HIGH PREVALENCE OF OBESITY AND PHYSICAL INACTIVITY AMONG SELECTED WORKERS IN KANO STATE NIGERIA
Abstract
There is increasing burden of cardiometabolic diseases in Africa. Increasing rates of physical inactivity and obesity are partly responsible for this development. The aim of this study was to determine the prevalence of physical inactivity and obesity among selected workers in Kano State, Nigeria. In this cross sectional study of 466 workers attending a part-time degree program at Bayero University Kano, Nigeria, body weight was measured using a standard digital weighing scale, body height was measured using a portable stadiometer, circumferences (waist and hip) were measured using an inelastic measuring tape and physical inactivity using a standardized questionnaire. Data analysis was done in R statistical environment. The subjects consisted of 280 males and 186 females with respective mean ages of 37 (±8.7) and 36 (±9.6). Mean waist circumference for males and females was 87.9 (±13.4) and 86.4 (±13.2) respectively. Both males and females sit on an average of 10 hours per weekday. Almost 2/3 of both male and female subjects were physically inactive. About the same proportion of the study subjects have generalized obesity (58% of male and 66% of female subjects). More than ¾ of female subjects and 2/3 of male subjects were centrally obese using waist-to-hip ratio measure. The high prevalence rates of physical inactivity and obesity among this group of urban workers mean they are at a particularly high risk of cardiometabolic diseases and should be a priority group for public health intervention programs designed to reduce the burden of cardiovascular disease and diabetes.
References
Abdulkadir, H., Adefila, J. O., & Yusuf, R. . (2018). Analysis of spatial variation in agricultural development programmes in kano state, nigeria. Dutse Journal of Pure and Applied Sciences (DUJOPAS), 4(1), 466476.
Adeloye, D., Ige-Elegbede, J. O., Auta, A., Ale, B. M., Ezeigwe, N., Omoyele, C., Dewan, M. T., Mpazanje, R. G., Agogo, E., Alemu, W., Gadanya, M. A., Harhay, M. O., & Adebiyi, A. O. (2022). Epidemiology of physical inactivity in Nigeria: a systematic review and meta-analysis. Journal of Public Health, 44(3), 595605. https://doi.org/10.1093/pubmed/fdab147 DOI: https://doi.org/10.1093/pubmed/fdab147
Adeloye, D., Ige-Elegbede, J. O., Ezejimofor, M., Owolabi, E. O., Ezeigwe, N., Omoyele, C., Mpazanje, R. G., Dewan, M. T., Agogo, E., Gadanya, M. A., Alemu, W., Harhay, M. O., Auta, A., & Adebiyi, A. O. (2021). Estimating the prevalence of overweight and obesity in Nigeria in 2020: a systematic review and meta-analysis. Annals of Medicine, 53(1), 495507. https://doi.org/10.1080/07853890.2021.1897665 DOI: https://doi.org/10.1080/07853890.2021.1897665
Alkali, N. H., & Bello, M. R. (2020). Tertiary hospital standards in Nigeria: A review of current status. Annals of African Medical Research, 3(1). https://doi.org/10.4081/aamr.2020.108 DOI: https://doi.org/10.4081/aamr.2020.108
Bashir, M. A., Yahaya, A. I., Muhammad, M., Yusuf, A. H., & Mukhtar, I. G. (2021). Prediabetes Burden in Nigeria: A Systematic Review and Meta-Analysis. Frontiers in Public Health, 9. https://doi.org/10.3389/fpubh.2021.762429 DOI: https://doi.org/10.3389/fpubh.2021.762429
Bashir, M. A., Yahaya, A. I., Muhammad, M., Yusuf, A. H., & Mukhtar, I. G. (2022). Prevalence of central obesity in Nigeria: a systematic review and meta-analysis. Public Health, 206, 8793. https://doi.org/10.1016/j.puhe.2022.02.020 DOI: https://doi.org/10.1016/j.puhe.2022.02.020
Bayero University kano. (2024). Continuing Education. https://www.buk.edu.ng/continuing_education
Brkner, P.-C. (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software, 80(1), 128. https://doi.org/10.18637/jss.v080.i01 DOI: https://doi.org/10.18637/jss.v080.i01
Centers for Disease Control and Prevention. (2014). National Health and Nutrition Examination Survey (NHANES): Anthropometry Procedures Manual. CreateSpace Independent Publishing Platform.
