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      The overweight and obesity transition from the wealthy to the poor in low- and middle-income countries: A survey of household data from 103 countries

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          Abstract

          Background

          In high-income countries, obesity prevalence (body mass index greater than or equal to 30 kg/m 2) is highest among the poor, while overweight (body mass index greater than or equal to 25 kg/m 2) is prevalent across all wealth groups. In contrast, in low-income countries, the prevalence of overweight and obesity is higher among wealthier individuals than among poorer individuals. We characterize the transition of overweight and obesity from wealthier to poorer populations as countries develop, and project the burden of overweight and obesity among the poor for 103 countries.

          Methods and findings

          Our sample used 182 Demographic and Health Surveys and World Health Surveys ( n = 2.24 million respondents) from 1995 to 2016. We created a standard wealth index using household assets common among all surveys and linked national wealth by country and year identifiers. We then estimated the changing probability of overweight and obesity across every wealth decile as countries’ per capita gross domestic product (GDP) rises using logistic and linear fixed-effect regression models. We found that obesity rates among the wealthiest decile were relatively stable with increasing national wealth, and the changing gradient was largely due to increasing obesity prevalence among poorer populations (3.5% [95% uncertainty interval: 0.0%–8.3%] to 14.3% [9.7%–19.0%]). Overweight prevalence among the richest (45.0% [35.6%–54.4%]) and the poorest (45.5% [35.9%–55.0%]) were roughly equal in high-income settings. At $8,000 GDP per capita, the adjusted probability of being obese was no longer highest in the richest decile, and the same was true of overweight at $10,000. Above $25,000, individuals in the richest decile were less likely than those in the poorest decile to be obese, and the same was true of overweight at $50,000. We then projected overweight and obesity rates by wealth decile to 2040 for all countries to quantify the expected rise in prevalence in the relatively poor. Our projections indicated that, if past trends continued, the number of people who are poor and overweight will increase in our study countries by a median 84.4% (range 3.54%–383.4%), most prominently in low-income countries. The main limitations of this study included the inclusion of cross-sectional, self-reported data, possible reverse causality of overweight and obesity on wealth, and the lack of physical activity and food price data.

          Conclusions

          Our findings indicate that as countries develop economically, overweight prevalence increased substantially among the poorest and stayed mostly unchanged among the wealthiest. The relative poor in upper- and lower-middle income countries may have the greatest burden, indicating important planning and targeting needs for national health programs.

          Abstract

          Tara Templin and colleagues project the burden of obesity in 103 countries.

          Author summary

          Why was this study done?
          • Obesity prevalence has been rising in every country in the world since 1975 and contributes to an increasing proportion of noncommunicable disease risk and burden.

          • Within countries, obesity prevalence is highest among wealthier population strata in poorer countries, but the burden of obesity shifts to poorer population strata as national wealth increases.

          • While the flipped wealth gradients of obesity in poor and rich countries are documented, no research shows how this shift happens or where it occurs along the range of economic development.

          • This work was motivated by a desire to inform policy makers of when and how this reversal is likely to occur, because obesity among the poor has different implications for public health policy than obesity among the wealthy.

          What did the researchers do and find?
          • We collated 182 Demographic and Health Surveys and World Health Surveys [ n = 2.24 million respondents] from 103 countries with information on respondent height, weight, personal wealth, and country wealth.

          • We estimated the relationship of personal wealth with overweight and obesity, and examined how that relationship varies with country wealth.

          • At a gross domestic product (GDP) per capita of $8,000, the prevalence of obesity is no longer the highest among those in the top wealth decile ($10,000 for overweight), and at $30,000, obesity prevalence among those in the poorest decile is higher than among the wealthiest ($50,000 for overweight). The transition is driven by increasing obesity among the poor without appreciable decreasing obesity among the wealthy.

          • Above $10,000 GDP per capita, the relationship between overweight and personal wealth starts to change as overweight prevalence among those in the lower deciles of wealth increases.

          • We estimate that 70.2% (64.1%–76.4%) of countries will begin or have undergone this shift by 2040, and the number of people who are both obese and poor (in the lowest quintile) in our study countries will increase by 17.3 million people (15.3–19.6).

          What do these findings mean?
          • Distinct points along the obesity transition may represent a particularly effective time for policy makers to implement obesity interventions.

          • At a GDP per capita of $8,000, the burden of paying for the costs of obesity may start to increase, as the prevalence of obesity is no longer uniquely concentrated among the wealthy.

          • People in the richest decile may not be affected by the same economic mechanisms that increase obesity in the poor, as obesity prevalence of the wealthy within each country does not change substantially with economic development.

