Austin Sandler

Anthropometric evaluation of children is among the most vital and widely used instruments of public health and clinical medicine. Anthropometry is used for establishing norms, identifying variations, and monitoring development. Yet the accurate assessment of physical growth and development of children remains a perpetually beleaguering subject. This paper focuses on the evolution of anthropometry as a science and its associated measurements, indices, indicators, standards, references, and best practices. This paper seeks to clarify aspects of the assessment of child growth, explores the historical trajectory of the study of anthropometry and its contemporary limitations, and contributes to the debate surrounding references and standards, and the applicability of international anthropometric standards to an individual's health. Among its findings is a surprisingly nonlinear and contested record of events, up to and including leading contemporary practices and datasets. It contextualizes the legacy of child malnutrition studies in a broad framework, including the linkage between the early eugenics movement and contemporary notions of a “normal” child, the interpersonal and intuitional competition to become the preeminent child growth authority, the obfuscated distinction between reference growth charts and standards of growth, and the hidden consequences of universal growth standards that no longer reflect any observable populations.

https://doi.org/10.1016/j.ssmph.2021.100865 

Droughts are associated with several societal ills, especially in developing economies that rely on rainfed agriculture. Recently, researchers have begun to examine the effect of droughts on the risk of Intimate-Partner Violence (IPV), but so far this work has led to inconclusive results. For example, two large recent studies analyzed comparable data from multiple sub-Saharan African countries and drew opposite conclusions. We attempt to resolve this apparent paradox by replicating previous analyses with the largest data set yet assembled to study drought and IPV. Integrating the methods of previous studies and taking particular care to control for spatial autocorrelation, we find little association between drought and most forms of IPV, although we do find evidence of associations between drought and women’s partners exhibiting controlling behaviors. Moreover, we do not find significant heterogeneous effects based on wealth, employment, household drinking water sources, or urban-rural locality.

https://doi.org/10.1371/journal.pone.0254346 

Anthropometry is the study of the measurements and proportions of the human body. In the field, many practitioners have adopted a questionable quality control maxim. The maxim is, essentially, to dismiss any survey of anthropometric measurements whose standard deviation exceeds that of a benchmark survey, sample, or distribution by some amount (e.g., 30 percent). To date there is no published study which properly substantiates the maxim. Despite the lack of sound statistical justification and lack of scientific evidence, the standard deviation as quality control indicator persists. Practitioners who endorse the maxim transpose the conditional and muddle samples with populations and references with standards. The practice is endemic and may have real consequences in terms of financial resources and global morbidity and mortality. This paper details the genesis and propagation of the maxim in the literature, exposes its theoretical and logical weaknesses, illustrates its demerits, and offers an alternative attitude toward the problem of quality control.

https://econjwatch.org/File+download/1182/SandlerMar2021.pdf?mimetype=pdf 

This study examines the economic, fiscal, and workforce impacts of two Dayton Power & Light (DP&L) coal-fired power plant closures in Adams County, Ohio. The decommissioning of these facilities, and the closure of an associated training centre, will result in over 1,100 total lost jobs in the Appalachian region. A skillshed analysis revealed that displaced workers transitioning to emerging occupations with similar skill requirements will experience wage decreases. Decommissioned power plants in Ohio no longer pay tangible personal property (TPP) taxes, which will result in $8.5 million in lost tax revenue for local governments. These findings suggest that a multi-pronged recovery effort will be required to assist this region, which has implications for similar communities in Appalachian Ohio dealing with coal plant closures.

https://doi.org/10.1111/rsp3.12191 

This study makes a unique contribution to the economic and regional science literature on the impacts of disasters by focusing on an understudied area of fiscal impacts of disasters in rural areas. Specifically, it focuses on the differences in sales tax collections in Appalachian and non-Appalachian Ohio counties following a series of Derecho wind storms in the summer of 2012. We find Appalachian counties experience a decrease in sales tax collections of $254,845 per county post storm compared to their non-Appalachian counterparts in the state. In total, the Appalachian region lost nearly $5.1 million in sales tax collections. We argue that the limited economic base of rural economies not only makes them less resilient to natural disasters, but also prevents them from experiencing the post-disaster economic and fiscal benefits that often occur in urban areas.

https://jrap.scholasticahq.com/article/3711 

Satellite-based land-use data sets are providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in typical land-use models. Results from satellite imagery data from the Northern Great Plains indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., 35%), ignoring misclassification can lead to systematically erroneous land-use policies.

https://doi.org/10.1016/j.landusepol.2018.04.008 

Malnutrition devastates millions of children globally every year, yet the consensus of determining factors remains mixed and obscure. Based on a systematic literature search, I reviewed 184 disaggregate empirical studies of the determinants of childhood malnutrition in Africa published since 1990. The literature concerning disaggregate empirical studies of childhood malnutrition is found wanting for answers to two essential questions: What are the determinants of malnutrition? And how much do the determinants affect malnutrition? The role of spatial heterogeneity, hierarchical institutions, and divergent causal pathways of various non-illness related latent determinants is growing. Few studies consider conflict and environment etiologies: despite being the primary factors attributed to malnutrition, hunger, and death in most catastrophic famine events. Despite an extensive body of research, I find there are a number of opportunities for development within this corpus, in terms of an unmet need for more studies with broad temporal, spatial, and hierarchical perspectives, with an exhaustive set of nutrition outcomes, and findings that are quantifiable and epidemiologically significant. 

FEWS NET are the leading provider of early warning for food insecurity. However, little is known concerning its prediction accuracy and reliability. Inaccurate forecasts are either over- or under-predicted, and amplified by the level of remoteness. Over-predicted forecasts cost limited financial and humanitarian resources whereas under-predicted forecasts cost lives in terms of avoidable morbidity and mortality, and all inaccuracies cost credibility in future forecasts. For example, July 2011 represents an under-predicted forecast. Of the subsequent perceived Famine areas, 0% were forecast as Famines, 4.9% were forecast as Emergencies, 88.5% were forecast as Crises, and 6.3% were forecast as Stressed. I developed accuracy assessments along various space, scope, scale, and time vectors. My preliminary results show that at best only 20% of all FEWS NET predicted famines are actualized as famines. Geovisulaizations and spatio-statistical analysis accompany each of the dimensional vectors. This research will help public health and international aid agencies better forecast and ameliorate potential nutrition disasters.

A skillshed analysis identifies occupations and occupational clusters that a state or region has an absolute advantage in, and leverages that advantage to its fullest potential. A skillshed analysis not only illustrates where the regions strengths lie by detailing the current workforce mix, but also which occupations and industries are growing and declining and how easily workers can adapt the changing economic climate. This gap analysis is developed by comparing the skills and knowledge possessed by the current declining industry workforce supply to those demanded by current and prospective employers of growing industries.Skillshed analyses for rural workforce development can help regional economies anticipate and accommodate gaps between workforce occupational demand and workforce capability supply. My skillshed framework assesses geospatial regional level disparities in workforce supply and to provides customizable workforce development plans to close mismatches between the quantity supplied by the workforce and the quantity demanded by employers in terms of of skills, knowledge, and abilities. And the gap analysis matches the skills and knowledge possessed by declining industry workforce supply to those demanded by growing industries. This project will assists employees, industries, and local governments in planning for their future development needs.