for example, that 5 percent of children would have heights at or below the 5th percentile. If a screened population has TABLE 4-1 Summary of Anthropometric Risk Criteria in the WIC Program and Use by States States Using Postpartum Women Pregnant Lactating Nonlactating Infants Children Women Women Prepregnancy 54 18 15 — — underweight Low maternal 53 — — — — weight gain Maternal weight 33 — — — — loss during pregnancy Prepregnancy 53 17 12 — — overweight High gestational 37 38 15 — — weight gain Maternal short 0 1 1 — — statue Postpartum — 43 43 — — underweight Postpartum — 42 39 — — overweight Infants and Children Low birth weight — — — 53 8 Small for — — — 10 — gestational age Short statute — — — 48 50 Underweight — — — 53 52 Low head — — — 7 — circumference Large for — — — 14 — gestational age Overweight — — — 53 49 Failure to thrive — — — 30 27 NOTE: Dashes indicate criterion was not used for that subgroup. SOURCE: Adapted from USDA (1994).

ANTHROPOMETRIC RISK CRITERIA 69 an excess of children with height-for-age below a cutoff point (e.g., 10 percent below the 5th percentile), one could assume that at least the difference (10 minus 5 equals 5 percent) represents short stature resulting from environmental causes, including diet. Most anthropometric measurements that are below the 5th or the 10th percentile or above the 95th percentile are considered abnormal. These statistical cutoffs define the central 85 or 90 percent of the reference distribution as the normality range. For some anthropometric measures, such as maternal weight gain, recommended cutoffs reflect an even smaller portion of the distribution. These cutoffs do not truly define the normal range from a health or nutrition point of view; rather, they are used as a guide to facilitate clinical assessment (IOM, 1990). It is impossible to find a cutoff that has both the highest sensitivity and the highest yield (Rasmussen and Habicht, 1989), as discussed in Chapter 3. When interventions have no adverse effects, the choice of cutoff points for defining risk depends mainly on the available resources and the priorities to be addressed. However, if factors causing decreased nutrition status tend to affect all mothers or children in the population, all individuals can be assumed to be malnourished (Keller, 1988; Yip, 1993), and selection of a specific cutoff point may be irrelevant. Experience shows that in populations with high prevalences of both short stature and underweight children, major causes of such abnormalities are usually health and nutrition. Likewise, low maternal prepregnancy weight or weight gain in pregnancy may result from a variety of factors, but populations with high prevalences of both are often malnourished. Although anthropometry has widely been used as a measure of or proxy for various conditions related to health and nutrition, abnormal anthropometric measures themselves do not provide specific etiologic information. For example, a child may be abnormally short because of infection, inadequate food intake, psychological disorders, endocrine or metabolic diseases, or simply normal variation in a population. Finally, although most anthropometric criteria are able to predict some present or future risk, they may not be indicative of a possible response to or benefit from participating in the WIC program. Indicators of risk and indicators of benefit are not always identical. As discussed in Chapter 3, for the best use of WIC program resources, one should use benefit indicators and cutoff points to target services to those individuals who are likely to benefit. For most anthropometric criteria, a positive response can be viewed as a benefit from participation in the WIC program. All the anthropometric measurements covered in this chapter are practical and can be obtained with reliability in the WIC program setting with adequate training of personnel, periodic quality assurance reviews, and use of appropriate equipment that is calibrated regularly.

ANTHROPOMETRIC RISK CRITERIA 70 MATERNAL ANTHROPOMETRIC RISK CRITERIA A summary of anthropometric risk criteria as predictors of risk and benefit for pregnant and postpartum women appears in Table 4-2. Prepregnancy Underweight Prepregnancy underweight is defined as a prepregnant weight below a certain cutoff point based on reference data of desirable weights for nonpregnant women of the same height. Weight alone is not a very sensitive measure of maternal body size: at the same weight, a tall woman may be underweight, while a short woman, overweight (IOM, 1990). Thus, weight-for-height status is a better way of assessing women for poor health and nutritional status, although still crude and indirect. The lower a woman's weight-for-height, the more likely it is that she is undernourished (IOM, 1990). Maternal prepregnancy weight-for-height is usually defined in one of two ways: (1) weight below a designated percentage of a reference standard or (2) body mass index (BMI = kg/m2) below a specified cutoff. Although reference standards for women have not been validated specifically in relation to reproduction, prepregnancy underweight has been defined as less than 90 percent of the 1959 Metropolitan Life Insurance weight value for a given height

ANTHROPOMETRIC RISK CRITERIA 71 (ideal body weight, or IBW), which is equivalent to a BMI of less than 19.8 (IOM, 1990). This definition has been widely adopted in the United States (e.g., ACOG, 1993; Wilcox and Marks, 1995) and is used in this chapter unless otherwise noted. Prevalence of and Factors Associated with Prepregnancy Underweight Underweight may be associated with poverty, substandard living conditions, inadequate food intake, chronic or infectious diseases, or conditions that induce malabsorption of nutrients (IOM, 1990). Using the above cutoff value, 20 percent of the low-income women included in the 1990 Pregnancy Nutrition Surveillance System (PNSS) data set were underweight, and 6 percent of these PNSS women were classified as being very underweight (BMI < 18.0) (Wilcox and Marks, 1995). The percentage of underweight women decreased as age increased, with the highest prevalence of underweight observed among Asian women (Wilcox and Marks, 1995). White adolescents, in particular, may routinely attempt to limit their body weights by restricting their dietary intakes and exercising excessively (Larson, 1991). Substance abuse is also associated with low prepregnancy weight-for-height (Johnson et al., 1994). However, some women may be healthy and well nourished, but simply lean. In a study of about 600 WIC program participants in California who were followed through two consecutive pregnancies, the most important factor predicting a low prepregnancy weight-for-height at the beginning of the second pregnancy was low prepregnancy weight in the first pregnancy (Caan et al., 1987). As household size increased, the risk of prepregnancy underweight decreased. Maternal age was inversely associated with prepregnancy underweight, and black race was associated with increased risk, but these findings did not quite reach statistical significance (p < .07 and p < .09, respectively). Prepregnancy Underweight as an Indicator of Nutrition and Health Risk Compared with women with normal weight-for-height, women with low prepregnancy weight-for-height are at higher risk for low-birth-weight (LBW) infants (Brown and Schloesser, 1990; Elkblad and Grenman, 1992; IOM, 1990; Nandi and Nelson, 1992; WHO, 1995), retarded fetal growth (Abrams, 1991; Elkblad and Grenman, 1992; Kramer, 1987a, b), and perinatal mortality (Hogberg et al., 1990; IOM, 1990). Some studies have found that prepregnancy underweight is associated with a higher incidence of various pregnancy complications, such as antepartum hemorrhage, premature rupture of membranes, anemia, endometritis (IOM, 1992b), and cesarean delivery (Elkblad and Grenman, 1992), but the small number of studies examining this question limits the ability to draw inferences.

ANTHROPOMETRIC RISK CRITERIA 72 The relationship between maternal underweight and preterm delivery (delivery before 37 weeks' gestation) is controversial, with some reports concluding that the relationship is strong and others finding no significant association (Berkowitz and Papiernik, 1993). The committee could find no studies assessing whether prepregnancy underweight is associated with increased risk for poor lactational performance or poor health during the postpartum period. This is a complicated question to address, because it is also necessary to consider the potential mediating influence of gestational weight gain. Prepregnancy Underweight as an Indicator of Nutrition and Health Benefit Data from several food supplementation trials have demonstrated that intervention to improve nutrition can increase birth weight in underweight women (Edozien et al., 1979; IOM, 1990). Two evaluations of the Missouri WIC program separately examined the impact of WIC program participation in underweight women. Schramm (1986) reported that participants who were at least 15 percent underweight before pregnancy had significantly lower Medicaid paid claims for newborn medical services than did nonparticipants. However, using another sample of Missouri WIC participants, Stockbauer (1987) reported that WIC program participation was not associated with significantly lower rates of LBW in women who began pregnancy at least 10 percent underweight. Neither of these studies adjusted for gestational weight gain. Providing WIC program benefits to underweight women is likely to reduce the rate of LBW even if only a subset of underweight women respond, because prepregnancy underweight is a prevalent condition among low-income American women. In the study by Caan and colleagues (1987), receiving WIC program benefits after the first pregnancy was associated with a decreased risk of maternal underweight, but this finding was not statistically significant. Results of recent studies suggest that maternal underweight may be associated with poor fetal growth because of poor plasma volume expansion early in pregnancy (Rosso et al., 1992) or because of interaction among low prepregnancy weight, psychosocial stress, and cigarette smoking (Cliver et al., 1992). With improved understanding of the complex mechanisms by which maternal underweight influences fetal growth, it may become possible to target those underweight women who will readily benefit from WIC program participation. The committee identified no data addressing the efficacy of maternal prepregnancy underweight as a nutrition risk indicator for either breastfeeding or postpartum nonlactating women. Since gestational weight gain may change a woman's weight category after delivery, postpartum weight-for-height is a more relevant indicator of maternal nutritional status for lactating or postpartum women.

ANTHROPOMETRIC RISK CRITERIA 73 Use of Prepregnancy Underweight as a Nutrition Risk Criterion in the WIC Setting Table 4-1 summarizes the extent to which prepregnancy underweight is used as a nutrition risk criterion by the WIC program. The ideal weight-for-height cutoffs ranged from 85 to 95 percent. Recommendations for Prepregnancy Underweight The risk of prepregnancy underweight is well documented for pregnant women but not for postpartum women. There is both empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends use of maternal prepregnancy underweight as a nutrition risk criterion for pregnant women by the WIC program, with a cutoff value of 90 percent of IBW or a BMI less than 19.8. The committee recommends discontinuation of the use of maternal prepregnancy underweight as a nutrition risk criterion for postpartum women by the WIC program. The committee recommends research to determine the cutoffs for underweight that would produce the highest yield for reproductive outcomes and to improve the ability to distinguish healthy, well-nourished, slender women from women who are underweight because of poor nutrition or other factors that could be ameliorated through WIC program participation. The committee also recommends studies to examine interventions aimed at improving maternal health, lactation performance, or other postpartum outcomes for women who had low prepregnancy weight-for-height. Low Maternal Weight Gain Low maternal weight gain is often defined in relation to the lower limits of the Institute of Medicine's (IOM) BMI-specific total weight gain recommendations: less than 12.5 kg for women who begin pregnancy with a low BMI (< 19.8), less than 11.5 kg for women with a normal BMI (19.8–26.0), and less than 7 kg for those with a high BMI (> 26.0 to 29.0) or obese BMI (> 29.0) (IOM, 1990). Because total gain is not known until delivery, weight gain during the second and third trimesters is substituted. The IOM (1990) recommended cutoffs of less than 0.45 kg/month in obese women and less than 0.9 kg/month in nonobese women. These recommendations, as well as ''provisional" weight gain grids, were provided with the acknowledgment that validated data on which to provide confident recommendations were not available. A slightly lower than recommended gain is not necessarily a problem, provided that weight gain appears to progress toward the BMI-specific target (IOM, 1990). Before intervening, further evaluation is recommended to rule out measurement

ANTHROPOMETRIC RISK CRITERIA 74 error, assess health and nutrition status, and consider other possible explanations for the low gain. Little is known about the prevalence of a low maternal weight gain assessed during gestation, but approximately 39 percent of the women included in the 1990 PNSS had a total gain that was less than the lower limit recommended for their prepregnant BMI category (Wilcox and Marks, 1995). Prevalence of and Factors Associated with Low Maternal Weight Gain The published literature consistently shows that maternal weight gain is highly variable. A low gestational weight gain occurs most commonly among women with a high prepregnancy BMI, especially those who are obese (IOM, 1990). This lower gain may reflect intentional weight restriction on the part of the mother, but low rates of weight gain also occur in settings in which all women were encouraged to gain weight (Taffel et al., 1993). Conversely, many other obese women experience high rates of gestational weight gain. Among married mothers delivering live singleton infants who participated in the 1980 National Natality Survey, a total maternal weight gain of less than 6.8 kg was associated with maternal short stature, cigarette smoking, black race, Hispanic ethnicity, low levels of maternal education, and high maternal BMI (IOM, 1990; Kleinman, 1990). Southeast Asian background, young maternal age (within 2 years of menarche), multiparity, unmarried status, and low-income have also been associated with an increased risk of low total maternal weight gain in U.S. women (IOM, 1990). Physical activity, work outside the home, stress, or moderate alcohol use appear to have little effect on gestational weight gain in U.S. women (IOM, 1990), but data are limited. The 1990 PNSS reported that Asian and American-Indian women were the ethnic/racial groups most likely to have a low total gestational weight gain, but maternal age was not a risk factor for a low weight gain (Wilcox and Marks, 1995). The use of illegal drugs, especially cocaine, is associated with low maternal weight gain (Petitti and Coleman, 1990). The literature does not give a clear answer as to whether cigarette smokers tend to gain less weight than nonsmokers during pregnancy (Johnston, 1991). Data are not available to assess whether older age (> 35 years) affects weight gain beyond the contributions of increased parity or BMI. One report on the determinants of weight gain in a small group of black adolescents concluded that delayed enrollment in the WIC program (late in pregnancy) and consumption of less than three snacks per day were significant predictors of a slow gestational weight gain (Stevens-Simon and McAnarney, 1992). Recent results from a multiethnic cohort study of about 10,000 pregnancies concluded that maternal height, hypertension, cesarean delivery, and fetal size

ANTHROPOMETRIC RISK CRITERIA 75 were positively associated with the maternal weight gain in each of the three trimesters. However, association with weight gain differed by trimester for prepregnancy body size, age, parity, smoking status, race/ethnicity, and diabetes mellitus (Abrams et al., 1995). The most important predictors of weight gain were maternal age and Asian race or ethnicity in the first trimester; prepregnant body mass, parity, and height in the second trimester; and hypertension, age, and parity in the third trimester. Low Maternal Weight Gain as an Indicator of Nutrition and Health Risk The IOM (1990) concluded that low maternal weight gain during the second and third trimester is a determinant of fetal growth, and that low maternal gain is associated with smaller average birth weights and an increased risk of delivering an infant with fetal growth restriction. Studies published since that report confirm this finding (Hickey et al., 1993; Parker and Abrams, 1992; Scholl et al., 1990a). In the recently conducted World Health Organization (WHO) collaborative meta-analysis of studies from populations around the world, low maternal weight gain or low maternal attained weight at 20, 28, or 36 weeks' gestation was associated with increased risk of fetal growth restriction or an infant small for gestational age (SGA). Odds ratios were especially high for women with low prepregnancy weights (WHO, 1995). Attained weights at 20, 28, and 36 weeks predicted LBW and SGA with reasonable sensitivity (at least 35 percent) and odds ratios of about 2.5 (WHO, 1995). However, two studies of presumably well-nourished clinic populations reported that low total maternal weekly weight gain (Dawes and Grudzinskas, 1991a) or deviation from an "optimal curve" (Theron and Thompson, 1993) had relatively low specificity and yields as predictors of SGA. Low yields are not surprising given that fetal growth is multifactorial, and total maternal weight gain by healthy pregnant women with good pregnancy outcome is highly variable (Abrams and Parker, 1990). The relationship between low maternal weight gain and small fetal size is modified by maternal prepregnancy BMI. At high BMIs, a low maternal weight gain has less impact. However, there is also evidence that a low maternal weight gain (< 6.8 kg) is associated with an increased risk of delivering infants who are SGA (Parker and Abrams, 1992). Thus, low rates of gestational weight gain remain a concern, even among obese women. Overall, women with both a low gestational weight gain and a low prepregnancy BMI are at highest risk for delivering a low-birth-weight infant. Studies of preterm delivery usually express total weight gain as a rate of weight gain (total gain/gestational age) to adjust for gestation. Although several studies suggested that a low weekly rate of maternal weight gain throughout pregnancy is associated with early spontaneous delivery, the data could be

ANTHROPOMETRIC RISK CRITERIA 76 considered only suggestive, especially given difficulties in accurately determining gestational age (IOM, 1990). Studies published in the 1990s tend to support a relationship between low rate of maternal weight gain and preterm birth (Hickey et al., 1995; Kramer et al., 1992; Siega-Riz et al., 1994; Wen et al., 1990; WHO, 1995). Effects of the specific pattern of maternal weight gain on fetal size or preterm delivery are under study. Some investigators provide evidence that a low maternal weight gain early in pregnancy is significantly related to low-birth- weight infants (Scholl et al., 1990a) and infants who are SGA (Abrams and Newman, 1991); others do not agree (Dawes and Grudzinskas, 1991b; Petitti et al., 1991). A recent study of almost 3,000 white women concluded that, after controlling for total maternal weight gain and other factors, a low gestational weight gain during the second trimester was associated with decreased birth weight (Abrams and Selvin, 1995). At least three studies suggest that a low rate of maternal weight gain late, but not early, in pregnancy is associated with spontaneous preterm delivery (Abrams et al., 1989; Hediger et al., 1989; Hickey et al., 1995). Some studies have also found associations of a low maternal weight gain with neonatal complications. A study of low-income, black adolescents reported that a slow rate of maternal weight gain (< 0.23 kg per week) was associated with longer infant hospital stays, more admissions to the neonatal intensive care units, and more antibiotic treatments (Stevens-Simon and McAnarney, 1992). Fetal or infant mortality appears to be higher in women with low rates of weight gain (Hogberg et al., 1990), and the relationship is particularly strong in women with low prepregnancy weights-for-height (IOM, 1992b; Johnson, 1991). It is postulated that nutrition during pregnancy may play a role in the development of long-term health conditions in the offspring during childhood or adulthood. In support of this, Godfrey and co-workers (1994) found that a low maternal triceps skinfold thickness at 15 weeks of gestation and a low weight gain from 15 to 35 weeks of gestation were associated with higher blood pressure in the offspring at about 11 years of age. This is an area of active investigation. Maternal weight gain may relate to other health outcomes in pregnancy or postpartum, but few data have been published. A Finnish study reported that women with low gestational weight gain (< 5 kg) had fewer deliveries requiring surgery and a shorter second stage of labor (Elkblad and Grenman, 1992). Little is known about the effects of low rates of gestational weight gain on spontaneous abortion, congenital malformations, maternal complications, or the long-term health of the mothers. Gestational weight gain does not appear to be associated with the volume or composition of breast milk for women residing in industrialized countries (Dewey et al., 1991a; IOM, 1990). However, a recent study of well-nourished lactating Danish women reported that women who gained more than 17 kg produced milk with a much higher fat concentration

ANTHROPOMETRIC RISK CRITERIA 77 than did women with a low (< 11 kg) prenatal weight gain (Michaelson et al., 1994). Low Maternal Weight Gain as an Indicator of Nutrition and Health Benefit Studies to examine whether low maternal weight gain is a useful indicator of nutrition and health benefit are hindered by problems in study methodology, difficulties in estimating dietary intake accurately, and low statistical power (IOM, 1990). The great variability among women in such characteristics as energy requirements, physical activity, body size, and health practices also complicates understanding of the relationship. Most experimentally designed studies have been conducted in developing countries and have demonstrated that dietary supplementation can improve infant birth weight, especially in women with the poorest nutritional status (IOM, 1990). However, relatively few experimental nutrition supplementation trials have specifically examined effects of such supplementation on maternal weight gain. Although the results of those studies tend to show that supplementation improves both maternal weight gain and infant birth weight, results have been inconclusive. Furthermore, the link between energy supplements and gestational weight gain is weaker among women in industrialized countries, presumably because of lesser degrees of malnutrition before and during pregnancy. Observational studies have reported on the relationship between dietary intake and maternal weight gain, with conflicting results (IOM, 1990). Gestational weight gain, but not dietary intake, was strongly associated with birth weight in a study of 529 primarily white, middle-class women (Aaronson and Macnee, 1989). No statistically significant relationships between dietary intake and birth weight were detected in a recent study of black inner-city women (the relationship between diet and weight gain was not reported) (Johnson et al., 1994). In pregnant adolescents, Scholl and colleagues (1991) reported a significant association between energy intake early in pregnancy and total weight gain. They also reported a relationship between gestational weight gain and infant birth weight, but the relationship between energy intake and birth weight was not significant. Kramer (1993) reported only slight effects of protein and energy intake on maternal weight gain. However, Susser's review of data from the Dutch famine and supplementation trials concluded that dietary influences on birth weight appear to bypass gestational weight gain (Susser, 1991). Of the three WIC program evaluations that have reported on the program's impact on maternal weight gain, two suggest a positive effect. The first National WIC Evaluation (Edozien et al., 1979) showed associations between food supplementation of more than 3 months and increases in both maternal weight

ANTHROPOMETRIC RISK CRITERIA 78 gain and birth weight. Results of the second National WIC Evaluation (Rush et al., 1988c) suggested that WIC supplemented mothers consumed more energy and gained more weight; although birth weight was not improved overall, fetal head circumference was greater. Of special note is the significant finding in this study that WIC program participation reversed initial low maternal weight gain identified at the time of the first visit to the WIC program. WIC program participation was also associated with lower maternal fat stores late in pregnancy. Newer evidence suggests that maternal fat mobilization in late pregnancy reflects improved fetal growth (Hediger et al., 1994). The single randomized controlled trial of the WIC program, which has been criticized for its small sample size (Kramer, 1993), did not show improvements in either maternal weight gain or birth weight with WIC program participation overall, but improvements were observed in smokers and members of other higher-risk subgroups (Metcoff et al., 1985). In addition to providing food supplements, the WIC program also provides education with the objective of improving maternal anthropometric status and infant outcomes. Observational studies have correlated advice about weight gain with actual prenatal weight gain (Taffel et al., 1993) and dietary counseling and milk vouchers with improved dietary scores (Mendelson et al., 1991). A recent meta-analysis identified only three experimental trials assessing the impact of providing maternal education or counseling with the goal of increasing maternal energy or protein intake (Kramer, 1993). The single study that specifically evaluated gestational weight gain as an outcome reported that those who received nutrition education gained on average 1 kg more than those who did not. There was not a significant increase in birth weight in this study, possibly because the study subjects were not at nutritional risk. In another critical review of the experimental studies of nutrition education during pregnancy, it was determined that the literature was so sparse and poorly designed that it was difficult to determine whether interventions were effective (Boyd and Windsor, 1993). Nonetheless, increases in the official recommendations for weight gain during pregnancy in the United States have been accompanied by a 50 percent increase in the average amount of weight gained by pregnant women (IOM, 1990). Thus, practical experience suggests that pregnant women respond to the advice that they are given.

ANTHROPOMETRIC RISK CRITERIA 79 Use of Low Maternal Weight Gain as a Nutrition Risk Criterion in the WIC Setting Definitions of inadequate weight gain during pregnancy vary widely among the 53 state WIC agencies (see Table 4-1) that use this risk criterion. Specified cutoff values for rate of weight gain range from 0.7 kg per month to 1.8 kg per month in the last two trimesters. Some states compare pattern of gain against a weight gain chart (presumably similar to that recommended by the IOM). Recommendations for Low Maternal Weight Gain The risk of low maternal weight gain is well documented in pregnant women. There is both empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends use of low maternal weight gain as a nutrition risk criterion for pregnant women by the WIC program, with the IOM cutoff values of < 0.9 kg/month in nonobese women and < 0.45 kg/month in obese women. The committee also recommends research to define low weight gain throughout gestation in relation to reproductive and longer-term outcomes, its yield as a indicator of risk, and its response to WIC program intervention. Maternal Weight Loss During Pregnancy Weight loss can occur any time during a pregnancy. A woman can have a net loss by the time she delivers, or her weight can fluctuate up and down periodically. Prevalence of and Factors Associated with Maternal Weight Loss During Pregnancy Although it is uncommon for a women to experience a net loss in weight by the time that she delivers, it is not uncommon for a woman to lose some weight, especially during the first trimester. No data are available on the prevalence of this occurrence. Maternal Weight Loss During Pregnancy as an Indicator of Nutrition and Health Risk Most of the studies that examine weight loss during pregnancy do so in women experiencing hyperemesis gravidarum (severe nausea and vomiting of pregnancy). Gross and colleagues (1989) found that women who lost more than

ANTHROPOMETRIC RISK CRITERIA 80 5 percent of their prepregnancy weight in the first trimester had lower total weight gains, were more likely to deliver by cesarean section, and had infants who had lower mean birth weights and more growth retardation. The study's findings are interesting but should be viewed with caution because the sample size was small (64) and the analyses were bivariate. Maternal Weight Loss During Pregnancy as an Indicator of Nutrition and Health Benefit The committee could identify no studies examining interventions to address maternal weight loss. Weight loss may indicate underlying dietary or health practices or health or social conditions that could be improved by the supplemental food, nutrition education, and referrals provided by the WIC program. Use of Maternal Weight Loss During Pregnancy as a Nutrition Risk Criterion in the WIC Setting Of the 33 state WIC agencies that reported using weight loss as a nutrition risk criterion (see Table 4-1), the most common cutoff values were any weight loss or weight falling below the self-reported prepregnancy weight. Recommendation for Maternal Weight Loss During Pregnancy The risk of weight loss during pregnancy is documented. There is a theoretical basis for pregnant women to benefit from participation in the WIC program. Therefore, the committee recommends use of weight loss during pregnancy as a risk criterion for pregnant women by the WIC program, with a cutoff value of greater than 2 kg during the first trimester and greater than 1 kg during the second or third trimesters. Prepregnancy Overweight The definitions used to define excess body weight vary substantially throughout the scientific literature and in clinical and public health practice. The terms obesity and overweight are often used interchangeably to describe a high weight-for-height. The IOM (1990) defined overweight as a BMI range of 26 to 29 kg/m2 (consistent with 120 to 135 percent of the 1959 Metropolitan Life Insurance Company weight-specific tables) and obesity as a BMI of > 29 kg/m2 (consistent with > 135 percent of IBW on the basis of the same reference).

