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Progress in Preventing Childhood Obesity: How Do We Measure Up? 3 Diverse Populations The obesity epidemic is occurring among boys and girls throughout the United States, among younger children and adolescents, across all socioeconomic groups and among all racial/ethnic subpopulations. However, in several racial/ethnic groups, in low-income populations, and among recent immigrants to the United States, the rates of obesity among children and youth are alarmingly high or are increasing faster than average. The children and youth who are at the highest risk for obesity often experience other social, economic, and health disparities concurrently and do not live in environments that inherently support health-promoting behaviors. In addition, although some of the risk factors for obesity are relatively ubiquitous in settings where American children and youth spend their time (e.g., communities, schools, shopping malls, retail stores, and home), epidemiologic evidence shows that African-American, Hispanic/ Latino, American Indian/Alaska Native, and Pacific Islander populations and children experiencing poverty are more likely to live in environments with inadequate support for health-promoting behaviors. Assessing the impact of these different environments presents an enormous challenge for tracking progress against obesity in diverse populations. On the other hand, the diversity of the U.S. population and the variation in patterns of obesity-related risks also provide opportunities to expand our understanding of how trends, patterns, and risk factors manifest in certain environments and to identify the types of interventions that are likely to be effective when they are tailored specifically to build on a population’s characteristics, perspectives, and social and cultural assets.
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Progress in Preventing Childhood Obesity: How Do We Measure Up? Much remains to be learned about the role of race/ethnicity, socioeconomic status (SES), and regional disparities in childhood obesity to build an evidence base that will support the most effective strategies and promising practices. Progress in preventing childhood obesity should include an examination of efforts to define and address the contexts and mechanisms that lead to and perpetuate childhood obesity in environments with excessive risks. Several recommendations in the Health in the Balance report (IOM, 2005) emphasized the need for prominent government leadership and community collaboration to develop and promote programs and policies that will collectively encourage healthful eating patterns and physical activity behaviors, particularly for young populations at the highest risk for obesity and related chronic diseases. Helping at-risk children and youth balance their energy intakes and their energy expenditures requires an understanding of the complex and interacting influences of the social, economic, and built environments and the adverse environmental conditions that low-income and racially/ethnically diverse populations encounter as they regularly attempt to obtain affordable foods, beverages, and meals that contribute to a healthful diet and find opportunities to engage in recreational play and physical activity (Day, 2006; Glanz et al., 2005; Goodman, 2003; Gordon-Larsen et al., 2006; IOM, 2005; Jetter and Cassady, 2005; Powell et al., 2004). A multifaceted approach to address obesity and related health considerations is relevant to children and youth overall but leads to different perspectives on the appropriate solutions for specific populations, depending on their historical and sociopolitical contexts and the timing and rate of relevant economic and lifestyle transitions (Kumanyika, 1994; Kumanyika and Golden, 1991). Because the focus of this report is on evaluation, this chapter provides only a brief overview of the context for these issues. The reader is referred to the extensive body of research regarding the interactions among societal, cultural, genetic, and biobehavioral risk and protective factors and their implications for promoting population health (Dabelea et al., 2000; Gillman et al., 2003; Halfon and Hochstein, 2002; Halfon and Inkelas, 2003; IOM, 2001, 2003; Krieger, 1994; Krieger and Davey Smith, 2004; McEwen, 2001; NRC and IOM, 2000, 2004; Reilly et al., 2005; Rosenbloom, 2002). The chapter focuses on the key issues relevant to improving the implementation and evaluation of obesity prevention efforts involving high-risk and culturally diverse populations. UNDERSTANDING SPECIFIC CONTEXTS Many aspects of society have changed concomitantly with the rise in childhood obesity. A broader understanding of the potential interplay
