The pattern of poor household food consumption: The case of West Java Province

The result of a LA-AIDS showed that the food consumption of poor households in West Java is influenced by its own-price, the price of other commodities, income, number of household members, household location, education of the head of household, and work type of the head of the household. The own-price elasticity identified that the price increase in each commodity group does not affect the consumption of the general food group. The cross-price elasticity of food groups showed more complementary.

Impact of imprecise household location on effective coverage estimates generated through linking household and health provider data by geographic proximity: a simulation study

Background Geographic proximity is often used to link household and health provider data to estimate effective coverage of health interventions. Existing household surveys often provide displaced data on the central point within household clusters rather than household location. This may introduce error into analyses based on the distance between households and providers. Methods We assessed the effect of imprecise household location on quality-adjusted effective coverage of child curative services estimated by linking sick children to providers based on geographic proximity. We used data on care-seeking for child illness and health provider quality in Southern Province, Zambia. The dataset included the location of respondent households, a census of providers, and data on the exact outlets utilized by sick children included in the study. We displaced the central point of each household cluster point five times. We calculated quality-adjusted coverage by assigning each sick child to a provider’s care based on three measures of geographic proximity (Euclidean distance, travel time, and geographic radius) from the household location, cluster point, and displaced cluster locations. We compared the estimates of quality-adjusted coverage to each other and estimates using each sick child’s true source of care. We performed sensitivity analyses with simulated preferential care-seeking from higher-quality providers and randomly generated provider quality scores. Results Fewer children were linked to their true source of care using cluster locations than household locations. Effective coverage estimates produced using undisplaced or displaced cluster points did not vary significantly from estimates produced using household location data or each sick child’s true source of care. However, the sensitivity analyses simulating greater variability in provider quality showed bias in effective coverage estimates produced with the geographic radius and travel time method using imprecise location data in some scenarios. Conclusions Use of undisplaced or displaced cluster location reduced the proportion of children that linked to their true source of care. In settings with minimal variability in quality within provider categories, the impact on effective coverage estimates is limited. However, use of imprecise household location and choice of geographic linking method can bias estimates in areas with high variability in provider quality or preferential care-seeking.

Effectiveness of spatially targeted interventions for control of HIV, tuberculosis, leprosy and malaria: a systematic review

BackgroundAs infectious diseases approach global elimination targets, spatial targeting is increasingly important to identify community hotspots of transmission and effectively target interventions. We aimed to synthesise relevant evidence to define best practice approaches and identify policy and research gaps.ObjectiveTo systematically appraise evidence for the effectiveness of spatially targeted community public health interventions for HIV, tuberculosis (TB), leprosy and malaria.DesignSystematic review.Data sourcesWe searched Medline, Embase, Global Health, Web of Science and Cochrane Database of Systematic Reviews between 1 January 1993 and 22 March 2021.Study selectionThe studies had to include HIV or TB or leprosy or malaria and spatial hotspot definition, and community interventions.Data extraction and synthesisA data extraction tool was used. For each study, we summarised approaches to identifying hotpots, intervention design and effectiveness of the intervention.ResultsTen studies, including one cluster randomised trial and nine with alternative designs (before–after, comparator area), satisfied our inclusion criteria. Spatially targeted interventions for HIV (one USA study), TB (three USA) and leprosy (two Brazil, one Federated States of Micronesia) each used household location and disease density to define hotspots followed by community-based screening. Malaria studies (one each from India, Indonesia and Kenya) used household location and disease density for hotspot identification followed by complex interventions typically combining community screening, larviciding of stagnant water bodies, indoor residual spraying and mass drug administration. Evidence of effect was mixed.ConclusionsStudies investigating spatially targeted interventions were few in number, and mostly underpowered or otherwise limited methodologically, affecting interpretation of intervention impact. Applying advanced epidemiological methodologies supporting more robust hotspot identification and larger or more intensive interventions would strengthen the evidence-base for this increasingly important approach.PROSPERO registration numberCRD42019130133.

The Role of Smart Growth in Residential Location Choice: Heterogeneity of Location Preferences in the Chicago Region

We investigate the role of smart growth in household location choice in the Chicago region, using a discrete choice analysis. In the midst of continued region-wide suburbanization, households tend to move to neighborhoods with rich consumption amenities and high transit access. However, this study does not find evidence that the neighborhood’s physical compactness is a significant location factor. Location preference for compact, mixed-use, and transit-oriented neighborhoods is significantly affected by the life cycle stage and income level, but less influenced by generation and age. Millennial households show strong preference for amenities and transit access only before they marry and have children.

