Inadequate water, sanitation and hygiene (WASH) represent an important health burden

Inadequate water, sanitation and hygiene (WASH) represent an important health burden in the Philippines. development of effective and appropriate interventions. unsanitary such as disposing faeces in rivers according to 41294-56-8 manufacture WHO/UNICEF [26]). All variables shown in Table 1 were examined for collinearity; for any two showing a Spearmans correlation coefficient of >0.6 one variable was excluded. Table 1 Risk Factors according to diarrhoea occurrence during two weeks preceding the survey (= 3443 children). The impact of all explanatory variables was assessed using univariable logistic regression; interactions between selected variables were also explored. Subsequently, a multivariable logistic regression model 41294-56-8 manufacture was applied to examine how the WASH complex impacted diarrhoea changes, as one increasingly adjusts for confounders and competing risk factors. We entered each pre-defined set of covariates stepwise, starting with a simple model containing the WASH complex (model 1: water source, distance to water source, sanitation, stool disposal), then adjusting for non-modifiable characteristics (model 2: child age, sex, twin, region), susceptibility to diarrheal diseases based on a childs nutritional and immune status (model 3: iron and vitamin A supplementation, intestinal parasite medication, breastfeeding, vaccination, including an interaction term for vaccination and child age) and socio-economic characteristics (model 4: household wealth, maternal characteristics, religion). Following ODonnell [30]. The approach sets out to identify meta-themes across the findings from different methods, while specifically looking at agreement, partial agreement, silence, or dissonance between findings from different components [31]. To do so, a convergence FRP coding matrix was created, contrasting findings from the qualitative and quantitative components while specifically focusing on inter-method discrepancies. Integrated findings were presented following the structure of the quantitative analysis. 2.4. Ethic Statement For this study, ethical approval was not required sinceexcept for ageno personal data were gathered. 3. Results 3.1. Quantitative Component This section is concerned with the quantitative impact of multiple risk factors of childhood diarrhoea in the Philippines. While most variables showed a low level of collinearity; maternal and paternal education and age were highly correlated with Spearmans correlation coefficients of 0.61 and 0.76 respectively. Consequently; paternal education was not considered in multivariable analyses. Table 1 depicts the distribution of all risk factors with respect to diarrhoea 41294-56-8 manufacture status. While type of water source and distance to 41294-56-8 manufacture water source do not show statistical significance in any of the models, overall, the multivariable logistic regression analyses suggest that unimproved sanitation facilities and unsanitary stool disposal are relevant predictors of diarrhoeal disease risk. In the comprehensive model, however, these two WASH predictors also lose statistical significance. All results are shown in Table 2. Table 2 Effect of WASH complex and other risk factors on childhood diarrhoea: WASH complex (Model 1) and adjustments for non-modifiable factors (Model 2), susceptibility (Model 3) and socioeconomic characteristics (Model 4). In the first model, improved (reference group) as well as unimproved sanitation (1.77, 95% CI 1.14C2.76) facilities were statistically significantly associated with diarrhoea risk, as well as unsanitary disposal of childrens stool (OR 1.54, 95% CI 1.23C1.94). Contrary to expectations, the trend in the ORs for water source suggests that unimproved sources of drinking water as well as surface water may be protective against diarrhoea. With increasing adjustments for non-modifiable characteristics (model 2), susceptibility (model 3) and socio-economic characteristics (model 4), the effect of unsanitary stool disposal becomes non-significant in models 2, 3 and 4. Improved and unimproved sanitation facilities remain statistically significant in models 2 (unimproved, OR 1.98, 95% CI 1.23C3.18) and 3 (unimproved, OR 2.01, 95% CI 1.24C3.24). Distance to water source exceeding 5 minutes from a participants home were also associated with increased diarrhoeal risk in models 2 (OR 1.43, 95% CI 1.03C2.00) and 3 (OR 1.40, 95% CI 1.00C1.96). The comprehensive model (model 4) revealed two variables as predictive of diarrhoea: region and vaccination index (VI); the interaction between VI.