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Progress in Preventing Childhood Obesity: How Do We Measure Up? among these societal changes and children’s biological and behavioral responses is needed. For the population subgroups most affected by obesity, the relevant adverse social and environmental factors may be concentrated or magnified. A variety of causal pathways are associated with many aspects of systemic disadvantage (e.g., poverty, substandard housing, limited educational opportunities, and low levels of social integration), which can lead to adverse health, social, and economic circumstances (Gostin and Powers, 2006). These factors have greater impacts on those with the fewest resources to buffer these influences. The subpopulations that have the highest prevalence of obesity are those considered to be socially, economically, and politically disadvantaged in other respects. Thus, although the determinants of obesity are generally of the same nature among all population groups, special considerations are needed to assess whether the pathways to progress in preventing childhood obesity in the entire population will also reach the subgroups who are the most affected. Long-term investments that support the development or adaptation and evaluation of childhood obesity prevention initiatives are needed. These initiatives also need to be adapted to various settings, contexts, and subpopulations for their dissemination if they are proven to be effective. Obesity Prevalence Obesity and its risk-behavior determinants (e.g., high levels of consumption of energy-dense and low-nutrient diets, physical inactivity, and sedentary behaviors) are major drivers of health disparities by race/ethnicity as they contribute to three of the disease categories responsible for the majority of excess mortality: type 2 diabetes, cardiovascular diseases (CVDs), and cancer (Wong et al., 2002). Obesity and at-risk obesity prevalence rates in American children and youth reveal significant differences by age and sex and between racial/ethnic groups (Freedman et al., 2006; Hedley et al., 2004; Ogden et al., 2006; Sherry et al., 2004). There does not appear to be a general excess risk in all age and gender groups, although the increases in obesity over the past 30 years have been especially pronounced at the upper part of the body mass index (BMI) distribution for children and youth. From 1971–1974 to 1999–2002, the prevalence of individuals in certain subgroups with BMI levels above the 99th percentile increased substantially. Additionally, African-American girls ages 6 to 17 years have experienced greater increases in obesity prevalence than white children and adolescents. These increases began in the 1970s, whereas the increases among individuals in other racial/ethnic groups were not observed until the 1980s (Freedman et al., 2006). By tracking obesity prevalence rates in subpopulations and evaluating the progress achieved by obesity prevention interventions, it may be pos-
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Progress in Preventing Childhood Obesity: How Do We Measure Up? sible to reduce the risk of obesity in these groups and ensure that primary obesity prevention strategies are reaching the entire target population. It is also important to track increases in BMI levels and obesity prevalence because childhood obesity is associated with an increased risk of CVD and mortality in adulthood (Li et al., 2004; Srinivasan et al., 2002). In 2003–2004, National Health and Nutrition Examination Survey (NHANES) data showed that 33.6 percent of U.S. children and adolescents were either obese (17.1 percent) or at risk of becoming obese (16.5 percent) (Ogden et al., 2006). The analysis of trends from NHANES data reveal that, when compared with non-Hispanic white cohorts, non-Hispanic black and Mexican-American children and adolescents, ages 2 to 19 years, have a greater prevalence of obesity.1 Non-Hispanic African-Americans and Mexican-American children and adolescents are also at greater risk of becoming obese (Hedley et al., 2004; Ogden et al., 2006). The prevalence rates of obesity and at risk for obesity in children and adolescents by age, sex, and racial/ethnic group for 2003 and 2004 are shown in Figure 3-1. State-specific prevalence and trends among 2- through 4-year-old children from low-income U.S. families were examined from 1989 to 2000. The results showed significant increases in obesity among low-income children in 30 states and significant decreases in childhood underweight in 26 states (Sherry et al., 2004). Although no geographic predominance was apparent, the number of states reporting obesity prevalence rates of more than 10 percent increased from 11 in 1989 to 28 in 2000. The number of states reporting decreased rates of underweight also rose during the same time frame, as reflected by 9 states in 1989 and 23 states in 2000 that had underweight prevalence rates equal to or less than 5 percent (Sherry et al., 2004). National obesity prevalence data are limited for American Indian/ Alaska Native and Asian/Pacific Islander children and youth. Nevertheless, an analysis of data for 9,464 American Indian children and youth, ages 5 to 18 years, compared with NHANES II data (1976 to 1980) found that 39 percent had BMIs above the 85th percentile (Jackson, 1993). Another analysis estimated the prevalence of obesity in a sample of 1,704 7-year-old children from 7 American-Indian communities across the United States to be between 27 and 30 percent for boys and girls, and the at-risk obesity prevalence was estimated at 20 to 21 percent for boys and girls (Caballero et al., 2003). In 2002 and 2003, an analysis of 11,538 American Indians, ages 5 to 17 years, attending 55 schools on 12 reservations located in the 1 Obesity is defined in this report as a BMI for age at or above the sex-specific 95th percentile of the Centers for Disease Control and Prevention (CDC) BMI charts developed in 2000. At risk for obesity is defined as a BMI for age at or above the sex-specific 85th percentile but less than the 95th percentile of the CDC BMI charts.
