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      Do neighbourhood socioeconomic circumstances not matter for weight status among Australian men? Multilevel evidence from a household survey of 14 691 adults

      research-article
        1 , 2 , 3 , 3
      BMJ Open
      BMJ Publishing Group
      PUBLIC HEALTH, SOCIAL MEDICINE, STATISTICS & RESEARCH METHODS

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          Abstract

          Objective

          A recent analysis of the Australian National Health Survey (2011–2012) reported that the patterning of overweight and obesity among men, unlike for women, was not associated with neighbourhood socioeconomic disadvantage. The purpose of this study was to examine whether this gender difference in potential neighbourhood ‘effects’ on adult weight status can be observed in analyses of a different source of data.

          Design, setting and participants

          A cross-sectional sample of 14 693 people aged 18 years or older was selected from the 2012 wave of the ‘Household, Income and Labour Dynamics in Australia’ (HILDA). Three person-level outcomes were considered: (1) body mass index (BMI); (2) a binary indicator of ‘normal weight’ versus ‘overweight or obese’; and (3) ‘normal weight or overweight’ versus ‘obese’. Area-level socioeconomic circumstances were measured using quintiles of the Socio Economic Index For Areas (SEIFA). Multilevel linear and logistic regression models were used to examine associations while accounting for clustering within households and neighbourhoods, adjusting for person-level socioeconomic confounders.

          Results

          Neighbourhood-level factors accounted for 4.9% of the overall variation in BMI, whereas 20.1% was attributable to household-level factors. Compared with their peers living in deprived neighbourhoods, mean BMI was 0.7 kg/m 2 lower among men and 2.2 kg/m 2 lower among women living in affluent areas, with a clear trend across categories. Similarly, the percentage of overweight and obese, and obesity specifically, was lower in affluent areas for both men and women. These results were robust to adjustment for confounders.

          Conclusions

          Unlike findings from the national health survey, but in line with evidence from other high-income countries, this study finds an inverse patterning of BMI by neighbourhood disadvantage for men, and especially among women. The potential mediators which underpin this gender difference in BMI within disadvantaged neighbourhoods warrant further investigation.

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          Most cited references6

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          The obesity epidemic in the United States--gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis.

          This review of the obesity epidemic provides a comprehensive description of the current situation, time trends, and disparities across gender, age, socioeconomic status, racial/ethnic groups, and geographic regions in the United States based on national data. The authors searched studies published between 1990 and 2006. Adult overweight and obesity were defined by using body mass index (weight (kg)/height (m)(2)) cutpoints of 25 and 30, respectively; childhood "at risk for overweight" and overweight were defined as the 85th and 95th percentiles of body mass index. Average annual increase in and future projections for prevalence were estimated by using linear regression models. Among adults, obesity prevalence increased from 13% to 32% between the 1960s and 2004. Currently, 66% of adults are overweight or obese; 16% of children and adolescents are overweight and 34% are at risk of overweight. Minority and low-socioeconomic-status groups are disproportionately affected at all ages. Annual increases in prevalence ranged from 0.3 to 0.9 percentage points across groups. By 2015, 75% of adults will be overweight or obese, and 41% will be obese. In conclusion, obesity has increased at an alarming rate in the United States over the past three decades. The associations of obesity with gender, age, ethnicity, and socioeconomic status are complex and dynamic. Related population-based programs and policies are needed.
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            The built environment and obesity: a systematic review of the epidemiologic evidence.

            We completed a systematic search of the epidemiologic literature on built environment and obesity and identified 63 relevant papers, which were then evaluated for the quality of between-study evidence. We were able to classify studies into one of two primary approaches for defining place and corresponding geographic areas of influence: those based on contextual effects derived from shared pre-determined administrative units and those based on individually unique geographic buffers. The 22 contextual papers evaluated 80 relations, 38 of which did not achieve statistical significance. The 15 buffer papers evaluated 40 relations, 24 of which did not achieve statistical significance. There was very little between-study similarity in methods in both types of approaches, which prevented estimation of pooled effects. The great heterogeneity across studies limits what can be learned from this body of evidence. Copyright 2009 Elsevier Ltd. All rights reserved.
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              Built environments and obesity in disadvantaged populations.

              In the United States, health disparities in obesity and obesity-related illnesses have been the subject of growing concern. To better understand how obesity-related health disparities might relate to obesogenic built environments, the authors conducted a systematic review of the published scientific literature, screening for studies with relevance to disadvantaged individuals or areas, identified by low socioeconomic status, black race, or Hispanic ethnicity. A search for related terms in publication databases and topically related resources yielded 45 studies published between January 1995 and January 2009 with at least 100 participants or area residents that provided information on 1) the built environment correlates of obesity or related health behaviors within one or more disadvantaged groups or 2) the relative exposure these groups had to potentially obesogenic built environment characteristics. Upon consideration of the obesity and behavioral correlates of built environment characteristics, research provided the strongest support for food stores (supermarkets instead of smaller grocery/convenience stores), places to exercise, and safety as potentially influential for disadvantaged groups. There is also evidence that disadvantaged groups were living in worse environments with respect to food stores, places to exercise, aesthetic problems, and traffic or crime-related safety. One strategy to reduce obesity would involve changing the built environment to be more supportive of physical activity and a healthy diet. Based on the authors' review, increasing supermarket access, places to exercise, and neighborhood safety may also be promising strategies to reduce obesity-related health disparities.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2015
                16 September 2015
                : 5
                : 9
                : e007052
                Affiliations
                [1 ]Early Start Research Institute, University of Wollongong, Wollongong, NSW, Australia
                [2 ]School of Health and Society, University of Wollongong, Wollongong, NSW, Australia
                [3 ]Menzies Centre for Health Policy, School of Public Health, University of Sydney, Sydney, New South Wales, Australia
                Author notes
                [Correspondence to ] Dr Xiaoqi Feng; xfeng@ 123456uow.edu.au
                Article
                bmjopen-2014-007052
                10.1136/bmjopen-2014-007052
                4577957
                26377502
                395f78a6-8bd6-421d-ac20-f61652b0293e
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 29 October 2014
                : 18 August 2015
                : 21 August 2015
                Categories
                Public Health
                Research
                1506
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                1724

                Medicine
                public health,social medicine,statistics & research methods
                Medicine
                public health, social medicine, statistics & research methods

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