ANTHROPOMETRIC RISK CRITERIA 81 Prevalence of and Factors Associated with Prepregnancy Overweight Data from the third National Health and Nutrition Examination Survey (NHANES III; 1988–1991) indicate that with a BMI cutoff of 27.3 kg/m2, 20 and 34 percent of women age 20 to 29 and 30 to 39 years, respectively, were overweight (Kuczmarski et al., 1994). Furthermore, comparison of these data with findings from previous national surveys showed a dramatic trend upward. For example, by using the same definition of overweight for all surveys, the prevalence of overweight among women 20 to 29 years of age was only 10 percent in 1960–1962, but it increased to 13 percent in 1971–1974 and then to 15 percent in 1976–1980. Obesity is especially common among minority women and is associated with lower levels of education, lower income, and increasing age (Flegal et al., 1988). Data from the 1990 PNSS indicate that 29 percent of the low-income women had a prepregnancy BMI greater than 26.0 kg/m2, and 19 percent were classified as very overweight (BMI > 29.0 kg/m2) (Wilcox and Marks, 1995). Older women and American-Indian women were most likely to be overweight. Another report of PNSS data from 1990 and 1991 indicated that very overweight (BMI > 29 kg/m2) women were more likely to be black and older than 35 years and were less likely to report smoking or alcohol use than women who were of normal weight or overweight (Cogswell et al., 1995). In a study of about 600 WIC program participants in California who were followed through two consecutive pregnancies, the following characteristics were significantly associated with increased risk of beginning the second pregnancy with a high maternal prepregnancy weight-for-height (> 120 percent of IBW): high prepregnancy weight-for-height during the first pregnancy, high birth weight of the first infant, and large number of individuals in the household. In that multiethnic study, Southeast Asian and black mothers were at lower risk of high second prepregnancy weight (Caan et al., 1987). Prepregnancy Overweight as an Indicator of Nutrition and Health Risk Although consistent evidence indicates that, on average, obese women have larger babies than women of lower weight-for-height, they are at substantially increased risk of delivering macrosomic infants (Larsen et al., 1990), a condition accompanied by higher risks of shoulder dystocia and morbidity in the mother or fetus (Elkblad and Grenman, 1992; IOM, 1990; Issacs et al., 1994; Perlow et al., 1992). The risk of delivering LBW infants is controversial for obese women. Some studies suggest that obesity is protective against LBW (Johnson et al., 1992); others report risks comparable to those in nonobese women; and still others suggest that obesity is associated with increased risk for

ANTHROPOMETRIC RISK CRITERIA 82 delivering growth-retarded infants (Perlow et al., 1992), especially if gestational weight gain is low (Hickey et al., 1993; Parker and Abrams, 1992). Relatively few studies have assessed the relationship between maternal obesity and the risk of spontaneous preterm delivery. Siega-Riz and colleagues (1994) noted a clear but nonsignificant trend toward a decreased risk of preterm delivery with increasing BMI. However, in the Collaborative Perinatal Project, Naeye (1990) found obese women to be at increased risk for preterm delivery and for higher perinatal mortality rates. Other investigators (Abrams and Parker, 1988; Lucas et al., 1988; Rahaman et al., 1990; Taffel, 1986) also reported higher perinatal mortality rates among obese mothers. Using data from the National Natality Survey, Little and Weinberg (1993) found that obesity was more strongly related to stillbirth in the intrapartum period (during labor and delivery) than in the antenatal period (before labor), perhaps because of the mechanical problems of delivery. Gestational diabetes, non-insulin-dependent diabetes mellitus, and hypertension are significantly more likely in obese women (Issacs et al., 1994; Perlow et al., 1992; Ratner et al., 1991). Obese women may also be at increased risk for developing preeclampsia (Eskenazi et al., 1991; Sibai et al., 1995). Labor and delivery complications are more common among overweight women than among their normal weight counterparts (Elkblad and Grenman, 1992; IOM 1990, 1992b). Most studies report a two- to threefold risk for cesarean delivery among overweight women (Elkblad and Grenman, 1992; Issacs et al., 1994; Perlow et al., 1992; Ratner et al., 1991; Witter et al., 1995), and several studies have reported a statistically significant increase in the number of infections such as endometritis (Issacs et al., 1994; Perlow et al., 1992). Maternal obesity may be associated with an increased risk for major congenital malformations (undefined, in aggregate) (Naeye, 1990). A recent study also suggested that obese women had twice the risk of delivering children with neural tube defects and certain other major birth defects (Waller et al., 1994). Prepregnancy overweight is thought to be a risk factor for postpartum retention of prenatal weight gain (Parker, 1994). In the 1988 National Maternal and Infant Health Survey, 20 percent of women with normal prepregnancy weight-for-height reported that they retained the weight they gained during pregnancy (defined as > 4 kg at 10 to 18 months postpartum), whereas 38 percent of the women whose prepregnancy weight-for-height was classified as overweight reported retaining their prenatal weight gain (Keppel and Taffel, 1993).

ANTHROPOMETRIC RISK CRITERIA 83 Prepregnancy Overweight as an Indicator of Nutrition and Health Benefit Although several dietary intervention studies have been conducted with the goal of restricting maternal food intake and minimizing weight gain and excessive fetal size, the safety and effectiveness of this approach are questionable (Abrams, 1988). Clinical trials of energy and protein restriction among women who have either a high weight-for-height or a high gestational weight gain have produced nonsignificant results, in opposite directions (Kramer, 1993). Two small studies have demonstrated that overweight women can be motivated to change their diets, but neither study had a control group (Dornhurst et al., 1991; Mendelson et al., 1991). Participation in the WIC program has been associated with significantly lower rates of LBW in overweight women (> 120 percent IBW) (Stockbauer, 1987). However, Schramm (1986) reported that WIC program participation was not associated with significantly lower Medicaid claims for newborns among women who began pregnancy at > 120 percent of their IBW. Virtually no studies have been published with the explicit objective of evaluating how WIC program participation affects maternal obesity. However, a study in California comparing women participating in the WIC program who received food supplementation during two consecutive pregnancies found that women who received supplementation for 5 to 7 months postpartum had half the risk of being overweight of those who received supplementation only briefly (Caan et al., 1987). Although the study was observational rather than experimental, it was very well designed. The investigators attributed the finding to supplementation with more nutrient-rich foods from the WIC program—an action that might reduce the consumption of inexpensive, high-calorie, low nutrient foods. A technology assessment panel for the National Institutes of Health concluded that most people desiring to lose and control weight need to make a lifelong commitment to changes in lifestyle, dietary practices, and behavioral responses (NIH Technology Assessment Conference Panel, 1992). Current guidelines for prenatal care call for individualized nutrition counseling for obese mothers. The objective is to promote adequate nutrient intake and maternal weight gain to meet the needs of the growing fetus while minimizing the risk of increasing obesity in the mother (IOM, 1992a). The receipt of nutritious foods, counseling, and education through the WIC program both before and after delivery, with or without lactation, has the potential to modify diet and activity patterns and thereby to reduce long-term obesity.

ANTHROPOMETRIC RISK CRITERIA 84 Use of Prepregnancy Overweight as a Nutrition Risk Criterion in the WIC Setting Table 4-1 summarizes the extent to which prepregnancy overweight is used as a nutrition risk criterion. Most states used a cutoff point of 120 percent of IBW for height, but the range for cutoff points went from a low of 110 percent to a high of 150 percent of IBW. Recommendations for Prepregnancy Overweight The risk of prepregnancy overweight is well documented for pregnant and postpartum women. There is both empirical evidence and a theoretical basis for benefit from WIC program participation. Therefore, the committee recommends use of prepregnancy overweight as a nutrition risk criterion for pregnant and postpartum women by the WIC program, with the cutoff values of BMI greater than 26. To improve potential for benefit from WIC program participation, the committee recommends research on culturally appropriate methods of effective intervention for obese women. High Gestational Weight Gain Definitions of excessive gestational weight gain that depend on knowledge of total weight gain are not practical in the WIC setting. There are no scientifically determined definitions of high weight gain at various points of pregnancy that are linked to reproductive or other health outcomes. The IOM (1990) recommended that a gain of more than 3 kg per month be considered potentially excessive, especially if it occurs during the second half of pregnancy. However, it is important to rule out other explanations (e.g., measurement error, fluid changes, multiple gestation) before concluding that excessive weight gain resulted from problems related to nutrient intake and energy balance. Prevalence of and Factors Associated with High Gestational Weight Gain Data from the 1990 PNSS indicate that 33 percent of these low-income women had total gestational weight gains that surpassed the upper limit of that recommended for their prepregnancy BMI category (Wilcox and Marks, 1995). Thus, high maternal weight gain is one of the most common nutritional problems occurring in U.S. pregnant women today. The committee could find no reports of the prevalence of excessive weight gain identified during pregnancy.

ANTHROPOMETRIC RISK CRITERIA 85 Compared to research on the determinants of low gestational weight gain, little is known about the women with high gestational gain. Data on married women in the 1980 National Natality Survey suggest that white women were more likely than black women to gain > 16 kg, which is the upper limit advised for normal weight women (IOM, 1990); however, among participants in the 1990 PNSS, black and Hispanic women were more likely to have a high total gestational weight gain than were Asian women (Wilcox and Marks, 1995). High Gestational Weight Gain as an Indicator of Nutrition and Health Risk Very high gestational weight gain is associated with increased rates of high birth weight or macrosomia (Cogswell et al., 1995; IOM, 1990). In adolescents, high maternal weight gain at 16 weeks of gestation or later was associated with a doubled risk of macrosomia (Scholl et al., 1990b). An increased risk for cesarean deliveries among women with large gestational weight gains (Elkblad and Grenman, 1992; Johnson et al., 1992; Parker and Abrams, 1992) is seen even after adjusting for birth weight. However, in adolescents, Stevens-Simon and McAnarney (1992) found that high weight gain was associated with complications in the newborn rather than the mother. These investigators reported that fetal distress, meconium aspiration, antibiotic use, and stays in the neonatal intensive care unit were more likely among the infants of mothers with high rates of weight gain (> 0.59 kg/week). After adjusting for several other risk factors, Johnson and co-workers (1992) noted that meconium staining (but no other neonatal complications) was more common among the offspring of mothers with high rates of weight gain. A very high rate of maternal weight gain may be associated with spontaneous preterm delivery (Siega-Riz et al., 1994; Wen et al., 1990). Although a high maternal weight gain is a hallmark of developing preeclampsia, evidence suggests that it results from rather than causes this condition (IOM, 1990). Postpartum weight retention is probably the most frequently studied outcome related to excessive weight gain. Evidence reviewed by the IOM (1990) and from the 1988 National Maternal and Infant Health Survey (NMIHS) suggests that women who exceed the upper limit of IOM weight gain recommendations are significantly more likely to retain weight after delivery, with black women twice as likely as white women to retain excess weight (Keppel and Taffel, 1993; Parker and Abrams, 1993). Among low-income black adolescents (who are at increased risk of obesity), those with high gestational weight gain were more likely than those with low weight gain to retain extra weight early in the postpartum period (Stevens-Simon and McAnarney, 1992).

ANTHROPOMETRIC RISK CRITERIA 86 High Gestational Weight Gain as an Indicator of Nutrition and Health Benefit An observational study by Cogswell and co-workers (1995) suggests that limiting total gestational weight gain for very overweight women to 11 kg might reduce the risk of delivering infants with macrosomia. Few data are available to assess whether interventions to reduce excessive maternal weight gain are effective. Two clinical trials of energy and protein restriction among women who either had a high weight-for-height or a high gestational weight gain had nonsignificant results, but in opposite directions (Kramer, 1993). In a third study, a small group of pregnant women with gestational diabetes were able to follow the controlled energy (1,200- to 1,800-kcal) diet that was prescribed for them during late pregnancy. That intervention led to lower maternal weight gain and fewer macrosomic infants (Dornhurst et al., 1991). However, the study had no control group, and it is not known whether women without diabetes would be as willing to change their behaviors. Evidence that women who participated in the WIC program postpartum began their subsequent pregnancies less overweight suggests that women with high prenatal weight gains may benefit from WIC program participation during the postpartum period especially (Caan et al., 1987). The WIC program provides highly nutritious food, counseling, and education to postpartum women with the objective of supporting behaviors that can produce a healthy weight over the long-term. This is especially important for women who seek to reduce their weight while maintaining successful lactation. Use of High Gestational Weight Gain as a Nutrition Risk Criterion in the WIC Setting Table 4-1 summarizes the extent to which high gestational weight gain is used as a nutrition risk criterion. There is little consistency in the cutoff points, which range from a low of 1.8 kg/month to a high of 4.5 kg/month. Recommendations for High Gestational Weight Gain The risk of high gestational weight gain is well documented for pregnant and postpartum women. There is a theoretical basis and limited empirical evidence for benefit from WIC program participation. Therefore, the committee recommends use of high maternal weight gain as a nutrition risk criterion for pregnant and postpartum women by the WIC program, with the IOM cutoff values of greater than 3 kg per month during pregnancy and the BMI-specific upper limits for total weight gain for postpartum women. The committee also strongly recommends research to identify valid cutoff values for high weight gain during pregnancy. It further recommends testing

ANTHROPOMETRIC RISK CRITERIA 87 interventions to protect fetal growth while preventing excessive maternal weight gain, as well as strategies to address excessive weight gain in the postpartum period. Maternal Short Stature Maternal short stature may be primarily genetically determined, but it also may reflect nutrition deprivation that occurred during the mother's growth when she was in utero or during childhood (e.g., stunting). No methods are available to differentiate these two etiologies, but a social, medical, and family history may be instructive. A cutoff point of 157 cm has been recommended to define maternal short stature (IOM, 1990). Prevalence of and Factors Associated with Maternal Short Stature Data from national surveys indicate that the proportion of U.S. women ages 18 to 24 years with short stature decreased from about 25 percent in the early 1960s to about 17 percent in the early 1970s. In the late 1970s, the prevalence increased to 18 percent (IOM, 1990). Current estimates were not available. A history of low socioeconomic status, large family size, exposure to malnutrition, chronic disease, and exposure to emotional or psychological stresses are factors associated with short stature in adults (Mascie-Taylor, 1991). Short stature is more prevalent in women of Asian and Hispanic background and among recent immigrants to the United States (Rimoin et al., 1986). Maternal Short Stature as an Indicator of Nutrition and Health Risk Some studies suggest that maternal height is positively associated with the birth weight of the offspring, even after considering maternal weight (Abrams, 1991; Luke et al., 1993), but other investigators report that the relationship of maternal height and birth weight is mediated through maternal weight (Krasovec and Anderson, 1991). Women with short stature are at increased risk of delivering infants who are SGA or growth-retarded (Abrams and Newman, 1991; Kramer, 1987b; Wen et al., 1990). In some populations, a statistically significant association between short stature and increased risk of spontaneous preterm delivery has been reported (Kramer et al., 1992; Wen et al., 1990) but not consistently (Abrams et al., 1989; Kramer, 1987b). Data from developing and industrialized countries suggest that maternal short stature is associated with increased perinatal mortality (Krasovec and Anderson, 1991). Analysis of data from the 1980 National Natality Survey and National Fetal Mortality Survey

ANTHROPOMETRIC RISK CRITERIA 88 found no association between maternal height and stillbirth (Little and Weinberg, 1993). Although women with short stature in the 1980 National Natality Survey gained about 1 kg less than taller women during pregnancy, after controlling for other variables, short stature was not associated with an increased risk of a low maternal weight gain (Kleinman, 1990). Women with short stature appear to be at increased risk for labor abnormalities and cesarean delivery because of cephalopelvic disproportion (IOM, 1990; Johnson et al., 1992). Maternal Short Stature as an Indicator of Health and Nutrition Benefit Although it is not possible to affect maternal short stature, interventions may still affect the outcomes of pregnancy. The environmental disadvantages that caused stunting in a woman with short stature during her own development may also limit fetal growth during her pregnancies (Baird, 1977; Luke et al., 1993; Ounsted and Ounsted, 1968). If transfer of nutritional stress across generations actually exists, then interventions designed to improve fetal growth as much as possible, such as improved nutrition through food supplementation during pregnancy, might break the cycle. However, the effect of food supplementation on birth weight did not differ by maternal stature in a Guatemalan women study (Habicht and Yarbrough, 1980), and the committee identified no WIC program evaluations that examined women with short stature in particular. Even if an intervention were shown to increase birth weight in the pregnancies of women who are stunted, appropriate application of the intervention would be a challenge. It would be difficult to target those women whose short stature resulted from stunting rather than genetics. Also, because short stature is associated with an increased risk of cephalopelvic disproportion, the benefits of increased birth weight must be counterbalanced against the potential for increased morbidity to mother and infant caused by difficulties during labor and delivery. Use of Maternal Short Stature as a Nutrition Risk Criterion in the WIC Program In 1992, no state WIC agency used maternal short stature as a nutrition risk criterion for pregnant women (see Table 4-1). One of 45 state agencies used short stature in combination with low prepregnancy weight as a nutrition risk criterion for breastfeeding and nonlactating, postpartum women.

ANTHROPOMETRIC RISK CRITERIA 89 Recommendations for Maternal Short Stature The risk of maternal short stature is well documented for pregnant women. There is no empirical evidence or theoretical basis for benefit from participation in the WIC program on the basis of short stature alone. Thus, until there is evidence that the adverse outcomes associated with short stature can be alleviated through intervention during pregnancy, the committee does not recommend that maternal short stature be used as a nutrition risk criterion for pregnant women by the WIC program. Nonetheless, evaluating short stature among women has clinical utility for both assessment for increased risk of poor intrauterine growth and individualizing maternal weight gain recommendations (short pregnant women are advised to gain at the lower end of the recommended weight gain range [IOM, 1990]). Height in combination with a social and nutrition history may be useful in identifying women who were stunted as children, and this information may be useful in tailoring specific educational or social service interventions for WIC program participants. This may be especially true for subgroups of women who were at risk for malnutrition earlier in their lives, such as recent immigrants. Postpartum Underweight Reference standards that take time since delivery into consideration are not available for identifying whether breastfeeding or nonlactating, postpartum women are underweight. It has been estimated that on average, a women will lose about 5 kg immediately after delivery of the infant and the products of conception and another 2 to 3 kg during the next few weeks postpartum, primarily because of diuresis (Prichard et al., 1985). The pattern of weight loss after this interval depends on how much weight was gained during pregnancy, the composition of the gestational weight gain (for example, whether there was a higher proportion of fluid or fat), maternal diet, exercise, and method of infant feeding. Maternal weight loss after delivery varies greatly, with some women falling well below their prepregnancy weights shortly after birth and others never losing much of the weight they gained. Prevalence of and Factors Associated with Postpartum Underweight Virtually nothing is known about the prevalence of low maternal weight- for-height in either lactating or nonlactating U.S. mothers after delivery. In a study of women who were not obese before pregnancy and who delivered living, singleton, term infants, about 25 percent of the respondents reported weights 10 to 18 months postpartum that were below the prepregnancy weights

ANTHROPOMETRIC RISK CRITERIA 90 that they reported at the same time (Keppel and Taffel, 1993). The extent to which these postpartum weights would qualify as underweight was not reported. Predictors of low postpartum weight-for-height have not been reported. On a theoretical basis, the following factors might be associated with low weight-for- height status in a postpartum woman, regardless of infant feeding method: inadequate diet during pregnancy, low prenatal weight gain, low prepregnancy weight-for-height, infections including human immunodeficiency virus infection, inadequate food availability or intentional dieting after pregnancy, excessive energy expenditure, and psychological conditions that impair appetite or food behaviors, including eating disorders and depression. Postpartum Underweight as an Indicator of Nutrition and Health Risk Low maternal weight-for-height during the postpartum period is of concern because it may indicate poor energy stores or the lack of replenishment of maternal nutrient stores that were mobilized during pregnancy. Low maternal weight-for-height may also indicate that a mother is not consuming an adequate amount of food to meet her energy needs. Breastfeeding is a robust process, even in seriously malnourished women. The major predictor of successful lactation is the infant's demand for milk (IOM, 1991). Although some studies in developing countries suggest that underweight women may produce a lower volume of milk, the findings are complex to interpret and are not consistent (IOM, 1991). The nutrition risk of postpartum underweight is greater to the breastfeeding mother than to the infant if the mother consumes less energy than required to cover her increased needs. In a study of well-nourished women in the United States, Nommsen and co- workers (1991) reported that the lipid content of human milk was positively associated with increased maternal weight-for-height, but only during the second 6 months of lactation. They suggested that the underlying relationship between percentage of IBW and the fat content of human milk becomes apparent only after women have depleted the fat that they stored during pregnancy (Nommsen et al., 1991). Postpartum Underweight as an Indicator of Health and Nutrition Benefit It is assumed that adequate nutrition during the postpartum period helps the mother to cope with intense physical and emotional demands as she recovers from pregnancy and delivery, breastfeeds her infant, adapts to new motherhood, and provides infant care. For breastfeeding mothers, the nutrition needs of lactation require special consideration. Because women with a low weight-for-height probably have low fat stores, which are ordinarily mobilized to help meet the extra energy costs of

ANTHROPOMETRIC RISK CRITERIA 91 lactation, it is reasonable to expect them to benefit from the supplemental foods provided by the WIC program. Studies of chronically undernourished Guatemalan women suggest that energy supplements offered during the postpartum period can buffer maternal nutrition stresses associated with concurrent lactation and pregnancy or short interconceptional periods (Marchant et al., 1990). Furthermore, provision of supplemental energy to this population throughout two consecutive pregnancies and the period of lactation between them was associated with large increases in birth weight not seen when supplements were provided only during pregnancy. Although maternal underweight per se was not the focus of those studies, it is likely that the majority of women included in the studies had low postpartum weight-for-height (Villar and Rivera, 1988). No studies have been reported addressing the efficacy of postpartum interventions to improve the maternal or infant health or nutrition specifically in underweight postpartum women and their infants living in the United States. However, a well-designed evaluation of the postpartum component of the WIC program suggests that the provision of WIC program benefits during the postpartum period is associated with better maternal and infant health (Caan et al., 1987). Circumstances at that time created a natural experiment in which postpartum participants were either served or not served by the WIC program on the basis of geographic, policy, and agency factors rather than individual maternal factors. The extended feeding group received WIC program benefits for 5 to 7 postpartum months, whereas the comparison group's benefits were terminated within 2 months after delivery. Both groups participated in the WIC program during both a first pregnancy and a subsequent pregnancy and delivered within 3 years of the first one. After adjusting for differences between the groups, extended feeding was associated with significantly improved fetal size at the end of the second pregnancy: weight at birth was increased by 131 g and length at birth was extended by 0.3 cm. The increased risk of delivering a low-birth-weight infant in the comparison group versus that in the extended feeding group approached statistical significance. Extended postpartum feeding was associated with improved prepregnancy weight at the beginning of the second pregnancy among women who began their first pregnancy underweight (<90 percent IBW), suggesting that postpartum supplementation may have improved or protected postpartum energy stores, although the finding was not statistically significant. It is not known if women who are underweight after delivery are less likely to initiate or succeed at breastfeeding. In developing countries, studies examining whether it is possible to improve lactational performance by feeding undernourished mothers, who are almost always underweight, have yielded mixed results and have been subject to methodologic difficulties (Abrams, 1991; IOM, 1991). Overall, these studies suggest that providing food supplements to lactating mothers may increase maternal postpartum weight and improve

