A F Fagbamigbe1,2,3, F F Oyinlola4, O M Morakinyo5, A S Adebowale6, O S Fagbamigbe7,8, A O Uthman9. 1. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria. franstel74@yahoo.com. 2. Division of Health Sciences, Populations, Evidence and Technologies Group, Warwick Medical School, University of Warwick, Coventry, UK. franstel74@yahoo.com. 3. Division of Population and Behavioural Studies, School of Medicine, University of St Andrews, Fife, UK. franstel74@yahoo.com. 4. Department of Demography and Social Statistics, Faculty of Social Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria. 5. Department of Environmental Health Sciences, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria. 6. Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria. 7. Techmodia, London, West Sussex, UK. 8. Portsmouth Business School, Faculty of Business and Law, University of Portsmouth, Portsmouth, UK. 9. Division of Health Sciences, Populations, Evidence and Technologies Group, Warwick Medical School, University of Warwick, Coventry, UK.
Abstract
BACKGROUND: Diarrhoea poses serious health problems among under-five children (U5C) in Low-and Medium-Income Countries (LMIC) with a higher prevalence in rural areas. A gap exists in knowledge on factors driving rural-non-rural inequalities in diarrhoea development among U5C in LMIC. This study investigates the magnitude of rural-non-rural inequalities in diarrhoea and the roles of individual-level and neighbourhood-level factors in explaining these inequalities. METHODS: Data of 796,150 U5C, from 63,378 neighbourhoods across 57 LMIC from the most recent Demographic and Health Survey (2010-2018) was analysed. The outcome variable was the recent experience of diarrhoea while independent variables consist of the individual- and neighbourhood-level factors. Data were analysed using multivariable Fairlie decomposition at p < 0.05 in Stata Version 16 while visualization was implemented in R Statistical Package. RESULTS: Two-thirds (68.0%) of the children are from rural areas. The overall prevalence of diarrhoea was 14.2, 14.6% vs 13.4% among rural and non-rural children respectively (p < 0.001). From the analysis, the following 20 countries showed a statistically significant pro-rural inequalities with higher odds of diarrhoea in rural areas than in nonrural areas at 5% alpha level: Albania (OR = 1.769; p = 0.001), Benin (OR = 1.209; p = 0.002), Burundi (OR = 1.399; p < 0.001), Cambodia (OR = 1.201; p < 0.031), Cameroon (OR = 1.377; p < 0.001), Comoros (OR = 1.266; p = 0.029), Egypt (OR = 1.331; p < 0.001), Honduras (OR = 1.127; p = 0.027), India (OR = 1.059; p < 0.001), Indonesia (OR = 1.219; p < 0.001), Liberia (OR = 1.158; p = 0.017), Mali (OR = 1.240; p = 0.001), Myanmar (OR = 1.422; p = 0.004), Namibia (OR = 1.451; p < 0.001), Nigeria (OR = 1.492; p < 0.001), Rwanda (OR = 1.261; p = 0.010), South Africa (OR = 1.420; p = 0.002), Togo (OR = 1.729; p < 0.001), Uganda (OR = 1.214; p < 0.001), and Yemen (OR = 1.249; p < 0.001); and pro-non-rural inequalities in 9 countries. Variations exist in factors associated with pro-rural inequalities across the 20 countries. Overall main contributors to pro-rural inequality were neighbourhood socioeconomic status, household wealth status, media access, toilet types, maternal age and education. CONCLUSIONS: The gaps in the odds of diarrhoea among rural children than nonrural children were explained by individual-level and neighbourhood-level factors. Sustainable intervention measures that are tailored to country-specific needs could offer a better approach to closing rural-non-rural gaps in having diarrhoea among U5C in LMIC.
BACKGROUND: Diarrhoea poses serious health problems among under-five children (U5C) in Low-and Medium-Income Countries (LMIC) with a higher prevalence in rural areas. A gap exists in knowledge on factors driving rural-non-rural inequalities in diarrhoea development among U5C in LMIC. This study investigates the magnitude of rural-non-rural inequalities in diarrhoea and the roles of individual-level and neighbourhood-level factors in explaining these inequalities. METHODS: Data of 796,150 U5C, from 63,378 neighbourhoods across 57 LMIC from the most recent Demographic and Health Survey (2010-2018) was analysed. The outcome variable was the recent experience of diarrhoea while independent variables consist of the individual- and neighbourhood-level factors. Data were analysed using multivariable Fairlie decomposition at p < 0.05 in Stata Version 16 while visualization was implemented in R Statistical Package. RESULTS: Two-thirds (68.0%) of the children are from rural areas. The overall prevalence of diarrhoea was 14.2, 14.6% vs 13.4% among rural and non-rural children respectively (p < 0.001). From the analysis, the following 20 countries showed a statistically significant pro-rural inequalities with higher odds of diarrhoea in rural areas than in nonrural areas at 5% alpha level: Albania (OR = 1.769; p = 0.001), Benin (OR = 1.209; p = 0.002), Burundi (OR = 1.399; p < 0.001), Cambodia (OR = 1.201; p < 0.031), Cameroon (OR = 1.377; p < 0.001), Comoros (OR = 1.266; p = 0.029), Egypt (OR = 1.331; p < 0.001), Honduras (OR = 1.127; p = 0.027), India (OR = 1.059; p < 0.001), Indonesia (OR = 1.219; p < 0.001), Liberia (OR = 1.158; p = 0.017), Mali (OR = 1.240; p = 0.001), Myanmar (OR = 1.422; p = 0.004), Namibia (OR = 1.451; p < 0.001), Nigeria (OR = 1.492; p < 0.001), Rwanda (OR = 1.261; p = 0.010), South Africa (OR = 1.420; p = 0.002), Togo (OR = 1.729; p < 0.001), Uganda (OR = 1.214; p < 0.001), and Yemen (OR = 1.249; p < 0.001); and pro-non-rural inequalities in 9 countries. Variations exist in factors associated with pro-rural inequalities across the 20 countries. Overall main contributors to pro-rural inequality were neighbourhood socioeconomic status, household wealth status, media access, toilet types, maternal age and education. CONCLUSIONS: The gaps in the odds of diarrhoea among rural children than nonrural children were explained by individual-level and neighbourhood-level factors. Sustainable intervention measures that are tailored to country-specific needs could offer a better approach to closing rural-non-rural gaps in having diarrhoea among U5C in LMIC.
Authors: Abdur Razzaque Sarker; Marufa Sultana; Rashidul Alam Mahumud; Nausad Ali; Tanvir M Huda; M Salim Uzzaman; Sabbir Haider; Hafizur Rahman; Ziaul Islam; Jahangir A M Khan; Robert Van Der Meer; Alec Morton Journal: Glob Health Res Policy Date: 2018-01-05
Authors: Ruixue Li; Yingsi Lai; Chenyang Feng; Rubee Dev; Yijing Wang; Yuantao Hao Journal: Int J Environ Res Public Health Date: 2020-03-23 Impact factor: 3.390
Authors: Ayed A Shati; Shamsun N Khalil; Khalid A Asiri; Abdulaziz Ahmed Alshehri; Yazeed A Deajim; Mohammad S Al-Amer; Hassan J Alshehri; Abdulaziz Abdullah Alshehri; Fahad S Alqahtani Journal: Int J Environ Res Public Health Date: 2020-01-22 Impact factor: 3.390
Authors: Adeniyi Francis Fagbamigbe; Folashayo Ikenna Peter Adeniji; Oyewale Mayowa Morakinyo Journal: BMC Public Health Date: 2022-04-15 Impact factor: 4.135