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APPENDIXES
421
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Appendix
A
Considerations in Constructing
Gestational Weight Gain Charts
Gestational weight gain charts have been used in clinical practice for
many years. In Chapter 4, the subcommittee reviews the characteristics
of some of the wide variety of charts currently in use in the United
States. The lack of standardization across charts is due primarily to the
lack of appropriate data on which to base the weight gain curves used
in these charts. In this appendix, the subcommittee outlines research and
development issues it believes should be considered in the construction of
gestational weight gain charts.
RECOMMENDED CHARACTERISTICS OF
GESTATIONAL WEIGHT GAIN CHARTS
The subcommittee recommends that a new gestational weight gain
chart be developed with the following characteristics and supporting mate-
rials:
1. Gestational age, i.e., weeks from last normal menstrual period, on
the horizontal axis, and achieved weight, i.e., total body weight in kilograms
or pounds, on the vertical axis. There should be some provision for
adjusting the gestational age scale for any early-second-trimester ultrasound
assessment suggesting that previous estimates of gestational age might be
in error. The weight scale (vertical axis) should include both metric and
American units. The vertical axis on the weight gain chart should be
423
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424
APPENDIX A
calibrated for the woman's weight at the initial prenatal visit by entering
prepregnancy weight at zero weeks of gestation and then adding a specified
increment to the prepregnancy weight at each tick mark similar to the
approach used by Dimperio (1988) and shown in Figure ~5, Chapter 4.
2. Different charts for different classifications of prepregnancy weight
for height, i.e., underweight, moderate weight, overweight, and obese, and
possibly for short women, similar to that shown in Figure 4-4, Chapter 4.
3. A normative or average curve to represent the pattern of weight
gain by week of gestation for each classification of prepregnancy weight for
height.
4. Lines drawn to show upper and lower limits around the aver-
age curve, similar to those shown in Figure 4-4, Chapter 4. These limits
should be based on epidemiologic evidence. They could be percentiles
or standard deviations of the observed representative (normative) popula-
tion. Alternatively, they could be cutoff values established by comparison
of two overlapping distributions: a distribution of maternal weight at any
gestational age for healthy women with good outcomes and a comparable
distribution of maternal weight for the abnormal population, i.e., the pop-
ulation with unfavorable pregnancy outcomes. A method for determining
these cutoff values is presented below. The general methodology originally
developed for application to postnatal child growth curves has been de-
scribed by Galen and Gambino (1975) and by Haas and Habicht (1990~. A
chart incorporating cutoff values would allow estimation of the probability
that a woman would have a poor pregnancy outcome given her weight
gain to a specific week of pregnancy. However, it would not be useful in
the evaluation of a woman's rate of weight gain measured over repeated
prenatal visits.
5. Criteria for evaluating the rate of weight gain and pattems of gain,
either as a part of the chart itself or in accompanying instructions. ~
a certain degree, the curve of average gain in the normative population
provides guidance to the practitioner. Data-based guidelines for normal
rates (kilograms or pounds per week) and acceptable upper and lower limits
should be developed so that the subcommittee's recommendation of a linear
gain during the second and third trimesters (Chapter 1) can be validated.
Such guidelines should be established in the same way as the upper and
lower limits of achieved weight, i.e., as either statistical measures of the
normative population or as empirically derived cutoff values to discriminate
favorable from unfavorable outcomes. The criteria may best be presented
as a table of acceptable rates of gain to accompany the gestational weight
gain chart. One alternative would be to' include three different slopes or
inclinations representing excessive (steep slope), desirable, or inadequate
(shallow or negative slope) rates of weight gain. The slopes of the three
curves may need to be changed for different trimesters of pregnancy if
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APPENDIX A
425
research shows different desirable or normative rates for different stages of
pregnancy.