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Progress in Preventing Childhood Obesity: How Do We Measure Up? FIGURE 3-1 Percentage of U.S. children and adolescents ages 2 to 19 years who are obese or at risk for obesity by sex and race/ethnicity in 2003 to 2004. SOURCE: Ogden et al. (2006). Aberdeen Area of the Indian Health Service (North Dakota, South Dakota, Iowa, and Nebraska), found that both the obesity prevalence and the at-risk obesity prevalence rates exceeded the levels for all U.S. children at almost every age group. The obesity prevalence rate was 24 percent for 5-year-old American-Indian children. Nearly one half (47 percent) of 5-year-old boys and 41 percent of 5-year-old girls were at risk for obesity (Zephier et al., 2006). There are limited data on the prevalence rates of obesity among Alaska-Native children and youth. One analysis examined the BMI levels of 1,632 students, ages 3 to 18 years, in 20 rural Alaskan communities. Results showed that nearly 50 percent were either obese (25 percent; n = 407) or at risk for obesity (24 percent; n = 392) (Dirks et al., 2006). National prevalence data for Asian/Pacific-Islander populations are not available. However, the obesity prevalence rate among a sample of low-income preschool children in Hawaii was 8.7 percent in 1997, whereas the national mean that year was 10.3 percent. However, the rate caught up to the national mean in 2002, with prevalence rates of 13.1 percent in Hawaii and 13.5 percent nationally (Baruffi et al., 2004). A cross-sectional study of 21,911 Samoan, Filipino, Hawaiian, Asian, Hispanic/Latino, African-American, and white toddlers ages 12 to 59 months participating in the Hawaii Special Supple-
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Progress in Preventing Childhood Obesity: How Do We Measure Up? mental Nutrition Program for Women, Infants, and Children (WIC) in 1997 and 1998 found a higher than expected prevalence of obesity among preschoolers ages 2 to 4 years. Samoan toddlers had the highest prevalence of obesity at 27 percent, followed by Filipinos (12.4 percent), Hawaiians (11.3 percent), Hispanics (10.1 percent), Asians (9.0 percent), whites (8.5 percent), and African Americans (7.3 percent) (Baruffi et al., 2004). Health Effects of Childhood Obesity Type 2 diabetes, which accounted for less than 3 percent of all cases of new-onset diabetes among children and adolescents two decades ago, today accounts for between 30 and 45 percent of new-onset cases among adolescences and young adults (ADA, 2000; Rosenbloom et al., 1999). An analysis of data from NHANES (1999–2000), representing 27 million U.S. adolescents, showed a higher prevalence of impaired fasting glucose levels (an indicator for type 2 diabetes risk) among obese adolescents (17.8 percent) that among adolescents of normal weight (7.0 percent). In addition, the data showed that the rate of impaired fasting glucose levels was most pronounced among Mexican-American adolescents (13.0 percent) compared with the rates among African-American (4.2 percent) and white adolescents (7.0 percent) (Williams et al., 2005). On the basis of an analysis of data from NHANES (1999 to 2002) with a sample of 4,370 adolescents ages 12 to 19 years, the prevalence of type 2 diabetes was substantial and was projected to affect more than 39,000 U.S. adolescents and 2.77 million adolescents with impaired fasting glucose levels. These estimates present important implications for public health because of the high level of conversion from an impaired fasting glucose level to type 2 diabetes in adults and the increased risk of CVD in individuals with type 2 diabetes (Duncan, 2006). American-Indian/Alaska-Native, African-American, and Hispanic/Latino adolescents have a higher prevalence of type 2 diabetes than white adolescents; and this rise has occurred in parallel with the obesity epidemic among both children and adults (Gahagan et al., 2003; Oeltmann et al., 2003; Pinhas-Hamiel and Zeitler, 2005). American Indians/Alaska Natives have the highest rates of type 2 diabetes of any racial/ethnic group in the United States (National Diabetes Information Clearinghouse, 2005) and significant rates of heritability of CVD (North et al., 2003). Type 2 diabetes is a major public health crisis among American Indian/Alaska Native adolescents. From 1990 to 1998, the total number of young American Indians/Alaska Natives diagnosed with diabetes increased by 71 percent, and the prevalence increased by 46 percent (6.4 per 1,000 population to 9.3 per 1,000 population). An increase in prevalence was greater among adolescents ages 15 to 19 years and young adults (Acton et al., 2002). Between
