ANALYSIS OF RISK FACTORS FOR OBESITY IN WOMEN AGED 15-49 YEARS IN SOUTH AFRICA (THE DHS PROGRAM 2016)
Overweight and obesity can be interpreted as abnormal fat accumulation that can cause health problems. The average BMI (Body Mass Index) in adult women has also continued to increase. This study aims to identify the relationship between age, alcohol consumption, cigarette consumption, employment status, economic status, ethnicity and area of "‹"‹residence with the incidence of obesity in women aged 15-49 years in South Africa and determine the most influential factors on obesity. This study is a quantitative study with a design cross-sectional using secondary data from The DHS Program 2016. Respondents in this study were women aged 15 - 49 years in South Africa as many as 1158 people. The dependent variable in this study is the nutritional status of obesity which is classified as obese if BMI ≥25 kg/m2. While the independent variables are age, alcohol consumption, cigarette consumption, employment status, economic status, ethnicity, and area of "‹"‹residence. Data were analyzed by chi-square and logistic regression. The results showed that the factors associated with obesity were age, employment status and economic status (p-value <0.05). The most influential factor is adult age with a range of 25 - 49 years. Therefore, there is a need for behavioral changes in adult women 25-49 years in South Africa and national monitoring evaluation of multisectoral programs for obesity prevention in South Africa.
WHO. Obesity [Internet]. World Health Organization Webpage. 2021. Available from: https://www.who.int/health-topics/obesity#tab=tab_1
CDC. About Overweight & Obesity [Internet]. Webpage of CDC. 2021. Available from: https://www.cdc.gov/obesity/about-obesity/index.html
Sa'adah N, Purnomo W. Karakteristik dan Perilaku Berisiko Pasangan Infertil di Klinik Fertilitas dan Bayi Tabung Tiara Cita Rumah Sakit Putri Surabaya. J Biometrika dan Kependud [Internet]. 2016;5(1):61–9. Available from: https://e-journal.unair.ac.id/JBK/article/view/5796
CDC. Healthy Weight, Nutrition, and Physical Activity [Internet]. Centers for Disease Control and Prevention Webpage. 2020. Available from: https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html
Cois A, Day C. Obesity Trends and Risk Factors in The South African Adult Population. BMC Obes [Internet]. 2015;2(42):1–10. Available from: http://dx.doi.org/10.1186/s40608-015-0072-2
WHO. Obesity and Overweight [Internet]. World Health Organization Webpage. 2021. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
Ritchie H, Roser M. Obesity [Internet]. OurWorldInData.org. 2017. Available from: https://ourworldindata.org/obesity
Hill JO, Wyatt HR, Peters JC. Energy Balance and Obesity. Circulation [Internet]. 2012;126(1):126–32. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3401553/pdf/nihms-390766.pdf
Hruby A, Frank. The Epidemiology of Obesity: A Big Picture. Pharmacoeconomics [Internet]. 2015;33(7):673–89. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4859313/pdf/nihms-780628.pdf
Kemp C. Obesity Still Increasing in Some Age Groups. American Academy of Pediatrics News [Internet]. 2018 Feb 26;1–2. Available from: https://www.aappublications.org/news/2018/02/26/obesity022618
Contu L, Hawkes CA. A Review of The Impact of Maternal Obesity on The Cognitive Function and Mental Health of The Offspring. Int J Mol Sci [Internet]. 2017;18(1093):1–11. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5455002/pdf/ijms-18-01093.pdf
Victoria State Government. Obesity and Hormones. In: Better Health Channel [Internet]. Department of Health, State Government of Victoria, Australia; 2016. p. 1–5. Available from: https://www.betterhealth.vic.gov.au/health/HealthyLiving/obesity-and-hormones