6. Clear, consistent criteria based on adequate research for assessing
prepregnancy weight status as part of the chart or supporting documen-
tation. These should include the appropriate way to express prepregnancy
weight (i.e., a body mass index or as a percentage of desirable body weight),
the appropriate reference standard to use, whether or not frame size should
be considered, and cutoff values to apply to the reference standard. The re-
search needed to establish the prepregnancy weight-for-height classification
scheme ideally should focus on establishing cutoff values for underweight
and overweight women based on data regarding unfavorable and favorable
pregnancy outcomes (as well as other short-term and long-term maternal
health risks such as postpartum obesity) for women with different weights
for height.
7. Easy to use, i.e., requiring only a few simple measurements, and
including indices that are easy to calculate or determine from tables or
nomograms, as well as an unambiguous classification scheme.
These and other design issues should be based on adequate research,
much of which has not yet been undertaken. The instrument needs to be
validated and evaluated in clinical settings. Consideration should be given
not only to its diagnostic capabilities but also to the training effort needed,
intra- and interobserver reliability of the measurements, acceptability to the
clinic staff, utility as an instructional tool for the patient, and, if relevant,
usefulness as a data collection instrument for research or surveillance.
RESEARCH NEEDS
To develop a chart with most of the characteristics described above,
new research will be needed, specifically, large-scale studies to establish
normative or desirable values for prepregnancy weight for height and
incremental and total weight gain patterns. The sample sizes should be
large enough to establish precise values for weight gain at the extremes (5th
and 95th percentiles). The limits of the range of normative or desirable
gestational weight gain should be established by examining the distribution
of prepregnancy weight for height in relation to gestational weight gain
among women with good as compared to poor pregnancy outcomes.
1b establish an optimal or ideal range of prepregnancy weight and
gestational weight gain, one needs to sample a population that experiences
both desirable and undesirable pregnancy outcomes. Most of the current
reference curves for gestational weight gain are based on data for women
who had favorable outcomes, i.e., healthy, full-term infants with normal
birth weights. As Figure A-1 shows, these women represent a subset (sub-
population B) of the total gestational weight gain distribution for the general
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426
- o
o-
>`
A:
a)
a'
LL
APPENDIX A
A Women Delivering Babies Weighing < 2,500 9
B Women Delivering Babies Weighing 2,500 to 4,000 9
C Women Delivering Babies Weighing > 4,000 9
High
Low
A
\
-
1 ~
Low
High
Total Gestational Weight Gain
FIGURE A-1 Hypothetical distributions of gestational weight gain in three subpopulations
of women.
population. There are women at the extremes of the gestational weight
gain distribution who have less favorable outcomes, such as intrauterine
growth retardation (subpopulation A) or fetal macrosomia (subpopulation
C). Similar subpopulations are likely to exist for other maternal measures
(horizontal axis), such as prepregnancy weight, accumulated weight gain
to a specific stage of pregnancy, or rate of weight gain during specific
trimesters of pregnancy. Moreover, the distribution of gestational weight
gain in the three subpopulations representing the range of fetal growth is
likely to be different for women with different prepregnancy weights. One
could also subdivide the distribution of gestational weight gain in Figure
A-1 to represent other outcomes. For example, subpopulation A could be
women who deliver preterm infants, and population C could be women
who retain the fat accumulated during pregnancy and are thus at risk of
later obesity. (In this case, the distribution of gestational weight gain for
subpopulations A and C would likely overlap.) Subpopulation B could be
women who deliver full-term infants and do not retain pregnancy-acquired
adipose tissue after delivery.
The Society of Actuaries (1959, 1960; Society of Actuaries/Association
of Life Insurance Medical Directors of America, 1980) applied this scheme
to obtain the 1959 and 1983 Metropolitan Life Insurance Company's tables
of ideal body weight. To distinguish the subgroups, it used mortality
data during a specified period following the measurement of weight. It
examined the distributions of body weight for those who died and for those
who survived during the period of observation: subpopulation B would
represent the weights of those who survived. Since the Metropolitan Life
OCR for page 427
APPENDIX A
427
Insurance Company's ranges are based on postreproductive mortality and
not pregnancy outcomes, they may be inappropriate for classifying mothers
by prepregnancy weight for height.