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Progress in Preventing Childhood Obesity: How Do We Measure Up? 1990 and 2001, the prevalence of type 2 diabetes increased by 106 percent among 15- to 19-year-old American-Indian youth and increased by 50 percent among American-Indian children and youth younger than 15 years of age (IHS National Diabetes Program, 2004). Sociodemographic Profiles Racial/Ethnic Diversity of the U.S. Population According to the 2000 U.S. Census, approximately 30 percent of the U.S. population identified themselves as members of a racial or an ethnic minority group. The 2000 Census counted more than 36 million African Americans (12.9 percent of the population); more than 35 million Hispanics/Latinos (12.5 percent) who live in the United States and another 3.8 million who live in the Commonwealth of Puerto Rico; nearly 12 million Asians (4.2 percent); 874,000 Native Hawaiians and other Pacific Islanders; and 4.3 million people (1.5 percent of the total U.S. population) reported that they were American Indians/Alaska Natives (2.4 million or 1 percent reported only American Indian/Alaska Native as their race), of which 35.9 percent live in American Indian areas (which include reservations) or Alaska Native village areas (Hobbs and Stoops, 2002; Ogunwole, 2006). By 2050, it is projected that these groups will account for almost 50 percent of the U.S. population (MBDA, 1999). The ethnic minority population is expected to account for nearly 90 percent of the total growth in the U.S. population, from an ethnic/racial minority population of 69 million in 1995 to one of 186 million in 2050 (MBDA, 1999). Thus, the term “minority” is increasingly misleading as a descriptor for diverse racial/ ethnic groups in the aggregate, at least with respect to the proportion of the multicultural U.S. population. Geographic Variation in Population Diversity Each of the 50 states throughout the nation has growing childhood, youth, and adult obesity burdens that are leading to overwhelming economic, health, and social challenges that will reverberate at the federal, state, and local levels. Certain issues for high-risk populations dominate in certain states and localities where racial and ethnic minority populations are a numerical majority. Currently, this is the case in California, given the higher proportion of Hispanics/Latinos and African Americans compared with the proportion of non-Hispanic whites. Hispanics/Latinos, who represent 20 different nationalities, are the nation’s largest and fastest-growing ethnic group as the result of ongoing immigration and natural increases in the birth rates of Hispanic/Latino
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Progress in Preventing Childhood Obesity: How Do We Measure Up? citizens (NRC, 2006a). Given current demographic trends, nearly one in five U.S. residents will be of Hispanic/Latino origin by 2025 (NRC, 2006b).2 In addition to California, it is projected that by 2025, Texas, New Mexico, Hawaii, and the District of Columbia will also have population distributions in which non-Hispanic whites will be the minority (MBDA, 1999). Collectively, these four states and the District of Columbia represent 25 percent of the entire U.S. population. From this perspective on U.S. population demographics, finding ways to meet the challenges of addressing childhood obesity in racially, ethnically, and culturally diverse contexts becomes an urgent priority. Socioeconomic Status, Poverty, Health Disparities, and Health Outcomes Socioeconomic Status and Poverty Patterns of disease are best understood within the context of social determinants of health, which represent the societal conditions that affect health and that can be changed by social and health policies and programs. Three categories of social determinants that potentially affect health include social institutions (e.g., cultural and faith-based organizations, political structures, and economic systems including availability and distribution of fresh fruits and vegetables), physical surroundings (e.g., neighborhoods, worksites, towns, and