Spatial Demography最新文献

Acute malnutrition affects a sizeable number of young children around the world, with serious repercussions for mortality and morbidity. Among the top priorities in addressing this problem are to anticipate which children tend to be susceptible and where and when crises of high prevalence rates would be likely to arise. In this article, we highlight the potential role of conflict and climate conditions as risk factors for acute malnutrition, while also assessing other vulnerabilities at the individual- and household-levels. Existing research reflects these features selectively, whereas we incorporate all the features into the same study. The empirical analysis relies on integration of health, conflict, and environmental data at multiple scales of observation to focuses on how local conflict and climate factors relate to an individual child's health. The centerpiece of the analysis is data from the Demographic and Health Surveys conducted in several different cross-sectional waves covering 2003-2016 in Kenya, Nigeria, and Uganda. The results obtained from multi-level statistical models indicate that in Kenya and Nigeria, conflict is associated with lower weight-for-height scores among children, even after accounting for individual-level and climate factors. In Nigeria and Kenya, conflict lagged 1-3 months and occurring within the growing season tends to reduce WHZ scores. In Uganda, however, weight-for-height scores are primarily associated with individual-level and household-level conditions and demonstrate little association with conflict or climate factors. The findings are valuable to guide humanitarian policymakers and practitioners in effective and efficient targeting of attention, interventions, and resources that lessen burdens of acute malnutrition in countries prone to conflict and climate shocks.

Women's empowerment has been a subject of interest because of its relevance to development and demography, particularly in West Africa. Women's empowerment is typically conceptualized as an individual attribute of women, associated with socioeconomic and demographic characteristics. However, we hypothesize a geography of women's empowerment in the West African region, where empowerment processes are culturally situated and embedded in place. Such a geography would be observable via spatial associations over the region. This study uses Demographic and Health Survey data from 14 West African states over the past decade and an innovative multi-stage approach combining advanced statistical methods and spatial assessment to analyze indicators of women's empowerment and its spatial variability across the West African region. First we use a multivariate classification method to identify patterns in responses to empowerment questions and derive an empowerment classification scheme. Next we use these classifications to render a map of West Africa depicting the spatial variation of women's empowerment in the region. Ultimately, we fit multinomial structured geo-additive regression models to the data to analyze spatial variation in women's empowerment while controlling for certain socioeconomic-demographic characteristics. Our results demonstrate that women's responses to empowerment survey questions indeed vary geographically, even when controlling for individual socioeconomic-demographic attributes. This finding suggests that women's empowerment may relate to aspects of culture embedded in place in addition to the ways it relates to socioeconomic and demographic characteristics.

This study analyzes at a local level (i.e. census tract) the spatial patterns and main contextual factors related to the electoral resurgence of the extreme-right party (VOX) in Southern Spain (Andalusia) in 2018 and 2019. The 2019 electoral data was associated with the percentage of total foreign-born population, degree of territorial concentration of economic migrants, average income level, percentage of elderly people, urban/rural areas and the percentage of vote for VOX in 2018 (t − 1). We used a global and local spatial autocorrelation analysis to detect the spatial patterns of the vote for VOX and a spatial Durbin regression model to assess the role of contextual variables and spatial effects. The results underline the importance of space in modelling the vote for VOX and point to the existence of a spatial diffusion process. Previous electoral behavior and the urban milieu also play key roles in explaining the vote for VOX. Moreover, the territorial concentration of economic migrants is negatively related with the vote for VOX, which illustrates the positive character of interracial contact.

India has substantially reduced the burden of under-five child malnutrition over the last two decades. Despite this, it is still gigantic and differs remarkably across districts, while the demographic and socio-economic groups are most affected by it. This paper aimed to decrypt the place-specific spatial dependence and heterogeneity in associations between district-level nutritional status (stunting, wasting and underweight) and its considered correlates using a geocoded database for all 640 Indian districts from the latest fourth wave of the National Family Health Survey, 2015–16. Univariate Moran’s I and LISA statistics were used to confirm the spatial clustering and dependence in under-five nutritional status. The Ordinary Least Square (OLS), Geographically Weighted Regression (GWR), Spatial (lag/error) models were employed to examine the effects of correlates on the district-level nutritional status. The mean (Moran’s I) district-level stunting, wasting and underweight were 38% (0.634), 21% (0.488) and 36% (0.721), respectively. The GWR results disclosed that the spatial heterogeneity in relationships between district-level nutritional status and its driving forces were strongly location-based, altering their direction, magnitude and strength across districts. Overall, the localized model performed better, and best fit the data than the OLS and spatial (lag/error) models. This nationwide study confirmed that the spatial dependencies and heterogeneities in the district-level nutritional status indicators were strongly explained by a multitude of factors and thus can help policymakers in formulating effective nutrition-specific programmatic interventions to speed up the coverage of under-five malnutrition status in most priority districts and geographical hot spots across India.