OBJECTIVES: As in many low-income and middle-income countries, out-of-pocket (OOP) payments by patients or their families are a key healthcare financing mechanism in Bangladesh that leads to economic burdens for households. The objective of this study was to identify whether and to what extent socioeconomic, demographic, and behavioral factors of the population had an impact on OOP expenditures in Bangladesh. METHODS: A total of 12 400 patients who had paid to receive any type of healthcare services within the previous 30 days were analyzed from the Bangladesh Household Income and Expenditure Survey data, 2010. We employed regression analysis for identify factors influencing OOP health expenditures using the ordinary least square method. RESULTS: The mean total OOP healthcare expenditures was US dollar (USD) 27.66; while, the cost of medicines (USD 16.98) was the highest cost driver (61% of total OOP healthcare expenditure). In addition, this study identified age, sex, marital status, place of residence, and family wealth as significant factors associated with higher OOP healthcare expenditures. In contrary, unemployment and not receiving financial social benefits were inversely associated with OOP expenditures. CONCLUSIONS: The findings of this study can help decision-makers by clarifying the determinants of OOP, discussing the mechanisms driving these determinants, and there by underscoring the need to develop policy options for building stronger financial protection mechanisms. The government should consider devoting more resources to providing free or subsidized care. In parallel with government action, the development of other prudential and sustainable risk-pooling mechanisms may help attract enthusiastic subscribers to community-based health insurance schemes.
Bangladesh* ; Delivery of Health Care* ; Family Characteristics ; Health Expenditures* ; Healthcare Financing ; Humans ; Insurance, Health ; Marital Status ; Methods ; Unemployment

OBJECTIVES: Low birth weight (LBW) is a major public health concern, especially in developing countries, and is frequently related to child morbidity and mortality. This study aimed to identify key determinants that influence the prevalence of LBW in selected developing countries. METHODS: Secondary data analysis was conducted using 10 recent Demography and Health Surveys from developing countries based on the availability of the required information for the years 2010 to 2013. Associations of demographic, socioeconomic, community-based, and individual factors of the mother with LBW in infants were evaluated using multivariate logistic regression analysis. RESULTS: The overall prevalence of LBW in the study countries was 15.9% (range, 9.0 to 35.1%). The following factors were shown to have a significant association with the risk of having an LBW infant in developing countries: maternal age of 35 to 49 years (adjusted odds ratio [aOR], 1.7; 95% confidence interval [CI], 1.2 to 3.1; p<0.01), inadequate antenatal care (ANC) (aOR, 1.7; 95% CI, 1.1 to 2.8; p<0.01), illiteracy (aOR, 1.5; 95% CI, 1.1 to 2.7; p<0.001), delayed conception (aOR, 1.8; 95% CI, 1.4 to 2.5; p<0.001), low body mass index (aOR, 1.6; 95% CI, 1.2 to 2.1; p<0.001) and being in the poorest socioeconomic stratum (aOR, 1.4; 95% CI, 1.1 to 1.8; p<0.001). CONCLUSIONS: This study demonstrated that delayed conception, advanced maternal age, and inadequate ANC visits had independent effects on the prevalence of LBW. Strategies should be implemented based on these findings with the goal of developing policy options for improving the overall maternal health status in developing countries.
Body Mass Index ; Child ; Demography ; Developing Countries* ; Fertilization ; Global Health ; Health Surveys ; Humans ; Infant ; Infant, Low Birth Weight* ; Infant, Newborn ; Literacy ; Logistic Models ; Maternal Age ; Maternal Health ; Mortality ; Mothers ; Odds Ratio ; Prevalence ; Public Health ; Statistics as Topic

Objective: The purpose of this study was to investigate the distribution of chronic illness and associated disability, out-of-pocket payment (OOPP), and other related factors using survey data from Bangladesh. Methods: This study analyzed Bangladesh Household Income and Expenditure Survey data that include socio-economic and demographic data, such as consumption, expenditures, and assets, along with information regarding chronic illness and disability. Multiple linear regression models were used to identify factors significantly associated with OOPP. Furthermore, a binary Logistic regression model was employed to assess the association of the explanatory variables with disability status. Results: A higher prevalence of chronic illness was found for those with chronic gastritis (18.70%), and 41.92%of the population had at least one side disability. The average OOPP healthcare expenditure for chronic illness was estimated to be US$7.59. Higher OOPP was found among the upper 2 wealth quintiles. Overall OOPP health expenditure was significantly higher among individuals with an associated disability (P<0.001). The likelihood of having an associated disability was higher among those individuals with a lower education level (OR=2.36, 95%CI:1.95-4.06), those who not earning an income (OR=2.85, 95%CI:2.53-3.21), those who did not seek care (OR=1.73, 95%CI:1.57-1.90), those who sought care from a pharmacy (OR=8.91, 95%CI:7.38-10.74), and those in the lowest wealth quintile (OR=7.21, 95%CI:6.41-8.12). Conclusions: The high OOPP illustrates the necessity of financial risk protection for the population at low socio-economic status. Therefore, we recommend that the government strengthen the healthcare system with appropriate support directed to the rural and elderly populations.

Objective: The purpose of this study was to investigate the distribution of chronic illness and associated disability, out-of-pocket payment (OOPP), and other related factors using survey data from Bangladesh. Methods: This study analyzed Bangladesh Household Income and Expenditure Survey data that include socio-economic and demographic data, such as consumption, expenditures, and assets, along with information regarding chronic illness and disability. Multiple linear regression models were used to identify factors significantly associated with OOPP. Furthermore, a binary Logistic regression model was employed to assess the association of the explanatory variables with disability status. Results: A higher prevalence of chronic illness was found for those with chronic gastritis (18.70%), and 41.92%of the population had at least one side disability. The average OOPP healthcare expenditure for chronic illness was estimated to be US$7.59. Higher OOPP was found among the upper 2 wealth quintiles. Overall OOPP health expenditure was significantly higher among individuals with an associated disability (P<0.001). The likelihood of having an associated disability was higher among those individuals with a lower education level (OR=2.36, 95%CI:1.95-4.06), those who not earning an income (OR=2.85, 95%CI:2.53-3.21), those who did not seek care (OR=1.73, 95%CI:1.57-1.90), those who sought care from a pharmacy (OR=8.91, 95%CI:7.38-10.74), and those in the lowest wealth quintile (OR=7.21, 95%CI:6.41-8.12). Conclusions: The high OOPP illustrates the necessity of financial risk protection for the population at low socio-economic status. Therefore, we recommend that the government strengthen the healthcare system with appropriate support directed to the rural and elderly populations.