Socioeconomic Status, Water, Sanitation, Hygiene, and Economic Cost of Childhood Diarrheal Diseases in Uganda

• Main Author: Nahalamba, Sarah Birungi
• Format: Others
• Language: en
• Published: ScholarWorks 2019
• Subjects: childhood; Cost; Diarrhea; household; Socioeconomic; WASH; Medicine and Health Sciences
• Online Access: https://scholarworks.waldenu.edu/dissertations/7317; https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=8594&context=dissertations

Worldwide, diarrhea is the second leading cause of death in children aged under 5, yet it is both preventable and treatable. Several studies have established the effects of exposure to inadequate water, sanitation, and hygiene (WASH) on diarrhea prevalence, but little was known on how the interactions of socioeconomic status and WASH influence the economic cost of treatment of diarrhea. This retrospective cross-sectional survey study was focused on assessing the correlation between socioeconomic status, WASH, and household cost of treatment of diarrhea among children aged under 5 in Uganda using the multiple exposure-multiple effect model. Secondary data from the 2015/16 Uganda National Panel Survey were used. At bivariate level of analysis, 5 of 6 independent variables (education level of mother, household expenditure, residence type, source of drinking water, and type of toilet facility) had statistically significant associations with household cost of treatment of diarrhea (p value < .05). The multivariate-hierarchical multiple linear regression indicated that only 3 of the 6 variables significantly predicated household cost of treatment of diarrhea. These were highest education level of mother (p = 0.001), source of drinking water (p = 0.022), and type of toilet facility (p = 0.012). At p value < .05, about 67% of the variation in the cost of treatment was explained by the independent variables. Households with a higher socioeconomic status incurred higher costs of treatment, although those with a lower status experienced the highest prevalence rates. Therefore, policy makers and practitioners could use these findings to employ multiple interventions to address the disease burden and cause behavior change.