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Birth Cohort Effects Among US-Born Adults Born in the 1980S: Foreshadowing Future Trends in US Obesity Prevalence

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Birth Cohort Effects Among US-Born Adults Born in the 1980S: Foreshadowing Future Trends in US Obesity Prevalence International Journal of Obesity (2013) 37, 448–454 & 2013 Macmillan Publishers Limited All rights reserved 0307-0565/13 www.nature.com/ijo ORIGINAL ARTICLE Birth cohort effects among US-born adults born in the 1980s: foreshadowing future trends in US obesity prevalence WR Robinson1,2, KM Keyes3, RL Utz4, CL Martin1 and Y Yang2,5 BACKGROUND: Obesity prevalence stabilized in the US in the first decade of the 2000s. However, obesity prevalence may resume increasing if younger generations are more sensitive to the obesogenic environment than older generations. METHODS: We estimated cohort effects for obesity prevalence among young adults born in the 1980s. Using data collected from the National Health and Nutrition Examination Survey between 1971 and 2008, we calculated obesity for respondents aged between 2 and 74 years. We used the median polish approach to estimate smoothed age and period trends; residual non-linear deviations from age and period trends were regressed on cohort indicator variables to estimate birth cohort effects. RESULTS: After taking into account age effects and ubiquitous secular changes, cohorts born in the 1980s had increased propensity to obesity versus those born in the late 1960s. The cohort effects were 1.18 (95% CI: 1.01, 1.07) and 1.21 (95% CI: 1.02, 1.09) for the 1979–1983 and 1984–1988 birth cohorts, respectively. The effects were especially pronounced in Black males and females but appeared absent in White males. CONCLUSIONS: Our results indicate a generational divergence of obesity prevalence. Even if age-specific obesity prevalence stabilizes in those born before the 1980s, age-specific prevalence may continue to rise in the 1980s cohorts, culminating in record-high obesity prevalence as this generation enters its ages of peak obesity prevalence. International Journal of Obesity (2013) 37, 448–454; doi:10.1038/ijo.2012.66; published online 1 May 2012 Keywords: age factors; young adult; developmental origins; epidemiology; models; statistical INTRODUCTION therefore, Faeh et al.4 concluded that overweight prevalence may The 1980s are generally regarded as the start of the US ‘obesity resume increasing as susceptible cohorts, adults currently in their epidemic’.1 During the 1980s, age-standardized obesity preva- 30s and 40s, age into their 50s and 60s, when risk of overweight is lence (body mass index (BMI) X30.0 kg m À 2) increased in the US at its highest. This type of birth-cohort analysis is not definitive, adults by 55%, from 14.5% to 22.5%. This increase occurred after however, because it failed to disentangle period effects from age- 5 two decades in which obesity prevalence was relatively stable.2 specific cohort trends. The obesity increases of the 1980s continued in the 1990s, then To forecast future trends in the US, understanding the cohort- levelled off in the 2000s.2,3 In fact, between the early and late specific obesity susceptibility of those born in the 1980s may be 5 2000s, in child and adult populations in the US, Europe and key. Individuals born during the 1980s experienced gestation and Australia, obesity prevalence either stopped increasing, or early childhood—potentially key developmental life stages for increases decelerated.3 It is unclear whether obesity prevalence obesity development—during an era of rapidly increasing obesity in the US and other countries has peaked or whether prevalence prevalence. We hypothesize that the 1980s cohorts may be will resume increasing in the future.2,3 On the one hand, obesity particularly sensitive to the obesogenic environment. For instance, prevalence may peak as anti-obesity efforts abate rising rates or as hypotheses about the developmental origins of adult obesity posit populations reach a prevalence ceiling. On the other hand, even in that in utero and early-childhood exposures to obesogenic the US, the majority of adults are not obese and may remain environments have latent biological or behavioral consequences susceptible to increasing rates of obesity. that increase a person’s susceptibility to excess weight gain into Because the causes of previous increases are not fully under- adulthood.6–9 Two previous analyses of the US data found limited stood, it is difficult to predict future obesity trends.2 Age–period– evidence of obesity risk being increased for cohorts born in the cohort analysis can improve forecasting by estimating one 1980s versus those born in the 1950s and 1960s but not the component of obesity trends: the relative susceptibility of birth 1970s.10,11 However, both studies had limited data on these birth cohorts to obesity. For example, Faeh et al.4 used a birth-cohort cohorts. The studies only assessed adult body size. Therefore, they analysis to examine whether the stabilization of overweight observed the young adults born in the early 1980s for only the prevalence