ANTHROPOMETRIC RISK CRITERIA 92 maternal health (IOM, 1991). Well-designed supplementation studies of women with a high degree of malnutrition show an adverse effect of malnutrition on milk volume (Gonzalez-Cossio et al., 1991; Khin-Maung-Naing, 1987), but most studies of less malnourished women do not (IOM, 1991). It is also possible that maternal dietary supplementation contributes to decreased duration of lactational amenorrhea in malnourished women (IOM, 1991), but this may have only minor importance to actual health outcomes (Kurz, 1993). Because maternal underweight after delivery or throughout the first year postpartum can be a marker of poor maternal health or environmental stress, identification of these women and assessment of their social, nutrition, and medical risk factors have the potential to identify interventions that can improve maternal and fetal health. Use of Postpartum Underweight as a Nutrition Risk Criterion in the WIC Setting Table 4-1 summarizes use of maternal postpartum underweight as a nutrition risk criterion. The majority of WIC state agencies defined underweight at < 90 percent ideal weight-for-height or a BMI of < 19.8, but cutoff values vary widely. Recommendations for Postpartum Underweight The risk of maternal postpartum underweight is documented in postpartum women. There is empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends use of maternal postpartum underweight as a nutrition risk criterion for postpartum women by the WIC program, with the IOM cutoff value of a BMI of 19. It also recommends research to determine the most valid postpartum cutoff points for lactating and nonlactating women. Postpartum Overweight Recent data indicate that, depending on age, the prevalence of overweight among U.S. women of childbearing age ranges from about 20 to 30 percent (Kuczmarski et al., 1994). Given that the median gestational weight gain in the United States was almost 14 kg in 1989 (CDC, 1992), it is important to know the extent to which postpartum weight retention contributes to this public health problem. No standard definition exist for postpartum weight retention or postpartum obesity. Women can be classified as overweight by comparing their postpartum

ANTHROPOMETRIC RISK CRITERIA 93 weight-for-height with the reference for nonpregnant women. Postpartum weight retention is often defined as postpartum weight minus prepregnancy weight. By 6 weeks postpartum, much of the weight retained is likely to be maternal fat (Prichard et al., 1985). Review of older studies, when the average gestational weight gain was much lower than it is currently, indicates that women with an average prenatal weight gain retained about 1 kg more than the expected weight increase with age (IOM, 1990). Results from studies of postpartum weight retention vary according to study population, the follow-up periods after delivery, and definitions or observations of infant feeding practices. Methodologic problems include bias from inaccurate recall of prepregnancy weight, failure to adjust for the expected increase in body weight with age, and lack of information on energy intake and exercise patterns. In the absence of reference standards specific to postpartum lactating or nonlactating women, the IOM (1992a) recommended application of the nonpregnant BMI cutoff values to these populations: 120 to 135 percent IBW (BMI 26 to 29 kg/m2) to define overweight, and greater than 135 percent IBW or BMI > 29 kg/m2 to define obesity. Prevalence of and Factors Associated with Postpartum Overweight Using nationally representative data on postpartum weight retention of 2,845 U.S. women whose pregnancies resulted in term, live, singleton births, the 1988 NMIHS reported the median weight retention of 1.5 kg at 10 to 18 months after delivery. However, 25 percent of the white women and 45 percent of black women retained more than 4 kg. These data suggest that it is possible that pregnancy contributes to postpartum overweight or obesity (IOM, 1990; Keppel and Taffel, 1993; Parker, 1994; Parker and Abrams, 1993). Data from the 1988 NMIHS suggest that median weight retention was 0.7 kg for white mothers and 3.2 kg for black mothers among women whose gestational weight gains were in accordance with their recommended BMI-specific ranges (Keppel and Taffel, 1993). In another analysis of the same data set that focused on women whose prepregnancy weight-for-height was in the normal range and that controlled for other factors, black women were more than twice as likely as white women to retain 9 kg or more postpartum (Parker and Abrams, 1993). This racial differential is extremely important because cross-sectional studies have shown that black women are already at a high risk for obesity (Flegal et al., 1988; Kuczmarski et al., 1994). Studies of postpartum overweight for women of other racial/ethnic groups have not been reported. Overall, the bulk of the evidence does not support the view that lactation promotes increased weight loss (IOM, 1991; Parker, 1994). However, a study comparing postpartum weight loss between breastfeeders (defined as nursing for

ANTHROPOMETRIC RISK CRITERIA 94 at least 12 months) and bottle feeders (who weaned their infants to the bottle by age 3 months) reported highly significant differences at between 6 and 12 months after birth, but not earlier (Dewey et al., 1993). Among the breastfeeders, high feeding frequency and milk energy output were associated with less weight loss between 3 and 6 months after birth but more rapid weight loss between 9 and 12 months after birth. These results underscore the need for studies that precisely classify women by infant feeding method and follow them for an extended period of time. Other risk factors for postpartum weight retention include a high prepregnancy weight-for-height (such women have wide variations in postpartum weight loss) and low-income (Parker, 1994). Cigarette smoking is associated with less weight retention. The influences of maternal age, parity, and length of interconceptional periods are interrelated and complex. Segel and McAnarney (1994) followed 30 black, low-income adolescents for about 3 years after pregnancy and concluded that high gestational weight gain as well as prepregnancy obesity were risk factors for postpartum obesity in this group. Postpartum Overweight as an Indicator of Nutrition and Health Risk There is little question that overweight is a serious health problem. Obese women are at increased risk of heart disease, diabetes mellitus, hypertension, and some types of cancer (Abrams and Berman, 1993; NRC, 1989). Furthermore, obese postpartum women are at increased risk for maternal complications and poor perinatal outcomes during subsequent pregnancy. Evidence from a study of more than 700 primiparous Australian women suggests that a high postpartum weight-for-height (BMI > 26 kg/cm2) at 1 month postpartum is associated with a statistically significant increased risk of discontinuing breastfeeding by 6 months (Rutishauser and Carlin, 1992). Other studies are needed to examine the influence of postpartum obesity on lactation success. A recent study of 121 white and 224 black women (7 to 12 months postpartum) who participated in a South Carolina WIC program concluded that the most important variables in predicting postpartum weight loss were prepregnancy weight, prenatal weight gain, parity, and prenatal exercise. After these factors were controlled, race predicted that black women retained 6.4 pounds more than white women. Black women reported significantly higher mean energy and fat intake and significantly lower amounts of prenatal and postpartum activity. The authors concluded that the weight differential between black and white mothers might be explained by higher energy intake and lower activity levels in black women postpartum (Boardley et al., 1995).

ANTHROPOMETRIC RISK CRITERIA 95 Postpartum Overweight as an Indicator of Nutrition and Health Benefit No studies have specifically described the health effects of dieting among nonlactating mothers during the postpartum period (Parker, 1994). It has been proposed that weight losses of less than 2 kg/month for normal-weight women and 3 kg/month for overweight or obese women after the first month postpartum are consistent with successful lactation (Dewey and McCrory, 1994; IOM, 1991). A recent uncontrolled study demonstrated that lactating women can lose weight and maintain adequate milk quantity and quality by following a moderately restricted diet over a 10-week postpartum period; however, one-third of the original subjects dropped out of the study (Dusdieker et al., 1994). The single evaluation of postpartum intervention by participation in the WIC program suggested that women who participated in the WIC program for 5 to 7 months after birth had half the odds of being overweight at the beginning of their next pregnancy (Caan et al., 1987). The investigators hypothesized that WIC program participants who already have adequate energy intakes may have substituted the more nutrient-dense WIC foods for less expensive foods that provided more calories but fewer nutrients. By assessing maternal postpartum overweight, the WIC program is in a position to identify women who are retaining excess postpartum weight, women whose overweight status continues, and women who have become overweight because of weight gain during the postpartum period. The WIC program's assessment and follow-up of women's weight during the postpartum period may provide the only possibility of intervention, because in contrast to the intensive monitoring of health status that occurs during pregnancy, most women receive relatively little medical care during the postpartum period. Use of Postpartum Overweight as a Nutrition Risk Criterion in the WIC Setting In 1992, most of the agencies that used postpartum overweight as a risk criterion for breastfeeding and nonlactating women (see Table 4-1) used the cutoff point of 120 percent of IBW. Cutoff values ranged from 110 to 135 percent of IBW and included several categories of overweight. Recommendations for Postpartum Overweight The risk of postpartum overweight is documented in postpartum women. There is empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends use of postpartum overweight as a nutrition risk criterion for postpartum women by state WIC agencies, using cutoff values of> 120 percent of IBW or a BMI of> 26.0 kg/m2

ANTHROPOMETRIC RISK CRITERIA 96 after 6 weeks postpartum. The committee also recommends research to determine the most valid cutoff points. The committee recommends the design and testing of culturally appropriate interventions to reduce maternal overweight after delivery or to prevent further gain. Abnormal Postpartum Weight Change Theoretically, the criterion abnormal postpartum weight change has the potential to identify a group of women who are at special and acute nutrition risk, especially when it is related to weight loss. However, there is no standard definition for abnormal postpartum weight change in either lactating or postpartum women. Weight loss that exceeds suggested rates of maternal weight loss consistent with adequate lactation has been proposed (IOM, 1991, 1992a). Prevalence of and Factors Associated with Abnormal Postpartum Weight Change Abnormal postpartum weight change has not been described in the literature; therefore, nothing is known about its epidemiology or factors associated with its occurrence. Abnormal Postpartum Weight Change as an Indicator of Health and Nutrition Risk A recent review concluded that if a woman has adequate fat reserves, it is probably safe to restrict energy intake moderately to enhance weight loss during lactation (Dewey and McCrory, 1994), and a subsequent study supports this view of no increased risk (Dusdieker et al., 1994). Abnormal Postpartum Weight Change as an Indicator of Health and Nutrition Benefit No studies have examined the possible health benefits of intervening for women with high rates of weight loss or gain after delivery. Common sense suggests that when a rapid weight loss or gain over a short period of time is observed in a postpartum woman, additional assessments of maternal health and psychological, social, and economic status are warranted to determine the cause and that the food and/or nutrition education provided by the WIC program can help remedy the problem.

ANTHROPOMETRIC RISK CRITERIA 97 Use of Abnormal Maternal Weight Change as a Nutrition Risk Criterion in the WIC Setting The few state WIC agencies that used abnormal postpartum weight change as a nutrition risk criterion for postpartum women (see Table 4-1) used cutoff points that ranged from maternal weight loss of greater than 0.9 kg/month to a 6- month postpartum weight of 18 kg less than the postpartum weight at 6 weeks, or an increase in weight of at least 10 percent in women who were at desirable weight at 6 weeks postpartum. Detection of abnormal maternal postpartum weight change requires repeated measurements of maternal weight over a relevant time period, which may sometimes not be possible in WIC program settings. Recommendation for Abnormal Postpartum Weight Change Although there is a theoretical basis for benefit from participation in the WIC program, no risks have been documented, and there is no standard definition for this change in either lactating or postpartum women. Therefore, the committee recommends discontinuation of use of abnormal postpartum weight change as a nutrition risk criterion for postpartum women by the WIC program. ANTHROPOMETRIC RISK CRITERIA FOR INFANTS AND CHILDREN A summary of anthropometric risk criteria as predictors of risk and benefit for infants and children appears in Table 4-3. Low Birth Weight The term low birth weight (LBW) is used to describe a weight of less than 2,500 g at birth. Infants and children with LBWs can be broadly categorized into two subgroups: (1) those who are born preterm, that is, at less than 37 weeks of gestation and (2) those who are growth retarded in utero and who are born SGA (see the section Small for Gestational Age). Because weight at birth is a function of both duration of gestation and interuterine growth of the fetus, an LBW infant can be both preterm and SGA.

ANTHROPOMETRIC RISK CRITERIA 98 Prevalence of and Factors Associated with LBW The national prevalence of LBW in 1991 was 70.8 per 1,000 live-born infants (CDC, 1994). Across ethnic groups, the prevalence of LBW was substantially higher among infants of black mothers (135 per 1,000 live births) than among white, Hispanic, Native American, and Asian groups. Similar ethnic differences were observed among infants of low-income families (Yip et al., 1992a). LBW is caused by a short gestational period, intrauterine growth retardation (IUGR), or both. In general, factors related to IUGR and preterm delivery are not identical (see SGA following and Chapter 5 for specifics). For example, poor maternal nutrition status is one of the major causes of SGA, but it is not an important determinant of prematurity (Kramer et al., 1992). On the other hand, infections (Taha et al., 1993; Villar et al., 1989), maternal cocaine use (Petitti and Coleman, 1990), and prepregnancy and gestational hypertension (particularly severe preeclampsia) (Kramer et al., 1990a, 1992) are related to both SGA and preterm delivery. The causes of LBW vary for different populations, as does the nature of LBW (WHO, 1995). In developing countries, most LBW infants are SGA or had IUGR. In contrast, in industrialized countries, the majority of LBW infants were delivered preterm (Ashworth and Feachem, 1985; CDC, 1994; IOM, 1990). LBW as an Indicator of Nutrition and Health Risk LBW is one of the most important biologic predictors of infant death and deficiencies in physical and mental development during childhood among those

ANTHROPOMETRIC RISK CRITERIA 99 babies who survive (IOM, 1985). The consequences of LBW caused by IUGR differ from those of LBW caused by prematurity. Premature LBW infants generally exhibit higher neonatal, perinatal, and postnatal mortalities than their full-term counterparts of the same birth weight, primarily because immunologic immaturity is more pronounced in preterm infants (Meyer and Comstock, 1972; Read et al., 1994; Sappenfield et al., 1987; Starfield et al., 1982). A recent study comparing perinatal weight-specific mortality in the United States and Norway found that, after adjustment for the mean birth weight in each country, the higher rate of perinatal death among U.S. infants could be entirely attributed to a small excess of preterm deliveries (Wilcox and Marks, 1995). Despite their earlier disadvantage, premature infants, if they survive, experience a lower risk of infections such as diarrhea and exhibit more growth during childhood than infants with IUGR (Barros et al., 1992). The associations of LBW with poor health, growth, and development may persist throughout childhood, but the magnitudes of these associations may weaken as a child becomes older. LBW continues to be a strong predictor of growth in early childhood (Binkin et al., 1988). It has been reported that 20 to 40 percent of the prevalence of low length-for-age in the first 2 years of life can be attributed to LBW (Gayle et al., 1987). A recent study has shown that children with extreme LBWs (i.e., below 750 g) are at very high risk for long-term neurobehavioral dysfunction and poor school performance (Hack et al., 1994; Klebanov et al., 1994; McCormick et al., 1992). LBW as an Indicator of Nutrition and Health Benefit Infants and children born with LBW, particularly LBW caused by IUGR, must receive an optimal nutrient intake to survive, meet the needs of an extended period of relatively rapid postnatal growth, and complete their growth and development. They therefore have the potential to benefit from the WIC program. Interventions that support breastfeeding and that provide nutrient-dense food, nutrition education, and health referrals help to assure that this will occur. Little information is available on potential benefits relative to different WIC program components and different types of LBW. Use of LBW as a Nutrition Risk in the WIC Setting Low birth weight was used as a nutrition risk criterion for infants by 53 state WIC agencies in 1992 (see Table 4-1). The cutoff point was set universally as 2,499 or 2,500 g in all state WIC agencies. One of eight agencies that used LBW as a criterion for children ages 1 to 5 years used 1,500 g as the cutoff point. Birth-weight data are routinely collected in most hospitals and perinatal clinics, and the information is readily available to the WIC program.

ANTHROPOMETRIC RISK CRITERIA 100 Recommendations for LBW The risk of LBW is well documented in infants and also is documented in children. There is empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends use of LBW as a nutrition risk criterion for infants and children by the WIC program, with the conventional cutoff value of less than 2,500 g. However, priority should be given to using the SGA and prematurity criteria (see subsequent section and ''Prematurity" in Chapter 5) over the LBW criterion for infants. If LBW is used as the sole nutrition risk criterion for infants, a cutoff value of 2,500 g may be too low, because some heavier newborns also have elevated nutrition and health risks. However, there is no need to increase the LBW cutoff value in the WIC program for infants if the SGA and prematurity criteria are followed. In addition, the committee recommends research to assess the effectiveness of interventions used to improve health and nutrition outcomes for LBW infants. Small for Gestational Age Small for gestational age (SGA) is defined as an infant's weight at birth below a certain cutoff point compared with some reference point for infants of comparable gestational age. Because weight at birth is a function of both the duration of gestation and the intrauterine growth of the fetus, assessment of birth weight on the basis of gestational age has a great advantage in that it differentiates LBW that results from poor fetal growth from LBW that results from prematurity. SGA implies intrauterine growth retardation (IUGR) and as such, the two terms are often used interchangeably. Strictly speaking, however, SGA and IUGR are not synonymous (Altman and Hytten, 1989). Some infants who are SGA (e.g., those born to short mothers) may merely represent the lower tail of the normal fetal growth distribution, but the growth of some infants who are not identified as SGA may have actually been restricted in utero (e.g., infants born to tall cigarette smokers). In individual cases, however, it is very difficult to know whether the observed birth weight is the result of true IUGR. The likelihood that the SGA is due to IUGR increases as the prevalence of IUGR increases in the population. For infants born after 26 weeks of gestation, WHO (1995) recommends the use of William's Birth Weight Curve, which was derived from a large, multiracial population in California (Williams et al., 1982). The most frequently used cutoff point for diagnosing SGA is the 10 th percentile. For full-term infants, this value (corresponding to 2,900 g in William's Birth Weight Curve) is greater than the conventional cutoff point of 2,500 g for LBW. Mounting evidence indicates that infants with birth weights above 2,500 g but below some

ANTHROPOMETRIC RISK CRITERIA 101 predefined cutoff point around the 10th percentile still carry significantly higher health and nutrition risks than infants with birth weights above the 10th percentile (Balcazar and Haas, 1991; Kimball et al., 1982; Kramer, 1987a; Lester et al., 1986). Prevalence of and Factors Associated with SGA The national prevalence of full-term (≥37 weeks of gestation) LBW infants was 26.5 per 1,000 live-born infants in 1991 (CDC, 1994). The prevalence was much higher among black infants than white infants (47.2 versus 22.0 per 1,000 live births, respectively). The determinants of fetal growth have been the subject of considerable research (e.g., Abrams, 1994; Abrams and Newman, 1991; Barros et al., 1992; IOM, 1990; Kramer, 1987b; Kramer et al., 1990a; Stein and Susser, 1984; Wen et al., 1990). In general, maternal stature, prepregnancy weight, weight gain during gestation, gestational energy intake and expenditure during pregnancy, and maternal health all have important and independent influences on the rate of fetal growth. These factors are also related to underlying socioeconomic deprivation (IOM, 1985). Gestational nutrition status is affected by maternal energy and nutrient intakes, weight gain, and fat deposition during pregnancy (Villar et al., 1992). Consequently, research has focused on nutrition interventions to improve maternal nutrition status as a means of reducing SGA. The consistently positive, although sometimes modest, effect of food supplementation and the negative effect of increased energy needs during pregnancy on birth weight have been demonstrated both in developing countries and in low-income populations of industrialized countries (Adair and Pollitt, 1985; Chavéz and Martínez, 1980; Habicht and Yarbrough, 1980; Kramer, 1993; Lechtig and Klein, 1981; Prentice et al., 1983; Rush et al., 1988c). Maternal height and weight may be influenced by the mother's past nutritional status; and they, in turn, can affect fetal growth. Other factors affecting fetal growth include maternal health (such as the presence of infection and prepregnancy and gestational hypertension— particularly severe preeclampsia), cigarette smoking, and alcohol consumption (Jacobson et al., 1994; Kramer et al., 1990a; Plouin et al., 1983; Shu et al., 1995). The use of certain pharmacologic substances (including cocaine) adversely affects birth weight (Ashworth and Feachem, 1985; Dolan-Mullen et al., 1994). Teenage mothers have a higher frequency of LBW infants for any given parity, and a short interconceptional interval is associated with an increased risk of SGA and prematurity (Lieberman, 1995; Rawling et al., 1995). A greater percentage of LBW babies is born to blacks and Asians than to whites of similar socioeconomic status (James, 1992; Wang et al., 1994). High altitude is also related to a higher prevalence of LBW (Yip et al., 1993). Many of these

ANTHROPOMETRIC RISK CRITERIA 102 factors influence both fetal growth and gestational duration (WHO, 1995). Some risk factors are amenable to appropriate health interventions (e.g., maternal health, cigarette smoking), but others are not (e.g., altitude, race). SGA as an Indicator of Nutrition and Health Risk Overwhelming evidence indicates that impairment of fetal growth can have adverse effects on the nutrition and health of children during infancy and childhood, including higher mortality and morbidity, slower physical growth, and possibly slower mental development (Ashworth and Feachem, 1985; Binkin et al., 1988; Fancourt et al., 1976; Harvey et al., 1982; IOM, 1990; McCormick, 1985; Parkinson et al., 1981; Teberg et al., 1988; Villar et al., 1984). Infants who are SGA are more likely to have congenital abnormalities (Khoury et al., 1988). Severely growth-retarded infants are at markedly increased risk for fetal and neonatal death, hypoglycemia, hypocalcemia, polycythemia, and neurocognitive complications of pre- and intrapartum hypoxia (IOM, 1990; Kramer et al., 1990b). Over the long-term, growth-retarded infants may have permanent mild deficits in growth and neurocognitive development (Binkin et al., 1988; Dunn et al., 1986; IOM, 1991; Teberg et al., 1988). Some studies have even suggested that the restriction of fetal growth may increase the risk of ischemic heart disease, hypertension, obstructive lung disease, diabetes mellitus, and death from cardiovascular disease in adulthood (Barker et al., 1993a, b; 1989; Valdez et al., 1994). When infants who are SGA are also preterm, their health risks also include those associated with prematurity (WHO, 1995) (see Chapter 5). Body proportionality may be related to different outcomes of babies who are SGA. The most commonly used proportionality index is Rohrer's ponderal index, which is defined as (100 × weight in grams)/(crown-heel length in centimeters)3 (Khoury et al., 1990). An infant with a high ponderal index has a relatively high weight-for-length, whereas an infant with a low ponderal index is thin, with low weight-for-length. Infants who are SGA and who have an adequate ponderal index exhibit less catch-up growth than their counterparts with a low ponderal index (Kramer, 1987a). In contrast, infants who are SGA and who have a low ponderal index have an increased risk for postnatal morbidity compared with those with an adequate ponderal index (Caulfield et al., 1991; Villar et al., 1990). Conlisk (1993) studied the risk in the United States of neonatal mortality among infants with proportionate weight-for-length and those with disproportionate weight-for-length (decreased weight-for-length). The results showed that, in both blacks and whites, disproportionate infants with lower birth weights had a higher risk of mortality. Those with birth weights greater than 2,400 g (black) and 2,800 g (white) had a lower risk of mortality than proportionate

ANTHROPOMETRIC RISK CRITERIA 103 infants. The effect of birth weight on mortality was significantly greater for the disproportionate versus the proportionate infants with birth weights of less than 2,200 g (black) or less than 2,600 g (white). Several studies report that SGA and low ponderal index are related to increased insulin resistance during infancy and a higher risk of mortality from cardiovascular disease during adulthood (Barker et al., 1993b; Phillips et al., 1994). SGA as an Indicator of Nutrition and Health Benefit Appropriate nutrition and health interventions for infants who are SGA can help minimize the adverse health and nutrition consequences associated with SGA as well as maximize the potential for subsequent catch-up growth and development among these infants. Infants who are SGA can benefit from breastfeeding, which is promoted by the WIC program. Human milk is the most appropriate food for young infants because it is nutritious and confers immunity and because it is fed in a manner that avoids bacterial contamination (Atkinson et al., 1990; IOM, 1991). The beneficial effects of human milk on reducing morbidity and mortality and promoting optimal growth have been demonstrated in both developing and industrialized countries (DaVanzo et al., 1983; Habicht et al., 1986; IOM, 1991; Launer et al., 1990). When breastfeeding is not possible or feasible, infants who are SGA need formula that is tailored to their special needs (IOM, 1992b), and this can be provided through the WIC program. The WIC program may also benefit infants by leading to regular surveillance, early prevention, and referral for treatment of health complications related to SGA. Among infants and children admitted to the WIC program on the basis of the presence of LBW and SGA (among other criteria), Rush and colleagues (1988b) observed better immunization levels, a more frequent regular source of health care, better digit memory, and more advantageous child behavior than among infants in control groups. Use of SGA as a Nutrition Risk Criterion in the WIC Setting Of the 10 state WIC agencies using the small for gestational age nutrition risk criterion in 1992 (USDA, 1994) (see Table 4-1), the reference data used for evaluating SGA differed from state to state. Measuring SGA can easily be implemented in the WIC program setting.