A better criterion for establishing the desirable range of prepreg-
nancy weights in gestational weight gain charts might be the risk of poor
pregnancy outcomes, such as extremes in fetal growth, risk of obstetric
complications, or development of postpartum obesity. However, an anal-
ysis that considers prepregnancy weight in identifying an optimal range
for gestational weight gain requires application of sophisticated statistical
methods, because prepregnancy weight plays two roles in the causal chain
leading to some outcomes: it has an independent effect on fetal growth,
and it modifies the effect of gestational weight gain on fetal growth (Figure
2-2, Chapter 2~.
The degree of overlap among the three distributions illustrated in
Figure A-1 is relatively easy to analyze, if it is not necessary to assume
complex relationships of prepregnancy weight and gestational weight gain
to outcomes. Such an analysis can yield important information on the ap-
propriate cutoff values for gestational weight gain or prepregnancy weight.
These values can then be used as the upper and lower limits of the gesta-
tional weight gain charts or for classification of underweight and overweight
prior to pregnancy. The analytic methods were described in detail by Galen
and Gambino (1975) and elaborated by Habicht et al. (1982), Swets and
Pickett (1982), and Swets (1988~.
An analysis of this type could be applied to incremental gestational
weight gain data as well. Results of analysis of gestational weight gain
rates could lead to recommendations for optimal rates at different stages
of pregnancy.
1b be useful to the clinician, the status or course of a patient's weight
gain must be assessed accurately early enough in the pregnancy to allow for
intervention. The determination of desirable total weight gain is useful in
that it provides the end point through which a gestational weight gain curve
should pass. However, the pattern of gain by trimester of pregnancy and the
rate of gain between prenatal visits are more informative to the clinician.
Therefore, future research should be longitudinal, allowing for frequent
(at least monthly) measurements of weight beginning as early as possible
in gestation and continuing throughout pregnancy. This type of research
could yield essential information on the variation in rates of weight gain but
would require a large sample size to evaluate effectively the relationship
of these rates to the occurrence of relatively infrequent outcomes such as
preterm delivery, intrauterine growth retardation, macrosomia, or perinatal
death.
Data on normative rates of weight gain throughout pregnancy would
allow for the construction of improved incremental weight gain charts and
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428
APPENDIX A
also of weight gain velocity charts, which display gestational duration on
the horizontal axis and rate of gain on the vertical awns. Weight gain
velocity graphs are powerful research tools but are infrequently used by
clinicians to study postnatal growth of children Inner, 1986~. There
are no weight velocity curves for monitoring pregnancy in healthy adult
women, but some have been developed for the assessment of pregnancies
in teenagers (Hediger et al., 1989~.
The research proposed here would provide the basic information
needed to construct clinically useful gestational weight gain charts. Re-
search should also be encouraged in the development of simplified assess-
ment tools, such as those described by Rosso (1985) (Chapter 4, Figure
4-8), but the assumptions on which they are based need to be scrutinized
and the instruments properly validated.
REFERENCES
Dimperio, D. 1988. Prenatal Nutrition: Clinical Guidelines for Nurses. March of Dimes
Birth Defects Foundation, White Plains, N.Y. 134 pp.
Galen, R.S., and S.R. Gambino. 1975. Beyond Normality: The Predictive Value and
Efficiency of Medical Diagnoses. John Wiley & Sons, New York. 237 pp.
Haas, J.D., and J.P. Habicht. 1990. Growth and growth charts in the assessment of
preschool nutritional status. Pp. 160-183 in G.A. Harrison and J.C. Waterlow, eds.
Diet and Disease in Traditional and Developing Societies. Cambridge University Press,
Cambridge.
Habicht, J.P., LD. Meyers, and C. Brownie. 1982. Indicators for identifying and counting
the improperly nourished. Am. J. Clin. Nutr. 35:1241-1254.
Hediger, M.L., TO. 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.