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          Most cited references14

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          Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR–INDIAB population-based cross-sectional study

          Previous studies have not adequately captured the heterogeneous nature of the diabetes epidemic in India. The aim of the ongoing national Indian Council of Medical Research-INdia DIABetes study is to estimate the national prevalence of diabetes and prediabetes in India by estimating the prevalence by state.
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            Uneven dietary development: linking the policies and processes of globalization with the nutrition transition, obesity and diet-related chronic diseases

            In a "nutrition transition", the consumption of foods high in fats and sweeteners is increasing throughout the developing world. The transition, implicated in the rapid rise of obesity and diet-related chronic diseases worldwide, is rooted in the processes of globalization. Globalization affects the nature of agri-food systems, thereby altering the quantity, type, cost and desirability of foods available for consumption. Understanding the links between globalization and the nutrition transition is therefore necessary to help policy makers develop policies, including food policies, for addressing the global burden of chronic disease. While the subject has been much discussed, tracing the specific pathways between globalization and dietary change remains a challenge. To help address this challenge, this paper explores how one of the central mechanisms of globalization, the integration of the global marketplace, is affecting the specific diet patterns. Focusing on middle-income countries, it highlights the importance of three major processes of market integration: (I) production and trade of agricultural goods; (II) foreign direct investment in food processing and retailing; and (III) global food advertising and promotion. The paper reveals how specific policies implemented to advance the globalization agenda account in part for some recent trends in the global diet. Agricultural production and trade policies have enabled more vegetable oil consumption; policies on foreign direct investment have facilitated higher consumption of highly-processed foods, as has global food marketing. These dietary outcomes also reflect the socioeconomic and cultural context in which these policies are operating. An important finding is that the dynamic, competitive forces unleashed as a result of global market integration facilitates not only convergence in consumption habits (as is commonly assumed in the "Coca-Colonization" hypothesis), but adaptation to products targeted at different niche markets. This convergence-divergence duality raises the policy concern that globalization will exacerbate uneven dietary development between rich and poor. As high-income groups in developing countries accrue the benefits of a more dynamic marketplace, lower-income groups may well experience convergence towards poor quality obseogenic diets, as observed in western countries. Global economic polices concerning agriculture, trade, investment and marketing affect what the world eats. They are therefore also global food and health policies. Health policy makers should pay greater attention to these policies in order to address some of the structural causes of obesity and diet-related chronic diseases worldwide, especially among the groups of low socioeconomic status.
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              Obesity in Low- and Middle-Income Countries: Burden, Drivers, and Emerging Challenges

              We have reviewed the distinctive features of excess weight, its causes, and related prevention and management efforts, as well as data gaps and recommendations for future research in low- and middle-income countries (LMICs). Obesity is rising in every region of the world, and no country has been successful at reversing the epidemic once it has begun. In LMICs, overweight is higher in women compared with men, in urban compared with rural settings, and in older compared with younger individuals; however, the urban-rural overweight differential is shrinking in many countries. Overweight occurs alongside persistent burdens of underweight in LMICs, especially in young women. Changes in the global diet and physical activity are among the hypothesized leading contributors to obesity. Emerging risk factors include environmental contaminants, chronic psychosocial stress, neuroendocrine dysregulation, and genetic/epigenetic mechanisms. Data on effective strategies to prevent the onset of obesity in LMICs or elsewhere are limited. Expanding the research in this area is a key priority and has important possibilities for reverse innovation that may also inform interventions in high-income countries.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                27 November 2019
                November 2019
                : 16
                : 11
                : e1002968
                Affiliations
                [1 ] Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America
                [2 ] Organisation for Economic Co-operation and Development ELS/HD, Paris, France
                [3 ] Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
                [4 ] Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
                [5 ] Center for Population Health Sciences, Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, California, United States of America
                Carolina Population Center, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-4984-6472
                http://orcid.org/0000-0001-7976-7412
                http://orcid.org/0000-0002-8364-4711
                Article
                PMEDICINE-D-18-04077
                10.1371/journal.pmed.1002968
                6880978
                31774821
                b69d71b1-a9da-4641-9790-3f67f037681b
                © 2019 Templin 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
                : 20 November 2018
                : 29 October 2019
                Page count
                Figures: 4, Tables: 0, Pages: 15
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Social Sciences
                Economics
                Economic Analysis
                Medicine and Health Sciences
                Public and Occupational Health
                Research and Analysis Methods
                Research Design
                Survey Research
                Surveys
                Health Surveys
                Social Sciences
                Economics
                Development Economics
                Economic Development
                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 Processes
                Food Consumption
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Food Consumption
                Research and Analysis Methods
                Research Design
                Survey Research
                Surveys
                Custom metadata
                All data are publicly available. The Demographic and Health Surveys (DHS) are available from the United States Agency for International Development's DHS program ( https://dhsprogram.com/data/). The World Health Surveys are available from the World Health Organization ( https://www.who.int/healthinfo/survey/en/). The population projections are available from the United Nations World Population Prospects ( https://population.un.org/wpp/Download/Standard/Population/). The gross domestic product per capita projections are available from the Financing Global Health project at the Institute for Health Metrics and Evaluation ( http://ghdx.healthdata.org/record/ihme-data/global-expected-health-spending-2017-2050).

                Medicine
                Medicine

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