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      Does dissatisfaction with, or accurate perception of overweight status help people reduce weight? Longitudinal study of Australian adults

      research-article
      1 , 2 , , 2 , 3
      BMC Public Health
      BioMed Central
      Body mass index, Weight misperception, Disadvantage, Longitudinal

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          Abstract

          Background

          With studies around the world suggesting a large proportion of people do not recognise that they are overweight (or feel satisfied with being overweight), this fuels the view that such ‘misperceptions’ need to be ‘corrected’. However, few longitudinal studies have examined the consequences of under-perceived weight status, nor over-perceived weight status (when a person feels overweight when they are not) and weight-related satisfaction on trajectories in body mass index (BMI).

          Methods

          Five-year BMI trajectories were examined among 8174 participants in an Australian nationally representative cohort. Each person was classified into groups according to their neighbourhood socioeconomic circumstances, baseline BMI and answers to “how satisfied are you with your current weight?” and “ do you consider yourself to be… acceptable weight / underweight / overweight?” Gender-specific multilevel linear regressions were used to examine five-year BMI trajectories for people in each group, adjusting for potential confounders.

          Results

          At baseline, weight-related dissatisfaction and perceived overweight were generally associated with higher mean BMI for men and women, regardless of whether they were classified as ‘normal’ or overweight by World Health Organization (WHO) criteria. Mean BMI did not decrease among people classified as overweight who perceived themselves as overweight, or expressed weight-related dissatisfaction, regardless of where they lived. Among men and women with ‘normal’ BMI at baseline but expressing weight-related dissatisfaction, mean BMI increased disproportionately among those living in disadvantaged areas compared to their counterparts in affluent areas. Similarly, mean BMI rose disproportionately among people in disadvantaged areas who felt they were overweight despite having a ‘normal’ BMI by WHO criteria, compared to people with the same over-perceptions living in affluent areas. These differences exacerbated pre-existing socioeconomic inequities in mean BMI.

          Conclusions

          No evidence was found to suggest accurate recognition of overweight or expressing weight-related dissatisfaction leads to a lower BMI. However, there was evidence of an increase in mean BMI among people who felt dissatisfied with, or over-perceived their ‘normal’ weight, especially in socioeconomically disadvantaged areas. Correction of under-perceptions may not drive weight loss, but circumstances contributing to over-perception and dissatisfaction with weight status may contribute to increased weight gain and exacerbate socioeconomic inequities in BMI.

          Electronic supplementary material

          The online version of this article (10.1186/s12889-019-6938-3) contains supplementary material, which is available to authorized users.

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          Most cited references65

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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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            Neighborhoods and health.

            Features of neighborhoods or residential environments may affect health and contribute to social and race/ethnic inequalities in health. The study of neighborhood health effects has grown exponentially over the past 15 years. This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health (specifically depression and depressive symptoms). Empirical work is classified into two main eras: studies that use census proxies and studies that directly measure neighborhood attributes using a variety of approaches. Key conceptual and methodological challenges in studying neighborhood health effects are reviewed. Existing gaps in knowledge and promising new directions in the field are highlighted.
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              Gender differences in stress and coping styles

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                Author and article information

                Contributors
                02 4221 5713 , xfeng@uow.edu.au
                a.wilson@sydney.edu.au
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                22 May 2019
                22 May 2019
                2019
                : 19
                : 619
                Affiliations
                [1 ]ISNI 0000 0004 0486 528X, GRID grid.1007.6, Population Wellbeing and Environment Research Lab (PowerLab), School of Health and Society, Faculty of Social Sciences, , University of Wollongong, ; Wollongong, NSW 2522 Australia
                [2 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Menzies Centre for Health Policy, School of Public Health, the Faculty of Medicine and Health, , The University of Sydney, ; Sydney, Australia
                [3 ]ISNI 0000 0004 0601 4585, GRID grid.474225.2, The Australian Prevention Partnership Centre, , The Sax Institute, ; Sydney, Australia
                Author information
                http://orcid.org/0000-0002-3421-220X
                Article
                6938
                10.1186/s12889-019-6938-3
                6530191
                31113396
                b46a90b9-7d46-4cb6-8f63-d370e3f231ab
                © The Author(s). 2019

                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. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 March 2018
                : 2 May 2019
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Public health
                body mass index,weight misperception,disadvantage,longitudinal
                Public health
                body mass index, weight misperception, disadvantage, longitudinal

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