Inequalities In Body Mass Index Research Articles

The relative roles of early life, physical activity, sedentarism and diet in social and economic inequalities in body mass index and obesity risk between 9 and 18

BackgroundStudies in many middle and high-income countries describe an increasing prevalence of adiposity and obesity among children and adolescents. Prevalence is higher among families of low socioeconomic position (SEP) and systematic reviews have identified relevant factors, but have not quantified their relative importance to SEP differentials. This paper examines the relative importance of different factors to Body Mass Index (BMI) and obesity trajectories from age 9 to age 17/18. MethodsMulti-level models of child BMI/obesity risk trajectory by maternal education were conducted using a nationally representative cohort of children born in Ireland in 1998 and aged 9 at baseline (N = 8568), with follow-up at 13 and 17/18 years (88% and 73% response rate respectively). Models were stratified by sex and both time-varying (e.g. child physical activity, diet, sedentary activity) and time-invariant (e.g. early life) factors were tested. ResultsSignificant inverse gradients in BMI and obesity risk by level of maternal education were present across both sexes and at each age; unadjusted absolute differentials in obesity risk between highest/lowest education groups increased by 56% for males and 42% for females between age 9 and 17/18. Early life factors accounted for 22% of the differential in obesity risk between the lowest and highest education groups among males at age 9, falling to 13% at 17/18. Among females the proportion fell from 33 to 23%. Unadjusted absolute high/low maternal education group differentials in BMI were 7.5 times higher among males and 11 times higher among females at 17/18 than at age 9. ConclusionsGiven the importance of early life exposures to subsequent differentials in BMI and obesity risk our findings suggest that policy makers should focus resources on primary prevention during the prenatal and early life period if they wish to reduce the prevalence of child and adolescent obesity.

Socio-economic inequalities in body mass index among preschool children: do sports programs in early childhood education and care centers make a difference?

Overweight in childhood is considered to be one of the most serious public health challenges. Many studies have investigated individual-level determinants of children's body mass index (BMI), yet studies exploring determinants at the meso-level are sparse. The aim of our study was to examine how a sports focus at early childhood education and care (ECEC) centers moderates the effect of parental socio-economic position (SEP) on children's BMI. We used data from the German National Educational Panel Study and included 1,891 children (955 boys and 936 girls) from 224 ECEC centers in our analysis. Linear multilevel regressions were used to estimate the main effects of family SEP and the ECEC center sports focus, as well as their interaction, on children's BMI. All analyses were stratified by sex and adjusted for age, migration background, number of siblings, and employment status of parents. Our analysis confirmed the wellknown health inequalities in childhood overweight with a social gradient toward a higher BMI for children from lower SEP families. An interactive effect between family SEP and ECEC center sports focus was found. Boys with low family SEP not attending a sports-focused ECEC center had the highest BMI among all boys. In contrast, boys with low family SEP attending a sports-focused ECEC center had the lowest BMI. For girls, no association regarding ECEC center focus or interactive effects emerged. Girls with a high SEP had the lowest BMI, independent of the ECEC center focus. We provided evidence for the gender-specific relevance of sports-focused ECEC centers for the prevention of overweight. Especially boys from low SEP families benefited from a sports focus, whereas for girls the family's SEP was more relevant. As a consequence, gender differences in determinants for BMI at different levels and their interaction should be considered in further research and preventive measures. Our research indicates that ECEC centers may decrease health inequalities by providing opportunities for physical activity.

The role of energy balance related behaviors in socioeconomic inequalities in childhood body mass index: A comparative analysis of Germany, the Netherlands, the United Kingdom, and the United States