Rosso, P. 1985. A new chart to monitor weight gain during pregnancy. Am. J. Clin. Nutr.
41:644-652.
Society of Actuaries. 1959. Build and Blood Pressure Study 1959, Vol. I. Society of
Actuaries, Chicago. 268 pp.
Society of Actuaries. 1960. Build and Blood Pressure Study 1959, Vol. II. Society of
Actuaries, Chicago. 240 pp.
Society of Actuaries/Association of Life Insurance Medical Directors of America. 1980.
Build Study 1979. Society of Actuaries/Association of Life Insurance Medical Directors
of America, Chicago. 255 pp.
Swets, J.A. 1988. Measuring the accuracy of diagnostic systems. Science 240:1285-1293.
Swets, J.N, and R.M. Pickett. 1982. Evaluation of Diagnostic Systems: Methods from
Signal Detection Theory. Academic Press, New York. 253 pp.
Tanner, J.M. 1986. Use and abuse of growth standards. Pp. 95-109 in F. Falkner and
J.M. Tanner, eds. Human Growth: A Comprehensive Treatise, 2nd ea., Vol. 3.
Methodology Ecological, Genetic, and Nutritional Effects on Growth. Plenum Press,
New York.
OCR for page 429
Spends
B
Pro~siona1 Debt Gain Embark by
Preprognan~ Body Hass Index (BRIG
429
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430
APPENDIX B
A. For Normal Weight Women with BMI
of 19.8 to 26.0 (Metric~a
50
40
30
._
20
10
o
1 st 2nd 3rd
l l
TARGET: 15.5 TO 16 kg (25 to 35 lb) at 40 wks
with a gain of 0.4 kg (1 lb) / wk
during trimester 2 and 3.
_ / 10
/
- / _
/
·1--~--1 1 1 1 1 1 ~1
0 5 10 15 20 25 30 35 40 45
Week of Gestation
20
15
5
by
._
Cal
CD
aAssumes a 1.6-kg (3.5-lb) gain in first trimester and the remaining gain at
a rate of 0.44 kg (0.97 lb) per week.
bAssumes a 2.3-kg (5-lb) gain in first trimester and the remaining gain at a
rate of 0.49 kg (1.07 lb) per week.
CAssumes a O.9-kg (2-lb) gain in first trimester and the remaining gain at a
rate of 0.3 kg (0.67 lb) per week.
OCR for page 431
APPENDIX B
431
B. For Underweight Women with BMI
Less Than 19.8 (Metric~b
50
40
- 30
._
cry
20
10
o
1 st 2nd 3rd
' ' ' ' 1
TARGET: 12.5 to 18 kg (28 to 40 lb) at 40 wks
with a gain of 0.5 kg ( 1 lb) / wk
during trimester 2 and 3.
/
· -
· -
.1. ~I 1 1 1 1 1 1 1
0 5 10 15 20 25 30 35 40 45
Week of Gestation
/
C. For Overweight Women with BMI
of >26.0 to 29.0 (Metric)C
50
40
30
._
~ 20
1 st 2nd 3rd
TARGET: 7 to 11.5 kg (15 to 25 lb) at 40 wks
with a gain of 0.3 kg (0.5 to 0.75 lb) / wk
during trimester 2 and 3.
/
10
O .... /
/
, . . . . .
0 5 10 15 20 25 30 35 40 45
Week of Gestation
20
15 Y
-
._
cry
10
5
20
15 Y
._
c:
10 3:
5
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Appendix
CTable for Estimating Body Mass Index (Metricya by Using Either Metric or
English Measurements of Prepregnangy Weight and Height; BMIs < 19.8
= low; BMIs 26.1 - 29.0 = high; BMIs > 29.0 = obesity (see shaded area
above heavy line).
(Bible follows on pages 434 and 435.)
