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Prevalence and Factors Associated with Overweight And Darebo et al. BMC Obesity (2019) 6:8 https://doi.org/10.1186/s40608-019-0227-7 RESEARCHARTICLE Open Access Prevalence and factors associated with overweight and obesity among adults in Hawassa city, southern Ethiopia: a community based cross-sectional study Teshale Darebo1, Addisalem Mesfin2* and Samson Gebremedhin3 Abstract Background: In Ethiopia, limited information is available about the epidemiology of over-nutrition. This study assessed the prevalence of, and factors associated with overweight and obesity among adults in Hawassa city, Southern Ethiopia. Methods: A community-based cross-sectional survey was conducted in August 2015 in the city. A total of 531 adults 18–64 years of age were selected using multistage sampling approach. Interviewer administered qualitative food frequency questionnaire was used to assess the consumption pattern of twelve food groups. The level of physical exercise was measured via the General Physical Activity Questionnaire (GPAQ). Based on anthropometric measurements, Body Mass Index (BMI) was computed and overweight including obesity (BMI of 25 or above) was defined. For identifying predictors of overweight and obesity, multivariable binary logistic regression model was fitted and the outputs are presented using Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CI). Results: The prevalence of overweight including obesity was 28.2% (95% CI: 24.2–32.2). Significant proportions of adults had moderate (37.6%) or low (2.6%) physical activity level. As compared to men, women had 2.56 (95% CI: 1.85–4.76) times increased odds of overweight/obesity. With reference to adults 18–24 years of age, the odds were three times higher among adults 45–54 (3.06, 95% CI: 1.29–7.20) and 55–64 (2.88, 95% CI: 1.06–7.84) years. Those from the highest incometercilewere3.16times(95%CI:1.88–5.30) more likely to be overweight/obese as compared to adults from the lowest tercile. Having moderate (3.10, 95% CI: 1.72–5.60) or low (4.80 95% CI: 2.50–9.23) physical activity was also significantly associated with the outcome. Further, daily intake of alcohol and, frequent consumption of sweets, meat and eggs were associated with overweight/obesity. Conversely, no significant associations were evident for meal frequency, practices of skipping breakfast, behavior of eating away from home and frequency of consumption of fast foods, fruits and vegetables. Conclusions: Prompting active lifestyle, limiting intakes of sweets, advocating optimum consumption of alcohol and calorie dense animal source foods, especially amongst the better-off segment of the population, may reduce the magnitude of over-nutrition. Keywords: Overweight and obesity, Physical exercise, Body mass index, Risk factors, Hawassa, Ethiopia * Correspondence: [email protected] 2School of Nutrition, Food Science and Technology, Hawassa University, Hawassa, Ethiopia Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This 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. Darebo et al. BMC Obesity (2019) 6:8 Page 2 of 10 Background practical significance, may vary from one setting to an- Globally, each year non-communicable diseases (NCDs) other. Hence this study was conducted to assess the cause 40 million deaths and loss of 1.5 million prevalence of, and factors associated with overweight disability-adjusted life years (DALY) [1, 2]. Cardiovascular and obesity among adult (18–64 years) in Hawassa city, diseases, cancers, chronic respiratory disease and diabetes Southern Ethiopia. mellitus in combination cause more than three-fourth of all global deaths secondary to NCDs. In absolute numbers, Study setting the four medical conditions alone annually result in 32 Hawassa is the capital city of Southern Nations Nation- million deaths throughout the world [1]. In the last two alities Peoples Region (SNNPR), located 273 km south of decades, the epidemiological significance of NCDs has Addis Ababa, the capital of Ethiopia. Projection based been rapidly growing both in developed and developing on the 2007 national census indicates, as of 2015 the city countries. Globally between 2000 and 2015, the total adult had a total population of 319,023, of whom 51.9% were mortality attributable to NCDs has increased by 16% [3]. adults18–64 years of age [9]. Non-communicable diseases have wide-range of genetic, environmental and behavioral determinants. However, the Study design and study participants rapid epidemiological shift observed in the last few decades This community-based cross-sectional study was con- is largely attributable to changes in few, known and modifi- ducted in 2015. Adults 18 years of age or older who were able risk factors. These factors are tobacco and alcohol use, the permanent residents of Hawassa city were eligible physical