Chang, A. R., Grams, M. E., Ballew, S. H., Bilo, H., Correa, A., Evans, M., Gutierrez, O. M., Hosseinpanah, F., Iseki, K., Kenealy, T., Klein, B., Kronenberg, F., Lee, B. J., Li, Y., Miura, K., Navaneethan, S. D., Roderick, P. J., Valdivielso, J. M., Visseren, F. L. J., Woodward, M. (2019). Adiposity and risk of decline in glomerular filtration rate: meta-analysis of individual participant data in a global consortium. BMJ, 364, k5301. https://doi.org/10.1136/bmj.k5301 DOI: https://doi.org/10.1136/bmj.k5301
Chooi, Y. C., Ding, C., & Magkos, F. (2019). The epidemiology of obesity. Metabolism, 92, 610. https://doi.org/10.1016/j.metabol.2018.09.005 DOI: https://doi.org/10.1016/j.metabol.2018.09.005
Deng, G., Yin, L., Liu, W., Liu, X., Xiang, Q., Qian, Z., Ma, J., Chen, H., Wang, Y., Hu, B., Li, W., & Jiang, Y. (2018). Associations of anthropometric adiposity indexes with hypertension risk. Medicine, 97(48), e13262. https://doi.org/10.1097/MD.0000000000013262 DOI: https://doi.org/10.1097/MD.0000000000013262
EPITOOLS. (2021). Epitools - Sample Size to Estimate a Proportion or Appar ... https://epitools.ausvet.com.au/oneproportion
Guthold, R., Stevens, G. A., Riley, L. M., & Bull, F. C. (2018). Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 19 million participants. The Lancet Global Health, 6(10), e1077e1086. https://doi.org/10.1016/S2214-109X(18)30357-7 DOI: https://doi.org/10.1016/S2214-109X(18)30357-7
Kim, M. S., Kim, W. J., Khera, A. V, Kim, J. Y., Yon, D. K., Lee, S. W., Shin, J. Il, & Won, H.-H. (2021). Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. European Heart Journal, 42(34), 33883403. https://doi.org/10.1093/eurheartj/ehab454 DOI: https://doi.org/10.1093/eurheartj/ehab454
Lear, S. A., Humphries, K. H., Kohli, S., Chockalingam, A., Frohlich, J. J., & Birmingham, C. L. (2007). Visceral adipose tissue accumulation differs according to ethnic background: results of the Multicultural Community Health Assessment Trial (M-CHAT). The American Journal of Clinical Nutrition, 86(2), 353359. https://doi.org/10.1093/ajcn/86.2.353 DOI: https://doi.org/10.1093/ajcn/86.2.353
Liu, X., Zhang, D., Liu, Y., Sun, X., Han, C., Wang, B., Ren, Y., Zhou, J., Zhao, Y., Shi, Y., Hu, D., & Zhang, M. (2017). DoseResponse Association Between Physical Activity and Incident Hypertension. Hypertension, 69(5), 813820. https://doi.org/10.1161/HYPERTENSIONAHA.116.08994 DOI: https://doi.org/10.1161/HYPERTENSIONAHA.116.08994
MacArthur Foundation. (2024). Bayero University, Kano Kano, Nigeria. https://www.macfound.org/grantee/bayero-university-kano-33204/#:~:text=Bayero University%2C Kano (BUK) is a federal university%2C,about 50%2C000 students currently enrolled.