ANTHROPOMETRIC RISK CRITERIA 104 Recommendations for SGA The risk of SGA is well documented in infants and children. There is empirical evidence and a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends the use of SGA as a nutrition risk criterion for infants and children by the WIC program, with a cutoff value of less than the 10th percentile because it includes full-term infants who are SGA with birth weights of greater than 2,500 g. In addition, the committee recommends further studies to relate body proportionality to risks and also to potential benefits from interventions. Short Stature Short stature is defined by an infant's length-for-age or a child's height-for- age below some cutoff point compared with the National Center for Health Statistics-U.S. Centers for Disease Control and Prevention (NCHS-CDC) reference data. The term length is used for infants and children under 2 years of age when their body height is measured in a recumbent position. For older children, standing height is measured and the term height applies. For simplicity, the word stature is used in this section when either measure might apply. Stature represents the amount of linear growth that has been achieved. Short stature may result from normal variation or from health and nutrition inadequacies that are usually long-term in nature. In the latter case, the term stunting is used to indicate that shortness is pathologic. In contrast to older children, in whom stunting may be a past event, stunting in infants and younger children (i.e., under 3 to 4 years of age) represents an ongoing process of failing to grow. Prevalence of and Factors Associated with Short Stature The prevalence of short stature among infants and children targeted by the WIC program in 1991 (defined as below the 5th percentile of the NCHS-CDC reference standard) was 5 percent or higher. The highest prevalence, about 12 percent, was observed in Asian children (USDA, 1991; Yip et al., 1992a). Abnormal short stature in infants and children is widely recognized as a response to a limited nutrient supply at the cellular level. The maintenance of basic metabolic functions takes precedence, and resources are diverted from linear growth. Unavailability of nutrients for cells results directly from inadequate food intake and frequent diseases, particularly infectious diseases. Short stature is related to the lack of total dietary energy and to a poor quality of diet, namely, a diet that provides inadequate protein, particularly animal protein, and inadequate amounts of such micronutrients as zinc, vitamin A, iron, copper,

ANTHROPOMETRIC RISK CRITERIA 105 iodine, calcium, and phosphorus. However, the mechanisms by which these factors affect bone growth are poorly understood (Allen, 1994; Chwang et al., 1988; Golden, 1994; Golden and Golden, 1981; Prentice and Bates, 1994; Waterlow, 1994b; West et al., 1988). The negative effect of diseases, most commonly infectious diseases, on the growth of children is well-known, and the magnitude of the effect depends on infection management practices, feeding practices, and food adequacy and quality (Tomkins and Watson, 1989). Insufficient amounts of growth hormone and a lack of physical exercise, either as a result of inadequate nutrient intake or poor health, may also contribute to some cases of stunting (Karlberg et al., 1994; Torun and Viteri, 1994). Food inadequacy and infection are often synergistically related to each other in their effects on child growth. Stature deficits are significantly greater when both food inadequacy and infection occur together than when these two conditions occur separately over the same period Lutter et al., 1992). This indicates the importance of offering interventions that combine both food and health components. The impact of inadequate food and frequent episodes of infectious disease on short stature is especially pronounced in the first few years of life. During early infancy, breastfeeding reduces morbidity and mortality, especially in developing countries, and promotes and maintains normal growth (Feachem and Koblinsky, 1984; Habicht et al., 1986; Seward and Serdula, 1984). Exclusive and frequent breastfeeding is recommended to promote health and well-being in industrialized countries as well as in developing countries (IOM, 1991; WHO, 1988, 1991). The first 2 to 3 years is a time of vulnerability: linear growth is very rapid; young children are highly dependent on others for care; they are susceptible to infectious disease; their nutritional requirements, expressed as the amounts of energy or nutrients received per kilogram per day, are greater than at any subsequent time of life; and most adverse factors will have significant and lasting effects. Consequently, stature deficits are more likely to accrue actively before 3 years of age and ease in later childhood. In general, later growth cannot completely compensate for previous losses (Martorell et al., 1994). The impact of poverty on nutrition status varies from place to place, depending in part on the existence of public health and nutrition programs (Dreze and Sen, 1991). In general, strong associations between short stature and poverty exist in the developing world; and of all commonly used anthropometric indices, short stature is generally regarded as the best summary indicator of general deprivation and poor environment in developing countries (ACC/SCN, 1992; Beaton et al., 1990; WHO, 1995). Similar associations, albeit less strong, can also be found in the industrialized world. In the United States, income-related short stature in children is consistently observed in large surveys (Abraham et al., 1975; CDC, 1972; Hamill et al., 1972; Kerr et al., 1982; Owen and Lubin, 1973; Owen et al., 1974). An examination of poverty-related height differences in U.S. children using the first and second National Health and

ANTHROPOMETRIC RISK CRITERIA 106 Nutrition Examination Surveys (NHANES I) and (NHANES II) data found that children from families living above the poverty level were about 1 to 2 cm taller than children living below the poverty level (Jones et al., 1985). Differentials in short stature are more strongly associated with long-term than with single-year measures of income (Miller and Korenman, 1994). A child's height-for-age is also affected by mode of feeding and other factors. After the third month of exclusive breastfeeding, infants may have median lengths of 0.1 to 0.2 z-scores (about 4 to 8 percentiles) less than the NCHS-CDC reference median (Dewey et al., 1991b). (These reference data are based on the length of predominantly bottle-fed infants.) Breastfed infants may remain slightly shorter during the ensuing period of ad libitum mixed feeding of human milk and solid foods (WHO, 1995). Parents' size, particularly height, influences a child's stature through genetic endowment and fetal growth. Birth weight, even in the range commonly accepted as normal (2.5 to 4.0 kg), is a powerful predictor of linear growth during both infancy and childhood (Binkin et al., 1988). The fact that some of the variation in birth weight and subsequent infant linear growth is determined by maternal health and nutrition status indicates the importance of targeting interventions to pregnant women and mothers. Demonstrable differences in stature exist among children of different ethnic and racial groups. Black infants, for example, tend to be shorter during infancy (Yip et al., 1993). Insufficient evidence is available to indicate that the shorter stature of Asian children is not influenced by nutrition, because many Asian children in the United States have a refugee background, and there has been a clear upward secular trend in the growth of these children (Yip et al., 1992b). Ethnic and racial differences, however, are relatively minor compared with the differences associated with environmental factors (Habicht et al., 1974; WHO, 1995). Higher altitude or a lower partial pressure of oxygen is associated with shorter statures, with the difference between 500 and 2,000 m being 0.4 z-scores (about a 1.0-cm difference for 3-year-old children) (Yip et al., 1988). Short Stature as an Indicator of Nutrition and Health Risk Short stature because of inadequate dietary intake combined with high rates of infection is a strong predictor of nutrition and health risk, but short stature because of normal variations in a population is not. Stunted infants are likely to become stunted children, and stunted children are likely to be stunted adolescents and adults, especially if there are no improvements in health and nutrition. Stunting early in life leads to reduced maximal physical working capacity and capacity for sustained work (endurance) and probably a reduced level of intellectual capacity (Martorell et al., 1994; Waterlow, 1994b). In a Guatemalan study, childhood stature at 3 years of age

ANTHROPOMETRIC RISK CRITERIA 107 was highly related to adult height, grip strength of the right hand, and fat-free mass—all of which are key determinants of adult work capacity. Size at 3 years of age also predicted nonverbal intelligence, numeracy, literacy, and school attainment when analyses controlled for village characteristics and characteristics of the home environment (Martorell et al., 1992). Stunted infants and children are also likely to become severely ill when they develop infections and are more likely to die than normal individuals (Martorell and Ho, 1984). A consistent finding in studies of the relationship between malnutrition and mortality has been that stunting in infants and young children has a greater ability than severe underweight of recent origin to predict subsequent (e.g., 6 to 24 months of follow-up) mortality, but low weight-for-age is usually the best predictor of all (Pelletier, 1994). Relationships between stunting and mortality are influenced by age, gender, seasonality, socioeconomic status, and burden of infectious disease, which vary from population to population (Pelletier et al., 1993). Short stature has been consistently associated with comparatively low performance in developmental scales among infants and toddlers, and with poor intelligence quotient and other cognitive test scores among children. In economically impoverished populations where children are nutritionally at risk, it seems likely that this association is partly explained by environmental factors, including poor nutrition. Short Stature as an Indicator of Nutrition and Health Benefit The effects of food supplementation on the stature of malnourished infants and children have been mixed. A review of more than 200 supplementary feeding programs in developing countries concluded that the effect of supplementation on nutrition status, as assessed by growth performance, was surprisingly small (Beaton and Ghassemi, 1982). It was suggested that the small effect might simply reflect a low level of improvement in the diet. Alternatively, the small effect could be due to the fact that few studies were adequately designed to infer causality, and thus the expected effect may have been diminished by confounding (Pinstrup-Anderson et al., 1993). When supplementary feeding is demonstrated to be given in adequate amounts to malnourished young children, stature has improved (Habicht and Butz, 1979). Benefits have resulted from a number of food supplementation and health interventions that have produced demonstrable changes in food intake. Some interventions that supported improved growth and development started at early stages of life, even as early as the prenatal period (Heikens et al., 1993; Martorell and Habicht, 1986; Martorell et al., 1982; Mora et al., 1981; Walker et al., 1991). After 14 months of food supplementation, 1- to 5-year-old children who had heights-for-age below the 3rd percentile of U.S. heights-for-age gained, on

ANTHROPOMETRIC RISK CRITERIA 108 average, 1.5 cm more in stature than children who were above the 3rd percentile (Rao and Naidu, 1977). Early supplementary feeding also has been shown to improve cognition in adolescence (Pollitt et al., 1993). Compared with results from developing countries, benefits in terms of improved linear growth from nutrition and health interventions, including the WIC program, are much smaller and often statistically insignificant in industrialized countries. Edozien et al. (1979) found that the WIC program had a significant impact on the linear growth of infants and children (±0.23–0.56 cm) after 6 to 11 months of program participation. However, because short stature was used as a criterion for eligibility for participation in the WIC program, the increase in average length after WIC program participation might be due to regression to the mean: those whose values were low tend to rise and those whose values were high tend to fall independent of any treatment effect (Rush et al., 1988a). In one study that made more than one follow-up measurement after enrollment in the WIC program, a decrease in the prevalence of short stature (defined as below the 10th percentile) was seen between follow-up visits only in children ages 6–23 months (CDC, 1978). Hick and colleagues (1982) reported that children who had received WIC program benefits prenatally were less likely to be below the 10th percentile of height for their age group. Rush and colleagues (1988b) found statistically significant increases in the heights of infants and children who participated in the WIC program either prenatally or within 3 months of birth, once differences in birth weight were taken into account in their analyses. Furthermore, these investigators showed effects of the WIC program specific to some minority children enrolled in the program early in life. In comparison with controls, for example, Hispanic children enrolled before their first birthday had smaller discrepancies in stature than white or black children enrolled later. Among the many factors that explain the varying effectiveness of food supplementation and health intervention in improving linear growth, age and infectious disease are now being reemphasized. Increased age tends to decrease the responsiveness of growth to food supplementation. Other things being equal, food supplementation of infants generates a greater response than food supplementation of children (Martorell et al., 1994). Within the period of infancy, the greatest response of stature to nutrition supplementation coincides with weaning (ages 3–6 months) and the peak incidence and duration of infectious diseases (ages 9–12 months) (Lutter et al., 1990). In a Guatemalan food supplementation study, each 100 kcal of supplement received per day was associated with approximately 5 mm in additional gains in stature in children age 2 years and 4 mm in those age 3 years. Similar age differences in impact have been noted in India (Gopalan et al., 1973) and in Jamaica (Walker et al., 1991). A high frequency of infections increases nutrition requirements, and dietary intakes that would otherwise be sufficient become inadequate. Food supplementation

ANTHROPOMETRIC RISK CRITERIA 109 benefits not only children who have inadequate dietary intakes, but also those who have high rates of infections, in that supplementation protects children from the negative effects of infections on growth (Lutter et al., 1989). Food supplementation combined with treatment of infections often results in a height response greater than that from either food supplementation or treating the infection alone (Heikens et al., 1993; Lutter et al., 1989). Despite the improved linear growth demonstrated by many food supplementation studies, the mean stature of children, particularly older children, was often less than that of children in higher socioeconomic groups and less than the 50th percentile of the NCHS-CDC reference standard. This indicates that the interventions overcome only part of the height deficits incurred by stunted children (Lutter et al., 1989; Martorell and Habicht, 1986; Mora et al., 1981; Walker et al., 1991). Complete reversal of stunting may take several generations and may involve broad improvements in socioeconomic status and general living conditions. In this sense, mean height-for-age among older children at population levels is a useful indicator of health and nutrition benefit from long-term socioeconomic development. Use of Short Stature as a Nutrition Risk Criterion in the WIC Setting Use of short stature as a risk criterion by state WIC agencies is summarized in Table 4-1. Cutoff points ranged from the 5th to 25th (infants) and the 5th to 30th (children) percentiles, with the median values being the 5th (infants) and 10th (children) percentiles (USDA, 1994). Measuring an infant's length is difficult compared with measuring a child's standing height, but it still easier and less expensive and invasive than many biochemical and clinical assessments. Recommendation for Short Stature The risk of short stature that is caused by inadequate nutrition and poor health is well documented for infants and children, and the anthropometric measurement is practical in the WIC setting. There is clear evidence that short stature that resulted from malnutrition may respond to appropriate health and nutrition interventions Therefore, the committee recommends use of short stature as a nutrition risk criterion for infants and children by the WIC program, with a cutoff value of below the 5th percentile.

ANTHROPOMETRIC RISK CRITERIA 110 Underweight Underweight is defined by a weight-for-height below a certain cutoff in comparison with the reference standard of the NCHS and the CDC. Underweight reflects the body's thinness, but the term does not necessarily imply the nature and causes of underweight. The term wasting applies to underweight that results from a recent abnormal process leading to significant failure to gain weight or to the loss of weight (WHO, 1995). Differentiation between underweight and wasting therefore requires understanding of the process that leads to underweight. Prevalence of and Factors Associated with Underweight The prevalence of underweight, defined as weight-for-height below the 5th percentile of the reference standard in the general U.S. population, was less than 5 percent in 1991 (Yip et al., 1992a). A similar prevalence of underweight was seen in each of five racial/ethnic groups: white, black, Hispanic, Indian, and Asian. Poverty, infectious disease, and inadequate energy intake, especially occurring recently, are major factors that contribute to a higher than expected prevalence of underweight. The effect of diet on a body's thinness has been suggested to be related more to a total energy deficit than to deficits of any specific nutrients (Malcolm, 1978; Waterlow, 1978). Sudden disasters or seasonal food shortages increase the prevalence of underweight in affected areas (Brown et al., 1982; Yip and Sharp, 1993). In the United States, where the overall prevalence of underweight is low, relatively little underweight can be attributed to nutrition and health problems at the population level. This does not mean, however, that underweight reflecting poor nutrition status is not present among some subgroups of the population, especially low-income subgroups. Low-income U.S. infants and children have a higher than expected prevalence of underweight, and the degree of underweight is often serious (CDC, 1987; Jones et al., 1985; Miller and Korenman, 1994; Miller et al., 1989; Owen et al., 1974). Infectious disease, as well as reduced dietary intake, may contribute. Severely wasted infants with no evidence of medical causes for their wasting but who respond to feeding treatment have been reported among low-income families and teenage mothers (Listernick et al., 1985). For infants, especially during their first 6 months, formula feeding does not afford the same protection against common infections diseases, and food-borne illness, as does breastfeeding (IOM, 1990). During late infancy, inappropriate weaning and feeding practices also contribute to the development of underweight (IOM, 1991). During the entire period of infancy and childhood, birth weight has a strong influence on weight-for-height values. Infants with lower

ANTHROPOMETRIC RISK CRITERIA 111 birth weights, even if they are within the normal range, are more likely to be thinner (Binkin et al., 1988). Given the same birth weights, premature infants have higher weights-for-height than infants with fetal growth restriction (Binkin et al., 1988). Among the nonpathologic factors affecting an infant's weight-for-height, a notable one is feeding practice. Breastfed infants living under favorable conditions and infants studied in various geographic areas have been reported to grow faster than the NCHS weight-for-height norm during the first 6 months and then slower than this norm after the recommended exclusive breastfeeding period (WHO, 1995). The absolute deviation from the reference median in each period was a z-score of about 0.2 (a change of 8 percentiles). The reasons for and consequences of this marked difference are not yet understood. Other nonpathologic factors that reduce weight-for-height of infants include high altitude (Yip et al., 1988), health and nutrition problems of the parents, parental short stature, and certain racial and ethnic backgrounds. The influence of parents' stature and race is generally minor. Underweight as an Indicator of Nutrition and Health Risk To study the relationship of underweight to mortality, 2,019 Bangladesh children ages 13 to 23 months were followed for 24 months (Chen et al., 1980). Severe, but not mild to moderate, underweight was related to higher rates of mortality. However, compared with other anthropometric predictors (e.g., arm circumference, height-for-age, and weight-for-age), weight-for-height had the lowest ability to predict subsequent mortality. Similar studies have since been conducted in other developing countries. In most of those studies, weight-for- height was indeed a weak predictor of subsequent child mortality (Alam et al., 1989; Bairagi, 1981; Bagenholm and Nasher, 1989; Briend et al., 1986, 1987; Heywood, 1982; Kasango Project Team, 1983; Katz et al., 1989; Smedman et al., 1987; Vella et al., 1994). Analysis of some of these studies with a multiplicative model that incorporated both disease burden and nutrition status showed something different from previous investigations: a substantial proportion of mortality could be explained by mild to moderate malnutrition, and there was no threshold in the relationship between malnutrition and death at the population level (Pelletier et al., 1993). Thus, even mild to moderate malnutrition, the kind more commonly seen in low-income populations in industrialized countries, is of concern. Underweight is also a poor correlate of short stature at either an individual or a population level (Gorstein et al., 1994; Haaga, 1986; Victora, 1992), but new approaches to examining this relationship may be needed (Brown et al., 1982; Martorell, 1989; Waterlow, 1994a).

ANTHROPOMETRIC RISK CRITERIA 112 Underweight and other health and nutrition risks may share common determinants, or they may be causally related to one another; but other factors may affect the way in which they are related. Underweight and short stature, for example, are two different dimensions of poor growth, and each may be related to different aspects of diet (Garrow et al., 1994; Victora, 1992). Compared with height-for-age and weight-for-age, weight-for-height is an equally good or even better predictor of subsequent respiratory infections and diarrhea in some developing countries (Black et al., 1984; Delgado et al., 1983; Schelp et al., 1990; Tomkins, 1981). Across different communities, wasting was also a more consistent predictor of infections than was stunting (Lindtjorn et al., 1993). Underweight as an Indicator of Nutrition and Health Benefit Although underweight is in general a poor indicator of risk, many studies show that it is a fairly good indicator that a severely wasted infant or child being treated for malnutrition would benefit from participation in a feeding program. Positive responses might take the form of increases in weight-for-height for age, and decreases in morbidity and mortality. Significant responses in weight-for- height were reported in infants and children attending nutrition-rehabilitation centers, and the extent of the response was hypothesized to be related to initial levels of malnutrition (Beaudry-Darismé and Latham, 1973; Beghin and Viteri, 1973; Rivera, 1988). In areas with a high rate of malnutrition, a common practice of feeding programs is that one uses weight-for-height to select individuals for enrollment. Review of some of the early food supplementation studies reveals that, in general, supplementary feeding, when given in adequate amounts to malnourished infants, had a positive effect on weights-for-height (Habicht and Butz, 1979; Rivera, 1988). No significant improvement in weight was found when there was no clear evidence of dietary improvement. On the other hand, in studies that noted an improvement in total dietary intake after supplementation, positive changes in body weight were consistently found among children with low weights-for- height or weights-for-age. Two common difficulties in evaluating the response of weight-for-height in intervention studies were noted. One is the absence of an appropriate comparison group; this lack may bias the response in either direction. The other difficulty is the presence of regression to the mean, which is especially relevant to weight- for-height, because measurements involve both height and weight. If a child is admitted to an intervention program only because he or she suffered from a temporary deficiency in weight-for-height or a measurement error, he or she is more likely to have a higher weight-for-height some time later, even in the absence of any program effect. However, in studies that adopted appropriate designs and analytical methods to reduce such problems, weight-for-height was

ANTHROPOMETRIC RISK CRITERIA 113 still responsive to interventions for malnourished children in developing countries (Heikens et al. 1989, 1993; Rivera et al. 1991). Positive changes in weight-for-height as a response to nutrition and health interventions have also been observed in some populations in industrialized countries, but they have been much smaller and often statistically insignificant. Such evidence can be found with the WIC program (Edozien et al., 1979; Heimendinger et al., 1984; Hick et al., 1982). The prevalence of underweight (defined as less than the 10th percentile) among infants enrolled in the WIC program, for example, was negatively related to the number of follow-up visits (a proxy for duration in the program) (CDC, 1978). Participation in the WIC program had no significant impact on weight but had a positive effect on weight- for-height for infants and children who had participated in the program either prenatally or within 3 months of birth (Rush et al., 1986). Changes in weight-for-height are associated negatively with the initial level of wasting, which cannot be attributed to the effect of regression to the mean (Rivera, 1988). This explains why in developing countries the benefit from food supplementation in terms of weight changes is usually small or even indiscernible. Although weight-for-height can be calculated without knowing the age, changes in weight-for-height as a response to food supplementation usually increase with an infant's age and peak between the ages of 6 and 24 months, which coincides with weaning and the peak incidence and duration of diarrhea and other infectious diseases (Heimendinger et al., 1984; Lutter et al., 1990; Martorell and Habicht, 1986). The presence of infections or other diseases may offset the positive effect of food supplementation on weight changes. Weight-for-height has also been shown to be an indicator of benefit of nutrition intervention when defined as improvements in linear growth and survival. A recent study in Guatemala indicated that weight-for-height, but not height-for-age, at 3 and 6 months of infancy were significant determinants of benefit from supplementation as measured by height-for-age at 3 years of age (Ruel et al., 1995). The study suggested that lower weight-for-height increased the effect of food supplementation on height. In addition, although weight-for- height may decrease when interventions are removed, lasting improvements in linear growth and survival can be achieved by targeting interventions to wasted children. Using weight changes as an indicator of benefit, Rao and Naidu (1977) indicated that Indian children who were wasted gained more weight following food supplementation than did children who were stunted. In famine-prone areas of Africa, cutoff values of weight-for-height in a population have been used successfully to trigger emergency food relief efforts to reduce mortality in young children (Lawrence et al., 1994).

