The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

INTRODUCTION: Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants. METHODS: A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit. RESULTS: Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context. CONCLUSIONS: Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

Linking Electronic Health Records to the American Community Survey: Feasibility and Process.

Objectives. To assess linkages of patient data from a health care system in the southeastern United States to microdata from the American Community Survey (ACS) with the goal of better understanding health disparities and social determinants of health in the population. Methods. Once a data use agreement was in place, a stratified random sample of approximately 200 000 was drawn of patients aged 25 to 74 years with at least 2 visits between January 1, 2016, and December 31, 2019. Information from the sampled electronic health records (EHRs) was transferred securely to the Census Bureau, put through the Census Person Identification Validation System to assign Protected Identification Keys (PIKs) as unique identifiers wherever possible. EHRs with PIKs assigned were then linked to 2001-2017 ACS records with a PIK. Results. PIKs were assigned to 94% of the sampled patients. Of patients with PIKs, 15.5% matched to persons sampled in the ACS. Conclusions. Linking data from EHRs to ACS records is feasible and, with adjustments for differential coverage, will advance understanding of social determinants and enhance the ability of integrated delivery systems to reflect and affect the health of the populations served. (Am J Public Health. 2022;112(6):923-930. https://doi.org/10.2105/AJPH.2022.306783).

Migration and Fuel Use in Rural Zambia.

What is the effect of migration on fuel use in rural Zambia? Opportunities to increase income can be scarce in this setting; in response, households may pursue a migration strategy to increase resources as well as to mitigate risk. Migrant remittances may make it possible for households to shift from primary reliance on firewood to charcoal, and the loss of productive labor through migration may reinforce this shift. This paper uses four waves of panel data collected as part of the Child Grant Programme in rural Zambia to examine the connection between migration and the choice of firewood or charcoal as cooking fuel and finds evidence for both mechanisms. Importantly, this paper considers migration as a process, including out- as well as return migration, embedding it in the context of household dynamics generally. Empirical results suggest that while migration helps move households away from firewood as a fuel source, return migration moves them back, but because firewood is more common, the overall effect of migration is to shift households away from primary reliance on firewood towards charcoal.

Life Course Events and Migration in the Transition to Adulthood.

Do life course events stimulate migration during the transition to adulthood? We identify nine specific life events in the family, education, and employment domains and test whether they lead to migration in the short term, using fixed-effects models that remove the influence of all stable individual-level characteristics and controlling for age. Marital and school completion events have substantively large effects on migration compared to individual work transitions, although there are more of the latter over the young adult years. Furthermore, young adults who are white and from higher class backgrounds are more likely to migrate in response to life events, suggesting that migration may be a mechanism for the reproduction of status attainment. Overall, the results demonstrate a close relationship between life course events and migration, and suggest a potential role for migration in explaining the effect of life course events on well-being and behavior.

Population Responses to Environmental Change: Looking Back, Looking Forward.

Over the past two decades, population researchers have engaged in a far-reaching and productive program of research on demographic responses to changes in the natural environment. This essay "looks back" to the origins of these developments, identifying pivotal agenda-setting moments in the 1990s and tracing the impact on contemporary research. The essay also "looks forward" to identify critical gaps and challenges that remain to be addressed and to set an agenda for future research on population responses to environmental change. It recommends that the multidimensionality of environmental contexts and change be fully embraced, long run as well as short term effects be investigated, variability in the effects of environmental change in relation to social institutions, policy implementation, and environmental context be examined, movement between contexts as well as change in situ as sources of environmental change be considered, and interconnections among demographic processes in response to environmental change be explored. Taking these steps will position demographers to contribute significantly to a larger and deeper understanding of environmental change and its consequences, locally, regionally, and globally.

Climate Change and Migration: New Insights from a Dynamic Model of Out-Migration and Return Migration.

In popular accounts, stories of environmental refugees convey a bleak picture of the impacts of climate change on migration. Scholarly research is less conclusive, with studies finding varying effects. This paper uses an agent-based model (ABM) of land use, social networks, and household dynamics to examine how extreme floods and droughts affect migration in Northeast Thailand. The ABM explicitly models the dynamic and interactive pathways through which climate-migration relationships might operate, including coupled out and return streams. Results suggest minimal effects on out-migration but marked negative effects on return. Social networks play a pivotal role in producing these patterns. In all, the portrait of climate change and migration painted by focusing only on environmental refugees is too simple. Climate change operates on already established migration processes that are part and parcel of the life course, embedded in dynamic social networks, and incorporated in larger interactive systems where out- and return migration are integrally connected.

