which interpolated EC values for each cluster location to get groundwater salinity data for each of the BDHS clusters were extracted. Groundwater arsenic concentration and groundwater depth point data values were obtained through the same source and processed by the same interpolation technique.

The geographical distribution of all BDHS clusters from 2000 to 2014 and its categorical salinity level are shown in Figure 1. There are no official guidelines for drinking water in Bangladesh or worldwide considering the human health perspective. Hence the water salinity categories defined by FAO were used. The level of drinking water salinity is color marked at each clusters’ geo-location according to the classification by the Food and Agriculture Organization (FAO) of the United Nations for irrigation water: freshwater (EC<0.7 mS/cm), mild-salinity (EC>=0.7 and <2 mS/cm), moderate-salinity (EC>=2 and <10 mS/cm), and severe-salinity (EC>=10 mS/cm). Salinity is clearly higher in the coastal regions than inland. Barisal division has the highest number of household clusters exposed to severe-salinity (above 10 mS/cm) while Khulna has the second highest number of household clusters exposed to moderate salinity (above 2 mS/cm). Clusters with high level exposure to salinity in Chittagong and Dhaka are mostly located along the coast. For the inland divisions, Rangpur, Sylhet, and Rajshahi, household clusters have drinking water salinity level under 0.7 mS/cm.

# **IV. Methodology and Statistical Analysis**

The BDHS data sets were pooled, and revised sample weights were calculated following denormalization of the standard weights. Next, the survey-weighted proportions of neonatal and infant mortality were computed for each survey year and presented in Table 1 for the period 2000-2014. A general decline in infant and maternal mortality is noted even as the number of live births increased indicating overall declines in both infant and maternal mortality rates. Since our key objective is to evaluate the association between groundwater salinity and neonatal or infant deaths, we restricted the sample to the subpopulation of children from households which reported tubewell as their primary source of drinking water in every BDHS survey. The distribution of groundwater EC is skewed right (Figure 2). Since the EC data contained outliers, we winsorized the data at 95<sup>th</sup> percentile distribution when modeling EC as continuous exposure.

Non-Parametric Regression (NPR) was utilized to diagnose the functional form for the relationship between health outcomes and salinity using Stata 15. NPRs have the advantage of estimating mean outcomes for a given set of covariates without assuming a functional form, thus avoiding errors due to misspecification. Figures 3 and 4 present mean functions with 95% confidence interval (CI) predicted by NPR using EC as covariate variable over 1 mS/cm interval with 100 times simulation of bootstrap standard errors. The mean function of probability of infant and neonatal death show similar non-linearity patterns over different salinity levels. Groundwater salinity is modeled as a continuous variable, categorical variable and restricted cubic splines. In continuous exposure models, Ordinary Least Square (OLS) model using EC 8