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1. How Do Rural Ethiopians Rate the Severity of Water Insecurity Scale Items? Implications for Water Insecurity Measurement and Interventions

   https://doi.org/10.17730/1938-3525.79.2.95  

   Tesfaye, Yihenew; Maes, Kenneth; Abesha, Roza; Young, Sera; Snyder, Jedidiah S.; Gebremariam, Abebe; Freeman, Matthew C. (June 2020, Human Organization)

   null (Ed.)

   Recently developed scales aim to advance understanding of household water insecurity and inform interventions to address this critical global problem. The relative severity of items included in household water insecurity scales has been established as an inverse of the proportion of the population that reports experiencing the item. Here, we assess subjective perceptions of scale item severity among people who experience household water insecurity. In 2017, we surveyed 259 women in Amhara, Ethiopia, assessing both experiences of water insecurity and perceptions of item severity using a pictorial scale. The mean subjective severity of most items was at the high end of our pictorial scale. Subjective severity of items was not associated with whether or not a participant experienced the item in the last thirty days, with a participant’s summary household water insecurity score, or with rural versus peri-urban residence, but was consistently associated with community of residence. Item severity as defined by the proportion of the population experiencing the item aligned with average perceptions of item severity, with one exception: drinking water that might not be safe. We discuss these findings’ implications for water insecurity measurement, evaluation of interventions, and studies of the relationship between water insecurity and psychological distress. 

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2. Debiased inference on heterogeneous quantile treatment effects with regression rank scores

   https://doi.org/10.1093/jrsssb/qkad075  

   Giessing, Alexander; Wang, Jingshen (August 2023, Journal of the Royal Statistical Society Series B: Statistical Methodology)

   Abstract Understanding treatment effect heterogeneity is vital to many scientific fields because the same treatment may affect different individuals differently. Quantile regression provides a natural framework for modelling such heterogeneity. We propose a new method for inference on heterogeneous quantile treatment effects (HQTE) in the presence of high-dimensional covariates. Our estimator combines an ℓ1-penalised regression adjustment with a quantile-specific bias correction scheme based on rank scores. We study the theoretical properties of this estimator, including weak convergence and semi-parametric efficiency of the estimated HQTE process. We illustrate the finite-sample performance of our approach through simulations and an empirical example, dealing with the differential effect of statin usage for lowering low-density lipoprotein cholesterol levels for the Alzheimer’s disease patients who participated in the UK Biobank study. 

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3. Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

   https://doi.org/10.1371/journal.pone.0275916  

   Thompson, Amy E.; Walden, John P.; Chase, Adrian S.; Hutson, Scott R.; Marken, Damien B.; Cap, Bernadette; Fries, Eric C.; Guzman Piedrasanta, M. Rodrigo; Hare, Timothy S.; Horn, Sherman W.; et al (November 2022, PLOS ONE)

   Hart, John P. (Ed.)

   Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization. 

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4. Heterogeneity, Household Co-Production, and Risks of Water Services — Water Demand of Private Households with Multiple Water Sources

   https://doi.org/10.1142/S2382624X22500060  

   Zozmann, Heinrich; Klassert, Christian; Klauer, Bernd; Gawel, Erik (January 2022, Water Economics and Policy)

   Private households around the world use and combine multiple water sources, including diverse forms of market services and self-supply. The reasons for this have so far not been explained in a coherent framework, nor have the implications for water management and policy been sufficiently analyzed. Here, we examine how heterogeneity of water services, household co-production, and risks of provision influence household demand patterns. We apply an economic household production model that incorporates two water quality levels for different household activities to exemplary situations. We derive a number of explanations why households use and combine water services that expand the current state of research. Relevant findings include: (i) The diverse characteristics of available water services result in different time requirements for water procurement and varying degrees of suitability for household activities. (ii) Differences in the value placed on time can induce households to demand heterogeneous water services because these enable them to find a balance between using time and money to access water. (iii) Certain water services may be demanded because they function as insurance against both uncertain and unreliable supply. Our insights are relevant for water policy, in particular for developing and managing demand-responsive systems, and for the implementation and monitoring of normative goals for access to water. 

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5. The association between crop diversity and children’s dietary diversity: multi-scalar and cross-national comparisons

   https://doi.org/10.1007/s12571-024-01458-9  

   Isbell, Carina; Tobin, Daniel; Thiede, Brian_C; Jones, Kristal; Reynolds, Travis (July 2024, Food Security)

   Abstract Food insecurity is rising across sub-Saharan Africa (SSA), where undernourishment continues to affect a large portion of the population, particularly young children. Studies examining the associations between crop diversity and childhood nutrition have recently proliferated but are characterized by inconsistent results and two key limitations. First, many studies focus only on the household level, overlooking the prospect that more diverse crops at village and regional levels may contribute to household food security. Second, many studies pool data from multiple countries, which may obscure important context-specific aspects of nutrition outcomes. Drawing on Demographic and Health Survey (DHS) data from 10 SSA countries, in combination with agricultural production estimates for 112 crop species, this study explores the associations between crop diversity at multiple scales (10-, 25-, and 50-kilometer radii) and children’s dietary diversity (HDDS). In addition to producing overall estimates across our sample, we measure country-specific associations to account for spatial heterogeneity. Results of the overall model show a negative association between crop diversity and dietary diversity. However, the country-specific analyses uncover extensive variability in these associations: in some cases, diversity is highly positively correlated with HDDS, while in others the estimated effect is negative or nonexistent. Our findings suggest that country-level analyses provide important nuance that may be masked in pooled analyses. Moreover, these findings foreground the importance of looking beyond household-level analyses to understand the dynamic role that local crop diversity, and its exchange across space, can play in supporting children’s dietary diversity. 

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