A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA

Differentiated impacts of environmental contexts on residents' environmental attitudes towards ecological restoration programs of China's drylands

Residents' environmental attitudes (EAs) towards ecological restoration programs are vital for evaluating program effectiveness and promoting environmental management. However, most local studies have neglected the indirect environmental contextual influences on residents' EAs, and have omitted the regional variations in the environmental contextual influences. To investigate the multilevel factors affecting residents' EAs, we conducted a transect survey that included the eastern, middle, and western regions in northern China's drylands, where have experienced ecological restoration. Multilevel linear models (MLMs) were applied to analyse the direct and indirect impacts of environmental contexts and individual characteristics on rural residents' EAs. The results showed the environmental context can indirectly impact EAs by amplifying the influence of individual characteristics such as family structure and income on EAs. The EAs are influenced by different local environmental contexts among the east, middle and west of China's drylands. The humidity attitude was influenced by precipitation only in the highly arid western and middle regions, while precipitation attitude is strongly influenced by land surface temperature and humidity in eastern China's drylands. These findings hold important implications for understanding the cross-scale impact of environmental contexts on EAs in drylands.

Spatial variation and factors associated of solid fuel use in Ethiopia a multilevel and spatial analysis based on EDHS 2016

Cooking and heating using solid fuels, such as dung, wood, agricultural residues, grass, straw, charcoal, and coal, is a main source of household air pollution. This indoor combustion encompasses a diversity of health detrimental pollutants, especially for people from low-income countries like Ethiopia since solid fuels are accessible easily at a lesser cost. Limited studies done showing factors affecting in choosing fuel type and no study, which revealed spatial heterogeneity of solid fuel used based on such nationally representative data. Therefore, this study, aimed at investigating spatial variation and determinants of solid fuel use in Ethiopia. This study was done using the data from the Ethiopian Demographic and Health Survey 2016, a national representative sample (16,650) households were included. Spatial and Multi-level logistic regression analysis was done by considering the DHS data hierarchal nature. Variables in the final model with a p-value < 0.05 were reported as significant predictors of using solid fuel. All analyses were done using ArcGIS V.10.7.1 and STATA V.14 software. The finding of this study revealed that 90.8% (95% CI (87.9%, 91.2%)) of households depend on solid fuel for cooking. Based on the final model ;Male household head (AOR 1.38, 95% CI (1.12-1.71)), age of household head (AOR 1.61, 95% CI (1.20, 2.17)), and 1.49 (OR 1.49, 95% CI (1.12, 1.99)) respectively for the age classes of < 30, and 30-40, education attainment no education (OR 3.14, 95% CI (1.13, 8.71)) and primary education (AOR 2.16, 95% CI (2.78, 5.96), wealth index Poorest (AOR 11.05, 95% CI (5.68, 15.78)), Poorer (OR 5.19, 95% CI (5.43, 13.19)), Middle (OR 3.08, 95% CI (2.44, 8.73)), and Richer (OR 1.30, 95IC (1.07, 13.49)) compared to richest, and not accessibility of electricity (AOR 31.21, 95% CI (35.41, 42.67)), were individual-level factors significantly associated with using solid fuel. Community-level factors like households found at large city (AOR 2.80, 95CI (1.65, 4.77)), small city (AOR 2.58, 95% CI (1.55, 4.32)) town (AOR 4.02, 95% CI (2.46, 6.55)), and countryside (AOR 14.40, 95% CI (6.23, 21.15)) compared households found in capital city, community level media exposure (AOR 6.00, 95% CI (4.61, 7.82)) were statistically predictors in using solid fuel for cooking. This finding revealed that a large proportion of households in Ethiopia heavily depend on biomass, especially wood, for cooking. There was a greater disparity on solid fuel use for cooking in Ethiopia. Implementing major policy interventions should be introduced to reduce solid fuel use for cooking and inequalities in accessing clean fuel in Ethiopia.

Spatial variations in the associations of term birth weight with ambient air pollution in Georgia, USA

Birth weight is an important indicator of overall infant health and a strong predictor of infant morbidity and mortality, and low birth weight (LBW) is a leading cause of infant mortality in the United States. Numerous studies have examined the associations of birth weight with ambient air pollution, but the results were inconsistent. In this study, a spatial statistical technique, geographically weighted regression (GWR) is applied to explore the spatial variations in the associations of birth weight with concentrations of ozone (O3) and fine particulate matter (PM2.5) in the State of Georgia, USA adjusted for gestational age, parity, and six other socioeconomic, behavioral, and land use factors. The results show considerable spatial variations in the associations of birth weight with both pollutants. Significant positive, non-significant, and significant negative relationships between birth weight and concentrations of each air pollutant are all found in different parts of the study area, and the different types of the relationships are affected by the socioeconomic and urban characteristics of the communities where the births are located. The significant negative relationships between birth weight and O3 indicate that O3 is a significant risk factor of LBW and these associations are primarily located in less-urbanized communities. On the other hand, PM2.5 is a significant risk factor of LBW in the more-urbanized communities with higher family income and education attainment. These findings suggest that environmental and health policies should be adjusted to address the different effects of air pollutants on birth outcomes across different types of communities to more effectively and efficiently improve birth outcomes.