Socioeconomic inequalities in childhood Body Mass Index (BMI) are becoming increasingly more pronounced across the world. Although countries differ in the direction and strength of these inequalities, cross-national comparative research on this topic is rare. This paper draws on harmonized longitudinal cohort data from four wealthy countries—Germany, the Netherlands, the United Kingdom (UK), and the United States (US)—to 1) map cross-country differences in the magnitude of socioeconomic inequalities in childhood BMI, and 2) to examine cross-country differences in the role of three energy-balance-related behaviors—physical activity, screen time, and breakfast consumption—in explaining these inequalities. Children were aged 5–7 at our first timepoint and were followed up at age 8–11. We used data from the German National Educational Panel Study, the Dutch Generation R study, the UK Millennium Cohort Study and the US Early Childhood Longitudinal-Kindergarten Study. All countries revealed significant inequalities in childhood BMI. The US stood out in having the largest inequalities. Overall, inequalities between children with low versus medium educated parents were smaller than those between children with high versus medium educated parents. The role of energy-balance-related behaviors in explaining inequalities in BMI was surprisingly consistent. Across countries, physical activity did not, while screen time and breakfast consumption did play a role. The only exception was that breakfast consumption did not play a role in the US. Cross-country differences emerged in the relative contribution of each behavior in explaining inequalities in BMI: Breakfast consumption was most important in the UK, screen time explained most in Germany and the US, and breakfast consumption and screen time were equally important in the Netherlands. Our findings suggest that what constitutes the most effective policy intervention differs across countries and that these should target both children from medium as well as low educated families.

The socio-economic inequality in body mass index: a PERSIAN cohort-based cross-sectional study on 20,000 Iranian adults

IntroductionThe aim of the present study was to explore and determine the association between BMI and socio-economic factors in Iran.MethodsAdults aged 35 to 70 (n = 20,460) were included from Ardabil Non-Communicable Disease (ArNCD) cohort study. BMI was calculated as kg/m2. Principal Component Analysis (PCA) was used to determine the socio-economic quintiles. Multivariate linear regression was performed to analyze the association of BMI as dependent variable with explanatory variables, Additionally, decomposition analyzing conducted to identify factors that explained wealth-related inequality in obesity.ResultsThe prevalence of overweight and obese people was 83.7% (41.4% overweight and 42.5% obese) wherein the highest frequency of obese people belonged to the age group of 45 to 49 years old (19.9%) and to the illiterate people (33.1%). The results of multivariate linear regression model showed that age, being female, marriage, lower education level, having chronic disease, alcohol use, and higher socioeconomic level positively associated with obesity. The results of the decomposition model showed that the most important variables affecting socioeconomic inequality in higher BMI level were socioeconomic status (75.8%), being women (5.6%), education level (− 4.1%), and having chronic disease (2.4%).ConclusionBMI showed significant association with socio-economic status, where richest people had significantly higher BMI than poorest group. Considering the direct role of high BMI in non-communicable diseases, new policies are needed to be developed and implemented by means of diet intervention and increased physical activity to control the BMI in the population of Iran.

Trends and Disparities in Adult Body Mass Index Across the 47 Prefectures of Japan, 1975-2018: A Bayesian Spatiotemporal Analysis of National Household Surveys.

BackgroundAmong high-income countries, Japan has a low prevalence of obesity, but little is understood about subnational trends and variations in body mass index (BMI), largely owing to the lack of data from representative samples of prefectures. We aimed to examine long-term trends and distributions of adult BMI at the prefecture level in Japan from the late 1970s using a spatiotemporal model.MethodsWe obtained cross-sectional data for 233,988 men and 261,086 women aged 20–79 years from the 44 annual National Health and Nutrition Surveys (NHNS) conducted during 1975–2018. We applied a Bayesian spatiotemporal model to estimate the annual time series of age-standardized and age-specific mean BMI by 20-year age group and sex for each of the 47 prefectures. We assessed socioeconomic inequalities in BMI across prefectures using the concentration index, according to population density.ResultsIn men, the age-standardized prefectural mean BMI ranged from 21.7 kg/m2 (95% credible interval, 21.6–21.9) to 23.1 kg/m2 (22.9–23.4) in 1975 and from 23.5 kg/m2 (23.3–23.7) to 24.8 kg/m2 (24.6–25.1) in 2018. In women, the age-standardized prefectural mean BMI ranged from 22.0 kg/m2 (21.9–22.2) to 23.4 kg/m2 (23.2–23.6) in 1975 and from 21.7 kg/m2 (21.6–22.0) to 23.5 kg/m2 (23.2–23.8) in 2018. Mean BMI was highest in the southernmost prefecture for most of the study period, followed by northeast prefectures. The increase in mean BMI was largest in southwest prefectures, which caught up with northeast prefectures over time. The concentration index was negative, indicating higher BMI in less-populated prefectures. Absolute values of the concentration index were greater in women than in men and increased over time.ConclusionsThere were variations in adult mean BMI across prefectures, and geographic distributions changed over time. Further national and local efforts are needed to address the rising trend in mean BMI, particularly among men in rural prefectures, and socioeconomic inequalities among women. Bayesian hierarchical modeling is useful for reconstructing long-term spatiotemporal trends of mean BMI by integrating small-sized survey samples at the prefecture level in the NHNS.