Climate Shocks and Migration: An Agent-Based Modeling Approach.

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.

Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation.

The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications.

Recruitment of women in the National Children's Study Initial Vanguard Study.

The initial Vanguard Study of the National Children's Study was conducted during 2009-2010 in 7 locations in the United States. A goal was to evaluate the feasibility and yield of a household-based sampling design to recruit pregnant women. A multistage area probability sampling design was used to identify study locations (generally, counties) that were subsequently divided into smaller geographical units, termed segments. Between 7 and 18 segments were selected in each location, and dwelling units within segments were listed. A household-based recruitment process was implemented, which included enumeration of households to identify age-eligible women, pregnancy screening to identify pregnant women eligible for immediate enrollment and nonpregnant women for telephone follow-up, and administration of informed consent to eligible women. After a recruitment period of 17-20 months, 67,181 (89%) households were enumerated, which identified 34,172 (88%) age-eligible women to whom the pregnancy screener was administered. Among those who completed the screener, 2,285 women became eligible for enrollment, of whom 1,399 (61%) enrolled. Although response rates were fairly high at initial contact and among pregnant women, the overall yield was lower than anticipated. In particular, telephone follow-up of nonpregnant women was not a practicable strategy for prospective recruitment of newly pregnant women.

Design of an Agent-Based Model to Examine Population-Environment Interactions in Nang Rong District, Thailand.

The design of an Agent-Based Model (ABM) is described that integrates Social and Land Use Modules to examine population-environment interactions in a former agricultural frontier in Northeastern Thailand. The ABM is used to assess household income and wealth derived from agricultural production of lowland, rain-fed paddy rice and upland field crops in Nang Rong District as well as remittances returned to the household from family migrants who are engaged in off-farm employment in urban destinations. The ABM is supported by a longitudinal social survey of nearly 10,000 households, a deep satellite image time-series of land use change trajectories, multi-thematic social and ecological data organized within a GIS, and a suite of software modules that integrate data derived from an agricultural cropping system model (DSSAT - Decision Support for Agrotechnology Transfer) and a land suitability model (MAXENT - Maximum Entropy), in addition to multi-dimensional demographic survey data of individuals and households. The primary modules of the ABM are the Initialization Module, Migration Module, Assets Module, Land Suitability Module, Crop Yield Module, Fertilizer Module, and the Land Use Change Decision Module. The architecture of the ABM is described relative to module function and connectivity through uni-directional or bi-directional links. In general, the Social Modules simulate changes in human population and social networks, as well as changes in population migration and household assets, whereas the Land Use Modules simulate changes in land use types, land suitability, and crop yields. We emphasize the description of the Land Use Modules - the algorithms and interactions between the modules are described relative to the project goals of assessing household income and wealth relative to shifts in land use patterns, household demographics, population migration, social networks, and agricultural activities that collectively occur within a marginalized environment that is subjected to a suite of endogenous and exogenous dynamics.

New models for large prospective studies: is there a risk of throwing out the baby with the bathwater?

Manolio et al. (Am J Epidemiol. 2012;175:859-866) proposed that large cohort studies adopt novel models using "temporary assessment centers" to enroll up to a million participants to answer research questions about rare diseases and "harmonize" clinical endpoints collected from administrative records. Extreme selection bias, we are told, will not harm internal validity, and "process expertise to maximize efficiency of high-throughput operations is as important as scientific rigor" (p. 861). In this article, we describe serious deficiencies in this model as applied to the United States. Key points include: 1) the need for more, not less, specification of disease endpoints; 2) the limited utility of data collected from existing administrative and clinical databases; and 3) the value of university-based centers in providing scientific expertise and achieving high recruitment and retention rates through community and healthcare provider engagement. Careful definition of sampling frames and high response rates are crucial to avoid bias and ensure inclusion of important subpopulations, especially the medically underserved. Prospective hypotheses are essential to refine study design, determine sample size, develop pertinent data collection protocols, and achieve alliances with participants and communities. It is premature to reject the strengths of large national cohort studies in favor of a new model for which evidence of efficiency is insufficient.

Migrant remittances and the web of family obligations: ongoing support among spatially extended kin in North-east Thailand, 1984-94.

Exchanges of money, goods, and assistance among family/kin members are influenced by the intertwined lives of individuals and their family/kin. As people pass through the young adulthood years, acquiring obligations as spouses and parents, and migrating in search of economic opportunities, tensions can arise over existing obligations. Using rich longitudinal data from Northeast Thailand, we examined the role of family networks (origin and destination) on migrants' exchanges with family/kin. Our approach overcame many shortcomings of earlier studies, allowing us to 'see' the family social network arrayed in a broader network. We show that intra-family exchanges are influenced by marital status, the presence of children, having parents in the origin household, and having siblings depart from it. The results are stable across sensitivity tests that systematically include or exclude various familial links. In addition, reports provided by origin households on migrant remittances are consistent with reports from migrants themselves.