cities), and social relationships (e.g., social networks and the differential treatment of subpopulations) (Anderson et al., 2003b). The implications of social determinants of health for assessing and evaluating progress in obesity prevention are discussed at the end of this chapter and in Chapter 6. Research has shown that the SES characteristics of the neighborhood in which individuals live (e.g., average income and percent unemployment) are better predictors than individual characteristics of morbidity and mortality (Diez-Roux et al., 1997; Finkelstein et al., 2004; Jargowsky, 1997), and that poverty is the most powerful single determinant of health (Lynch et al., 1997). Poverty causes poor health through its connection with reduced access to and use of health care services (with the quality of preventive, primary, and specialty health care services for this population often 2 The terms Hispanic and Latino are used interchangeably in this report. Both terms are used in the U.S. census. The United States population includes individuals from 20 Spanish-speaking nationalities, of which nearly one-half are foreign born and 40 percent are undocumented immigrants. Immigrants from Mexico, Puerto Rico, and Cuba represent more than 75 percent of the Hispanic/Latino population in the United States (NRC, 2006a,b).
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Progress in Preventing Childhood Obesity: How Do We Measure Up? being lower), food insecurity3 and low-quality diets, and behaviors that do not support healthy lifestyles (DHHS and AHRQ, 2005; NCHS, 2005). African-American, Hispanic/Latino, and American Indian/Alaska Native households are substantially overrepresented among all U.S. households with incomes below the poverty level (DeNavas-Walt et al., 2005; NRC, 2006b; Robert and House, 2000). Moreover, children and adults in families with incomes below or near the federal poverty level4 have poorer health outcomes than those in families with higher incomes (DHHS and AHRQ, 2005; IOM, 2003). In 2003, 11 percent of U.S. children had no health insurance (Annie E. Casey Foundation, 2006). Children in low-income families are substantially more likely than children in higher-income families to lack health care coverage (NCHS, 2005). In 2002 and 2003, uninsured children were three times more likely than their counterparts with insurance (32 percent versus 11 percent, respectively) to have not had a visit to a physician or health clinic for health care within the previous year (NCHS, 2005). Racial/ethnic minority children and youth face a number of barriers to receiving timely, appropriate, and high-quality health care services (NCHS, 2005; NRC, 2006a). Children covered by Medicaid are nearly six times more likely than children covered by private insurance to be treated for obesity. In addition, the treatment of obesity in children covered by Medicaid is more expensive (approximately $6,700/year) than the treatment of obesity for children covered by private insurance (approximately $3,700/year) (Thomson Medstat, 2006). Children with obesity experience higher rates of hospitalizations and greater use of physician services than their nonobese peers (Thomson Medstat, 2006). The percentage of Americans living in poverty increased from 11.3 percent in 2000 to 12.5 percent in 2003. The 2004 poverty rate among children under 6 years of age was 21 percent (Annie E. Casey Foundation, 2006). In 2004, 38.2 million individuals (an estimated 11.9 percent of the total population), including 13.9 million children, lived in households with food insecurity (Nord et al., 2005). Several studies examining the relationships among food insecurity, SES, and obesity in children or youth have not been able to demonstrate a strong association or causal effect after adjustment for other factors (Hofferth and Curtin, 2005; Kaiser et al., 2002; Matheson et al., 2002; Whitaker and Orzol, 2006). 3 Food insecurity describes households that have limited or an uncertain availability of nutritionally adequate and safe foods or that have the inability to acquire such foods in a socially acceptable way. 4 Federal poverty guidelines are issued annually in the Federal Register by the U.S. Department of Health and Human Services and are used to determine the financial eligibility of individuals and households for federal assistance programs (DHHS, 2006a).
