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      Energy balance and obesity: what are the main drivers?

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          Abstract

          Purpose

          The aim of this paper is to review the evidence of the association between energy balance and obesity.

          Methods

          In December 2015, the International Agency for Research on Cancer (IARC), Lyon, France convened a Working Group of international experts to review the evidence regarding energy balance and obesity, with a focus on Low and Middle Income Countries (LMIC).

          Results

          The global epidemic of obesity and the double burden, in LMICs, of malnutrition (coexistence of undernutrition and overnutrition) are both related to poor quality diet and unbalanced energy intake. Dietary patterns consistent with a traditional Mediterranean diet and other measures of diet quality can contribute to long-term weight control. Limiting consumption of sugar-sweetened beverages has a particularly important role in weight control. Genetic factors alone cannot explain the global epidemic of obesity. However, genetic, epigenetic factors and the microbiota could influence individual responses to diet and physical activity.

          Conclusion

          Energy intake that exceeds energy expenditure is the main driver of weight gain. The quality of the diet may exert its effect on energy balance through complex hormonal and neurological pathways that influence satiety and possibly through other mechanisms. The food environment, marketing of unhealthy foods and urbanization, and reduction in sedentary behaviors and physical activity play important roles. Most of the evidence comes from High Income Countries and more research is needed in LMICs.

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          Most cited references64

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          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.
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            Objectively measured sedentary time, physical activity, and metabolic risk: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).

            We examined the associations of objectively measured sedentary time and physical activity with continuous indexes of metabolic risk in Australian adults without known diabetes. An accelerometer was used to derive the percentage of monitoring time spent sedentary and in light-intensity and moderate-to-vigorous-intensity activity, as well as mean activity intensity, in 169 Australian Diabetes, Obesity and Lifestyle Study (AusDiab) participants (mean age 53.4 years). Associations with waist circumference, triglycerides, HDL cholesterol, resting blood pressure, fasting plasma glucose, and a clustered metabolic risk score were examined. Independent of time spent in moderate-to-vigorous-intensity activity, there were significant associations of sedentary time, light-intensity time, and mean activity intensity with waist circumference and clustered metabolic risk. Independent of waist circumference, moderate-to-vigorous-intensity activity time was significantly beneficially associated with triglycerides. These findings highlight the importance of decreasing sedentary time, as well as increasing time spent in physical activity, for metabolic health.
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              Sugar-sweetened beverages and genetic risk of obesity.

              Temporal increases in the consumption of sugar-sweetened beverages have paralleled the rise in obesity prevalence, but whether the intake of such beverages interacts with the genetic predisposition to adiposity is unknown. We analyzed the interaction between genetic predisposition and the intake of sugar-sweetened beverages in relation to body-mass index (BMI; the weight in kilograms divided by the square of the height in meters) and obesity risk in 6934 women from the Nurses' Health Study (NHS) and in 4423 men from the Health Professionals Follow-up Study (HPFS) and also in a replication cohort of 21,740 women from the Women's Genome Health Study (WGHS). The genetic-predisposition score was calculated on the basis of 32 BMI-associated loci. The intake of sugar-sweetened beverages was examined prospectively in relation to BMI. In the NHS and HPFS cohorts, the genetic association with BMI was stronger among participants with higher intake of sugar-sweetened beverages than among those with lower intake. In the combined cohorts, the increases in BMI per increment of 10 risk alleles were 1.00 for an intake of less than one serving per month, 1.12 for one to four servings per month, 1.38 for two to six servings per week, and 1.78 for one or more servings per day (P<0.001 for interaction). For the same categories of intake, the relative risks of incident obesity per increment of 10 risk alleles were 1.19 (95% confidence interval [CI], 0.90 to 1.59), 1.67 (95% CI, 1.28 to 2.16), 1.58 (95% CI, 1.01 to 2.47), and 5.06 (95% CI, 1.66 to 15.5) (P=0.02 for interaction). In the WGHS cohort, the increases in BMI per increment of 10 risk alleles were 1.39, 1.64, 1.90, and 2.53 across the four categories of intake (P=0.001 for interaction); the relative risks for incident obesity were 1.40 (95% CI, 1.19 to 1.64), 1.50 (95% CI, 1.16 to 1.93), 1.54 (95% CI, 1.21 to 1.94), and 3.16 (95% CI, 2.03 to 4.92), respectively (P=0.007 for interaction). The genetic association with adiposity appeared to be more pronounced with greater intake of sugar-sweetened beverages. (Funded by the National Institutes of Health and others.).
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                Author and article information