Inequalities in body mass index, diet and physical activity in the UK: Longitudinal evidence across childhood and adolescence

We use longitudinal data across a key developmental period, spanning much of childhood and adolescence (age 5 to 17, years 2006–2018) from the UK Millennium Cohort Study, a nationally representative study with an initial sample of just over 19,000. We first examine the extent to which inequalities in overweight, obesity, BMI and body fat over this period are consistent with the evolution of inequalities in health behaviours, including exercise and healthy diet markers (i.e., skipping breakfast) (n = 7,220). We next study the links between SES, health behaviours and adiposity (BMI, body fat), using rich models that account for the influence of a range of unobserved factors that are fixed over time. In this way, we improve on existing estimates measuring the relationship between SES and health behaviours on the one hand and adiposity on the other. The advantage of the individual fixed effects models is that they exploit within-individual changes over time to help mitigate biases due to unobserved fixed characteristics (n = 6,883).We observe stark income inequalities in BMI and body fat in childhood (age 5), which have further widened by age 17. Inequalities in obesity, physical activity, and skipping breakfast are observed to widen from age 7 onwards. Ordinary Least Square estimates reveal the previously documented SES gradient in adiposity, which is reduced slightly once health behaviours including breakfast consumption and physical activity are accounted for. The main substantive change in estimates comes from the fixed effects specification. Here we observe mixed findings on the SES associations, with a positive association between income and adiposity and a negative association with wealth. The role of health behaviours is attenuated but they remain important, particularly for body fat.

Social inequalities and trends in pre-pregnancy body mass index in Swedish women

Obesity rates in adolescence and young adulthood have increased in Sweden, reflecting global trends. To which extent this occurs across different socioeconomic strata has not been clarified. The aim of the present study was to investigate trends in social inequalities in body mass index (BMI) in young/mid-adulthood Swedish women. We obtained weight and height for all women aged 20–45 years, at their first registered pregnancy (< 12 weeks of gestation) in the Swedish Medical Birth Register 1982–2013 (1,022,330, mean age = 28.8 years), documenting education and county of residence. Trends in mean BMI and in the prevalence of BMI categories between 1982 and 2013 were estimated across education levels and geographical location. Overall, mean BMI increased from 22.7 kg/m2 (SD 3.2) to 24.3 kg/m2 (SD 4.4) between 1982 and 2013. Simultaneously, the prevalence of overweight and obesity (BMI ≥ 25 kg/m2) increased from 18.1 to 33.4% while that of moderate obesity (BMI ≥ 30 to < 35 kg/m2) and severe obesity (BMI ≥ 35 kg/m2) increased markedly from 3.4 and 0.4% to 7.4 and 3.1%, respectively. The prevalence of moderate and severe obesity more than doubled during the study period across all educational levels. In conclusion, BMI and moderate and severe obesity increased markedly among young/mid-adulthood Swedish women regardless of education with a widening gap between those with lower and higher education. These growing social inequalities in BMI are likely to cause a rising divide in serious health problems following early and long-lasting obesity.

Socioeconomic inequalities in children\u2019s weight, height and BMI trajectories in Norway

Studies exploring when social inequalities in body mass index (BMI) and its composites emerge and how these evolve with age are limited. Thus, this study explored parental income and education related inequalities in children’s weight, height, weight velocity and body mass index among Norwegian children from 1 month to 8 years. The study population included 59,927 family/children pairs participating in the Norwegian Mother, Father, and Child Cohort Study. Growth was modelled using the Jenss–Bayley model and linear mixed effects analyses were conducted. Maternal and paternal educational differences in children’s weight and BMI trajectories emerged during infancy, continuing to age 8 years. Parental income-related inequalities in children’s weight were observed from the age of 1 month to 4 years for maternal and up to 1 year for paternal income-related differences but then disappeared. Parental income-related inequalities in child’s BMI were observed from 18 months to 8 years for maternal income, and from 9 months to 8 years for paternal income-related differences. These results suggest that social inequalities in children’s BMI present early in infancy and continue to 8 years of age. The inequalities sometimes differed by indicator of socioeconomic position used. Interventions to combat these inequalities early in life are, thus needed.