inactivity, unhealthy diets, raised blood pressure, for the study. Pregnant women, women in the first 6 overweight/obesity, hyperglycemia and hyperlipidemia [4]. months after giving birth and adults with obvious spinal Most of the risk factors function in complex and synergistic deformity were excluded from the study. fashion and, tend to co-occur together [2, 4]. Overweight including obesity refer to abnormal or ex- Sample size cessive accumulation of fat that may result in health im- The sample size for the study was determined using single pairment and its usually measured based on high Body population proportion formula. The formula estimates the Mass Index (BMI) [1]. There is convincing evidence that minimum sample size required for determining a propor- overweight and obesity increase the risk of several types tion in a source population as a function of desired level of cancers and elevate blood pressure, cholesterol and of significance, margin of error and the expected level of insulin resistance [4]. Each year worldwide, 2.8 million the proportion. Specifications made during the computa- deaths and 2.3% of the global DALY loss are attributed tion were: 21% expected prevalence of overweight and to the consequences of overweight or obesity [5]. In the obesity [10], 95% confidence level, 5% margin of error, last few decades, a substantial rise in the prevalence of 10% compensation for possible non-response and design overweight and obesity has been observed both in devel- effect of 2. The final calculated sample size was 565. The oped and developing countries [6, 7]. According to the adequacy of the sample size for determining the factors World Health Organization (WHO), in 2014 globally ap- associated with overweight and obesity was assessed using proximately two billion adults – 39% of women and a post-hoc power calculation. men – were overweight or obese [7, 8]. Between 1975 and 2016, the combined prevalence almost doubled from Sampling technique the baseline level of 22% [7]. Study participants were selected using multistage cluster According to the estimate of WHO, in 2014 1.2% of sampling technique. Initially, 6 kebeles (the smallest ad- men and 6.0% of females were either overweight or ministrative unit in Ethiopia) were randomly selected obese in Ethiopia [7]. Between 1997 and 2016, the com- out of the existing 32 kebeles in the city, and the total bined prevalence in the country grew considerably from sample size was distributed to the selected kebeles pro- 2.6 to 6.9% in females and, from 0.6 to 1.9% in males [7]. portional to their population size. Then, using existing Presumably, in urban areas of Ethiopia including administrative records as sampling frame, households Hawassa city, the prevalence is growing. Yet, epidemio- were selected via systematic random sampling approach. logical evidence on the underlying risk factors is scarce. From each of the selected household, an adult aged 18– The recent Ethiopian Demographic and Health Survey 64 years was drawn. When multiple adults were available (DHS) determined the national magnitude of overweight within the household, an adult was chosen at random and obesity both in urban and rural areas. However, lim- from the same household. Conversely, when no adult ited information is provided on the underlying drivers of was available, one was selected from the immediate the problem. While the general risk factors for over- neighboring household. If sampled adult was absent weight and obesity are known; the magnitude and from their home on the data collection day, another visit strength of association of the factors, and hence their was arranged. Darebo et al. BMC Obesity (2019) 6:8 Page 3 of 10 Data collection These were: (1) age, (2) gender, (3) educational status, Data were collected by trained data collectors and super- (4) type of occupation, (5) household income terciles visors using structured and pretested questionnaire. The (low, middle, high), (6) ethnicity, (7) religion, (8) marital questionnaire was prepared in English, and finalized and status, (9) family size, (10) awareness about chronic dis- administered in Amharic language which is widely eases, (11) level of physical activity, (12) behavior of spoken in the city. Questions pertaining to socio-demo- skipping breakfast, (13) frequency of consumption away graphic characteristics were directly adopted from the from home, (14) frequency of consumption of fast foods, standard Demographic and Health Survey (DHS) ques- (15) frequency of alcohol intake, and consumption pat- tionnaire [10]. On average, each interview lasts for 40 tern of the 12 food groups listed earlier. Consequently, min. the frequencies of consumption of the twelve food The frequency of consumption of twelve food groups groups were treated as twelve different variables.
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