ANTHROPOMETRIC RISK CRITERIA 114 Use of Underweight as a Nutrition Risk Criterion in the WIC Setting Underweight is widely used as a criterion of nutrition risk in infants and children, respectively (see Table 4-1). Specific cutoff points ranged from the 5th to the 25th percentiles for infants, and the 5th to the 30th percentiles for children, with the median value for both infants and children being the 10th percentile (USDA, 1994). Measurement of underweight is relatively easy to implement and highly feasible in the WIC program. Recommendation for Underweight The risk of underweight that results from nutrition and health problems is documented in infants and children, and a practical method to identify this risk is available. There is indirect evidence from supplementation trials that underweight infants and children can benefit from participation in the WIC program. Therefore, the committee recommends the use of underweight as a nutrition risk criterion for infants and children, with a cutoff value of the 5th percentile. Low Head Circumference Low head circumference (LHC) is diagnosed when an infant's head circumference (occipital frontal circumference) is below a specified cutoff point using NCHS-CDC reference data for comparable age. Head circumference during infancy and early childhood relates directly to brain weight and volume (Bray et al., 1969; Cooke et al., 1977), and LHC is widely used in clinical settings to screen for potential developmental or neurologic disabilities in infants and children (Avery et al., 1972; Babson and Henderson, 1974). However, LHC alone does not necessarily indicate an abnormal head size. The diagnosis of abnormal LHC (microcephaly) must also be based on the presence of other evidence and knowledge of the causes of LHC. Prevalence of and Factors Associated with LHC Some evidence indicates that the mean head circumference is increasing among healthy populations in industrialized countries (Gerver et al., 1989; Lindgren et al., 1994; Ounsted et al., 1985; Paul et al., 1986; Tsuzaki et al., 1990). This positive secular trend should be taken into account in estimating and comparing the prevalence of LHC. No specific information is available regarding the prevalence of LHC in low-income U.S. populations, except that

ANTHROPOMETRIC RISK CRITERIA 115 head circumference is in general lower in children of lower socioeconomic status (see below). LHC is related to a variety of genetic, nutrition, and health factors. Although some LHCs are normal, some result directly from impaired brain development during pregnancy and the perinatal or postnatal period. Abnormal LHCs can be caused by genetic disorders such as autosomal and sex chromosome abnormalities (Palmer et al., 1992; Ratcliffe et al., 1994). Health factors related to LHC include phenylketonuria, exposure to neurotoxic substances, cocaine and alcohol use during pregnancy, intracranial hemorrhages, perinatal asphyxia, ischemic brain injury, and other major congenital central nervous system abnormalities (Eckerman et al., 1985; Ikenoue et al., 1993; Levy et al., 1994; Little and Snell, 1991; Nulman et al., 1994; Regev and Dubowitz, 1988; Verkerk et al., 1994). Malnutrition during critical stages of brain development (i.e., from early fetal life through approximately 3 months following delivery) can result in reduced numbers of brain cells (Manser, 1984; Dobbing, 1973; Winick, 1969; Winick and Rosso, 1969), which may correlate with diminished growth of the head and other dimensions of growth (Dobbing, 1974; Stein et al., 1975). Thus, maternal prepregnancy weight, fat stores, and weight gain during pregnancy positively predict the head circumferences of newborn infants (Crawford et al., 1993; Miller and Merritt, 1979), and infants with fetal growth restriction tend to have smaller heads than infants with normal weight-for-gestational age (Kramer et al., 1989). Ample evidence indicates that head size is related to socioeconomic status, and the relationship is mediated in part by nutrition factors. The head circumference of children in developing countries is significantly lower than that of children in industrialized countries (Hamill et al., 1979; Malina et al., 1975). In industrialized countries, children of low socioeconomic status usually have mean head circumferences less than those of children of higher socioeconomic status (CDC, 1972; Cook et al., 1976; Niswander and Gordon, 1972; Wright et al., 1992). LHC as an Indicator of Nutrition and Health Risk Abnormal LHC because of pathologic processes is indicative of future risk. The most common risk is poor neurocognitive abilities. Compared with infants of very low birth weight (VLBW) who have larger head circumferences, infants with very low birth weights (< 1.5 kg) who have a smaller head circumference have more motor abnormalities at 12 months of age (Simon et al., 1993), lower IQs at 3 years (Hack and Breslau, 1986), and poorer cognitive function, academic achievement, and behavior at 8 years (Hack et al., 1991). Because

ANTHROPOMETRIC RISK CRITERIA 116 LHC is associated with LBW and poor growth, LHC is also a strong marker of growth retardation and other dimensions of growth and development. Among infants who are SGA, those with LHC have neonatal mortalities significantly greater than those without LHC (Lubchenco, 1981). These infants with both SGA and LHC, termed proportionally small, also have higher rates of morbidity such as birth asphyxia, respiratory distress, and neonatal infections but less hyperbilirubinaemia than disproportionally small infants (i.e., infants with SGA but not LHC) (Cuttini et al., 1991). A small head circumference during infancy is even hypothesized to be a contributing factor to death from cardiovascular disease in adult life (Barker et al., 1993b). LHC as an Indicator of Nutrition and Health Benefit In contrast to many studies examining head circumference as a pregnancy outcome, only a few have linked head circumference changes to nutrition and health interventions directed to infants and children. Stunted Jamaican children ages 9 to 24 months were randomly assigned to four groups: control, milk-based formula supplementation, psychosocial stimulation, and both interventions (Walker et al., 1991). After 12 months, supplemented children had an average increase of 0.3 cm in head circumference, along with other improvements in growth. No changes were observed with stimulation. Most effects from food supplementation occurred in the first 6 months. A positive but statistically insignificant association was demonstrated between head circumference and WIC program participation among infants and children (Rush et al., 1988b). The association was stronger in children who were black, boys, or living alone with their mothers. In neither the Jamaican nor the U.S. study was LHC used as a major criterion to select children for supplementation interventions. Although more data are needed, increases in head circumference associated with postnatal nutrition intervention are plausible because they are parallel to the changes associated with prenatal interventions. Furthermore, the brain grows rapidly during infancy: the rate of head growth exceeds the rate of length and weight gain during the first 6 months of life. Thus, nutrition factors can be expected to have an important effect during this critical period (Dobbing, 1970, 1973). Use of LHC as a Nutrition Risk Criterion in the WIC Setting Few state WIC agencies presently use low head circumference as a nutrition risk criterion (USDA, 1994) (see Table 4-1). A head circumference can be measured more easily than length or height (Bhushan and Paneth, 1991; Kramer et al., 1989), but efforts should be made to avoid the influence of scalp edema or head molding (particularly after a difficult vaginal or forceps-assisted delivery)

ANTHROPOMETRIC RISK CRITERIA 117 on head circumference measurements in infants. A head circumference measurement should be compared with reference values for infants of comparable age rather than comparable length or height. Recommendation for LHC The risk of LHC is well documented in infants, and a practical method to identify this risk is available. There is indirect scientific evidence, suggestive evidence from a WIC program evaluation, and a theoretical basis for concluding that infants with LHC benefit from participation in the WIC program. Therefore, the committee recommends use of LHC as a nutrition risk criterion for infants by the WIC program, with a cutoff value of below the 5th percentile of increments in head circumference for age (Roche and Himes, 1980). Large for Gestational Age Large for gestational age (LGA) is defined as a birth weight above a specified cutoff point using reference data for comparable gestational age. LGA is sometimes termed high birth weight for full-term and postterm infants, but LGA may also occur with preterm birth. LGA represents the upper end of the birth weight distribution. Prevalence of and Factors Associated with LGA In the United States, 12.7 percent of white infants and 5.5 percent of black infants weighed 4,000 g or more at birth in 1985 (IOM, 1990). The prevalence of infants who weighed 4,500 g or more is estimated to be less than 2 percent (Puffer and Serrano, 1987). Maternal obesity, high prepregnancy weights, and large gestational weight gains contribute significantly to LGA (IOM, 1990). Many newborn babies who are LGA are born to women with diabetes mellitus, which may or may not have been diagnosed before or during pregnancy (Lubchenco, 1981). LGA can also be genetically determined (WHO, 1995). LGA as an Indicator of Nutrition and Health Risk Infant mortality rates are higher among full-term infants who weigh more than 4,000 g than for infants weighing between 3,000 and 4,000 g (IOM, 1973; Puffer and Serrano, 1987). However, the likelihood of dying because of a birth weight above 4,000 g is much less than that of infants with LBW (i.e., those weighing less than 2,500 g) (IOM, 1990) and the number of infant deaths

ANTHROPOMETRIC RISK CRITERIA 118 attributed to LGA is small. When LGA occurs with preterm birth, the mortality risk is higher than that when either condition exists alone (Battaglia et al., 1966) (see also Chapter 5). One study suggests that infants with a history of LGA are likely to remain taller and heavier and to have a higher risk of overweight during childhood than infants without LGA (Binkin et al., 1988). The committee found no other evidence that LGA indicates nutritional risk. LGA as an Indicator of Health and Nutrition Benefit When treated appropriately, LGA infants usually have a good prognosis (Lubchenco, 1981). LGA infants may benefit from the WIC program in the same ways that other newborns do: support from promoting breastfeeding and healthy infant feeding practices, the provision of nutrient-dense supplemental foods to the mother or formula for the infants, and health referrals from the program to detect or treat medical complications that may accompany LGA. Use of the LGA as a Nutrition Risk Criterion in the WIC Setting For the 14 state WIC agencies using high birth weight as a risk criterion for determining WIC program eligibility for infants in 1992, cutoff points ranged from 4,000 to 5,000 g, and the median cutoff point was 4,500 g (USDA, 1994). Birth weight data are routinely collected in most hospitals and are readily available to the WIC program. Recommendations for LGA The nutrition risk of LGA is low in infants. The benefit of the WIC program to infants who are LGA is no greater than that to any other newborn. Therefore, the use of LGA as a risk criterion for WIC program participation is not recommended. However, if LGA continues to be used, the committee recommends that the cutoff point be above the 90th percentile on William's Birth Weight Curve (Williams et al., 1982). For infants born at 40 weeks of gestation, the 90th percentile corresponds to a birth weight of approximately 4,000 g. Overweight Overweight is defined by weight-for-height above a specified cutoff point using NCHS-CDC reference data (Kanders, 1995). The term overweight is preferred over obesity to describe high weight-for-height because high weights- for-height can be a result of either greater lean body mass or adiposity.

ANTHROPOMETRIC RISK CRITERIA 119 A distinction between overweight and obesity cannot be made just by measuring weight-for-height. The term obesity implies excessive fatness. Prevalence of and Factors Associated with Overweight The prevalence of overweight among infants and children in low-income U.S. families, defined as weight-for-height above the 95th percentile of the NCHS-CDC reference standard, was about 9 percent in 1991—higher than the expected 5 percent in a normal distribution (Yip et al., 1992a). The prevalence was higher in Hispanic, Native American, and black children than in white or Asian children. In humans, overweight because of excess body fat can result from excessive energy intake, decreased energy expenditure, or impaired regulation of energy metabolism. Obesity therefore reflects an imbalance between energy intake and energy expenditure and is related to environmental and genetic factors (Kanders, 1995). One probable environmental factor is prolonged overfeeding. Bottle feeding and early introduction of solid food may contribute to this practice, but overfeeding has not been confirmed as a major cause of obesity in studies that compared the food intakes of lean and obese infants and young children (Dietz, 1983). In fact, studies indicate that obese infants do not eat significantly more than their lean peers (Mumford and Morgan, 1982; Vobecky et al., 1983). Similar conclusions were also reached by studies of older children and adolescents (Dietz, 1983; Frank et al., 1978; Keen et al., 1979; Kromhout, 1983; Rolland- Cachera and Bellisle, 1986). However, most studies used recall data to estimate energy intakes, and such data are subject to a number of errors (see Chapter 6). The results of a few studies have suggested that dietary composition may play a role in obesity. It has long been known that a high-fat, low-protein diet increases body fat content in animals (Filer, 1993). In humans, a high-fat, low- carbohydrate diet induces slightly greater levels of energy storage compared with a low-fat, high-carbohydrate diet with an equal energy content (Pi-Sunyer, 1993). A study of 48 children ages 9 to 11 years examined the relationship of percentage of body fat (measured by triceps skinfold thickness) and total fat intake (Gazzaniga and Burns, 1993). After adjusting for energy intake, resting energy expenditure, and physical activity, the percentage of body fat correlated positively with intake of total, saturated, monounsaturated, and polyunsaturated fatty acids and negatively with carbohydrate and total energy. In a cohort study of 146 children ages 3 to 5 years, an increase in BMI over a 3-year period was associated with an increased intake of energy from fat but not an increased total energy intake (Klesges et al., 1995). These findings indicate the importance of an appropriately balanced diet for preventing and treating obesity.

ANTHROPOMETRIC RISK CRITERIA 120 Some evidence indicates that low energy expenditure contributes to the development of obesity. In a study by Roberts and colleagues (1988), total energy expenditure and metabolizable energy intake were measured by the doubly labeled water method and by indirect calorimetry at 3 months of age. Total energy expenditure was about 20 percent lower in the infants who became overweight by the age of 1 year than in the infants who did not. There was no significant difference in postprandial metabolic rates, suggesting that physical activity, not thermogenesis, was reduced in the overweight infants. Fontvieille and Ravussin (1993) compared the resting metabolic rates of Pima Indian children ages 3 to 5 years with those of white children. Although the Pima Indian children were taller, heavier, and fatter than the white children, the resting metabolic rate adjusted for body size, composition, and sex was similar in the two groups. Also, Pima Indian girls spent little time playing sports and considerable time watching television. In boys, the more time spent in sports activity, the leaner the child. Dietz and Gortmaker (1985) reported a direct association between television viewing and obesity in children. Genetic factors have long been hypothesized to be associated with obesity (Garn and Clark, 1976; Garn et al., 1989). The correlation between obesity in the parents and obesity in their children is often strong (Burns et al., 1993; Garn, 1985; Klesges et al., 1995). The risk of obesity among children is lowest when neither parent is obese, higher when one parent is obese, and highest when both parents are obese (Dietz, 1983). The children of obese parents are also more likely to develop persistent obesity than other children (Price et al., 1990). Genetic studies in animals have shown that mutations at loci on six different chromosomes produce the obese phenotype in mice (Friedman and Leibel, 1990; Leiter, 1993). Recently, an obese (ob) gene was identified in mice that, when mutated, causes profound obesity and type II diabetes resembling morbid obesity in humans (Zhang et al., 1994). Overweight as an Indicator of Nutrition and Health Risk Just as infantile fatness (as measured by subcutaneous fat) predicts fatness during childhood (Leung and Robson, 1990), weight-for-height during early infancy predicts weight-for-height during late infancy and childhood (Binkin et al., 1988). Similarly, children who are overweight are more likely than other children to become overweight adolescents and adults (Mossberg, 1989; Sorensen and Sonne-Holm, 1988; Stark et al., 1981). Rolland-Cachera and co-workers (1987, 1989) followed more than 100 French children from age 1 year to adulthood. They showed that BMI in childhood significantly predicted BMI at 18 to 25 years in both sexes; the prediction became stronger as the children became older. Associations between obesity in childhood and obesity in adulthood were consistently positive in a review of studies published between

ANTHROPOMETRIC RISK CRITERIA 121 1970 and 1992 (Serdula et al., 1993). About one-third of obese preschool-age children and about half of obese school-age children were obese as adults. The risk of adult obesity was at least twice as high for obese children as for nonobese children and was even greater for children who were obese at older ages. Studies have shown that obesity in adulthood is an important risk factor for hypertension, diabetes, heart disease, gall bladder disease, certain cancers, and premature mortality (NIH, 1985). Direct relationships between obesity and adverse health consequences are not as extensively documented in children as in adults. Among a few early studies that suggested a more frequent occurrence of illness in obese infants than in nonobese infants, methodologic problems such as inappropriate controls and diagnoses tend to invalidate their conclusions (Mallick, 1983). One study suggested that obese children may manifest many of the same disturbances as obese adults, including hyperinsulinism, hyperlipidemia, and hypertension (Rosenbaum and Leibel, 1989). Javier-Nieto and co-workers (1992) linked weight and height measures for children ages 5 to 18 years from 1933 to 1945 with follow-up mortality data over 30 to 40 years for both sexes combined. They found a statistically significant linear trend in the odds of adult mortality by quintile of childhood relative weight. However, because the measurements were obtained in the 1930s and 1940s from children who had relatively low weights- for-height by current standards, it is not clear how applicable the results are to children today. The censure of overweight people in modern industrial societies may lead to social and psychological problems, including feelings of inadequacy and poor self-esteem (Gortmaker, 1993; Wadden et al., 1984). Misclassification of a normal child as obese may have adverse consequences (Mallick, 1983). Unjustified and medically unsupervised dietary restriction based on such a misclassification may result in permanent stunting of growth and delayed development in infants and children (Lifshitz and Moses, 1989; Pugliese et al., 1983; Taitz, 1977). Even modest energy restriction in children with increased adiposity has been associated with a significant reduction in rate of increase in height (Dietz and Hartung, 1985). Because of these well-recognized health risks, the Committee on Nutrition of the American Academy of Pediatrics (1981) has recommended that dietary energy restriction not be used as a means to induce weight loss in infants and children. Overweight as an Indicator of Nutrition and Health Benefit Inasmuch as obesity during infancy and childhood is related to obesity during adulthood and adult obesity is associated with a number of adverse health consequences, it is assumed but not verified that treatment of excess adiposity in young children will be more effective than treatment of adiposity in

ANTHROPOMETRIC RISK CRITERIA 122 adults. This is because behavioral patterns and social environments can be strongly influenced by the caregiver, and reducing potential risk factors (e.g., hyperlipidemia and hypertension) as early as possible may maximize beneficial effects for preventing long-term morbidity and mortality. A 5- and 10-year follow-up of children from a family-based behavioral treatment program showed that weight reductions were significant compared with those for controls, but even in the best performing group, 30 to 40 percent of children were still overweight at 10 years (Epstein et al., 1990). Little information is available with regard to other long-term health consequences. Commonly accepted weight control regimens emphasize sufficient energy content and adequate vitamins, minerals, and proteins in the diet to meet requirements for normal growth, along with increased physical activity and behavior modification (CN-AAP, 1981; Epstein and Wing, 1987). More data are needed to identify optimal treatments for obesity as judged by their impacts on health outcomes, and the preventive roles of nutrition and health interventions require further investigation (Flegal, 1993; Robinson, 1993). Overweight infants and children may benefit from participation in the WIC program by receiving foods that are rich in such nutrients as protein, iron, calcium, vitamin A, and vitamin C. A food package modified to be low in fat might be especially beneficial. For those who are overweight because of obesity, the nutrient-dense WIC food package together with sensible eating plans provided by the WIC program may help to improve dietary quality and establish healthy eating habits. These interventions may place participants in a better position for future success of weight control and help them avoid the risks of unwarranted and self-imposed weight loss activities. Also, through its health referral function, the WIC program can help obese individuals with clinical complications to obtain early diagnosis and treatment by health professionals. Use of the Overweight as a Nutrition Risk Criterion in the WIC Setting Table 4-1 summarizes use of overweight as a nutrition risk criterion by state WIC agencies. The cutoff points used for overweight ranged from the 89th to 95th percentiles for the infants and 75th to 95th percentiles for children. Recommendation for Overweight The risk of overweight is documented in infants and children, and the method for identifying overweight is straightforward. There is a theoretical basis for benefit from participation in the WIC program. Therefore, the committee recommends the use of overweight as a nutrition risk criterion for infants and children in the WIC program, with a cutoff value at above the 95th percentile of NCHS-CDC references.

ANTHROPOMETRIC RISK CRITERIA 123 Slow Growth Assessing gain or loss of weight and growth involves repeated anthropometric measurements over time. Multiple measurements provide confirmatory information about attained growth and a dynamic picture of growth changes (velocity) that permit the early detection of slow growth. However, identification of abnormal growth cannot rely on measuring growth changes alone. A lack of weight gain may be a result of a successful weight control program. The diagnosis of slow growth must consider other evidence including previous growth conditions and possible causes of growth changes. Failure to thrive (FTT), a condition in which growth is abnormally slow, is a medical diagnosis and is covered in Chapter 5. Anthropometric assessment in the WIC program may identify the need for referral for the diagnosis and treatment of FTT of any origin. Nonorganic failure to thrive is a medical term for poor growth without apparent medical cause. Weight change is the anthropometric measurement that is most indicative of slow growth, especially in infants and young children. Two types of weight criteria are used in the literature: those based on weight loss and those based on attained growth below a specified percentile on the NCHS-CDC reference curve. An easy and common approach to identifying weight loss in a clinical setting is to plot a child's weights measured over time on the NCHS-CDC reference curve and examine if the plotted points cross major percentile lines more than once or fall from the lowest percentile. Prevalence of and Factors Associated with Slow Growth Undereating, for any number of reasons, and disease conditions are the main causes of abnormally slow growth. However, some infants who apparently have a genotype for a smaller size have a normal downward shift in growth rate between 3 and 18 months of age (Smith et al., 1976), which may be mistaken for growth faltering. Factors that are associated with undereating by an infant or child include lack of social support for the caregiver; an adverse social and psychological environment; a disorganized family; depressed parents or caregivers; and the caregiver's lack of education, health and nutrition knowledge, mental and physical abilities, and responsibility for child care (Lifshitz et al., 1991; McCrae et al., 1978).

ANTHROPOMETRIC RISK CRITERIA 124 Slow Growth as an Indicator of Nutrition and Health Risk Infants and children who have slow growth may be malnourished and likely to remain so over an extended period (Oates et al., 1985). Persistent malnutrition may be translated into elevated morbidity and mortality risks, especially when diseases secondary to nonorganic FTT occur. If an infant or child has FFT, he or she may remain developmentally delayed despite weight gain (see also Chapter 5) (Drotar and Sturm, 1992; Wolke et al., 1990). Slow Growth as an Indicator of Nutrition and Health Benefit Otherwise healthy infants and children with abnormally slow growth can certainly benefit from nutrition and health interventions to improve weight and height gain. Indeed, such a benefit has been recognized as so plausible and unique that a formal diagnosis of nonorganic FTT must be based on a positive response of weight gain to nutrition rehabilitation (Lifshitz et al., 1991; McCrae et al., 1978). Interventions promote compensatory catch-up growth that restores deficits in weight and other dimensions of growth (Casey and Arnold, 1985). Although nutrition and health interventions may restore physical growth, they may only partially correct any developmental delays (Frank and Zeisel, 1988). An actual diagnosis of FFT should be made by a physician. Use of Slow Growth as a Nutrition Risk in the WIC Setting Table 4-1 summarizes use of abnormal growth as a nutrition risk criterion by state WIC agencies. The method of measurement (i.e., attained growth versus growth velocity) and cutoff points varied greatly. Identifying poor growth requires repeated measurements, which is sometimes impossible in the WIC setting. For recent immigrants especially, longitudinal data may be unavailable for identifying abnormally slow growth. Recommendation for Slow Growth The risk of slow growth is well documented in infants and children, and repeated visits make its identification possible for some infants and children. There is an empirical and theoretical basis for infants and children with slow growth to benefit from participation in the WIC program. The committee recommends the use of slow growth as a nutrition risk criterion for infants and children, with a cutoff value of below the 3rd percentile of change in weight, stature, or head circumference for age (Roche and Himes, 1980).

ANTHROPOMETRIC RISK CRITERIA 125 SUMMARY AND CONCLUSIONS Conclusions Anthropometric measurements are objective, nonintrusive, and easy to obtain; and they have been used as major nutrition risk criteria in the WIC program. However, there are no clear cutoff points for distinguishing an abnormal from a normal state, and the measurements provide no specific information about the cause of a problem. In spite of this, the current emphasis on these risk criteria is justified and should be continued because most anthropometric criteria have reasonably close relationships with risks, benefits, or both. Improvements in measurements lead to program benefits. Anthropometric measurements are useful nutrition risk criteria for a number of conditions affecting pregnant or postpartum women, infants, and children. Their usefulness for women may improve if separate reference standards can be developed and tested for subgroups, such as adolescents and lactating women. Different cutoff points may be needed for setting the specific criteria for different groups or for different outcomes. The anthropometric criteria discussed here are at best weak predictors of health and nutrition outcomes. Given the multifactorial nature of pregnancy and lactational outcomes, it is likely that the use of combinations of anthropometric with other criteria may be more useful for predictive purposes than the use of a single criterion. Table 4-4 summarizes the committee's recommendations concerning the use of nutrition risk criteria for anthropometric measures. Research Needs 1. Establish reference standards for pregnant, breastfeeding, and postpartum weight-for-height. The most important gaps relate to cutoffs to assess inadequate and excessive maternal weight gain during pregnancy, and body weight status of postpartum lactating and nonlactating women. Studies are urgently needed to describe the distribution of these measures in normative populations, to validate cutoff values against health outcomes, and, using the principles described in Chapter 3, to establish cutoffs with the highest yield. 2. Establish reference standards for maternal weight gain during pregnancy and maternal weight change after delivery. 3. Determine the impact of WIC program participation on health outcomes for pregnant and lactating and nonlactating postpartum women who have specific risk factors. For example, it is important to understand whether WIC program participation increases maternal weight gain and thus birth weight,

ANTHROPOMETRIC RISK CRITERIA 126

ANTHROPOMETRIC RISK CRITERIA 127

ANTHROPOMETRIC RISK CRITERIA 128 whether WIC program participation has special benefit for women with prepregnancy underweight or short stature, and how the WIC program can affect long-term obesity in women. 4. Assess the effectiveness of interventions used to improve health and nutrition outcomes for LBW infants. 5. Relate body proportionality of SGA infants to risks and to potential benefits from interventions. 6. To ensure maximum benefit from the program, establish a priority system by comparing anthropometric criteria for their ability to predict the benefit intended by the program. 7. Examine the benefits of the WIC program relative to individual anthropometric criteria. Available data from the WIC program could be used for this purpose, or collection and analysis of these data could be organized. Such analysis would permit more accurate evaluation of the WIC program. 8. Compare populations with different distributions of an anthropometric measure (WHO, 1995) to determine the relative effects of different cutoff points on detection of nutrition and health risks and predictions of benefit. Results of this research will be useful for relating group attributes (e.g., low-income, lack of education, and minority background) to benefits from participation in the WIC program. REFERENCES Aaronson, L.S., and C.L. Macnee. 1989. The relationship between weight gain and nutrition in pregnancy. Nurs. Res. 38:223-227. Abraham, S., F.W. Lowenstein, and D.E. O'Connell. 1975. Preliminary Findings of the First Health and Nutrition Examination Survey, United States, 1971–1972: Anthropometric and Clinical Findings. DHEW Pub. No. (HRA) 75-1229. Rockville, MD: U.S. Department of Health, Education, and Welfare, National Center for Health Statistics. Abrams, B. 1988. Maternal weight gain and pregnancy outcome in overweight women. Clin. Nutr. 7:197–204. Abrams, B. 1991. Maternal undernutrition and reproductive performance. Pp. 31–60 in Infant and Child Nutrition Worldwide: Issues and Perspectives, F. Falkner, ed. Boca Raton, Fla.: CRC Press. Abrams, B. 1994. Weight gain and energy intake during pregnancy. Clin. Obstet. Gynecol. 37:515– 527. Abrams, B., and C. Berman. 1993. Women, nutrition and health. Curr. Probl. Obstet. Gynecol. Fertil. 16:3–61. Abrams, B., and V. Newman. 1991. Small-for-gestational-age birth: Maternal predictors and comparison with risk factors of spontaneous preterm delivery in the same cohort. Am. J. Obstet. Gynecol. 164:785–790. Abrams, B., and J. Parker. 1988. Overweight and pregnancy complications. Int. J. Obes. 12:293–303.