Suryadinata RV, Wirjatmadi B, Adriani M, Lorensia A. Effect of Age and Weight on Physical Activity. J Public health Res [Internet]. 2020;9(1840):187–90. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376490/pdf/jphr-9-2-1840.pdf
Brum MCB, Filho FF., Schnorr CC, Bertoletti OA, Bottega GB, Rodrigues T da C. Night Shift Work, Short Sleep and Obesity. Diabetol Metab Syndr [Internet]. 2020;12(13):1–9. Available from: https://dmsjournal.biomedcentral.com/track/pdf/10.1186/s13098-020-0524-9.pdf
Dinsa G., Goryakin Y, Fumagalli E, Suhrcke M. Obesity and Socioeconomic Status in Developing Countries: a Systematic Review. Obes Rev [Internet]. 2012;13(11):pp.1067-1079. Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1467-789X.2012.01017.x
Lee H, Andrew M, Gebremariam A, Lumeng JC, Lee JM. Longitudinal Associations Between Poverty and Obesity From Birth Through Adolescence. Am J Public Health [Internet]. 2014;104(5):e70–6. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3987582/pdf/AJPH.2013.301806.pdf
Marques A, Peralta M, Naia A, Loureiro N, Gaspar de Matos M. Prevalence of adult overweight and obesity in 20 European countries, 2014. Eur J Public Health [Internet]. 2017;28(2):295–300. Available from: https://academic.oup.com/eurpub/article/28/2/295/4210290?login=true
Shelton NJ, Knott CS. Association Between Alcohol Calorie Intake and Overweight and Obesity in English Adults. Am J Public Health [Internet]. 2014;104(4):629–31. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4025698/pdf/AJPH.2013.301643.pdf
Courtemanche C, Tchernis R, Ukert B. The Effect of Smoking on Obesity: Evidence From A Randomized Trial [Internet]. Cambridge; 2016. (112). Report No.: 21937. Available from: http://www.nber.org/papers/w21937
Sharma T, Manoharan B, Langlois C, Morassut RE, Meyre D. The Effect of Race/Ethnicity on Obesity Traits in First Year University Students from Canada: The GENEiUS study. PLoS One [Internet]. 2020;15(11):1–6. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242714
Wen M, Fan JX, Jones LK, Wan N. Rural–Urban Disparities in Obesity Prevalence Among Working Age Adults in the United States: Exploring the Mechanisms. Am J Heal Promot [Internet]. 2017;32(2):400–8. Available from: https://journals.sagepub.com/doi/pdf/10.1177/0890117116689488
Nisak BA. Determinants of Unmet Needs in Married Women in Indonesia (Indonesian DHS Analysis 2017). J Biometrika dan Kependud [Internet]. 2021;10(1):1–10. Available from: https://e-journal.unair.ac.id/JBK/article/view/17377
Jaacks LM, Vandevijvere S, Pan A, McGowan CJ, Wallace C, Imamura F, et al. The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol [Internet]. 2019;7(3):231–40. Available from: https://pubmed.ncbi.nlm.nih.gov/30704950/
Juhaidah L. The Correlation of Mother's Age at Marriage and Mother's Work Status with Exclusive Breastdfeeding. J Biometrika dan Kependud [Internet]. 2021;10(2):113–21. Available from: https://e-journal.unair.ac.id/JBK/article/view/19755
Fadhilah AR, Notobroto HB. Analisis Regresi Logistik Biner pada Kejadian Trasient Ischemic Attack (Tia) di RSUD Dr. Soetomo Surabaya. J Biometrika dan Kependud [Internet]. 2016;5(2):157–65. Available from: https://e-journal.unair.ac.id/JBK/article/view/5836/3742
Department Health Republic of South Africa. National Department of Health : Annual Report 2018/2019 [Internet]. South Africa; 2019. Available from: http://www.health.gov.za/wp-content/uploads/2020/11/annual-report-4web_compressed_1.pdf
Puoane T, Steyn K, Bradshaw D, Laubscher R, Fourie J, Lambert V, et al. Obesity in South Africa: The South African Demographic and Health Survey. Obes Res [Internet]. 2002;10(10):1–11. Available from: https://www.researchgate.net/publication/11082774_Obesity_in_South_Africa_The_South_African_Demographic_and_Health_Survey