Oyeyemi, A. L., & Adeyemi, O. (2013). Relationship of physical activity to cardiovascular risk factors in an urban population of Nigerian adults. Archives of Public Health, 71(1), 6. https://doi.org/10.1186/0778-7367-71-6 DOI: https://doi.org/10.1186/0778-7367-71-6
Parvathaneni, K., Surapaneni, A., Ballew, S. H., Palta, P., Rebholz, C. M., Selvin, E., Coresh, J., & Grams, M. E. (2021). Association Between Midlife Physical Activity and Incident Kidney Disease: The Atherosclerosis Risk in Communities (ARIC) Study. American Journal of Kidney Diseases, 77(1), 7481. https://doi.org/10.1053/j.ajkd.2020.07.020 DOI: https://doi.org/10.1053/j.ajkd.2020.07.020
Rockhill, B., Newman, B., & Weinberg, C. (1998). Use and misuse of population attributable fractions. American Journal of Public Health, 88(1), 1519. https://doi.org/10.2105/ajph.88.1.15 DOI: https://doi.org/10.2105/AJPH.88.1.15
Sedentary Behaviour Research Network. (2012). Letter to the Editor: Standardized use of the terms sedentary and sedentary behaviours. Applied Physiology, Nutrition, and Metabolism, 37(3), 540542. https://doi.org/10.1139/h2012-024 DOI: https://doi.org/10.1139/h2012-024
Seo, D.-C., Choe, S., & Torabi, M. R. (2017). Is waist circumference 102/88 cm better than body mass index 30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Meta-analysis. Preventive Medicine, 97, 100108. https://doi.org/10.1016/j.ypmed.2017.01.012 DOI: https://doi.org/10.1016/j.ypmed.2017.01.012
Silveira, E. A., Kliemann, N., Noll, M., Sarrafzadegan, N., & Oliveira, C. (2021). Visceral obesity and incident cancer and cardiovascular disease: An integrative review of the epidemiological evidence. Obesity Reviews, 22(1), e13088. https://doi.org/10.1111/obr.13088 DOI: https://doi.org/10.1111/obr.13088
Smith, A. D., Crippa, A., Woodcock, J., & Brage, S. (2016). Physical activity and incident type 2 diabetes mellitus: a systematic review and doseresponse meta-analysis of prospective cohort studies. Diabetologia, 59(12), 25272545. https://doi.org/10.1007/s00125-016-4079-0 DOI: https://doi.org/10.1007/s00125-016-4079-0
Stevens, J., Katz, E. G., & Huxley, R. R. (2010). Associations between gender, age and waist circumference. European Journal of Clinical Nutrition, 64(1), 615. https://doi.org/10.1038/ejcn.2009.101 DOI: https://doi.org/10.1038/ejcn.2009.101
Suk, S.-H., Sacco, R. L., Boden-Albala, B., Cheun, J. F., Pittman, J. G., Elkind, M. S., & Paik, M. C. (2003). Abdominal Obesity and Risk of Ischemic Stroke. Stroke, 34(7), 15861592. https://doi.org/10.1161/01.STR.0000075294.98582.2F DOI: https://doi.org/10.1161/01.STR.0000075294.98582.2F
Tajik, S., Mirzababaei, A., Ghaedi, E., Kord-Varkaneh, H., & Mirzaei, K. (2019). Risk of type 2 diabetes in metabolically healthy people in different categories of body mass index: an updated network meta-analysis of prospective cohort studies. Journal of Cardiovascular and Thoracic Research, 11(4), 254263. https://doi.org/10.15171/jcvtr.2019.43 DOI: https://doi.org/10.15171/jcvtr.2019.43
Tremblay, M. S., Aubert, S., Barnes, J. D., Saunders, T. J., Carson, V., Latimer-Cheung, A. E., Chastin, S. F. M., Altenburg, T. M., & Chinapaw, M. J. M. (2017). Sedentary Behavior Research Network (SBRN) Terminology Consensus Project process and outcome. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 75. https://doi.org/10.1186/s12966-017-0525-8 DOI: https://doi.org/10.1186/s12966-017-0525-8
Wahid, A., Manek, N., Nichols, M., Kelly, P., Foster, C., Webster, P., Kaur, A., Friedemann Smith, C., Wilkins, E., Rayner, M., Roberts, N., & Scarborough, P. (2016). Quantifying the Association Between Physical Activity and Cardiovascular Disease and Diabetes: A Systematic Review and MetaAnalysis. Journal of the American Heart Association, 5(9), e002495. https://doi.org/10.1161/JAHA.115.002495 DOI: https://doi.org/10.1161/JAHA.115.002495
WHO. (2000). Obesity: preventing and managing the global epidemic: report of a WHO consultation. https://apps.who.int/iris/handle/10665/42330
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag. https://ggplot2.tidyverse.org DOI: https://doi.org/10.1007/978-3-319-24277-4_9
Wong, M. C. S., Huang, J., Wang, J., Chan, P. S. F., Lok, V., Chen, X., Leung, C., Wang, H. H. X., Lao, X. Q., & Zheng, Z.-J. (2020). Global, regional and time-trend prevalence of central obesity: a systematic review and meta-analysis of 13.2 million subjects. European Journal of Epidemiology, 35(7), 673683. https://doi.org/10.1007/s10654-020-00650-3 DOI: https://doi.org/10.1007/s10654-020-00650-3
World Bank. (2021). WDI - The World by Income and Region. https://datatopics.worldbank.org/world-development-indicators/the-world-by-income-and-region.html
World Health Organization. (2008). Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation, Geneva, 8-11 December 2008. https://apps.who.int/iris/handle/10665/44583
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