ANTHROPOMETRIC RISK CRITERIA 129 Abrams, B., and J.D. Parker 1990. Maternal weight gain in women with good pregnancy outcome. Obstet. Gynecol. 76:1-7. Abrams, B., and S. Selvin. 1995. Maternal weight gain pattern and birth weight. Obstet. Gynecol. 86:163-169. Abrams, B., V. Newman, T. Key, and J. Parker. 1989. Maternal weight gain and preterm delivery. Obstet. Gynecol. 74:577-583. Abrams, B., S. Carmichael, and S. Selvin. 1995. Factors associated with the pattern of maternal weight gain during pregnancy. Obstet. Gynecol. 86:170-176. ACC/SCN (United Nations Administrative Committee on Coordination/Subcommittee on Nutrition). 1992. Second Report on the World Nutrition Situation, Vol. 1. Global and Regional Results. Geneva: ACC/SCN. ACOG (American College of Obstetricians and Gynecologists). 1993. Nutrition during pregnancy: ACOG Technical Bulletin No. 179. Int. J. Gynecol. Obstet. 43:67-74. Adair, L.S., and E. Pollitt. 1985. Outcome of maternal nutritional supplementation: A comprehensive review of the Bacon Chow study. Am. J. Clin. Nutr. 41:948-978. Alam, N., B. Wojtyniak, and M.M. Rahaman. 1989. Anthropometric indicators and risk of death. Am. J. Clin. Nutr. 49:884-888. Allen, L.H. 1994. Nutritional influences on linear growth: A general review. Eur. J. Clin. Nutr. 48 (suppl. 1):75-89. Altman, D.G., and F.E. Hytten. 1989. Intrauterine growth retardation: Let's be clear about it. Br. J. Obstet. Gynaecol. 96:1127-1132. Ashworth, A., and R.G. Feachem. 1985. Interventions for the control of diarrheal diseases among young children: Prevention of low birth weight. Bull. WHO 63:165-184. Atkinson, S.A., L.A. Hanson, and R.K. Chandra, eds. 1990. Human Lactation 4: Breastfeeding, Nutrition, Infection and Infant Growth in Developing and Emerging Countries. St. Johns, Newfoundland: ARTS Biomedical Publishers. Avery, G.B., L. Meneses, and A. Lodge. 1972. The clinical significance of ''measurement microcephaly". Am. J. Dis. Child. 123:214-217. Babson, S.G., and N.B. Henderson. 1974. Fetal undergrowth: Relation of head growth to later intellectual performance. Pediatrics. 53:890-894. Bagenholm, G.C., and A.A. Nasher. 1989. Mortality among children in rural areas of the People's Democratic Republic of Yemen. Ann. Trop. Paediatr. 9:75-81. Bairagi, R. 1981. On validity of some anthropometric indicators as predictors of mortality. Am. J. Clin. Nutr. 34:2592-2594. Baird, D. 1977. Epidemiological patterns over time. Pp. 5-15 in the Epidemiology of Prematurity, D.M. Reed and F.J. Stanley, eds. Baltimore, Md.: Urban and Shwarzenberg. Balcazar, H., and J.D. Haas. 1991. Retarded fetal growth patterns and early neonatal mortality in a Mexico City population. Bull. Pan. Am. Health Org. 25:55-63. Barker, D.J., P.D. Winter, C. Osmond, B. Margetts, and S.J. Simmonds. 1989. Weight in infancy and death from ischaemic heart disease. Lancet 2:577-580. Barker, D.J., P.D. Gluckman, K.M. Godfrey, J.E. Harding, J.A. Owens, and J.S. Robinson. 1993a. Fetal nutrition and cardiovascular disease in adult life. Lancet 341:938-941.

ANTHROPOMETRIC RISK CRITERIA 130 Barker, D.J., C. Osmond, S.J. Simmonds, and G.A. Wield. 1993b. The relation of small head circumference and thinness at birth to death from cardiovascular disease in adult life. Br. Med. J. 306:422-426. Barros, F.C., S. R. Huttly, C.G. Victora, B.R. Kirkwood, and J.P. Vaughan. 1992. Comparison of the causes and consequences of prematurity and intrauterine growth retardation: A longitudinal study in southern Brazil. Pediatrics 90:238-244. Battaglia, F.C., T.M. Frazier, and A.E. Hellegers. 1966. Birth weight, gestational age, and pregnancy outcome with special reference to high birth weight-low gestational age infant. Pediatrics 37:417-422. Beaton, G.H., and H. Ghassemi. 1982. Supplementary feeding programs for young children in developing countries. Am. J. Clin. Nutr. 35:863-916. Beaton, G.H., A. Kelly, J. Kevany, R. Martorell, and J. Mason. 1990. Appropriate Uses of Anthropometric Indices in Children. ACC/SCN State of the Art Series, Nutrition Policy Discussion Paper. No. 7. Geneva: Administrative Committee on Coordination/ Subcommittee on Nutrition. Beaudry-Darismé, M., and M.C. Latham. 1973. Nutrition rehabilitation centers: An evaluation of their performance. J. Trop. Pediatr. Environ. Child Health 19:299-332. Beghin, I.D., and F.E. Viteri. 1973. Nutrition rehabilitation centers: An evaluation of their performance. J. Trop. Pediatr. Environ. Child Health 19:403-416. Berkowitz, G.S., and E. Papiernik. 1993. Epidemiology of preterm birth. Epidemiol. Rev. 15:414-443. Bhushan, V., and N. Paneth. 1991. The reliability of neonatal head circumference measurement. J. Clin. Epidemiol. 44:1027-1035. Binkin, N.J., R. Yip, L. Fleshood, and F.L. Trowbridge. 1988. Birth weight and childhood growth. Pediatrics 82:828-834. Black, R.E., K.H. Brown, and S. Becker. 1984. Malnutrition is a determining factor in diarrhea duration, but not incidence, among young children in a longitudinal study in rural Bangladesh. Am. J. Clin. Nutr. 39:87-94. Boardley, D.J. R.G. Sargent, A.L. Coker, J.R. Hussey, and P.A. Sharpe. 1995. The relationship between diet, activity, and other factors, and postpartum weight change by race. Obstet. Gynecol. 86:834-838. Boyd, N.R., Jr., and R. Windsor. 1993. A meta-evaluation of nutrition education intervention research among pregnant women. Health Educ. Q. 20:327-345. Bray, P.F., W.D. Shields, G.J. Wolcott, and J.A. Madsen. 1969. Occipitofrontal head circumference— an accurate measure of intracranial volume. J. Pediatr. 75:303-305. Briend, A., C. Dykewicz, K. Graven, R.N. Mazumder, B. Wojtyniak, and M. Bennish. 1986. Usefulness of nutritional indices and classifications in predicting death of malnourished children. Br. Med. J. Clin. Res. Ed. 293:373-375. Briend, A., B. Wojtyniak, and M.G. Rowland. 1987. Arm circumference and other factors in children at high risk of death in rural Bangladesh. Lancet 2:725-728. Brown, J.E., and P.T. Schloesser. 1990. Prepregnancy weight status, prenatal weight gain, and the outcome of term twin gestations. Am. J. Obstet. Gynecol. 162:182-186. Brown, K.H., R.E. Black, and S. Becker. 1982. Seasonal changes in nutritional status and the prevalence of malnutrition in a longitudinal study of young children in rural Bangladesh. Am. J. Clin. Nutr. 36:303-313.

ANTHROPOMETRIC RISK CRITERIA 131 Burns, T.L., P.P. Moll, and R.M. Lauer. 1993. Genetic models of human obesity—family studies. Crit. Rev. Food Sci. Nutr. 33:339-343. Caan, B., D.M. Horgen, S. Margen, J.C. King, and N.P. Jewell. 1987. Benefits associated with WIC supplemental feeding during the interpregnancy interval. Am. J. Clin. Nutr. 45:29-41. Casey, P.H., and W.C. Arnold. 1985. Compensatory growth in infants with severe failure to thrive. South. Med. J. 78:1057-1060. Caulfield, L.E., J.D. Haas, J.M. Belizán, K.M. Rasmussen, and B. Edmonston. 1991. Differences in early postnatal morbidity risk by pattern of fetal growth in Argentina. Paediat. Perinat. Epidemiol. 5:263-275. CDC (Center for Disease Control). 1972. Ten-State Nutrition Survey 1968-1970. III. Clinical, Anthropometry, Dental. DHEW Pub. No. (HSM) 72-8131. Atlanta: CDC. CDC (Centers for Disease Control). 1978. CDC analysis of nutritional indices for selected WIC participants. Washington, D.C.: U.S. Food and Nutrition Service. CDC (Centers for Disease Control). 1987. Nutritional status of minority children: United States 1986. Morbid. Mortal. Weekly Rep. 36:366-369. CDC (Centers for Disease Control) 1992. Pregnancy risks determined from birth certificate data— United States, 1989. Morbid. Mortal. Weekly Rep. 41(30):556-563. CDC (Centers for Disease Control). 1994. Increasing incidence of low birthweight: United States, 1981-1991. Morbid. Mortal. Weekly Rep. 43(18):335-339. Chavéz, A., and C. Martínez. 1980. Effects of maternal undernutrition and dietary supplementation on milk production. Pp. 274-284 in Maternal Nutrition During Pregnancy and Lactation, H. Aebi and R. G. Whitehead, eds. Bern: Hans Huber. Chen, L.C., A. Chowdhury, and S.L. Huffman. 1980. Anthropometric assessment of energy-protein malnutrition and subsequent risk of mortality among preschool aged children. Am. J. Clin. Nutr. 33:1836-1845. Chwang, L.C., A.G. Soemantri, and E. Pollitt. 1988. Iron supplementation and physical growth of rural Indonesian children. Am. J. Clin. Nutr. 47:496-501. Cliver, S.P., R.L. Goldenberg, G.R. Cutter, H.J. Hoffman, R.L. Copper, S.J. Gotlieb, and R.O. Davis. 1992. The relationships among psychosocial profile, maternal size, and smoking in predicting fetal growth retardation. Obstet. Gynecol. 80:262-267. CN-AAP (Committee on Nutrition, American Academy of Pediatrics) 1981. Nutritional aspects of obesity in infancy and childhood. Pediatrics 68:880-883. Cogswell, M.E., M.K. Serdula, D.W., Hungerford, and R. Yip. 1995. Gestational weight gain among average-weight and overweight women-what is excessive? Am. J. Obstet. Gynecol. 172:705-712. Conlisk, E.A. 1993. The Heterogeneity of Low Birth Weight as it Relates to the Black-White Gap in Birthweight Specific Neonatal Mortality. Ph.D. Dissertation. Cornell University, Ithaca, N.Y. Cook, R.A., S.B. Davis, F.H. Radke, and M.E. Thornbury. 1976. Nutritional status of Head Start and nursery school children. I. Food intake and anthropometric measurements. J. Am. Diet. Assoc. 68:120-126. Cooke, R.W.I., A. Lucas, P.L.N. Yudkin, and J. Pryse-Davies. 1977. Head circumference as an index of brain weight in the fetus and newborn. Early Hum. Dev. 1:145-149.

ANTHROPOMETRIC RISK CRITERIA 132 Crawford, M.A., W. Doyle, A. Leaf, M. Leighfield, K. Ghebremeskel, and A. Phylactos. 1993. Nutrition and neurodevelopmental disorders. Nutr. Health. 9:219-235. Cuttini, M., I. Cortinovis, A. Bossi, and U. de Vonderweid. 1991. Proportionality of small for gestational age babies as a predictor of neonatal mortality and morbidity. Paediatr. Perinat. Epidemiol. 5:56-63. DaVanzo, J., W.P. Butz, and J-P. Habicht. 1983. How biological and behavioural influences on mortality in Malaysia vary during the first year of life. Population Studies 37:381-402. Dawes, M.G., and J.G. Grudzinskas. 1991a. Repeated measurement of maternal weight gain during pregnancy: Is this a useful practice? Br. J. Obstet. Gynaecol. 98:189-194. Dawes, M.G., and J.G. Grudzinskas. 1991b. Patterns of maternal weight gain in pregnancy. Br. J. Obstet. Gynaecol. 98:195-201. Delgado, H.L., V. Valverde, J.M. Belizan, and R.E. Klein. 1983. Diarrheal disease, nutritional status and health care: Analysis of their interrelationships. Ecol. Food Nutr. 12:229-234. Dewey, K.G., and M. McCrory. 1994. Effects of dieting and physical activity on pregnancy and lactation. Am. J. Clin. Nutr. 59:446S-453S. Dewey, K.G., M.J. Heinig, L.A. Nommsen, and B. Lonnerdal. 1991a. Maternal versus infant factors related to breast milk intake and residual milk volume: The DARLING study. Pediatrics 87:829-837. Dewey, K.G., M.J. Heinig, L.A. Nommsen, and B. Lonnerdal. 1991b. Adequacy of energy intake among breast-fed infants in the DARLING study: Relationships to growth velocity, morbidity, and activity levels. Davis Area Research on Lactation, Infant Nutrition and Growth. J. Pediatr. 119:538-547. Dewey, K.G., M.J. Heinig, and L.A. Nommsen. 1993. Maternal weight-loss patterns during prolonged lactation. Am. J. Clin. Nutr. 58:162-166. Dietz, W.H., Jr. 1983. Childhood obesity: Susceptibility, cause, and management. J. Pediatr. 103:676-686. Dietz, W.H., Jr., and S.L. Gortmaker. 1985. Do we fatten our children at the television set? Obesity and television viewing in children and adolescents. Pediatrics 75:807-812. Dietz, W.H., Jr., and R. Hartung. 1985. Changes in height velocity of obese preadolescents during weight reduction. Am. J. Dis. Child. 139:705-707. Dobbing, J. 1970. Undernutrition and the developing brain. The relevance of animal models to the human problem. Am. J. Dis. Child. 120:411-415. Dobbing, J. 1973. Quantitative growth and development of human brain. Arch. Dis. Child. 48:757-767. Dobbing, J. 1974. The later growth of the brain and its vulnerability. Pediatrics. 53:2-6. Dolan-Mullen, P., G. Ramirez, and J.Y. Groff. 1994. A meta-analysis of randomized trials of prenatal smoking cessation interventions. Am. J. Obstet. Gynecol. 171:1328-1334. Dornhorst, A., J.S. Nicholls, F. Probst, C.M. Paterson, K.L. Hollier, R.S. Elkeles, and R.W. Beard. 1991. Calorie restriction for treatment of gestational diabetes. Diabetes 40(suppl. 2):161-164. Dreze, J., and A. Sen. 1991. Hunger and Public Action. London: Oxford University Press.

ANTHROPOMETRIC RISK CRITERIA 133 Drotar, D., and L. Sturm. 1992. Personality development, problem solving, and behavior problems among preschool children with early histories of nonorganic failure-to-thrive: A controlled study. J. Dev. Behav. Pediatr. 4:266–273. Dunn, H.G., C. J. Hughes, and M. Schulzer. 1986. Physical growth. Pp. 35–53 in Sequelae of Low Birthweight: The Vancouver Study, H.G. Dunn, ed. London: Mac Keith Press. Dusdieker, L.B., D.L. Hemingway, and P.J. Stumbo. 1994. Is milk production impaired by dieting during lactation? Am. J. Clin. Nutr. 59:833–840. Eckerman, C.O., L.A. Sturm, and S.J. Gross. 1985. Different developmental courses for very-low- birthweight infants differing in early head growth. Dev. Psychol. 21:813–827. Edozien, J.C., B.R. Switzer, and R.B. Bryan. 1979. Medical evaluation of the Special Supplemental Food Program for Women, Infants, and Children. Am. J. Clin. Nutr. 32:677–692. Ekblad, U., and S. Grenman. 1992. Maternal weight, weight gain during pregnancy and pregnancy outcomes. Int. J. Gynaecol. Obstet. 39:277–283. Epstein, L.H., and R.R. Wing. 1987. Behavioral treatment of childhood obesity. Psychol. Bull. 101:331–342. Epstein, L.H., A. Valoski, R.R. Wing, and J. McCurley. 1990. Ten-year follow-up of behavioral family-based treatment for obese children. J. Am. Med. Assoc. 264:2519–2523. Eskenazi, B., L. Fenster, and S. Sidney. 1991. A multivariate analysis of risk factors for preeclampsia. J. Am. Med. Assoc. 266:237–241. Fancourt, R., S. Campbell, D. Harvey, and A.P. Normal. 1976. Follow-up study of small-for-dates babies. Br. Med. J. 1:1435–1437. Feachem, R.G., and M.A. Koblinsky. 1984. Interventions for the control of diarrhoeal diseases among young children: Promotion of breastfeeding. Bull. World Health Organ. 62:271–291. Filer, L.J., Jr. 1993. A summary of the workshop on child and adolescent obesity: What, how, and who? Crit. Rev. Food Sci. Nutr. 33:287–305. Flegal, K.M. 1993. Defining obesity in children and adolescents: Epidemiological approaches. Crit. Rev. Food Sci. Nutr. 33:307–312. Flegal, K.M., W.R. Harlan, and J.R. Landis. 1988. Secular trends in body mass index and skinfold thickness with socioeconomic factors in young adult women. Am. J. Clin. Nutr. 48:535– 543. Fontvieille, A.M., and E. Ravussin. 1993. Metabolic rate and body composition of Pima Indian and Caucasian children. Crit. Rev. Food. Sci. Nutr. 33:363–368. Frank, D.A., and S.H. Zeisel. 1988. Failure to thrive. Pediatr. Clin. North Am. 35:1187–1206. Frank, G.C., G.S. Berenson, and L. S. Webber. 1978. Dietary studies and the relationship of diet to cardiovascular disease risk factor variables in 10-year-old children: The Bogalusa Heart Study. Am. J. Clin. Nutr. 31:328–340. Friedman, J.M., and R.L. Leibel. 1990. Tackling a weighty problem. Cell 69:217–220. Garn, S.M. 1985. Continuities and changes in fatness from infancy through adulthood. Curr. Probl. Pediatr. 15:1–47. Garn, S.M., and D.C. Clark. 1976. Trends in fatness and origin of obesity. Ad Hoc Committee to Review the Ten-State Nutrition Survey. Pediatrics 57:443–456.

ANTHROPOMETRIC RISK CRITERIA 134 Garn, S.M., T.V. Sullivan, and V.M. Hawthorne. 1989. Fatness and obesity of the parents of obese individuals. Am. J. Clin. Nutr. 50:1308–1313. Garrow, J.S., J.C. Waterlow, and B. Schürch. 1994. Causes and mechanisms of linear growth retardation. Proceeding of an IDECG Workshop. London, January 15–18, 1993. Eur. J. Clin. Nutr. 48: S2–S216. Gayle, H.D., M.J. Dibley, J.S. Marks, and F.L. Trowbridge. 1987. Malnutrition in the first two years of life: The contribution of low birth weight to population estimates in the United States . Am. J. Dis. Child. 141:531–534. Gazzaniga, J.M., and T.L. Burns. 1993. Relationship between diet composition and body fatness, with adjustment for resting energy expenditure and physical activity, in preadolescent children. Am. J. Clin. Nutr. 58:21–28. Gerver, W.J.M., N.M. Drayer, and W. Schaafsma. 1989. Reference values of anthropometric measurements in Dutch children. The Oosterwolde Study. Acta. Paediatr. Scand. 78:307– 313. Godfrey, K.M., T. Forrester, D.J. Barker, A.A. Jackson, J.P. Landman, J.S. Hall, V. Cox, and C. Osmond. 1994. Maternal nutritional status in pregnancy and blood pressure in childhood. Br. J. Obstet. Gynaecol. 101:398–403. Golden, M.H. 1994. Is complete catch-up possible for stunted malnourished children? Eur. J. Clin. Nutr. 48:S58–S71. Golden, M.H.N., and B.E. Golden. 1981. Effect of zinc supplementation on the dietary intake, rate of weight gain, and energy cost of tissue deposition in children recovering from severe malnutrition. Am. J. Clin. Nutr. 34:900–908. González-Cossio, T., J-P. Habicht, H. Delgado, and K.M. Rasmussen. 1991. Food supplementation during lactation increases infant milk intake and the proportion of exclusive breast feeding. FASEB J 5:A917. Gopalan, C., M.C. Swaninathan, V.K. Kumari, D.H. Rao, and K. Vijayaraghavan. 1973. Effect of calorie supplementation on growth of under nourished children. Am. J. Clin. Nutr. 26:563– 566. Gorstein, J., K. Sullivan, R. Yip, M. de Onis, F. Trowbridge, P. Fajans, and G. Clugston. 1994. Issues in the assessment of nutritional status using anthropometry. Bull. World Health Organ. 72:273–283. Gortmaker, S.L., A. Must, J.M. Perrin, A.M. Sobol, and W.H. Dietz. 1993. Social and economic consequences of overweight in adolescence and young adulthood. N. Engl. J. Med. 329:1008– 1012. Gross, S., C. Librach, and A. Cecutti. 1989. Maternal weight loss associated with hyperemesis gravidarum: A predictor of fetal outcome. Am. J. Obstet. Gynecol. 160:906–909. Haaga, J.G. 1986. Negative bias in estimates of the correlation between children's weight-for-height and height-for-age. Growth 50:147–154. Habicht, J-P., and W.P. Butz. 1979. Measurement of health and nutrition effects of large scale nutrition intervention projects. Pp. 133–182 in Evaluating the Impact of Nutrition and Health Programs, R.E. Klein, ed. New York: Plenum Press. Habicht, J-P., and C. Yarbrough. 1980. Efficiency in selecting pregnant women for food supplementation during pregnancy. Pp. 314–336 in Maternal Nutrition During Pregnancy and Lactation, H. Aebi and R. G. Whitehead, eds. Bern: Hans Huber.