Examining Cumulative Inequality in the Association Between Childhood Socioeconomic Status and Body Mass Index From Midlife to Old Age.

Socioeconomic status (SES) is among the strongest determinants of body mass index (BMI), particularly for women. For older populations, selection bias due to attrition is a large barrier to assessing the accumulation of inequality. Under multiple missing data mechanisms, we investigated the extent to which childhood and midlife SES affects BMI from midlife to old age and gender differences in the association. Data come from a longitudinal national study of 2,345 U.S. adults aged 40-54 at baseline. We used latent growth models to estimate BMI trajectory over a period of 20 years. We examined results under different missing data patterns and applied methods that account for nonrandom-selection bias. Compared with individuals who had higher childhood SES, individuals who had lower childhood SES have higher BMI in midlife and experience a faster increase in BMI between midlife and old age. The observed associations remain significant even after controlling for midlife SES. After addressing nonrandom selection, the gap in BMI between high and low childhood SES widens from midlife to old age for women. The findings provide new evidence of cumulative inequality among older adults, documenting increasing BMI inequality from midlife to old age, particularly for women from low-SES families.

A Growing Social Divide in Body Mass Index, Strength, and Fitness of Swedish Male Conscripts

PurposeThe aim of the study was to monitor trends in socioeconomic inequalities in body mass index (BMI), cardiorespiratory fitness (CRF), and muscular strength over several decades in a population of Swedish males aged 18–19 years. MethodsThe cohort consists of 1.5 million young men attending military conscript examinations from late 1968 to 2005. Parental education was used as a marker for socioeconomic conditions in the conscripts' families of origin. Changing gradient in BMI, CRF, and muscular strength in sons of parents with higher and lower educational attainment was evaluated during four periods covering 36 years. ResultsOver the course of the obesity epidemic, BMI remained higher in conscripts with lesser (vs. higher) parental education. Moreover, the absolute difference in obesity prevalence between groups showed a continuous increase, from .6% to 3.9%, indicating growing inequalities. Regarding fitness, lower CRF was consistently associated with less parental education, but with no clear secular trend in the magnitude of the difference. Finally, social differences in muscular strength changed in direction, from lower strength among conscripts with higher parental education in the initial observation period to lower strength associated with lower parental education in the final decade studied. ConclusionsAmong Swedish conscripts entering adulthood, social gradients in BMI and obesity widened continuously between 1968 and 2005. An apparent reversal of the earlier gradient in muscular strength in young men may be related to societal trends in occupational and leisure-time physical activity over the observation period. This cohort is being continually monitored through national registries for obesity-related comorbidities in later life.

Socioeconomic inequalities in obesity: modelling future trends in Australia

ObjectivesTo develop a model to predict future socioeconomic inequalities in body mass index (BMI) and obesity.DesignMicrosimulation modelling using BMI data from adult participants of Australian Health Surveys, and published data...

Household income, active travel, and their interacting impact on body mass index in a sample of urban Canadians: a Bayesian spatial analysis

BackgroundActive travel for utilitarian purposes contributes to total physical activity and may help counter the obesity epidemic. However, the evidence linking active travel and individual-level body weight is equivocal. Statistical modeling that accounts for spatial autocorrelation and unmeasured spatial predictors has not yet used to explore whether the health benefits of active travel are shared equally across socioeconomic groups.MethodsBayesian hierarchical models with spatial random effects were developed using travel survey data from Saskatoon, Canada (N = 4625). Differences in log-transformed body mass index (BMI) were estimated for levels of active travel use (vehicular travel only, mixed vehicular/active travel, and active travel only), household income, and neighbourhood deprivation after controlling for sociodemographic and physical activity variables. The modifying effect of household income on the association between active travel and BMI was also evaluated.ResultsSignificant and meaningful decreases in BMI were observed for mixed (β = − 0.02, CrI − 0.036 to − 0.004) and active only (β = − 0.043, CrI − 0.06 to − 0.025) compared to vehicular only travelers. BMI was significantly associated with levels of household income and neighbourhood deprivation. Accounting for the interaction between travel mode and household income, decreases in BMI were observed for active only compared to vehicular only travellers in the highest income category (β = − 0.061, CrI − 0.115 to − 0.007).ConclusionStrategies to increase active travel use can support healthy weight loss and maintenance, but the opportunity to benefit from active travel use may be limited by low income. Considerations should be given to how interventions to increase active transportation might exacerbate social inequalities in BMI. Spatial statistical models are needed to account for unmeasured but spatially structured neighbourhood factors.

Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.

Many studies have demonstrated the existence of simple, unidimensional socioeconomic gradients in body mass index (BMI). However, in the present paper we move beyond such traditional analyses by simultaneously considering multiple demographic and socioeconomic dimensions. Using the Spanish National Health Survey 2011–2012, we apply intersectionality theory and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to analyze 14,190 adults nested within 108 intersectional strata defined by combining categories of gender, age, income, educational achievement and living situation. We develop two multilevel models to obtain information on stratum-specific BMI averages and the degree of clustering of BMI within strata expressed by the intra-class correlation coefficient (ICC). The first model is a simple variance components analysis that provides a detailed mapping of the BMI disparities in the population and measures the accuracy of stratum membership to predict individual BMI. The second model includes the variables used to define the intersectional strata as a way to identify stratum-specific interactions. The first model suggests moderate but meaningful clustering of individual BMI within the intersectional strata (ICC = 12.4%). Compared with the population average (BMI = 26.07 Kg/m2), the stratum of cohabiting 18-35-year-old females with medium income and high education presents the lowest BMI (-3.7 Kg/m2), while cohabiting 36-64-year-old females with low income and low education show the highest BMI (+2.6 Kg/m2). In the second model, the ICC falls to 1.9%, suggesting the existence of only very small stratum specific interaction effects. We confirm the existence of a socioeconomic gradient in BMI. Compared with traditional analyses, the intersectional MAIHDA approach provides a better mapping of socioeconomic and demographic inequalities in BMI. Because of the moderate clustering, public health policies aiming to reduce BMI in Spain should not solely focus on the intersectional strata with the highest BMI, but should also consider whole population polices.

Inequality in body mass indices across countries: Evidence from convergence tests

This study examines the long-term inequality in body mass index (BMI) based on convergence tests applied to a database of 172 countries recently published by the NCD Risk Factor Collaboration. First, we find that countries converge in clubs, which indicates that country disparities in BMIs will persist over time. Second, there are three and six convergence clubs in BMIs for female and male individuals, respectively. That is, we would not observe a single convergence pattern in body weights as the nutrition transition theory and the dietary convergence hypothesis seem to suggest. Females have only one healthy club (18.5 ≤ BMI < 25) and two overweight clubs (BMI ≥ 25). Males have three healthy clubs and three overweight clubs. Third, the analysis of club convergence indicates that BMI inequality has increased due to the BMI growth observed in club 1 (the one with the highest average BMI and led by the US) in each gender group. Finally, potential determinants of BMI such as globalization, human capital, income, and urbanization are relevant to understand differences across clubs. We interpret the club convergence as the result of a heterogeneous integration of countries into the global economy, which is probably related to strong domestic preferences, policies designed to manage the impacts of globalization, and shifts in productive structures.

BMI Trajectories in Adulthood: The Intersection of Skin Color, Gender, and Age among African Americans.

This study addresses three research questions critical to understanding if and how skin color shapes health among African Americans: (1) Does skin color predict trajectories of body mass index (BMI) among African Americans across ages 32 to 55? (2) To what extent is this relationship contingent on gender? (3) Do sociodemographic, psychosocial, and behavioral factors explain the skin color-BMI relationship? Using data from the Coronary Artery Risk Development in Young Adults Study and growth curve models, results indicate that dark-skinned women have the highest BMI across adulthood compared to all other skin color-gender groups. BMI differences between dark- and lighter-skinned women remain stable from ages 32 to 55. Among men, a BMI disadvantage emerges and widens between light- and dark-skinned men and their medium-skinned counterparts. Observed sociodemographic characteristics, stressors, and health behaviors do not explain these associations. Overall, findings suggest that skin color- and gender-specific experiences likely play an important role in generating BMI inequality.