in Switzerland is a temporary phenomenon. They first few years of their adult lives in the 2000s, a narrow window of estimated that the birth cohorts of the 1960s and 1970s are more time to draw conclusions about lifelong cohort-specific risk. In prone to overweight than those born between 1930 and 1959; addition, the studies only assessed trends in the US Whites and 1Department of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Chapel Hill, NC, USA; 2Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 3Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA; 4Department of Sociology, University of Utah, Salt Lake City, UT, USA and 5Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Correspondence: Dr WR Robinson, Department of Epidemiology, University of North Carolina at Chapel Hill, Gillings School of Global Public Health, McGavran-Greenberg Hall, CB# 7435, Chapel Hill 27510, NC, USA. E-mail: [email protected] Received 12 January 2012; revised 7 March 2012; accepted 26 March 2012; published online 1 May 2012 Cohort effects on obesity, 1980s birth cohort WR Robinson et al 449 Blacks, failing to incorporate the experience of other US racial and polish technique.5 The median polish approach explicitly defines cohort ethnic groups. effects as interactions of age and period effects. That is, this model assumes In this paper, we estimated cohort-specific propensity to obesity that effects of environmental influences vary by age and can be meaning- for those born in the US in the 1980s. We used data on childhood fully estimated as cohort effects. obesity as well as adult obesity in order to produce estimates over To implement the median polish technique, we first created a15Â 8 contingency table of obesity prevalence. The 15 rows represent the entire lifecourse of those born in the 1980s. Because the fifteen 5-year age groups, whereas the eight columns denote eight 5-year levelling off of obesity prevalence in the 2000s was more 2 blocks of calendar time (Figure 1). The diagonals represent 22 birth pronounced in women than in men, we produced analyses cohorts. NHANES assessed obesity prevalence during periods of variable stratified by sex. Further, because obesity prevalence varies timing and duration: 1971–1975, 1976–1980, 1988–1991, 1991–1994, then significantly by racial/ethnic and sex subgroups, we also in continuous 2-year blocks from 1999–2008. Therefore, we approximated produced stratified estimates for the subgroups on which we seven synthetic 5-year period categories using the NHANES data (Figure 1). had data extending back to the 1970s: non-Hispanic Black, non- Because no NHANES data were available between 1981 and 1988, we Hispanic White and US-born Mexican–American men and women. interpolated age-specific obesity prevalences for the synthetic period 1981–1985 by averaging age-specific prevalence for the previous (1976–1980) and subsequent (1986–1990) periods. For stratified analyses MATERIALS AND METHODS of subgroups with relatively small sample sizes and low obesity prevalence, for example, Mexican–American males, some cells in the contingency Sample tables had an obesity prevalence of 0%. For identification purposes, we We analyzed data from the National Health and Nutrition Examination replaced values of 0% with 1.0% in the initial contingency tables. Survey (NHANES), a nationally representative sample of the US civilian non- Once the contingency table was complete (Table 1), we performed the institutionalized population.12–14 We included survey waves conducted median-polish method by iteratively subtracting the median prevalence value between 1971 and 2008: NHANES I (1971–1975), NHANES II (1976–1980), of each row or column from all the cells in its respective row or column. This NHANES III, phase 1 (1988–1991), NHANES III, phase 2 (1991–1994), and the process was repeated until the median values of all rows and columns continuous surveys (1999–2008), which are released in 2-year increments. equalled 0. This process removes the additive period and age effects. The NHANES uses a complex, stratified, multi-stage probability cluster sampling values that remain in the table are non-additive residuals design. We included survey weights in all analyses to correct for of the period and age effects. The median polish technique interprets these oversampling and non-response.2 residuals as the sum of cohort effects and random error. Further statistical and We limited the data set to individuals aged 2–74 years who were born conceptual details of the median polish method are given elsewhere.18,20,22 in the United States. We omitted foreign-born respondents because years Using the residuals from the contingency table, we used generalized spent in another country before immigration violate the model’s linear regression to estimate cohort effect ratios for each birth cohort. To assumption that individuals shared period and birth cohort exposures define mutually exclusive birth cohort categories, we assigned each cell in across their lifespans.15,16 We further excluded respondents who had the contingency table to a synthetic 5-year birth cohort category.
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