ANTHROPOMETRIC RISK CRITERIA 135 Habicht, J-P., R. Martorell, C. Yarbrough, R.M. Malina, and R.E. Klein. 1974. Height and weight standards for pre-school children: How relevant are ethnic differences in growth potential? Lancet 1:611–614. Habicht, J-P., J. DaVanzo, and W.P. Butz. 1986. Does breastfeeding really save lives, or are apparent benefits due to biases? Am. J. Epidemiol. 123:279–290. Hack, M., and N. Breslau. 1986. Very low birth weight infants: Effects of brain growth during infancy on intelligence quotient at 3 years of age. Pediatrics. 77:196–202. Hack, M., N. Breslau, B. Weissman, D. Aram, N. Klein, and E. Borawski. 1991. Effect of very low birth weight and subnormal head size on cognitive abilities at school age. N. Engl. J. Med. 325:231–237. Hack, M., H.G. Taylor, N. Klein, R. Eiben, C. Schatschneider, and N. Mercuri-Minich. 1994. School-age outcomes in children birth weights under 750 g. N. Engl. J. Med. 331:753–759. Hamill, P.V.V., F.E. Johnston, and S. Lemeshow. 1972. Height and Weight of Children: Socioeconomic Status, United States. DHEW Pub. No. (HSM) 73–1601. National Centers for the Health Statistics. Vital Health Stat. 11(119). Hamill, P.V.V., T.A. Drizd, C.L. Johnson, R.B. Reed, A.F. Roche, and W.M. Moore. 1979. Physical growth: National Center for Health Statistics percentiles. Am. J. Clin. Nutr. 32:607–629. Harvey, D., J. Prince, J. Bunton, C. Parkinson, and S. Campbell. 1982. Abilities of children who were small-for-gestational-age babies. Pediatrics 69:296–300. Hediger, M.L., T.O. Scholl, D.H. Belsky, I.G Ances, and R.W. Salmon. 1989. Patterns of weight gain in adolescent pregnancy: Effects on birth weight and preterm delivery. Obstet. Gynecol. 74:6– 12. Hediger, M.L., T.O. Scholl, J.I. Schall, M.F. Healey, and R.L. Fischer. 1994. Changes in maternal upper arm fat stores are predictors of variation in infant birth weight. J. Nutr. 124:24–30. Heikens, G.T., W.N. Schofield, S. Dawson, and S.Grantham-McGregor. 1989. The Kingston Project. I. Growth of malnourished children during rehabilitation in the community, given a high energy supplement. Eur. J. Clin. Nutr. 43:145–160. Heikens, G.T., W.N. Schofield, and S. Dawson. 1993. The Kingston Project. II. The effects of high energy supplement and metronidazole on malnourished children rehabilitated in the community: Anthropometry. Eur. J. Clin. Nutr. 47:160–173. Heimendinger, J., N. Laird, J.E. Austin, P. Timmer, and S. Gershoff. 1984. The effects of the WIC program on the growth of infants. Am. J. Clin. Nutr. 40:1250–1257. Heywood, P. 1982. The functional significance of malnutrition: Growth and prospective risk of death in the highlands of Papua New Guinea. J. Food Nutr. 39:13–19. Hick, L.E., R.A. Langham, and J. Takenaka. 1982. Cognitive and health measures following early nutritional supplementation: A sibling study. Am. J. Public Health 72:1110–1118. Hickey, C.A., S.P. Cliver, R.L. Goldenberg, J. Kohatsu, and H.J. Hoffman. 1993. Prenatal weight gain, term birth weight, and fetal growth retardation among high-risk multiparous black and white women. Obstet. Gynecol. 81:529–535. Hickey, C.A., S.P. Cliver, S.F. McNeal, H.J. Hoffman, and R.L. Goldenberg. 1995. Prenatal weight gain patterns and spontaneous preterm birth among non obese black and white women . Obstet. Gynecol 85:909–914.

ANTHROPOMETRIC RISK CRITERIA 136 Hogberg, U., S. Wall, and D.E. Wiklund. 1990. Risk determinants of perinatal mortality in a Swedish county, 1980–1984. Acta Obstet. Gynecol. Scand. 69:575–579. Ikenoue, T., T. Ikeda, S. Ibara, M. Otake, and W.J. Schull. 1993. Effects of environmental factors on perinatal outcome: Neurological development in cases of intrauterine growth retardation and school performance of children perinatally exposed to ionizing radiation. Environ. Health Perspect. 101:53–57. IOM (Institute of Medicine). 1973. Infant Death: An Analysis By Maternal Risk and Health Care. Report of the Panel on Health Services Research. Washington, D.C.: National Academy Press. IOM (Institute of Medicine). 1985. Preventing Low Birthweight. Report of the Committee to Study the Prevention of Low Birthweight, Division of Health Promotion and Disease Prevention. Washington, D.C.: National Academy Press. IOM (Institute of Medicine). 1990. Nutrition During Pregnancy. Part I, Weight Gain; Part II, Nutrient Supplements. Report of the Subcommittee on Nutritional Status and Weight Gain During Pregnancy and Subcommittee on Dietary Intake and Nutrient Supplements During Pregnancy, Committee on Nutritional Status During Pregnancy and Lactation, Food and Nutrition Board. Washington, D.C.: National Academy Press. IOM (Institute of Medicine). 1991. Nutrition During Lactation. Report of the Subcommittee on Nutrition During Lactation, Committee on Nutritional Status During Pregnancy and Lactation, Food and Nutrition Board. Washington, D.C.: National Academy Press. IOM (Institute of Medicine). 1992a. Nutrition During Pregnancy and Lactation: An Implementation Guide. Report of the Subcommittee for a Clinical Application Guide, Committee on Nutritional Status during Pregnancy and Lactation, Food and Nutrition Board. Washington, D.C.: National Academy Press. IOM (Institute of Medicine). 1992b. Nutrition Services in Perinatal Care, 2nd ed. Report of the Committee on Nutritional Status During Pregnancy and Lactation, Food and Nutrition Board. Washington, D.C.: National Academy Press. Issacs, J.D., E.F. Magann, R.W. Martin, S.P. Chauhan, and J.C. Morrison. 1994. Obstetric challenges of massive obesity complicating pregnancy. J. Perinatol. 14:10–14. Jacobson, J.L., S.W. Jacobson, R.J. Sokol, S.S. Martier, J.W. Ager, and S. Shankaran. 1994. Effects of alcohol use, smoking, and illicit drug use on fetal growth in black infants. J. Pediatr. 124:731–733. James, S.A. 1992. Racial and ethnic differences in infant mortality and low birth weight: A psychosocial critique. Ann. Epidemiol. 3:130–136. Javier-Nieto, F., M. Szklo, and G.W. Comstock. 1992. Childhood weight and growth rate as predictors of adult mortality. Am. J. Epidemiol. 136:201–213. Johnson, A.A., E.M. Knight, C.H. Edwards, U.J. Oyemade, O.J. Cole, O.E. Westney, H. Laryea, and S. Jones. 1994. Dietary intakes, anthropometric measurements and pregnancy outcomes. J. Nutr. 124:936S–942S. Johnson, J.W., J.A. Longmate, and B. Frentzen. 1992. Excessive maternal weight and pregnancy outcome. Am. J. Obstet. Gynecol. 167:353–372. Johnston, E.M. 1991. Weight changes during pregnancy and the postpartum period. Prog. Food Nutr. Sci. 15:117–157.

ANTHROPOMETRIC RISK CRITERIA 137 Jones, D.Y., M.C. Nesheim, and J-P. Habicht. 1985. Influences on child growth associated with poverty in the 1970's: An examination of HANESI and HANESII, cross-sectional U.S. national surveys. Am. J. Clin. Nutr. 42:714–724. Kanders, B.S. 1995. Pediatric obesity. Pp. 210–233 in Weighing the Options: Criteria for Evaluating Weight-Management Programs, P.R. Thomas, ed. Report of the Committee to Develop Criteria for Evaluating the Outcomes of Approaches to Prevent and Treat Obesity, Food and Nutrition Board, Institute of Medicine. Washington, D.C.: National Academy Press. Karlberg, J., F. Jalil, B. Lam, L. Low, and C.Y. Yeung. 1994. Linear growth retardation in relation to the three phases of growth. Eur. J. Clin. Nutr. 48:S25–S44. Kasango Project Team. 1983. Anthropometric assessment of young children's nutritional status as an indicator of subsequent risk of dying. J. Trop. Pediatr. 29:69–75. Katz, J., K.P. West, Jr., I. Tarwotjo, and A. Sommer. 1989. The importance of age in evaluating anthropometric indices for predicting mortality. Am. J. Epidemiol. 130:1219–1226. Keen, H., B.J. Thomas, R. J.Jarrett, and J.H. Fuller. 1979. Nutrient intake, adiposity and diabetes. Br. Med. J. 1:655–658. Keller, W. 1988. The epidemiology of stunting. Pp. 17–29 in Linear Growth Retardation in Less Developed Countries , J.C. Waterlow, ed. New York: Raven Press. Keppel, K.G., and S.M. Taffel. 1993. Pregnancy-related weight gain and retention: Implications of the 1990 Institute of Medicine guidelines. Am. J. Public Health 83:1100–1103. Kerr, G.R., E.S. Lee, R.J. Lorimor, W.H. Mueller, and M.M. Lam. 1982. Height distributions of U.S. children: Associations with race, poverty status and parental size. Growth 46:135–149. Khin-Maung-Naing, T.T.O. 1987. Effect of dietary supplementation on lactation performance of undernourished Burmese mothers. Food Nutr. Bull. 9:59–61. Khoury, M.J., J.D. Erickson, J.F. Cordero, and B.J. McMarthy. 1988. Congenital malformations and intrauterine growth retardation: A population study. Pediatrics 82:83–90. Khoury, M.J., C.J. Berg, and E.E. Calle. 1990. The ponderal index in term newborn siblings. Am. J. Epid. 132:576–83. Kimball, K.J., R.L. Ariagno, D.K. Stevenson, and P. Sunshine. 1982. Growth to age 3 years among very low-birth-weight sequelae-free survivors of modern neonatal intensive care. J. Pediatr. 100:622–624. Klebanov, P.K., J. Brooks-Gunn, and M.C. McCormick. 1994. Classroom behavior of very low birth weight elementary school children. Pediatrics 94:700–708. Kleinman, J. 1990. Maternal Weight Gain During Pregnancy: Determinants and Consequences. NCHS Working Paper Series No. 33. Hyattsville, Md.: National Center for Health Statistics. Klesges, R.C., L.M. Klesges, L.H. Eck, and M.L. Shelton. 1995. A longitudinal analysis of accelerated weight gain in preschool children. Pediatrics. 95:126–130. Kramer, M.S. 1987a. Determinants of low-birth weight: Methodological assessment and meta- analysis. Bull. WHO 65:663–737. Kramer, M.S. 1987b. Intrauterine growth and gestational duration determinants. Pediatrics. 80:502– 511.

ANTHROPOMETRIC RISK CRITERIA 138 Kramer, M.S. 1993. Effects of energy and protein intakes on pregnancy outcome: An overview of the research evidence from controlled clinical trials. Am. J. Clin. Nutr. 58:627–635. Kramer, M.S., F.H. McLean, M. Olivier, D.M. Willis, and R.H. Usher. 1989. Body proportionality and head and length 'sparing' in growth-retarded neonates: A critical reappraisal. Pediatrics. 84:717–723. Kramer, M.S., M. Olivier, F.H. McLean, G.E. Dougherty, D.M. Willis, and R.H. Usher. 1990a. Determinants of fetal growth and body proportionality. Pediatrics 86:18–26. Kramer, M.S., M. Olivier, F.H. McLean, D.M. Willis, and R.H. Usher. 1990b. Impact of intrauterine growth retardation and body proportionality on fetal and neonatal outcome. Pediatrics 86:707–713. Kramer, M.S., F.H. McLean, E.L. Eason, and R.H. Usher. 1992. Maternal nutrition and spontaneous preterm birth. Am. J. Epidemiol. 136:574–583. Krasovec, K., and M.A. Anderson. 1991. Maternal Nutrition and Pregnancy Outcomes: Anthropometric Assessment. Scientific Pub. No. 529. Washington, D.C.: Pan American Health Organization. Kromhout, D. 1983. Energy and micronutrient intake in lean and obese middle-aged men (the Zutphen study). Am. J. Clin. Nutr. 37:295–299. Kuczmarski, R.J., K.M. Flegal, S.M. Campbell, and C.L. Johnson. 1994. Increasing prevalence of overweight among U.S. adults. The National Health and Nutrition Examination Surveys, 1960–1991. J. Am. Med. Assoc. 272:205–211. Kurz, K.M., J-P. Habicht, K.M. Rasmussen, and S.J. Schwager. 1993. Effects of maternal nutritional status and maternal energy supplementation on length of postpartum amenorrhea among Guatemalan women. Am. J. Clin. Nutr. 58:636–642. Larsen, C.E., M.K. Serdula, and K.M. Sullivan. 1990. Macrosomia: Influence of maternal overweight among a low-income population. Am. J. Obstet. Gynecol. 162:490–494. Larson, B.J. 1991. Relationship of family communication patterns to Eating Disorder Inventory scores in adolescent girls. J. Amer. Diet. Assoc. 91:1065–1067. Launer, L.J., J-P. Habicht, and S. Kardjati. 1990. Breast feeding protects infants in Indonesia against illness and weight loss due to illness. Am. J. Epidemiol. 131:322–331. Lawrence, M., T. Yimer, and J.K. O'Dea. 1994. Nutritional status and early warning of mortality in southern Ethiopia, 1988–1991. Eur. J. Clin. Nutr. 48:38–45. Lechtig, A., and R.E. Klein. 1981. Prenatal nutrition and birth weight: Is there a causal association? Pp. 131–156 in Maternal Nutrition in Pregnancy—Eating for Two? J. Dobbing, ed. London: Academic Press. Leibel, R.L., M. Rosenbaum, and J. Hirsch. 1995. Changes in energy expenditure resulting from altered body weight. New Engl. J. Med. 332:621–628. Leiter, E.H. 1993. Obesity genes and diabetes induction in the mouse. Crit. Rev. Food Sci. Nutr. 33:333–338. Lester, B.M., C. Garcia-Coll, M. Valcarcel, J. Hoffman, and T.B. Brazelton. 1986. Effects of atypical patterns of fetal growth on newborn (NBAS) behavior. Child Dev. 57:11–19. Leung, A.K., and W.L. Robson. 1990. Childhood obesity. Postgrad. Med. 87:123–130, 133.

ANTHROPOMETRIC RISK CRITERIA 139 Levy, H.L., S.E. Waisbren, D. Lobbregt, E. Allred, A. Schuler, F.K. Trefz., S.M. Schweitzer, I.B. Sardharwalla, J.H. Walter, B.E. Barwell et al. 1994. Maternal mild hyperphenylalaninaemia: An international survey of offspring outcome. Lancet. 344:1589–1594. Lieberman, E. 1995. Low birth weight—not a black-and-white issue. N. Engl. J. Med. 332:117–118. Lifshitz, F., and N. Moses. 1989. Growth failure. A complication of dietary treatment of hypercholesterolemia. Am. J. Dis. Child. 143:537–542. Lifschitz, F., N.M. Finch, and J.Z. Lifschitz, eds. 1991. Failure to thrive. Pp. 253–270 in Children's Nutrition. Boston: Jones and Bartlett Publishers. Lindtjorn, B., T. Alemu, and B. Bjorvatn. 1993. Nutritional status and risk of infection among Ethiopian children . J. Trop. Pediatr. 39:76–82. Lindgren, G., G. Aurelius, J. Tanner, and M. Healy. 1994. Standards for height, weight and head circumference of one month to six years based on Stockholm children born in 1980. Acta. Paediatr. 83:360–366. Listernick, R., K. Christoffel, J. Pace, and J. Chiaramonte. 1985. Severe primary malnutrition in U.S. children. Am. J. Dis. Child. 139:1157–1160. Little, B.B., and L.M. Snell. 1991. Brain growth among fetuses exposed to cocaine in utero: Asymmetrical growth retardation. Obstet. Gynecol. 77:361–364. Little, R.E., and C.R. Weinberg. 1993. Risk factors for antepartum and intrapartum stillbirth. Am. J. Epidemiol. 137:1177–1189. Lubchenco, L.O. 1981. Gestational age, birth weight, and the high-risk infant. Pp. 12–18 in Infants At Risk: Assessment and Intervention, C.C. Brown, ed. Piscataway, N.J.: Johnson & Johnson Baby Products Company. Lucas, A., R. Morley, T.J. Cole, M.F. Bamford, A. Boon, P. Crowle, J.F. Dossetor, and R. Pearse. 1988. Maternal fatness and viability of preterm infants. Br. Med. J. Clin. Res. Ed. 296:1495– 1497. Luke, B., T. Johnson, and R. Petrie. 1993. Clinical Maternal-Fetal Nutrition. Boston: Little, Brown and Co. Lutter, C.K., J.O. Mora, J-P. Habicht, K.M. Rasmussen, D.S. Robson, S.G. Sellers, C.M. Super, and M.G. Herrera. 1989. Nutritional supplementation: Effects on child stunting because of diarrhea. Am. J. Clin. Nutr. 50:1–8. Lutter, C.K., J.O. Mora, J-P. Habicht, K.M. Rasmussen, D.S. Robson, and M.G. Herrera. 1990. Age- specific responsiveness of weight and length to nutritional supplementation. Am J. Clin. Nutr. 51:359–364. Lutter, C.K., J-P. Habicht, J.A. Rivera, and R. Martorell. 1992. The relationship between energy intake and diarrhoeal disease in their effects on child growth: Biological model, evidence, and implications for public health policy. Food Nutr. Bull. 14:36–42. Malcolm, L. 1978. Protein energy malnutrition and growth. Pp. 361–371 in Human Growth, 1st ed. Vol. 3: Neurobiology and Nutrition, F. Falkner and J.M. Tanner, eds. New York: Plenum Press. Malina, R.M., J-P. Habicht, R. Martorell, A. Lechtig, C. Yarbrough, and R.E. Klein. 1975. Head and chest circumferences in rural Guatemalan Ladino children, birth to seven years of age. Am. J. Clin. Nutr. 28:1061–1070. Mallick, M.J. 1983. Health hazards of obesity and weight control in children: A review of the literature. Am. J. Public Health 73:78–82.

ANTHROPOMETRIC RISK CRITERIA 140 Manser, J.I. 1984. Growth in the high-risk infants. Clin. Perinatol. 2:19–40. Marchant, K., R. Martorell, and J.D. Haas. 1990. Consequences for maternal nutrition of reproductive stress across consecutive pregnancies. Am. J. Clin. Nutr. 52:616–620. Martorell, R. 1989. Body size, adaptation, and function. Hum. Org. 48:15–20. Martorell, R., and J-P. Habicht. 1986. Growth in early childhood in developing countries. Pp. 241– 262 in Human Growth: A Comprehensive Treatise, 2nd ed. Vol. 3: Methodology. Ecological, Genetic, and Nutritional Effects on Growth, F. Falkner and J.M. Tanner, eds. New York: Plenum Press. Martorell, R., and T.J. Ho. 1984. Malnutrition, morbidity, and mortality. Child Survival: Strategies for Research, H. Mosey and L.C. Chen, eds. Pop. Dev. Rev. 10(suppl.):49–68. Martorell, R., J-P. Habicht, and R.K. Klein. 1982. Anthropometric indicators of changes in nutritional status in malnourished population. Pp. 96–110 in Proceedings, Methodologies for Human Population Studies in Nutrition Related to Health, July 24–25, 1979, B.A. Underwood, ed. NIH Pub. No. 82–2462. Bethesda, Md.: U.S. Department of Health and Human Services. Martorell, R., J. Rivera, H. Kaplowitz, and E. Pollitt. 1992. Long-term consequences of growth retardation during early childhood. Pp. 143–149 in Human Growth: Basic and Clinical Aspects, M. Hernandez and J. Argente , eds. Amsterdam: Elsevier. Martorell, R., L.K. Khan, and D.G. Schroeder. 1994. Reversibility of stunting: Epidemiological findings in children from developing countries. Eur. J. Clin. Nutr. 48:S45–S57. Mascie-Taylor, C.G. 1991. Biosocial influences on stature: A review. J. Biosoc. Sci. 23:113–128. McCormick, M.C. 1985. The contribution of low birth weight to infant mortality and childhood mortality. N. Engl. J. Med. 312:82–90. McCormick, M.C., J. Brooks-Gunn, K. Workman-Daniels, J. Turner, and G.J. Peckham. 1992. The health and development status of very low-birth-weight children at school age. J. Am. Med. Assoc. 267:2204–2208. McCrae, W.M., I.J. Carré, P.W. Brunt, A.P. Mowat, and C.M. Andersen. 1978. Disorders of the alimentary tract. Pp. 438–442 in Textbook of Paediatrics, 2nd ed., vol. 1, J.O. Forfar and G.C. Arneil, eds. Edinburgh and New York: Churchill Livingstone. Mendelson, R., D. Dollard, P. Hall, S.Y. Zarrabi, and E. Desjardin. 1991. The impact of the healthiest babies possible program on maternal diet and pregnancy outcome in underweight and overweight clients. J. Can. Diet. Assoc. 52:229–234. Metcoff, J., P. Costiloe, W.M. Crosby, S. Dutta, H.H. Sandstead, D. Milne, C.E. Bodwell, and S.H. Majors. 1985. Effect of food supplementation (WIC) during pregnancy on birth weight. Am. J. Clin. Nutr. 41:933–947. Meyer, M.B., and G.W. Comstock. 1972. Maternal cigarette smoking and perinatal mortality. Am. J. Epidemiol. 96:1–10. Michaelson, K.F., P.S. Larsen, B.L. Thomsen, and G. Samuelson. 1994. The Copenhagen Cohort study of infant nutrition and growth: Breast milk intake, human milk macronutrient content, and influencing factors. Am. J. Clin. Nutr. 59:600–611. Miller, C.A., A. Fine, and S. Adams-Taylor. 1989. Monitoring Children's Health: Key Indicators, 2nd ed. Washington D.C.: American Public Health Association.

ANTHROPOMETRIC RISK CRITERIA 141 Miller, H.C., and T.A. Merritt. 1979. Fetal Growth in Humans. Chicago: Year Book Medical Publishers. Miller, J.E., and S. Korenman. 1994. Poverty and children's nutritional status in the United States. Am. J. Epidemiol. 140:233–243. Mitchell, W.G., R.W. Gorrell, and R.A. Greenberg. 1980. Failure to thrive: A study in a primary care setting. Epidemiology and follow-up. Pediatrics 65:971–977. Mora, J.O., M.G. Herrera, J. Suescun, L. de Navarro, and M. Wagner. 1981. The effects of nutritional supplementation on physical growth of children at risk of malnutrition. Am. J. Clin. Nutr. 34:1885–1892. Mossberg, H.O. 1989. 40-year follow-up of overweight children. Lancet 2:491–493. Mumford, P., and J.B. Morgan. 1982. A longitudinal study of nutrition and growth of infants initially on the upper and lower centile of weight and age. Int. J. Obes. 6:335–341. Naeye, R.L. 1990. Maternal body weight and pregnancy outcome. Am. J. Clin. Nutr. 52:273–279. Nandi, C., and M.R. Nelson. 1992. Maternal pregravid weight, age and smoking status as risk factors for low birth weight births. Public Heath Rep. 107:658–662. NIH (National Institutes of Health). 1985. Health Implications of Obesity: National Institutes of Health Consensus Development Conference Statement. Ann. Intern. Med. 103:1073–1077. NIH (National Institutes of Health) Technology Assessment Conference Panel. 1992. Methods for voluntary weight loss and control. Ann. Intern. Med. 116:942–949. Niswander, K.R., and M. Gordon. 1972. The Women and Their Pregnancies. The Collaborative Perinatal Study of the National Institute of Neurological Diseases and Stroke. DHEW Pub. No. (NIH) 73–379. Washington, D.C.: U.S. Government Printing Office. Nommsen, L.A., C.A. Lovelady, M.J. Heinig, B. Lonnerdal, and K.G. Dewey. 1991. Determinants of energy, protein, lipid, and lactose concentrations in human milk during the first 12 months of lactation: The DARLING Study. Am. J. Clin. Nutr. 53:457–465. NRC (National Research Council). 1989. Diet and Health: Implications for Reducing Chronic Disease Risk. Report of the Commission in Diet and Health, Food and Nutrition Board, Commission on Life Sciences . Washington, D.C.: National Academy Press. Nulman, I., J. Rovet, D. Altmann, C. Bradley, T. Einarson, and G. Koren. 1994. Neurodevelopment of adopted children exposed in utero to cocaine. Can. Med. Assoc. J. 151:1591–1597. Oates, R.K., A. Peacock, and D. Forrest. 1985. Long-term effects of nonorganic failure to thrive. Pediatrics. 75:36–40. Ounsted, M., and C. Ounsted. 1968. Rate of intra-uterine growth. Nature 220:599–600. Ounsted, M., V.A. Moar, and A. Sott. 1985. Head circumference charts updated. Arch. Dis. Child. 60:936–939. Owen, G.M., and A.H. Lubin. 1973. Anthropometric differences between black and white preschool children. Am. J. Dis. Child. 126:168–169. Owen, G.M., K.M. Kram, P.J. Garry, J.E. Lowe, and A.H. Lubin. 1974. A study of nutritional status of preschool children in the United States, 1968–70. Pediatrics 53:597–646.