                Contributors
                romieu@iarc.fr
                Journal
                Cancer Causes Control
                Cancer Causes Control
                Cancer Causes & Control
                Springer International Publishing (Cham )
                0957-5243
                1573-7225
                17 February 2017
                17 February 2017
                2017
                : 28
                : 3
                : 247-258
                Affiliations
                [1 ]ISNI 0000000405980095, GRID grid.17703.32, Nutrition and Metabolism Section, , International Agency for Research on Cancer, ; 150 cours Albert Thomas, 69372 Lyon Cedex 08, France
                [2 ]ISNI 0000 0004 1773 4764, GRID grid.415771.1, Centro de Investigación en Nutrición y Salud, , Instituto Nacional de Salud Pública, ; Cuernavaca, Mexico
                [3 ]ISNI 0000 0004 4910 6535, GRID grid.460789.4, Micalis Institute, MGP MetagenoPolis, INRA, AgroParisTech, , Université Paris-Saclay, ; Jouy-en-Josas, France
                [4 ]ISNI 0000 0004 0623 9987, GRID grid.412650.4, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, CRC, , University hospital Malmö, ; Malmö, Sweden
                [5 ]ISNI 0000 0004 1936 9801, GRID grid.22903.3a, Faculty of Agricultural and Food Science, , American University of Beirut, ; Beirut, Lebanon
                [6 ]ISNI 0000000122483208, GRID grid.10698.36, Department of Nutrition and the Nutrition Research Institute, , The University of North Carolina, ; Chapel Hill, USA
                [7 ]ISNI 0000 0001 2190 5763, GRID grid.7727.5, Department of Epidemiology and Preventive Medicine, , University of Regensburg, ; Regensburg, Germany
                [8 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, Faculty of Medicine, Southampton General Hospital, , University of Southampton, ; Southampton, UK
                [9 ]ISNI 0000000121633745, GRID grid.3575.4, Nutrition Policy and Scientific Advice (NPU), Department of Nutrition for Health and Development (NHD), , World Health Organization (WHO), ; Geneva, Switzerland
                [10 ]ISNI 0000 0004 1936 8075, GRID grid.48336.3a, Office of the Associate Director, Applied Research Program, Division of Cancer Control and Population Sciences, , National Cancer Institute, ; Bethesda, USA
                [11 ]ISNI 0000000084992262, GRID grid.7177.6, Faculty of Earth and Life Sciences, Department of Health Sciences, , University Amsterdam, ; Amsterdam, The Netherlands
                [12 ]ISNI 0000 0000 9554 2494, GRID grid.189747.4, Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, Joint Appointments, School of Medicine and Biomedical Sciences, University at Buffalo, , State University of New York, ; Buffalo, USA
                [13 ]ISNI 0000 0001 0481 6099, GRID grid.5012.6, NUTRIM School of Nutrition and Translational Research in Metabolism, , Maastricht University, ; Maastricht, The Netherlands
                [14 ]ISNI 0000 0004 1937 0490, GRID grid.10223.32, Institute of Nutrition, , Mahidol University Salaya, ; Nakhon Pathom, Thailand
                [15 ]World Cancer Research Fund International, London, UK
                [16 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Nutrition, , Harvard T.H. Chan School of Public Health, ; Boston, USA
                Article
                869
                10.1007/s10552-017-0869-z
                5325830
                28210884
                7b3c8c7c-e436-4248-a148-b60c5c499e38
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 21 October 2016
                : 6 February 2017
                Categories
                Original Paper
                Custom metadata
                © Springer International Publishing Switzerland 2017

                Oncology & Radiotherapy
                energy intake,energy expenditure,energy balance,obesity,satiety,diet
                Oncology & Radiotherapy
                energy intake, energy expenditure, energy balance, obesity, satiety, diet

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