Mosha D, Paulo HA, Mwanyika-Sando M, Mboya IB, Madzorera I, Leyna GH, et al. Risk Factors for Overweight and Obesity Among Women of Reproductive Age in Dar es Salaam, Tanzania. BMC Nutr [Internet]. 2021;7(37):1–10. Available from: https://bmcnutr.biomedcentral.com/articles/10.1186/s40795-021-00445-z
Song N, Liu F, Han M, Zhao Q, Zhao Q, Zhai H, et al. Prevalence of Overweight and Obesity and Associated Risk Factors Among Adult Residents of Northwest China: a Cross Sectional Study. BMJ Open [Internet]. 2019;9(9):1–9. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773337/
Mkuu RS, Epnere K, Chowdhury MAB. Prevalence and Prodictors of Overweight and Obesity Among Kenyan Women. Prev Chronic Dis [Internet]. 2018;15(E44):1–10. Available from: https://www.cdc.gov/pcd/issues/2018/17_0401.htm
Eum M-J, Jung H-S. Association between Occupational Characteristics and Overweight and Obesity among Working Korean Women: The 2010–2015 Korea National Health and Nutrition Examination Survey. Int J Environ Res Public Health [Internet]. 2020;17(1585):1–13. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7084197/
Tecco CD, Fontana L, Adamo G, Petyx M, Lavicoli S. Gender differences and occupational factors for the risk of obesity in the Italian working population. BMC Public Health [Internet]. 2020;20(706):1–14. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08817-z
Jang T-W, Kim H-R, Lee H-E, Myong J-P, Koo J-W. Long work hours and obesity in Korean adult workers. J Occup Health [Internet]. 2014;55(5):359–66. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1539/joh.13-0043-OA
Ko GTC, Chan JCN, Chan AWY, Wong PTS, Hui SSC, Tong SDY. Association between sleeping hours, working hours and obesity in Hong Kong Chinese: the ‘better health for better Hong Kong' health promotion campaign. Int J Obes [Internet]. 2007;31(01):254–60. Available from: https://www.nature.com/articles/0803389?message=remove&free=2#citeas
Houle B. How Obesity Relates to Socioeconomic Status [Internet]. Population Reference Bureu. Washington; 2013. Available from: https://www.prb.org/resources/how-obesity-relates-to-socioeconomic-status/
Department of Health Western Australia. Overweight and Obesity in Adults [Internet]. Goverment of Western Australia Department of Health Webpage. 2021. Available from: https://www.healthywa.wa.gov.au/Articles/N_R/Overweight-and-obesity-in-adults
Kamphuis CB, De Bekker-Grob EW, Lenthe FJ van. Factors Affecting Food Choices of Older Adults From High and Low Socioeconomic Groups: a Discrete Choice Experiment. Am J Clin Nutr [Internet]. 2015;101(4):768–74. Available from: https://academic.oup.com/ajcn/article/101/4/768/4564502
Dewi SP, Othman M Bin. Penerapan Klaster K-MEANS Untuk Pengelompokan Kawasan Kesehatan Lingkungan Jawa Timur Pada Tahun 2017. J Biometrika dan Kependud [Internet]. 2020;9(1):1–9. Available from: https://e-journal.unair.ac.id/JBK/article/view/13152
Copyright (c) 2023 Jurnal Biometrika dan Kependudukan
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright ©2022 Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
1. Copyright of all journal manuscripts is held by the Jurnal Biometrika dan Kependudukan.
2. Formal legal provisions to access digital articles of the electronic journals are subject to the provision of the Creative Commons Attribution-ShareAlike license (CC BY-NC-SA), which means that Jurnal Kesehatan Biometrika dan Kependudukan to keep, transfer media/format, manage in the form of databases, maintain, and publish articles.
3. Published manuscripts both printed and electronic are open access for educational, research, and library purposes. Additionally, the editorial board is not responsible for any violations of copyright law.