433
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Appendix D
Biographical Sketches of
Committee Members
Barbara Abrams, Dr.P.H., R.D., is assistant professor in the Depart-
ments of Social and Administrative Health Sciences, School of Public
Health, University of California, Berkeley, and the Department of Obstet-
rics, Gynecology and Reproductive Sciences, School of Medicine, University
of California, San Francisco. She worked as a perinatal nutritionist for more
than a decade and has conducted several epidemiologic studies on maternal
weight gain, nutrition, and pregnancy outcome.
Lindsay Allen, Ph.D., is professor in the Department of Nutritional
Sciences at the University of Connecticut, Storrs. She has conducted
research on relationships between nutrition and the outcome of human
pregnancy and lactation in the United States as well as in other countries. In
recent years, her special interest has been the effect of marginal malnutrition
on the function of women and children in Mexico.
Gertrud S. Berkowitz, Ph.D., is perinatal epidemiologist and associate
professor in the Department of Obstetrics, Gynecology, and Reproductive
Science and the Department of Community Medicine at Mount Sinai School
of Medicine, New York. She has conducted various research studies on
preterm delivery and intrauterine growth retardation and has written about
the role of environmental and occupational hazards during pregnancy.
Nancy F. Butte, Ph.D., is assistant professor of pediatrics at Baylor
College of Medicine. She has conducted research on infant nutrition,
lactation, and energy metabolism.
437
OCR for page 438
438
APPENDIX D
Ronald A. Chez, M.D., is professor of obstetrics and gynecology at the
University of South Florida School of Medicine in Tampa. He previously
held positions as chief of the Pregnancy Research Branch and clinical
director of the National Institute of Child and Human Development as well
as chair of the Department of Obstetrics and Gynecology at Pennsylvania
State University. His research has focused on aspects of fetal physiology,
including the exchange of substrates across the placenta.
Peter R. Dallman, M.D., is professor of pediatrics at the University
of California, San Francisco. His research deals with the manifestations,
diagnosis, and prevalence of iron deficiency. He has served on national and
international committees and panels to establish iron requirements and to
devise strategies for preventing iron deficiency.
lere D. Haas, Ph.D., is professor of nutritional sciences at Cornell
University. He has conducted research on the maternal, fetal, and infant
responses to stresses at extreme high altitudes as well as on relationships
between maternal nutritional status and fetal growth, postnatal growth,
and postnatal development and morbidity in Bolivia, Peru, Guatemala,
Indonesia, and the United States.
Michael Hambidge, M.D., Sc.D., is professor of pediatrics at the
University of Colorado Health Sciences Center. He is also director of both
the Center for Human Nutrition and the Pediatric Clinic Research Center
in the School of Medicine at the university. His major interest is human
nutrition, including research, training, education. and improving nutrition
practices in the community.
--a ~~-~ --I- ~
Margit Hamosh, Ph.D., is professor in the Department of Pediatrics
and chief of the department's Division of Developmental Biology and Nutri-
tion at Georgetown University Medical Center. She has conducted research
on lung development and on fat digestion and absorption, emphasizing the
ontogeny of digestive enzymes and compensatory digestive function in pan-
creatic insufficiency, lipid clearance, the composition of human milk and
the function of its components in the neonate. Dr. Hamosh has served on
several committees of the National Institutes of Health and is president of
the International Society of Research on Human Milk and Lactation.
Francis E. Johnston, Ph.D., is professor and chairman of the De-
partment of Anthropology of the University of Pennsylvania. His research
focuses on the growth, development, and body composition of children and
youth, especially in relationship to nutritional status.
la net C. King, Ph.D., is professor of nutrition and chair of the De-
partment of Nutritional Sciences at the University of California, Berkeley.
She has conducted research on nutritional needs during pregnancy and
OCR for page 439
APPENDIX D
439
has published on the protein, energy, and zinc requirements of pregnant
women. She has served on many national committees involved in estab-
lishing policies relating to prenatal care.
Avanelle Kirksey, Ph.D., is Meredith Distinguished Professor of Nutri-
tion at Purdue University. She has published widely in the area of vitamin
B6 in pregnancy and lactation. She has been a collaborator in maternal
and infant nutrition research in Egypt and presently serves as facilitator for
Midwest Universities Consortium for International Activities for graduate
nutrition programs in Indonesia.
