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      Risk Factors for Childhood Stunting in 137 Developing Countries: A Comparative Risk Assessment Analysis at Global, Regional, and Country Levels

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          Abstract

          Background

          Stunting affects one-third of children under 5 y old in developing countries, and 14% of childhood deaths are attributable to it. A large number of risk factors for stunting have been identified in epidemiological studies. However, the relative contribution of these risk factors to stunting has not been examined across countries. We estimated the number of stunting cases among children aged 24–35 mo (i.e., at the end of the 1,000 days’ period of vulnerability) that are attributable to 18 risk factors in 137 developing countries.

          Methods and Findings

          We classified risk factors into five clusters: maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction (FGR) and preterm birth, child nutrition and infection, and environmental factors. We combined published estimates and individual-level data from population-based surveys to derive risk factor prevalence in each country in 2010 and identified the most recent meta-analysis or conducted de novo reviews to derive effect sizes. We estimated the prevalence of stunting and the number of stunting cases that were attributable to each risk factor and cluster of risk factors by country and region.

          The leading risk worldwide was FGR, defined as being term and small for gestational age, and 10.8 million cases (95% CI 9.1 million–12.6 million) of stunting (out of 44.1 million) were attributable to it, followed by unimproved sanitation, with 7.2 million (95% CI 6.3 million–8.2 million), and diarrhea with 5.8 million (95% CI 2.4 million–9.2 million). FGR and preterm birth was the leading risk factor cluster in all regions. Environmental risks had the second largest estimated impact on stunting globally and in the South Asia, sub-Saharan Africa, and East Asia and Pacific regions, whereas child nutrition and infection was the second leading cluster of risk factors in other regions.

          Although extensive, our analysis is limited to risk factors for which effect sizes and country-level exposure data were available. The global nature of the study required approximations (e.g., using exposures estimated among women of reproductive age as a proxy for maternal exposures, or estimating the impact of risk factors on stunting through a mediator rather than directly on stunting). Finally, as is standard in global risk factor analyses, we used the effect size of risk factors on stunting from meta-analyses of epidemiological studies and assumed that proportional effects were fairly similar across countries.

          Conclusions

          FGR and unimproved sanitation are the leading risk factors for stunting in developing countries. Reducing the burden of stunting requires a paradigm shift from interventions focusing solely on children and infants to those that reach mothers and families and improve their living environment and nutrition.

          Abstract

          Using risk factor and height data from population-based surveys, Goodarz Danaei estimate the greatest contributors to childhood stunting worldwide.

          Author Summary

          Why Was This Study Done?
          • Even though child mortality is decreasing, children around the world are still suffering from delayed physical growth. In fact, 30% of children in developing countries are stunted (i.e., have heights more than two standard deviations below the global standard median height for their age).

          • The first 1,000 days of life (up until a child turns two) are most important because development during this period impacts a child for the rest of his or her life. Stunting during this period is related to poor outcomes in health, cognitive development, and educational and economic attainment later in life.

          • In order to reduce stunting, it is important to understand its determinants and their relative effect, to help priority-setting in designing policies to improve childhood growth.

          What Did the Researchers Do and Find?
          • We identified 18 key risk factors for stunting and grouped them into five clusters (maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction and preterm birth, child nutrition and infection, and environmental factors).

          • We used data on the prevalence of each risk factor in each country and its effect on stunting. We then estimated the prevalence and number of cases of stunting among children aged 24 to 35 months in 2010 that were attributable to each of these risk factors, and to each cluster of risk factors combined, in 137 developing countries.

          • We found that the leading risk for stunting worldwide was being “term, and small for gestational age” (that is, being born at or after 37 weeks of pregnancy, but being too small), to which 10.8 million cases of stunting among two-year-olds were attributable (out of 44.1 million). This was followed by poor sanitation (7.2 million cases) and diarrhea (5.8 million cases).

          • When we grouped the risks together, fetal growth restriction and preterm birth was the leading risk factor cluster in all regions, but there were differences in the ranking of other risk factor clusters across regions. For example, environmental risk factors (i.e., poor water quality, poor sanitary conditions, and use of solid fuels) had the second largest impact on stunting globally and in South Asia, sub-Saharan Africa, and East Asia and Pacific, whereas risk factors related to child nutrition and infection were the second leading risk factors in other regions.

          What Do These Findings Mean?
          • Efforts to further reduce stunting should be focused on fetal growth restriction and poor sanitation, and this will require refocusing prevention programs on interventions that reach mothers and families and improve their living environment and nutrition.

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          Most cited references31

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          Maternal and child undernutrition and overweight in low-income and middle-income countries

          The Lancet, 382(9890), 427-451
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            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.
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              Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost?

              The Lancet, 382(9890), 452-477
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                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
                1 November 2016
                November 2016
                : 13
                : 11
                : e1002164
                Affiliations
                [1 ]Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
                [2 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
                [3 ]Harvard Graduate School of Education, Cambridge, Massachusetts, United States of America
                [4 ]RAND Corporation, Pittsburgh, Pennsylvania, United States of America
                [5 ]Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
                [6 ]MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
                [7 ]Wellcome Trust Centre for Global Health Research, Imperial College London, London, United Kingdom
                [8 ]Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
                Makerere University Medical School, UGANDA
                Author notes

                The authors have declared that no competing interests exist.

                • Conceived and designed the experiments: WWF ME GF MCSF GD CRS.

                • Performed the experiments: KGA CRS GF DCM EP AS.

                • Analyzed the data: KGA CRS.

                • Contributed reagents/materials/analysis tools: ME.

                • Wrote the first draft of the manuscript: GD KGA ME.

                • Contributed to the writing of the manuscript: CRS GF DCM EP AS MCSF WWF.

                • Agree with the manuscript’s results and conclusions: GD KGA ME CRS GF DCM EP AS MCSF WWF.

                • All authors have read, and confirm that they meet, ICMJE criteria for authorship.

                Author information
                http://orcid.org/0000-0001-6147-3475
                http://orcid.org/0000-0002-2109-8081
                Article
                PMEDICINE-D-15-03504
                10.1371/journal.pmed.1002164
                5089547
                27802277
                99471e22-8ceb-4336-8418-c19f120a4b02
                © 2016 Danaei 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 2015
                : 23 September 2016
                Page count
                Figures: 3, Tables: 2, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004828, Grand Challenges Canada;
                Award ID: # 0073-03
                Award Recipient :
                Grand Challenges Canada under the Saving Brains program (grant # 0073-03). The funder 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
                Environmental Health
                Sanitation
                Medicine and Health Sciences
                Public and Occupational Health
                Environmental Health
                Sanitation
                Biology and Life Sciences
                Nutrition
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                Nutrition
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                Gastroenterology and Hepatology
                Diarrhea
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                Preventive Medicine
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                Custom metadata
                Data underlying our analysis is available as described in Table 1 and the S1 Data Supporting Information file.

                Medicine
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