The Importance of Location Factors in Determining Land Prices: The Evidence from Bratislava Hinterland

Bratislava, the capital city of Slovakia, is currently experiencing a period of intensive suburbanisation, which in turn creates demand pressures and increases the price of urban land located in its hinterland. This paper investigates several locational factors, which likely significantly influence the demand for land plots and modulate `price-maker' conditions. Based on the population sample of 102 units, the results indicate that built-in infrastructure facilities on land under analysis, advanced transport connectivity in municipalities, and various amenities in the municipality cadastre tend to elevate land prices significantly. Moreover, the factor of distance from the city of Bratislava plays a major role in household location, which was identified by the apparent decreasing rent gradient pattern.

Impact of Imprecise Household Location on Effective Coverage Estimates Generated through Linking Household and Health Provider Data by Geographic Proximity

Background: Combining household and health provider data can be used to estimate coverage of interventions and identify barriers to use. Without data on specific sources of care utilized by individuals, researchers often assign individuals to healthcare providers based on geographic proximity. The Demographic and Health Survey (DHS), a common source of population health data, does not collect data on the location of participant households. They present displaced data on the central point within household clusters. This may introduce error into analyses based on the distance between households and providers. Methods: We assessed the effect of imprecise household location on quality-adjusted effective coverage of child curative services estimated by linking sick children to providers based on geographic proximity. We used data on care-seeking for child illness and health provider quality in Southern Province, Zambia. The dataset included the location of respondent households, a census of providers, and data on the exact outlets utilized by sick children included in the study. We displaced the central point of each household cluster point five times. We calculated quality-adjusted coverage by assigning each sick child to a provider’s care based on three measures of geographic proximity (absolute distance, travel time, and geographic radius) from the household location, cluster point, and displaced cluster locations. We compared the estimates of quality-adjusted coverage to each other and estimates calculated using each sick child’s true source of care. Results: Fewer children were linked to their true source of care using cluster locations than household locations. Estimates of coverage were not statistically different using different measures of geographic proximity or household location. Estimates did not vary significantly from estimates produced using each sick child’s true source of care. Conclusions: Use of original or displaced cluster location did not produce statistically different coverage estimates than using household location. However, it did reduce the proportion of children that linked to their true source of care. The limited effect of household location imprecision on quality-adjusted coverage estimates could be due to a lack of variability in provider quality. These findings may not hold in a setting with more considerable variation in provider quality. This work was supported by the Bill & Melinda Gates Foundation, Grant Number INV-006966

The Relationship Between Homeownership and the Utilization of Local Public Health Services Among Rural Migrants in China: A Nationwide Cross-Sectional Study

Background: Rural–urban migrants frequently suffer from overrepresented health risks but have poor access to public health services. In China, homeownership status may play a vital role in obtaining local welfare. However, the relationship between homeownership and utilization of public health services has remained largely unexplored. This study aims to address the direct linkage between homeownership and utilization of local public health services among rural migrants in China.Methods: We applied the dataset from the 2017 National Migrants Population Dynamic Monitoring Survey (NMPDMS-2017) to explore the direct relationship between homeownership and the utilization of local public health services. Logit regression was conducted to discuss the associations and to explore the interaction effect.Results: The logit estimations reveal that homeownership is positively related to the establishment of a health record and participation in health education. The interaction term of homeownership and household location and the interaction between homeownership and healthcare center location are related to the increased establishment of a health record. However, the interaction of homeownership and household location merely reveals significant correlations with the health education model.Conclusion: Homeownership is positively associated with the utilization of local public health services among rural migrants in China. Furthermore, homeowners living in urban residential communities and within the vicinity of the healthcare center are more likely to access public health services than those living in other locations.

U.S. HOUSEHOLD PREFERENCES FOR CLIMATE AMENITIES: DEMOGRAPHIC ANALYSIS AND ROBUSTNESS TESTING

We estimate how climate amenities influence where households decide to reside in the United States with two main objectives in mind: (i) to produce estimates with sufficient demographic detail to inform demographic population projections for use in climate impact analysis; (ii) to study the robustness of estimates from the existing literature. With respect to the former goal, we find important differences in job-related migration motives by age group and in the overall propensity to migrate among households with children. With respect to the latter aim, our framework shares a common methodological approach with other, recent attempts to recover climate preferences, allowing us to explore the consequences of a number of key assumptions in a systematic manner. Consistent with the existing literature, we find relatively robust estimates of the impact of the frequency of extreme heat days on household location decisions. The impacts of other common measures of climate, including the frequency of extreme cold days, average summer and winter temperatures, annual precipitation, humidity and frequency of sunshine, do not show a strong enough signal in the data to be estimated with precision.