Joel C. Kleinman, Ph.D., is director of the Division of Analysis,
National Center for Health Statistics, Centers for Disease Control. He has
published extensively on statistical and epidemiologic issues related to low
birth weight and infant mortality. He has been a member of the U.S. Public
Health Service Work Group on Maternal and Infant Health Objectives for
the Year 2000 and the Subcommittee on Infant Mortality and Low Birth
Weight of the Department of Health and Human Services Secretary's Task
Force on Minority Health.
Michael S. Kramer, M.D., is professor of pediatrics and of epidemi-
ology and biostatistics at the McGill University Faculty of Medicine in
Montreal. He has been a career research scholar of the National Health
Research and Development Program, Health and Welfare Canada, and
is currently a senior career investigator of the Fonds de la Recherche en
Sante du Quebec. His primary research interests are the determinants and
consequences of preterm birth and intrauterine growth retardation and the
diagnostic and therapeutic management of the young febrile child.
Sally Ann Lederman, Ph.D., is assistant professor of public health
and nutrition at Columbia University's Faculty of Medicine. In animals,
she has studied the effect of dietary changes on pregnancy outcome and
lactation performance, focusing on changes in maternal body composition.
In humans, she has studied the relationship of birth weight to maternal body
weight and pregnancy weight changes in teenage mothers and in mothers
bearing twins. She has also studied demographic factors influencing low
birth weight in New York City and psychosocial predictors of pregnancy
outcome in several ethnic groups and of lactation success among poor
women in Brazil.
Charles S. Mahan, M.D., is deputy secretary for health and state
health officer for Florida, director of the Robert Wood Johnson Healthy
Futures Program, and professor of obstetrics and gynecology at the Univer-
sity of Florida College of Medicine. His special interests have been preterm
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440
APPENDIX D
birth prevention, food supplementation in pregnancy, family-centered ma-
ternity care, prevention of unnecessary cesarean deliveries, infant mortality,
improved care for low-income women, and out-of-hospital birth centers.
Jennifer Niebyl, M.D., is professor and head of the Department of
Obstetrics and Gynecology at the University of Iowa, Iowa City. Earlier
in her career, she was director of the Division of Maternal-Fetal Medicine
in the Department of Gynecology and Obstetrics at the Johns Hopkins
University. Her major research interest is the use of medications during
pregnancy.
Roy M. Pitkin, M.D., is professor and chair of the Department of
Obstetrics and Gynecology at the University of California, Los Angeles.
Before assuming this post in 1987, he was professor and head of the
Department of Obstetrics and Gynecology at the University of Iowa, Ames.
He previously chaired the Committee on Nutrition of the Mother and
Preschool Child of the Food and Nutrition Board, National Academy of
Sciences.
Kathleen M. Rasmussen, Sc.D., R.D., is associate professor of nutri-
tion at Cornell University and program director of a National Institutes of
Health training grant in maternal and child nutrition. Her research has fo-
cused on the effects of maternal malnutrition on reproductive performance,
with an emphasis on lactation.
John W. Sparks, M.D., is associate professor in the Department of
Pediatrics at the University of Colorado. A neonatologist, he has served as
director of Newborn Services and medical director of the Neonatal Intensive
Care Unit at University Hospital, Denver. Scientific interests include the
physiology, metabolism, and nutrition of the fetus and newborn.
Melton Susser, M.B., B.Ch., D.P.H., is Sergievsky Professor of Epi-
demiology and founder and director of the Sergievsly Center at Columbia
University in New York The Center is endowed for the study of the
epidemiology of neurodevelopmental disorders. He has also been head of
epidemiology in the Columbia University School of Public Health. His work
covers several specific fields, including prenatal development and prenatal
nutrition, as well as such general topics as causality and the social sciences
in epidemiology.
Representative terms from entire chapter:
gestational weight