Illustrating a “consequential” shift in the study of health inequalities: a decomposition of racial differences in the distribution of body mass

PurposeWe present a conceptual introduction to “distributional inequalities”—differences in distributions of risk factors or other outcomes between social groups—as a consequential shift for research on health inequalities. We also review a companion analytical methodology, “distributional decomposition”, which can assess the population characteristics that explain distributional inequalities. MethodsUsing the 1999–2012 U.S. National Health and Nutrition Examination Survey, we apply statistical decomposition to (a) document gender-specific, black-white inequalities in the distribution of body mass index (BMI) and, (b) assess the extent to which demographic (age), socioeconomic (family income, education), and behavioral predictors (caloric intake, physical activity, smoking, alcohol consumption) are associated with broader distributional inequalities in BMI. ResultsBlack people demonstrate favorable or no different caloric intake, smoking, or alcohol consumption than whites, but worse levels of physical activity. Racial inequalities extend beyond the obesity threshold to the broader BMI distribution. Demographic, socioeconomic, and behavioral characteristics jointly explain more of the distributional inequality among men than women. ConclusionsBlack-white distributional inequalities are present both among men and women, although the mechanisms may differ by gender. The notion of “distributional inequalities” offers an additional purchase for studying social inequalities in health.

Neighbourhood disadvantage, geographic remoteness and body mass index among immigrants to Australia: A national cohort study 2006-2014.

Obesity is socioeconomically, geographically and ethnically patterned. Understanding these elements of disadvantage is vital in understanding population obesity trends and the development of effective and equitable interventions. This study examined the relationship between neighbourhood socioeconomic disadvantage and geographic remoteness with prospective trends in mean body mass index (BMI) among immigrants to Australia. Longitudinal data (2006–2014) from a national panel survey of Australian adults was divided into an immigrant-only sample (n = 4,293, 52.6% women and 19,404 person-year observations). The data were analysed using multi-level random effects linear regression modelling that controlled for individual socioeconomic and demographic factors. Male immigrants living in the most disadvantaged neighbourhoods had significantly higher mean BMI compared with those living in the least disadvantaged. Over time, mean BMI increased for all groups except for men living in the least disadvantaged neighbourhoods, for whom mean BMI remained almost static (0.1 kg/m2 increase from 2006 to 2014), effectively widening neighbourhood inequalities. Among women, mean BMI was also significantly higher in the most compared with the least, disadvantaged neighbourhoods (β = 2.08 kg/m2; 95%CI: 1.48, 2.68). Neighbourhood inequalities were maintained over time as mean BMI increased for all groups at a similar rate. Male and female immigrants residing in outer regional areas had significantly higher mean BMI compared with those living in major cities; however, differences were attenuated and no longer significant following adjustment for ethnicity, individual socioeconomic position and neighbourhood disadvantage. Over time, mean BMI increased in all male and female groups with no differences based on geographic remoteness. Obesity prevention policy targeted at immigrant cohorts needs to include area-level interventions that address inequalities in BMI arising from neighbourhood disadvantage, and be inclusive of immigrants living outside Australia’s major cities.

Intersecting Social Inequalities and Body Mass Index Trajectories from Adolescence to Early Adulthood.

This study combines multiple-hierarchy stratification and life course perspectives to address two research questions critical to understanding U.S. young adult health. First, to what extent are racial-ethnic inequalities in body mass index (BMI) gendered and/or classed? Second, do racial-ethnic, gender, and socioeconomic inequalities in BMI widen or persist between adolescence and early adulthood? Using data from the National Longitudinal Survey of Youth 1997 cohort and growth curve models, results suggest that among white, black, and Hispanic American men and women ages 13 to 31, racial-ethnic inequality in BMI is greatest among women. Black women experience the highest adolescent BMI and the greatest increases in BMI with age. Furthermore, socioeconomic resources are less protective against weight gain for blacks and Hispanics, with the nature of these relationships varying by gender. Findings present a more nuanced picture of health inequality that renders visible the disproportionate burden of poor health experienced by marginalized groups.