Social and Spatial Networks: Kinship Distance and Dwelling Unit Proximity in Rural Thailand.

We address a long hypothesized relationship between the proximity of individuals' dwelling units and their kinship association. Better understanding this relationship is important because of its implications for contact and association among members of a society. In this paper, we use a unique dataset from Nang Rong, Thailand which contains dwelling unit locations (GPS) and saturated kinship networks of all individuals living in 51 agricultural villages. After presenting arguments for a relationship between individuals' dwelling unit locations and their kinship relations as well as the particulars of our case study, we introduce the data and describe our analytic approach. We analyze how kinship - considered as both a system linking collections of individuals in an extended kinship network and as dyadic links between pairs of individuals -patterns the proximity of dwelling units in rural villages. The results show that in general, extended kin live closer to one another than do unrelated individuals. Further, the degree of relatedness between kin correlates with the distance between their dwelling units. Close kin are more likely to co-reside, a fact which drives much of the relationship between kinship relatedness and dwelling unit proximity within villages. There is nevertheless suggestive evidence of a relationship between kinship association and dwelling unit proximity among kin who do not live together.

The National Children's Study in North Carolina: a study of the effect of the environment on children's health, growth, and development.

The National Children's Study, a longitudinal cohort study exploring relationships among broadly defined environmental exposures and children's health, is assessing whether these exposures are harmful, harmless, or helpful. The study is presently underway in 37 locations (2 of which are in North Carolina) and will expand to enroll 100,000 children across the United States.

Simulated village locations in Thailand: A multi-scale model including a neural network approach.

The simulation of rural land use systems, in general, and rural settlement dynamics in particular has developed with synergies of theory and methods for decades. Three current issues are: linking spatial patterns and processes, representing hierarchical relations across scales, and considering nonlinearity to address complex non-stationary settlement dynamics. We present a hierarchical simulation model to investigate complex rural settlement dynamics in Nang Rong, Thailand. This simulation uses sub-models to allocate new villages at three spatial scales. Regional and sub-regional models, which involve a nonlinear space-time autoregressive model implemented in a neural network approach, determine the number of new villages to be established. A dynamic village niche model, establishing pattern-process link, was designed to enable the allocation of villages into specific locations. Spatiotemporal variability in model performance indicates the pattern of village location changes as a settlement frontier advances from rice-growing lowlands to higher elevations. Experiments results demonstrate this simulation model can enhance our understanding of settlement development in Nang Rong and thus gain insight into complex land use systems in this area.

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions.

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process.

Population Growth and Its Spatial Distribution as Factors in the Deforestation of Nang Rong, Thailand.

Frontiers constitute a major source of global land cover change hot spots, with forests and grass lands being converted into agricultural uses. As such, frontiers provide an opportunity to see how people manipulate the land and their lives in the context of social, cultural and environmental constraints. This paper examines frontier settlement and land cover change in Nang Rong district, Northeast Thailand for the last half century. It uses a Cellular Automata (CA) model to explore the land cover consequences of alternative patterns of settlement in a setting where people establish dwelling units in nucleated villages and work agricultural plots that surround villages. Forested land around the center of a village is converted into agricultural uses in an inverse relationship to the distance from the village center, but frequently modified by biophysical conditions. Land at the center of the village may be reforested after the village is established as a source of shade as well as fruit and other products. Model variation in land cover change is more sensitive to the spatial reach of village households than their temporal reach, suggesting the important role that technology plays in how villagers travel to their fields (walking versus motorized transit).

Putting people into place.

Over the past two decades, there has been an explosion of empirical research on neighborhoods and health. However, although the data and approaches owe much to the early contributions of demographers and population scientists, this debt is largely unrecognized. Likewise, challenges posed in the early literature remain largely unanswered. I argue that just as demographers and population scientists were pioneers in the study of neighborhoods and health, they are uniquely poised to lead the field again. Putting people into place means explaining behavior and outcomes in relation to a potentially changing local context. A more dynamic conceptualization is needed that fully incorporates human agency, integrates multiple dimensions of local social and spatial context, develops the necessary longitudinal data, and implements appropriate tools. Diverse approaches with complementary strengths will help surmount the many analytic challenges to studying the dynamics of neighborhoods and health, including agent-based microsimulation models.