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Progress in Preventing Childhood Obesity: How Do We Measure Up? Many racial/ethnic minority subpopulations have experienced social, political, and historical contextual events that continue to have long-lasting effects on their physical health, psychosocial well-being, and economic livelihoods (Duran et al., 1998; NRC, 2006b; Williams and Collins, 1995). The challenges associated with understanding the relationship between SES and obesity risk are discussed in Box 3-1. Immigration and Acculturation Immigrants are the fastest-growing segment of the U.S. population. As a percentage of the total population, the foreign-born population increased BOX 3-1 Challenges in Understanding the Relationship Between Socioeconomic Status and Obesity Risk Despite the substantial variation in BMI that exists as a function of both SES and race/ethnicity, uncertainties remain as to whether these rates can be attributed solely to SES, because obesity disparities are not the same across ethnic groups and they do not emerge at comparable times during childhood (Parsons et al., 1999). There is no consensus about the reasons for these disparities, although recent research provides certain insights. Variation in obesity risk by race/ethnicity and SES appears to occur early in life. An assessment of 16,000 preschool children, ages 2 to 4 years, enrolled in the Head Start Program in New York City found that 27 percent were obese and 15 percent were at risk for obesity. An estimated one in four Head Start children in that sample were found to be obese by the age of 2 years, and one in three children were obese by the age of 4 years. Although obesity was identified as a problem among all Head Start children in New York City, Hispanic/Latino and African-American preschoolers are disproportionately affected (New York City Department of Health and Mental Hygiene, 2006). Moreover, socioeconomic deprivation in childhood has been found to be both a strong predictor of obesity in adulthood for African-American adult women (James et al., 2006a) and adult hypertension in adulthood for African-American men (James et al., 2006b). Mexican-American children and youth living along the U.S.-Mexico border experience higher levels of economic disadvantages and special challenges in accessing foods that contribute to a healthful diet, regular physical activity, and health care services (Abarca and Ramachandran, 2005; Ruiz-Beltran and Kamau, 2001). Low-SES Mexican school-aged children living along the U.S. border in Tijuana, adjacent to San Diego County in California, have been found to be at increased risk of obesity and related chronic diseases, which may be related to less healthful food choices for children attending schools in low-SES neighborhoods (Villa-Caballero et al., 2006). In contrast, among Mexican children and adolescents, particularly those living in urban areas, obesity is increasing among higher SES groups (IOM, 2007).
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Progress in Preventing Childhood Obesity: How Do We Measure Up? Analyses of nationally representative longitudinal data—the National Longitudinal Survey of Youth (Strauss and Knight, 1999; Strauss and Pollack, 2001) and the National Longitudinal Study of Adolescent Health (NLSAH) (Goodman, 1999)—have suggested that family SES is inversely related to obesity prevalence in children and that the effects of SES and race/ethnicity are independent of other variables. A more recent analysis of a nationally representative sample of adolescents enrolled in the NLSAH examined trends in racial/ethnic disparities for leading health indicators from Healthy People 2010 (Harris et al., 2006) across multiple domains from adolescence to young adulthood. The results revealed that the health risk increased for 15 of 20 indicators among racially/ethnically diverse adolescents. Access to health care decreased from the teen to the adult years for most U.S. racial/ethnic groups, and the disparity was particularly high for American Indians (Harris et al., 2006). Analyses of nationally representative cross-sectional data reveal additional findings that can help to provide an understanding of the relationship between SES and obesity. An examination of the 1988 to 1994 NHANES data showed that the prevalence of obesity in white adolescents was higher for those in low-income families, but there was no clear relationship between family income and obesity in individuals in other age or racial/ethnic subgroups (Ogden et al., 2003; Troiano and Flegal, 1998). A more recent analysis of trends in the association