Neighborhood socioeconomic disadvantage and body mass index among residentially stable mid-older aged adults: Findings from the HABITAT multilevel longitudinal study

Despite a body of evidence on the relationship between neighborhood socioeconomic disadvantage and body mass index (BMI), few studies have examined this relationship over time among ageing populations. This study examined associations between level of neighborhood socioeconomic disadvantage and the rate of change in BMI over time. The sample included 11,035 participants aged between 40 and 65years at baseline from the HABITAT study, residing in 200 neighborhoods in Brisbane, Australia. Data were collected biennially over four waves from 2007 to 2013. Self-reported height and weight were used to calculate BMI, while neighborhood disadvantage was measured using a census-based composite index. All models were adjusted for age, education, occupation, and household income. Analyses were conducted using multilevel linear regression models. BMI increased over time at a rate of 0.08kg/m2 (95% CI 0.02, 0.13) and 0.17kg/m2 (95% CI 0.11, 0.29) per wave for men and women respectively. Both men and women residing in the most disadvantaged neighborhoods had a higher average BMI than their counterparts living in the least disadvantaged neighborhoods. There were no evident differences in the rate of BMI change over time by level of neighborhood disadvantage. The findings suggest that by mid-older age, the influence of neighborhood socioeconomic conditions over time on BMI may have already played out. Future research should endeavor to identify the genesis of neighborhood socioeconomic inequalities in BMI, the determinants of these inequalities, and then suitable approaches to intervening.

Socioeconomic Inequalities in Body Mass Index across Adulthood: Coordinated Analyses of Individual Participant Data from Three British Birth Cohort Studies Initiated in 1946, 1958 and 1970.

BackgroundHigh body mass index (BMI) is an important contributor to the global burden of ill-health and health inequality. Lower socioeconomic position (SEP) in both childhood and adulthood is associated with higher adult BMI, but how these associations have changed across time is poorly understood. We used longitudinal data to examine how childhood and adult SEP relates to BMI across adulthood in three national British birth cohorts.Methods and FindingsThe sample comprised up to 22,810 participants with 77,115 BMI observations in the 1946 MRC National Survey of Health and Development (ages 20 to 60–64), the 1958 National Child Development Study (ages 23 to 50), and the 1970 British Cohort Study (ages 26 to 42). Harmonized social class-based SEP data (Registrar General’s Social Class) was ascertained in childhood (father’s class at 10/11 y) and adulthood (42/43 years), and BMI repeatedly across adulthood, spanning 1966 to 2012. Associations between SEP and BMI were examined using linear regression and multilevel models.Lower childhood SEP was associated with higher adult BMI in both genders, and differences were typically larger at older ages and similar in magnitude in each cohort. The strength of association between adult SEP and BMI did not vary with age in any consistent pattern in these cohorts, but were more evident in women than men, and inequalities were larger among women in the 1970 cohort compared with earlier-born cohorts. For example, mean differences in BMI at 42/43 y amongst women in the lowest compared with highest social class were 2.0 kg/m2 (95% CI: −0.1, 4.0) in the 1946 NSHD, 2.3 kg/m2 (1.1, 3.4) in the 1958 NCDS, and 3.9 kg/m2 (2.3, 5.4) the in the 1970 BCS; mean (SD) BMI in the highest and lowest social classes were as follows: 24.9 (0.8) versus 26.8 (0.7) in the 1946 NSHD, 24.2 (0.4) versus 26.5 (0.4) in the 1958 NCDS, and 24.2 (0.3) versus 28.1 (0.8) in the 1970 BCS. Findings did not differ whether using overweight or obesity as an outcome.Limitations of this work include the use of social class as the sole indicator of SEP—while it was available in each cohort in both childhood and adulthood, trends in BMI inequalities may differ according to other dimensions of SEP such as education or income. Although harmonized data were used to aid inferences about birth cohort differences in BMI inequality, differences in other factors may have also contributed to findings—for example, differences in missing data.ConclusionsGiven these persisting inequalities and their public health implications, new and effective policies to reduce inequalities in adult BMI that tackle inequality with respect to both childhood and adult SEP are urgently required