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      Prevalence and time trends in overweight and obesity among urban women: an analysis of demographic and health surveys data from 24 African countries, 1991 2014

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          Abstract

          Objective

          To examine the prevalence and trends in overweight and obesity among non-pregnant urban women in Africa over the past two and a half decades.

          Design

          Cross-sectional surveys conducted between 1991 and 2014.

          Settings

          Demographic and Health Surveys (DHS), repeated cross-sectional data collected in 24 African countries.

          Participants

          Adult non-pregnant women aged 15–49 years. The earlier DHS collected anthropometric data on only those women who had children aged 0–5 years. The main analyses were limited to this subgroup. The participants were classified as overweight (25.0–29.9 kg/m 2) and obese (≥30.0 kg/m 2).

          Results

          The prevalence of overweight and obesity among women increased in all the 24 countries. Trends were statistically significant in 17 of the 24 countries in the case of obesity and 13 of the 24 for overweight. In Ghana, overweight almost doubled (p=0.001) while obesity tripled (p=0.001) between 1993 and 2014. Egypt has the highest levels of overweight and obesity at 44% (95% CI 42%, 46.5%) and 39% (95% CI 36.6%, 41.8%), respectively, in 2014 and the trend showed significant increase (p=0.005) from 1995 levels. Also, obesity doubled in Kenya, Benin, Niger, Rwanda, Ivory Coast and Uganda, while tripled in Zambia, Burkina Faso, Mali, Malawi and Tanzania. Ethiopia and Madagascar had the lowest prevalence of both obesity and overweight, with overweight ranging from 7% to 12% and obesity from 1% to 4%.

          Conclusions

          Overweight and obesity are increasing among women of reproductive age in urban Africa, with obesity among this age group having more than doubled or tripled in 12 of the 24 countries. There is an urgent need for deliberate policies and interventions to encourage active lifestyles and healthy eating behaviour to curb this trend in urban Africa.

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          Most cited references28

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          Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.

          Obesity and diabetes are increasing in the United States. To estimate the prevalence of obesity and diabetes among US adults in 2001. Random-digit telephone survey of 195 005 adults aged 18 years or older residing in all states participating in the Behavioral Risk Factor Surveillance System in 2001. Body mass index, based on self-reported weight and height and self-reported diabetes. In 2001 the prevalence of obesity (BMI > or =30) was 20.9% vs 19.8% in 2000, an increase of 5.6%. The prevalence of diabetes increased to 7.9% vs 7.3% in 2000, an increase of 8.2%. The prevalence of BMI of 40 or higher in 2001 was 2.3%. Overweight and obesity were significantly associated with diabetes, high blood pressure, high cholesterol, asthma, arthritis, and poor health status. Compared with adults with normal weight, adults with a BMI of 40 or higher had an odds ratio (OR) of 7.37 (95% confidence interval [CI], 6.39-8.50) for diagnosed diabetes, 6.38 (95% CI, 5.67-7.17) for high blood pressure, 1.88 (95% CI,1.67-2.13) for high cholesterol levels, 2.72 (95% CI, 2.38-3.12) for asthma, 4.41 (95% CI, 3.91-4.97) for arthritis, and 4.19 (95% CI, 3.68-4.76) for fair or poor health. Increases in obesity and diabetes among US adults continue in both sexes, all ages, all races, all educational levels, and all smoking levels. Obesity is strongly associated with several major health risk factors.
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            Relationship between body image disturbance and incidence of depression: the SUN prospective cohort

            Background Body image disturbance is an increasing problem in Western societies and is associated with a number of mental health outcomes including anorexia, bulimia, body dysmorphia, and depression. The aim of this study was to assess the association between body image disturbance and the incidence of depression. Methods This study included 10,286 participants from a dynamic prospective cohort of Spanish university graduates, who were followed-up for a median period of 4.2 years (Seguimiento Universidad de Navarra – the SUN study). The key characteristic of the study is the permanently open recruitment that started in 1999. The baseline questionnaire included information about body mass index (BMI) and the nine figure schemes that were used to assess body size perception. These variables were grouped according to recommended classifications and the difference between BMI and body size perception was considered as a proxy of body image disturbance. A subject was classified as an incident case of depression if he/she was initially free of depression and reported a physician-made diagnosis of depression and/or the use of antidepressant medication in at least one of the follow-up questionnaires. The association between body image disturbance and the incidence of depression was estimated by calculating the multivariable adjusted Odds Ratio (OR) and its 95% Confidence Interval (95% CI), using logistic regression models. Results The cumulative incidence of depression during follow-up in the cohort was 4.8%. Men who underestimated their body size had a high percentage of overweight and obesity (50.1% and 12.6%, respectively), whereas women who overestimated their body size had a high percentage of underweight (87.6%). The underestimation exhibited a negative association with the incidence of depression among women (OR: 0.72, 95% CI: 0.54 – 0.95), but this effect disappeared after adjusting for possible confounding variables. The proportion of participants who correctly perceived their body size was high (53.3%) and gross misperception was seldom found, with most cases selecting only one silhouette below (42.7%) or above (2.6%) their actual BMI. Conclusion We found no association between body image disturbance and subsequent depression in a cohort of university graduates in Spain.
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              Obesity and inequities in health in the developing world.

              To update the social distribution of women's obesity in the developing world and, in particular, to identify the specific level of economic development at which, if any, women's obesity in the developing world starts to fuel inequities in health. Multilevel logistic regression analyses applied to anthropometric and socioeconomic data collected by nationally representative cross-sectional surveys conducted from 1992 to 2000 in 37 developing countries within a wide range of world regions and stages of economic development (gross national product (GNP) from 190 to 4440 US dollars per capita). : In total, 148 579 nonpregnant women aged 20-49 y. Body mass index to assess obesity status; quartiles of years of education to assess woman's socioeconomic status (SES), and GNP per capita to assess country's stage of economic development. Belonging to the lower SES group confers strong protection against obesity in low-income economies, but it is a systematic risk factor for the disease in upper-middle income developing economies. A multilevel logistic model-including an interaction term between the country's GNP and each woman's SES-indicates that obesity starts to fuel health inequities in the developing world when the GNP reaches a value of about 2500 US dollars per capita. For most upper-middle income economies and part of the lower-middle income economies, obesity among adult women is already a relevant booster of health inequities and, in the absence of concerted national public actions to prevent obesity, economic growth will greatly expand the list of developing countries where this situation occurs.
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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
                2017
                27 October 2017
                : 7
                : 10
                : e017344
                Affiliations
                [1 ] departmentAfrican Population and Health Research Center , APHRC Campus , Nairobi, Kenya
                [2 ] departmentDepartment of Population Sciences and Development , University of Kinshasa , Kinshasa, Congo
                [3 ] Statistics Canada, Social Analysis and Modeling Division , Ottawa, Canada
                Author notes
                [Correspondence to ] Dr Dickson Abanimi Amugsi; damugsi2002@ 123456yahoo.com
                Author information
                http://orcid.org/0000-0002-5261-8481
                Article
                bmjopen-2017-017344
                10.1136/bmjopen-2017-017344
                5665233
                29079606
                377b3366-5c86-44e6-b8c6-605c6702286a
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                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
                : 17 April 2017
                : 15 September 2017
                : 22 September 2017
                Categories
                Epidemiology
                Research
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                Medicine
                overweight,obesity,africa,prevalence,trends,urban
                Medicine
                overweight, obesity, africa, prevalence, trends, urban

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