between poverty and adolescents’ obesity risk was conducted for four cross-sectional NHANES surveys conducted from 1971 to 2004 (Miech et al., 2006). Although the obesity prevalence did not differ by SES or family poverty status for teens through age 14 years, a widening disparity was observed for 15- to 17-year-olds, especially boys, girls, non-Hispanic whites, and non-Hispanic African Americans. There was a 50 percent higher risk of obesity among adolescents in poor families compared with that among adolescents in non-poor families. Possible mechanisms that contributed to the obesity risk for adolescents were physical inactivity, higher levels of consumption of sweetened beverages, and skipping breakfast (Miech et al., 2006). from 4.7 percent in 1970 to 11.5 percent in 2002 (Dey and Lucas, 2006). The children of immigrant families are thus among the fastest-growing and the most ethnically diverse segment of the American child population. The median age of the individuals who make up the Hispanic/Latino second generation, for example, is just over 12 years (NRC, 2006b). Significant differences in the physical health status exist among U.S.-born and foreign-born individuals. Differences in the lengths of stay of immigrants in the United States suggest that the role of acculturation on immigrant health is complex and differs for various racial/ethnic groups (Dey and Lucas, 2006; Goel et al., 2004; Gordon-Larsen et al., 2003). However, what is clear from the available evidence is that the acculturation of young and adult immigrant populations is associated with the adoption of lifestyle behaviors and social norms that promote weight gain and obesity. An analysis of a nationally representative sample of 13,783 adolescents from the National Longitudinal Study of Adolescent Health found that
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Progress in Preventing Childhood Obesity: How Do We Measure Up? proaches into the delivery of health care and social services (Anderson et al., 2003a; Andrulis, 2005). Address multiple health issues pertinent to a range of stakeholders in order to build momentum and community support for interventions (e.g., the Harlem Fitness Zone and the Cherokee Choices projects) and the Active Living by Design interventions (Sallis et al., 2006). Recognize that the use of nonintervention control groups may not be acceptable to ethnic minority communities; rather, delayed intervention designs may be more tenable (Boon and Clydesdale, 2005). Involve researchers who are knowledgeable about the racial/ethnic groups or cultures being studied or evaluated (American College of Epidemiology, 1995; Anderson et al., 2003a; Gil and Bob, 1999; Hopson, 2003; IOM, 1994; Kumanyika et al., 2005). Focus attention on the process of intervening in addition to achieving outcomes. This may include particular attention to delivery channels, messengers, materials and messages, and other cultural adaptations or targeting. Subgroup analyses are critical, and, when differences are found, further examination is needed to explore why the interventions are not effective for certain subgroups (e.g., characteristics of the intervention itself or how it was implemented) (Kreuter and McClure, 2004; Yancey et al., 2006b). Expanding Surveillance to Identify Areas With High Obesity Burdens and Related Chronic Disease Data collection and analyses for surveillance and monitoring are core functions of governmental public health practices. However, methodological limitations to the identification and documentation of health disparities must be addressed. The public health infrastructure has the capacity to monitor aggregate racial/ethnic groups (e.g., categories defined by the U.S. Bureau of the Census). However, some individuals in racially/ethnically diverse communities may not participate in formal national data-gathering efforts because of logistical issues and concerns about how the data might be used. These challenges may result in the underrepresentation of racial/ ethnic minority populations in national surveillance systems. Representative surveillance and monitoring systems must be established to allow the monitoring of minority populations at potential health risk. The REACH 2010 Risk Factor Survey, for example, is conducted annually in African-American, Hispanic/Latino, Asian/Pacific Islander, and American Indian communities throughout the United States (CDC, 2004). Data from this survey demonstrate that residents in racial/ethnic minority communities experience greater disease risk and burden than individuals in the general population living in similar areas or states.