ANTHROPOMETRIC RISK CRITERIA 142 Palmer, C.G., C. Cronk, S.M. Pueschel, K.E. Wisniewski, R. Laxova, A.C. Crocker, and R.M. Pauli. 1992. Head circumference of children with Down syndrome (0–36 months). Am. J. Med. Genet. 42:61–67. Parker, J.D. 1994. Postpartum weight change. Clin. Obstet. Gynecol. 37:528–537. Parker, J.D., and B. Abrams. 1992. Prenatal weight gain advice: An examination of the recent prenatal weight gain recommendations of the Institute of Medicine. Obstet. Gynecol. 79:664– 669. Parker, J.D., and B. Abrams. 1993. Differences in postpartum weight retention between black and white mothers. Obstet. Gynecol. 81:768–774. Parkinson, C.E., S. Wallis, and D.R. Harvey. 1981. School achievement and behaviour of children who are small-for-dates at birth. Dev. Med. Child. Neurol. 23:41–50. Paul, A.A., E.A. Ahmed, and R.G. Whitehead. 1986. Head circumference charts updated (letter). Arch. Dis. Child. 61:927–928. Pelletier, D.L. 1994. The relationship between child anthropometry and mortality in developing countries: Implications for policy, programs and future research. J. Nutr. 124:2047S–2081S. Pelletier, D.L., E.A. Frongillo, Jr., and J-P. Habicht. 1993. Epidemiologic evidence for a potentiating effect of malnutrition on child mortality. Am. J. Public Health 83:1130–1133. Perlow, J.H., M.A. Morgan, D. Montgomery, C.V. Towers, and M. Porto. 1992. Perinatal outcome in pregnancy complicated by massive obesity. Am. J. Obstet. Gynecol. 167:958–962. Petitti, D.B., and C. Coleman. 1990. Cocaine and the risk of low birth weight. Am. J. Public Health 80:25–28. Petitti, D.B., M.S. Croughan-Minihane, and R.A. Hiatt. 1991. Weight gain by gestational age in both black and white women delivered of normal-birth-weight and low-birth-weight infants. Am J Obstet Gynecol. 164:801–805. Phillips, D.I., D.J. Barker, C.N. Hales, S. Hirst, and C. Osmond. 1994. Thinness at birth and insulin resistance in adult life. Diabetologia 37:150–154. Pinstrup-Anderson, P., S. Burger, J-P. Habicht, and K.E. Peterson. 1993. Protein energy malnutrition. Pp. 391–420 in Disease Control Priorities in Developing Countries, D.T. Jamison and W.H. Mostley, eds. London: Oxford University Press. Pi-Sunyer, F.X. 1993. Metabolic efficiency of macronutrient utilization in humans. Crit. Rev. Food Sci. Nutr. 33:359–361. Plouin, P.F., G. Breart, Y. Rabarison, C. Rumeau-Rouquette, C. Sureau, and J. Menard. 1983. Fetal growth retardation in gestational hypertension: Relationships with blood pressure levels and the time of onset of hypertension. Eur. J. Obstet. Gynecol. Reprod. Biol. 16:253–262. Pollitt, E., K.S. Gorman, P.L. Engle, R. Martorell, and J. Rivera. 1993. Early supplementary feeding and cognition: Effects over two decades. Monogr. Soc. Res. Child Dev. 58:1–118. Prentice, A., and C.J. Bates. 1994. Adequacy of dietary mineral supply for human bone growth and mineralisation. Eur. J. Clin. Nutr. 48(suppl. 1):S161–$177. Prentice, A.M., R.G. Whitehead, M. Watkinson, W.H. Lamb, and T.J. Cole. 1983. Prenatal dietary supplementation of African women and birth-weight. Lancet 1:489–492.

ANTHROPOMETRIC RISK CRITERIA 143 Price, R.A., A.J. Stunkard, R. Ness, T. Wadden, S. Heshka, B. Kanders, and A. Cormillot. 1990. Childhood onset (age less than 10) obesity has high familial risk. Int. J. Obes. 14:185–195. Prichard, J.A., P.C. MacDonald, and N.F. Gant. 1985. Williams Obstetrics, 7th ed. Norwalk, Conn.: Appleton-Century-Crofts. Puffer, R.R., and C.V. Serrano. 1987. Patterns of Birthweights. Washington, D.C.: Pan American Health Organization, Pan American Sanitary Bureau, World Health Organization Regional Office. Pugliese, M.T., F. Lifshitz, G. Grad, P. Fort, and M. Marks-Katz. 1983. Fear of obesity: A cause for short stature and delayed puberty. N. Engl. J. Med. 309:513–518. Rahaman, J., G.V. Narayansingh, and S. Roopnarinesingh. 1990. Fetal outcome among obese parturients. Int. J. Gynaecol. Obstet. 31:227–230. Rao, D.H., and A.N. Naidu. 1977. Nutritional supplementation—whom does it benefit most? Am. J. Clin. Nutr. 30:1612–1616. Rasmussen, K.M., N.B. Mock, and J-P. Habicht. 1988. The biological meaning of low birthweight and the use of data on low birthweight for nutritional surveillance. Cornell Nutritional Surveillance Program, Working Paper No. 27. Ithaca, N.Y. Ratcliffe, S.G., N. Masera, and M. McKie. 1994. Head circumference and IQ of children with sex chromosome abnormalities. Dev. Med. Child Neurol. 36:533–544. Ratner, R.E., L.H. Hamner 3d, and N.B. Isada. 1991. Effects of gestational weight gain in morbidly obese women: 1. Maternal morbidity. Am. J. Perinatol. 8:21–24. Rawlings, J.S., V.B. Rawlings, and J.A. Read. 1995. Prevalence of low birth weight and preterm delivery in relation to the interval between pregnancies among white and black women. N. Engl. J. Med. 332:69–74. Read, J.S., J.D. Clemens, and M.A. Klebanoff. 1994. Moderate low birth weight and infectious disease mortality during infancy and childhood. Am. J. Epidemiol. 140:721–733. Regev, R., and L.M.S. Dubowitz. 1988. Head growth and neurodevelopmental outcome in neonates with intracranial hemorrhage and leukomalacia. Early Human Dev. 16:207–211. Rimoin, D.L., Z. Borochowitz, and W.A. Horton. 1986. Short stature: Physiology and pathology. West J. Med. 144:710–721. Rivera, J.A. 1988. Effect of supplementary feeding upon the recovery from mild-to-moderate wasting in children. Ph.D. Dissertation. Cornell University, Ithaca, N.Y. Rivera, J.A., J-P. Habicht, and D.S. Robson. 1991. Effects of supplementary feeding on recovery from mild to moderate wasting in preschool children. Am. J. Clin. Nutr. 54:62–68. Roberts, S.B., J. Savage, W.A. Coward, B. Chew, and A. Lucas. 1988. Energy expenditure and intake in infants born to lean and overweight mothers. N. Engl. J. Med. 318:461–466. Robinson, T.N. 1993. Defining obesity in children and adolescents: Clinical approaches. Crit. Rev. Food Sci. Nutr. 33:313–320. Roche, A.F., and J.H. Himes. 1980. Incremental growth charts. Am J Clin Nutr. 33:2041–2052. Rolland-Cachera, M.F., and F. Bellisle. 1986. No correlation between adiposity and food intake: Why are working class children fatter? Am. J. Clin. Nutr. 44:779–787.

ANTHROPOMETRIC RISK CRITERIA 144 Rolland-Cachera, M.F., M. Deheeger, M. Guilloud-Bataille, P. Avons, E. Patois, and M. Sempé. 1987. Tracking the development of adiposity from one month of age to adulthood. Ann. Hum. Biol. 14:219–229. Rolland-Cachera, M.F., F. Bellisle, and M. Sempé. 1989. The prediction in boys and girls of the weight/height2 index and various skinfold measurements in adults: A two-decade follow-up study . Int. J. Obes. 13:305–311. Rosenbaum, M., and R.L. Leibel. 1989. Obesity in children. Pediatr. Rev. 11:43–55. Rosso, P., E. Donoso, S. Braun, R. Espinoza, and S.P. Salas. 1992. Hemodynamic changes in underweight pregnant women. Obstet. Gynecol. 79:908–912. Ruel, M.T., J. Rivera, and J-P. Habicht. 1995. Length screens better than weight in stunted populations. J. Nutr. 125:1222–1228. Rush, D. 1986. The National WIC Evaluation: An Evaluation of the Special Supplemental Food Program for Women, Infants and Children. Research Triangle Park, N.C.: Research Triangle Institute. Rush, D., J. Leighton, N.L. Sloan, J.M. Alvir, and G.C. Garbowski. 1988a. The National WIC Evaluation: Evaluation of the Special Supplemental Food Program for Women, Infants, and Children. II. Review of past studies of WIC. Am. J. Clin. Nutr. 48 (suppl. 2):394–411. Rush, D., J. Leighton, N.L. Sloan, J.M. Alvir, D.G. Horvitz, W.B. Seaver, G.C. Garbowski, S.S. Johnson, R.A. Kulka, J.W. Devore, M. Holt, J.T. Lynch, T.G. Virag, M.B. Woodside, and D.S. Shanklin. 1988b. The National WIC Evaluation: Evaluation of the Special Supplemental Food Program for Women, Infants, and Children. VI. Study of infants and children. Am. J. Clin. Nutr. 48 (suppl. 2):484–511. Rush, D., N.L. Sloan, J. Leighton, J.M. Alvir, D.G. Horvitz, W.B. Seaver, G.C. Garbowsi, S.S. Johnson, R.A. Kulka, M. Holt, J.W. Devore, J.T. Lynch, M.B. Woodside, and D.S. Shanklin. 1988c. The National WIC Evaluation: Evaluation of the Special Supplemental Food program for Women, Infants, and Children. V. Longitudinal study of pregnant women. Am. J. Clin. Nutr. 48 (suppl. 2):439–483. Rutishauser, I.H., and J.B. Carlin. 1992. Body mass index and duration of breast feeding: A survival analysis during the first six months of life. J. Epidemiol. Community Health 46:559–565. Sappenfield, W.M., J.W. Buehler, N.J. Binkin, C.J. Hogue, L.T. Strauss, and J.C. Smith. 1987. Differences in neonatal and postneonatal mortality by race, birth weight, and gestational age. Public Health Rep. 102:182–192. Schelp, F.P., P. Vivatanasept, P. Sitaputra, S. Sornmani, P. Pongpaew, N. Vudhivai, S. Egormaiphol, and D. Bohning. 1990. Relationship of morbidity of under-fives to anthropometric measurements and community health intervention. Trop. Med. Parasitol. 41:121–126. Scholl, T.O, M.L. Hediger, and I.G. Ances. 1990a. Maternal growth during pregnancy and decreased infant birth weight. Am. J. Clin. Nutr. 51:790–793. Scholl, T.O., M.L. Hediger, I.G. Ances, D.H. Belsky, and R.W. Salmon. 1990b. Weight gain during pregnancy in adolescence: Predictive ability of early weight gain. Obstet. Gynecol. 75:948– 953. Scholl, T.O., M.L. Hediger, C.S. Khoo, M.F. Healey, and N.L. Rawson. 1991. Maternal weight gain, diet and infant birth weight: Correlations during adolescent pregnancy. J. Clin. Epidemiol. 44:423–428.

ANTHROPOMETRIC RISK CRITERIA 145 Schramm, W.F. 1986. Prenatal participation in WIC related to Medicaid costs for Missouri newborns: 1982 update. Public Health Rep. 101:607–615. Segel, J.S., and E.R. McAnarney. 1994. Adolescent pregnancy and subsequent obesity in African- American girls. J. Adolesc. Health 15:491–494. Serdula, M.K., D. Ivery, R.J. Coates, D.S. Freedman, D.F. Williamson, and T. Byers. 1993. Do obese children become obese adults? A review of the literature. Prev. Med. 22:167–177. Seward, J.F., and M.K. Serdula. 1984. Infant feeding and infant growth. Pediatrics 74:728–762. Shu, X.O., M.C. Hatch, J. Mills, J. Clemens, and M. Susser. 1995. Maternal smoking, alcohol drinking, caffeine consumption, and fetal growth: Results from a prospective study. Epidemiology 6:115–120. Sibai, B.M., T. Gordon, E. Thom., S.N. Caritis, M. Klebanoff, D. McNellis, and R.H. Paul. 1995. Risk factors for preeclampsia in healthy nulliparous women: A prospective multicenter study. Am. J. Obstet. Gynecol. 172:642–648. Siega-Riz, A.M., L.S. Adair, and C.J. Hobel. 1994. Institute of Medicine maternal weight gain recommendations and pregnancy outcome in a predominantly Hispanic population. Obstet. Gynecol. 84:565–573. Simon, N.P., Brady, N.R., and R.L. Stafford. 1993. Catch-up head growth and motor performance in very-low-birthweight infants. Clin. Pediatr. 32:405–411. Smedman, L., G. Sterky, L. Mellander, and S. Wall. 1987. Anthropometry and subsequent mortality in groups of children aged 6-59 months in Guinea-Bissau. Am. J. Clin. Nutr. 46:369–373. Sorensen, T.I., and S. Sonne-Holm. 1988. Risk in childhood of development of severe adult obesity: Retrospective, population-based case-cohort study. Am. J. Epidemiol. 1127:104–113. Starfield, B., S. Shapiro, M. McCormick, and D. Bross. 1982. Mortality and morbidity in infants with intrauterine growth retardation. J. Pediatr. 101:978–983. Stark, O., E. Atkins, O.H. Wolff, and J.W.B. Douglas. 1981. Longitudinal study of obesity in the National Survey of Health and Development. Br. Med. J. 283:13–17. Stein, Z., M. Susser, G. Saenger, and F. Marolla. 1975. Famine and Human Development: The Dutch Hunger Winter of 1944–1945. New York: Oxford University Press. Stein, Z.A., and M. Susser. 1984. Intrauterine growth retardation: Epidemiological issues and public health significance. Sem. Perinatol. 8:5–14. Stevens-Simon, C., and E.R. McAnarney. 1992. Determinants of weight gain in pregnant adolescents. J. Am. Diet Assoc. 92:1348–1351. Stockbauer, J.W. 1987. WIC prenatal participation and its relation to pregnancy outcomes in Missouri: A second look. Am. J. Public Health 77:813–818. Susser, M. 1991. Maternal weight gain, infant birth weight and diet: Causal sequences. Am. J. Clin. Nutr. 53:1384–1396. Taffel, S.M. 1986. Maternal Weight Gain and the Outcome of Pregnancy: United States, 1980. National Center for Health Statistics. Vital Health Stat. 21(44). Taffel, S.M., K.G. Keppel, and G.K. Jones. 1993. Medical advice on maternal weight gain and actual weight gain. Results from the 1988 National Maternal and Infant Health Survey. Ann. N.Y. Acad. Sci. 678:293–305.

ANTHROPOMETRIC RISK CRITERIA 146 Taha, T. el T., R.H. Gray, and A.A. Mohamedani. 1993. Malaria and low birth weight in Central Sudan. Am. J. Epidemiol. 138:318–325. Taitz, L.S. 1977. Obesity in pediatric practice: Infantile obesity. Pediatr. Clin. North. Am. 24:107– 115. Tanner, J.M. 1981. A History of the Study of Human Growth. Cambridge: Cambridge University Press. Teberg, A.J., F.J. Walther, and I.C. Pena. 1988. Mortality, morbidity, and outcome of the small-for- gestational age infant . Semin. Perinatol. 12:84–94. Theron, G.B., and M.L. Thompson. 1993. The usefulness of weight gain in predicting pregnancy complications. J. Trop. Pediatr. 39:269–272. Tomkins, A. 1981. Nutritional status and severity of diarrhoea among preschool children in rural Nigeria. Lancet 18:860–862. Tomkins, A., and F. Watson. 1989. Malnutrition and Infection: A Review. ACC/SCN State-of-the- Art Series, Nutrition Policy Discussion Paper No. 5. London: Centre for Human Nutrition, London School of Hygiene and Tropical Medicine. Torun, B., and F.E. Viteri. 1994. Influence of exercise on linear growth. Eur. J. Clin. Nutr. 48:186– 189. Tsuzaki, S., N. Matsuo, M. Saito, and M. Osano. 1990. The head circumference growth curve for Japanese children between 0–4 years of age: Comparison with Caucasian children and correlation with stature. Ann. Hum. Biol. 17:297–303. USDA (U.S. Department of Agriculture). 1991. Technical Papers: Review of WIC Nutritional Risk Criteria. Prepared for the Food and Nutrition Service by the Department of Family and Community Medicine, College of Medicine, University of Arizona, Tucson. Washington, D.C.: USDA. USDA (U.S. Department of Agriculture). 1994. Study of WIC Participant and Program Characteristics, 1992. Background Data. Office of Analysis and Evaluation, Food and Nutrition Service. Washington, D.C.: USDA. Valdez, R., M.A. Athens, G.H. Thompson, B.S. Bradshaw, and M.P. Stern. 1994. Birthweight and adult outcomes in a biethnic population in the U.S.A. Diabetologia 37:624–631. Vella, V., A. Tomkins, J. Ndiku, T. Marshal, and I. Cortinovis. 1994. Anthropometry as a predictor for mortality among Ugandan children, allowing for socio-economic variables. Eur. J. Clin. Nutr. 48:189–197. Verkerk, P.H., F.J. Van Spronsen, G.P. Smit, and R.C. Sengers. 1994. Impaired prenatal and postnatal growth in Dutch patients with phenylketonuria. The National PKU Steering Committee. Arch. Dis. Child. 71:114–118. Victora, C.G. 1992. The association between wasting and stunting: An international perspective. J. Nutr. 122:1105–1110. Villar, J., and J. Rivera. 1988. Nutritional supplementation during two consecutive pregnancies and the interim lactation period: Effect on birth weight . Pediatrics. 81:51–57. Villar, J., V. Smeriglio, R. Martorell, C.H. Brown, and R.E. Klein. 1984. Heterogeneous growth and mental development of intrauterine growth-retarded infants during the first 3 years of life. Pediatrics 74:783–791. Villar, J., M. Klebanoff, and E. Kestler. 1989. The effect on fetal growth of protozoan and helminthic infection during pregnancy. Obstet Gynecol. 74:915–920.

ANTHROPOMETRIC RISK CRITERIA 147 Villar, J., M. de Onis, E. Kestler, F. Bolanos, R. Cerezo, and H. Bernedes. 1990. The differential neonatal morbidity of the intrauterine growth retardation syndrome. Am. J. Obstet. Gynecol. 163:151–157. Villar, J., M. Cogswell, E. Kestler, P. Castillo, R. Menendez, and J.T. Repke. 1992. Effect of fat and fat-free mass deposition during pregnancy on birth weight. Am. J. Obstet. Gynecol. 167:1344–1352. Vobecky, J.S., J. Vobecky, D. Shapcott, and P.P. Demers. 1983. Nutrient intake patterns and nutritional status with regard to relative weight in early infancy. Am. J. Clin. Nutr. 38:730– 738. Wadden, T.A., G.D. Foster, K.D. Brownell, and E. Finley. 1984. Self-concept in obese and normal weight children. J. Consul. Clin. Psychol. 52:1104–1105. Walker, S.P., C.A. Powell, M. Grantham-MaGregor, J.H. Himes, and S.M. Chang. 1991. Nutritional supplementation, psychosocial stimulation, and growth of stunted children: The Jamaican study. Am. J. Clin. Nutr. 54:642–648. Waller, D.K., J.L. Mills, J.L. Simpson, G.C. Cunningham, M.R. Conley, M.R. Lassman, and G.G. Rhoads. 1994. Are obese women at higher risk for producing malformed offspring? Am. J. Obstet. Gynecol. 170:541–548. Wang, X., B. Guyer, and D.M. Paige. 1994. Differences in gestational age-specific birthweight among Chinese, Japanese and white Americans. Int. J. Epidemiol. 23:119–128. Waterlow, J.C. 1978. Observations on the assessment of protein-energy malnutrition with special reference to stunting. Courrier. 28:455–460. Waterlow, J.C. 1994a. Relationship of gain in height to gain in weight. Eur. J. Clin. Nutr. 48:S72– S74. Waterlow, J.C. 1994b. Causes and mechanisms of linear growth retardation (stunting). Eur. J. Clin. Nutr. 48:S1–S4. Wen, S.W., R.L. Goldenberg, G.R. Cutter, H.J. Hoffman, and S.P. Cliver. 1990. Intrauterine growth retardation and preterm delivery: Prenatal risk factors in an indigent population. Am. J. Obstet. Gynecol. 162:213–218. West, K.P., E. Djunaedi, A. Pandji, Kusdiono, I. Tarwotjo, A. Sommer, and the Aceh Study Group. 1988. Vitamin A supplementation and growth: A randomized community trial. Am. J. Clin. Nutr. 48:1257–1264. WHO (World Health Organization). 1988. Breast-feeding and Child Spacing: What Health Workers Need to Know. Geneva: WHO. WHO (World Health Organization). 1991. Indicators for Assessing Breast-feeding Practices: A Report of an Informal Meeting, 11–12 June, 1991 . WHO/CDD/SER 91.4. Geneva: WHO. WHO (World Health Organization). 1995. Physical Status: The Use and Interpretation of Anthropometry. WHO Technical Report Series 854. Geneva: WHO. Wilcox, L.S., and J.S. Marks, eds. 1995. From Data to Action: CDC's Public Health Surveillance for Women, Infants and Children. Atlanta: Centers for Disease Control. Williams, R.L., R.K. Creasy, G.C. Cunningham, W.E. Hawes, F.D. Norris, and M. Tashiro. 1982. Fetal growth and perinatal viability in California. Obstet. Gynecol. 59:624–632. Winick, M. 1969. Malnutrition and brain development. J. Pediatr. 74:667–679.

ANTHROPOMETRIC RISK CRITERIA 148 Winick, M., and P. Rosso. 1969. Head circumference and cellular growth of the brain in normal and marasmic children. J. Pediatr. 74:774–778. Witter, F.R., L.E. Caulfield, and R.J. Stolzfus. 1995. Influence of maternal anthropometric status and birth weight on the risk of cesarean delivery. Obstet. Gynecol. 85:947–951. Wolke, D., D. Skuse, and B. Mathisen. 1990. Behavioral style in failure-to-thrive infants: A preliminary communication. J. Pediatr. Psychol. 2:237–254. Wright, C.M., A. Aynsley-Green, P. Tomlinson, L. Ahmed, and J.A. MacFarlane. 1992. A comparison of height, weight and head circumference of primary school children living in deprived and non-deprived circumstances. Early Hum. Dev. 31:157–162. Yip, R. 1993. Expanded usage of anthropometry z-scores for assessing population nutrition status and data quality (abstract). P. 279 in Proceedings of the 15th International Congress of Nutrition, Adelaide. Yip, R., and T.W. Sharp. 1993. Acute malnutrition and high childhood mortality related to diarrhea: Lessons from the 1991 Kurdish refugee crisis. J. Am. Med. Assoc. 270:587–590. Yip, R., N.J. Binkin, and F.L. Trowbridge. 1988. Altitude and child growth. J. Pediatr. 113:486–489. Yip, R., I. Parvanta, K. Scanlon, E.W. Borland, C.M. Russell, and F.L. Trowbridge. 1992a. Pediatric nutrition surveillance system—United States, 1980–1991. Morbid. Mortal. Weekly Rep. 41 (SS-7):1–24. Yip, R., K. Scanlon, and F. Trowbridge. 1992b. Improving growth status of Asian refugee children in the United States. J. Am. Med. Assoc. 267:937–940. Yip, R., K. Scanlon, and F. Trowbridge. 1993. Trends and patterns in height and weight status of low-income U.S. children. Crit. Rev. Food Sci. Nutr. 33:409–421. Zhang, Y., R. Proenca, M. Maffei, M. Barone, L. Leopold, and J.M. Friedman. 1994. Positional cloning of the mouse obese gene and its human homologue. Nature 372:425–432.

Next: 5 Biochemical and Other Medical Risk Criteria »
WIC Nutrition Risk Criteria: A Scientific Assessment Get This Book
×
Buy Paperback | $53.00 Buy Ebook | $42.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

This book reviews the scientific basis for nutrition risk criteria used to establish eligibility for participation in the U.S. Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). The volume also examines the specific segments of the WIC population at risk for each criterion, identifies gaps in the scientific knowledge base, formulates recommendations regarding appropriate criteria, and where applicable, recommends values for determining who is at risk for each criterion. Recommendations for program action and research are made to strengthen the validity of nutrition risk criteria used in the WIC program.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!