49
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      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

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          High 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 Findings

          The 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/m 2 (95% CI: −0.1, 4.0) in the 1946 NSHD, 2.3 kg/m 2 (1.1, 3.4) in the 1958 NCDS, and 3.9 kg/m 2 (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.

          Conclusions

          Given 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

          Abstract

          In a harmonized analysis of socioeconomic and anthropometric data from three cohorts, David Bann and colleagues trace the relationship between socioeconomic status and BMI over time in the UK.

          Author Summary

          Why Was This Study Done?
          • High body mass index (BMI) is thought to be harmful to human health—in most adults, a high BMI is due to having high amounts of fat mass in the body.

          • Previous studies have found that those with fewer socioeconomic resources—both as children and as adults—are more likely, on average, to have a higher BMI as adults.

          • Reducing these socioeconomic inequalities in BMI is an important health policy goal, yet there is limited existing data to help us understand comprehensively how these inequalities have changed across time.

          What Did the Researchers Do and Find?
          • We used data from three national British birth cohort studies of those born in 1946, 1958, and 1970—these studies contain comparable data on social class in childhood and adulthood, and on BMI across adult life.

          • We confirm that large inequalities in BMI exist, according to both childhood and adult SEP—these were stronger among women, but also found among men.

          • Inequalities according to childhood SEP generally become progressively larger at older ages in all cohorts and in both genders; inequalities according to adult SEP were larger among more recently born generations of women.

          What Do These Findings Mean?
          • The fact that BMI inequalities have persisted or increased across different generations, despite policies designed to reduce them, suggests that new policies are required.

          • Results support the need to intervene earlier rather than later in adult life, since inequalities tend to become larger at older ages.

          • Limitations include the use of only one aspect of socioeconomic circumstances (social class), and the fact that not all participants continue to provide data in longitudinal studies—this may have led us to underestimating the size of BMI inequalities.

          Related collections

          Most cited references90

          • Record: found
          • Abstract: found
          • Article: not found

          Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

          In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants

            Summary Background Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. Findings We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world’s men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women. Interpretation If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world’s poorest regions, especially in south Asia. Funding Wellcome Trust, Grand Challenges Canada.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

              Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2, mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                10 January 2017
                January 2017
                : 14
                : 1
                : e1002214
                Affiliations
                [1 ]Centre for Longitudinal Studies, UCL Institute of Education, London, United Kingdom
                [2 ]School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
                [3 ]Population, Policy and Practice, UCL Institute of Child Health, London, United Kingdom
                [4 ]MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
                Stanford University, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                • Conceptualization: DB RH WJ LL DK.

                • Data curation: DB WJ RH.

                • Formal analysis: DB.

                • Funding acquisition: LL DK RH.

                • Methodology: DB RH WJ LL DK.

                • Project administration: DB RH LL DK.

                • Software: DB.

                • Supervision: RH.

                • Visualization: DB.

                • Writing – original draft: DB.

                • Writing – review & editing: DB RH WJ LL DK.

                Author information
                http://orcid.org/0000-0002-6454-626X
                http://orcid.org/0000-0001-7386-2857
                Article
                PMEDICINE-D-16-02828
                10.1371/journal.pmed.1002214
                5224787
                28072856
                e37694dc-118f-4d25-a4c7-89ab875b52e6
                © 2017 Bann et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 September 2016
                : 1 December 2016
                Page count
                Figures: 4, Tables: 2, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000269, Economic and Social Research Council;
                Award ID: ES/K000357/1
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12019/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12019/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12019/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_12019/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000269, Economic and Social Research Council;
                Award ID: ES/M001660/1
                Funded by: funder-id http://dx.doi.org/10.13039/501100000269, Economic and Social Research Council;
                Award ID: ES/M008584/1
                Award Recipient :
                This project is part of a collaborative research programme entitled ‘Cohorts and Longitudinal Studies Enhancement Resources’ (CLOSER). This programme is funded by the ESRC ( http://www.esrc.ac.uk) grant reference: ES/K000357/1. The UK Medical Research Council ( http://www.mrc.ac.uk) provides core funding for the MRC National Survey of Health and Development and RH and DK (MC_UU_12019/1, MC_UU_12019/2). The UK Economic and Social Research Council provides core funding for the National Child Development Study and the British Cohort Study (ES/M001660/1). DB is partly funded by the ESRC (grant reference ES/M008584/1), but has no involvement in funding decisions from ESRC. RH and DK work at the MRC Unit for Lifelong Health and Ageing at UCL but have no involvement in funding decisions for the MRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                People and Places
                Population Groupings
                Age Groups
                Adults
                Research and Analysis Methods
                Research Design
                Cohort Studies
                Social Sciences
                Sociology
                Social Stratification
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                People and Places
                Population Groupings
                Families
                Fathers
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Linear Regression Analysis
                Custom metadata
                The dataset used in this research uses harmonised data from three cohort studies. The original and the harmonised 1946 NSHD data are made available to researchers who submit data requests to mrclha.swiftinfo@ 123456ucl.ac.uk ; see also the full policy documents at http://www.nshd.mrc.ac.uk/data.aspx. The original data for the 1958 NCDS and 1970 BCS are available from the UK Data Archive ( http://www.data-archive.ac.uk).

                Medicine
                Medicine

                Comments

                Comment on this article