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Progress in Preventing Childhood Obesity: How Do We Measure Up? The continuous and expanded surveillance of health status in racial/ ethnic minority communities is an important measurement challenge for evaluators, yet it is needed to provide accurate disease prevalence estimates for evaluating culturally targeted prevention strategies for smaller geographic areas (e.g., for certain zip codes, school catchments areas, or census tracts). Expanding access to surveillance data would decrease the burden placed on community-based organizations, school districts, and other local government agencies to monitor and evaluate interventions, thereby allowing them to focus on the service delivery missions that motivate their activities (Yancey et al., 2005). The federal and state governments can expand their roles in collecting data by race/ethnicity and refining the definitions of race/ethnicity categories (Lurie et al., 2005). Surveillance and monitoring systems may not provide the data needed for a comprehensive assessment of program quality. Community-based participatory research is one qualitative research approach to inquiry that emphasizes community partnerships and action for social change and the reduction of health disparities as an integral component of the research process (McAllister et al., 2003). Indeed, qualitative indicators require more precise definitions. Yet, effective programs and services will depend on the ability to measure and evaluate these indicators and integrate an understanding of the indicators into interventions. The ability to measure an array of indicators, both qualitative and quantitative, for a variety of diverse populations and outcomes is central to the elimination of health disparities and the prevention of childhood obesity in high-risk communities. SUMMARY AND RECOMMENDATIONS Quantitative assessment of progress over the past few years in preventing childhood obesity in diverse population groups is difficult. Examples are provided throughout the chapter of localized successes and innovative programs that are being implemented and evaluated across the nation. Large-scale initiatives focused on disproportionately affected groups are needed and should incorporate participatory approaches into their design, implementation, and evaluation. Making progress toward closing the childhood obesity and health disparity gaps in high-risk racial/ethnic minority populations and diverse low-income populations will depend on several factors. These include a national commitment to substantially improve the social and built environments of high-risk communities; defining the contexts and mechanisms that lead to and perpetuate childhood obesity; and designing, implementing, and evaluating effective and culturally competent interventions, evaluation tools, and outcome measures.
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Progress in Preventing Childhood Obesity: How Do We Measure Up? Childhood obesity prevention efforts should creatively identify and build upon community assets, collective efficacy, and other leverage points where the needs of diverse populations are served, such as federal nutrition safety-net programs and shared cultural values and traditions. Attention to these factors will promote the implementation and evaluation of promising interventions that can help identify future best practices that support childhood obesity prevention efforts. Recommendations 2 and 3 discussed in Chapter 2 explicitly propose further action focused on strengthening the implementation and the evaluation of obesity prevention interventions, policies, and initiatives relevant to culturally and ethnically diverse populations. This emphasis highlights the need to carefully consider and involve the people most affected in the policy change or intervention. Recommendation 2: Policy makers, program planners, program implementers, and other interested stakeholders—within and across relevant sectors—should evaluate all childhood obesity prevention efforts, strengthen the evaluation capacity, and develop quality interventions that take into account diverse perspectives, that use culturally relevant approaches, and that meet the needs of diverse populations and contexts. Recommendation 3: Government, industry, communities, and schools should expand or develop relevant surveillance and monitoring systems and, as applicable, should engage in research to examine the impact of childhood obesity prevention policies, interventions, and actions on relevant outcomes, paying particular attention to the unique needs of diverse groups and high-risk populations. Additionally, parents and caregivers should monitor changes in their family’s food, beverage, and physical activity choices and their progress toward healthier lifestyles. REFERENCES Abarca J, Ramachandran S. 2005. Using community indicators to assess nutrition in Arizona-Mexico border communities. Prev Chronic Dis [Online]. Available: http://www.cdc.gov/Pcd/issues/2005/jan/04_0082.htm [accessed July 23, 2006]. Ackard DM, Neumark-Sztainer D, Story M, Perry C. 2003. Overweight among adolescents: Prevalence and associations with weight-related characteristics and psychological health. Pediatrics 111(1):67–74. Acton KJ, Burrows NR, Moore K, Querec L, Geiss LS, Engelgau MM. 2002. Trends in diabetes prevalence among American Indian and Alaska Native children, adolescents, and young adults. Am J Public Health 92(9):1485–1490. ADA (American Diabetes Association). 2000. Type 2 diabetes in children and adolescents. Pediatrics 105(3):671–680. American College of Epidemiology. 1995. Committee on Minority Affairs Statement of Principles on Epidemiology and Minority Populations. Ann Epidemiol 5:505–508.
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