An inferential spatiotemporal approach for knowledge synthesis to identify trends in public health research.

Background: Decisions follow patterns that are introduced by human perception. Research and development (R&D) are influenced by these patterns. Furthermore, R&D publications can represent repetitive attempts to solve similar, or the same problems. Literature reviews serve as an important tool for identifying these trends, but they are time consuming. The time commitment of a literature review can be reduced by using a sample of research. This will allow an infinite population of research to be generalized. Additionally, spatiotemporal analysis is most appropriate for fields that follow time and geographic trends, such as public health. Also, using research locations to perform this analysis potentially captures the social return of R&D, as knowledge gained. As a result, an inferential spatiotemporal methodological framework is introduced to quickly identify research trends using public health research. This was applied to a childhood Pb exposure case study. Methods: A body of more than 1000 childhood elevated blood lead (Pb) level (EBLL) research articles were used to extract publication years, research locations, and subtopics. These publications were grouped into research locations (i.e., U.S. states where research was conducted; not publication location) and averaged over years published (i.e., 29 years). Binary indicator variables were derived using the subtopics extracted and the periods identified in time trend analyses. Explanatory variables were used to conduct hypothesis testing. Significant variables were used to generalize the population of the annual average EBLL articles written per state. Results: The range of the annual average of EBLL research articles by state was 0-1.7 articles, with a mean of 0.3 articles. Thirty-eight explanatory variables suggested a significant effect on research article production. These included temporal, sociodemographic, education, structure age, environmental, and economic variables. The strongest effect on research production for U.S. states came from the number of structures built before 1950. A predictive model was selected to generalize the population of articles using time-periods 1990-95, environmental subtopic, and structures built before 1950. The locations with the most research production for this topic were California and New York. The locations with the least research production for this topic were Alaska, Hawaii, Nevada, Wyoming, North Dakota, South Dakota, Mississippi, Delaware, and New Hampshire. Conclusion: If the trend for R&D is to make fast decisions, more human bias will be introduced into the decision-making process. Analytical tools that enable researchers to identify trends and ask more questions about their field will mitigate these biases. This hypothesis testing and predictive modeling methodology provide researchers and other decision makers with analytical tools they can use to quickly identify research trends and narrow their field of research. Additionally, this analysis potentially captures the impact of discovered ideas, as a social return spillover, for this topic.

Assessing lead exposure in U.S. pregnant women using biological and residential measurements.

There is strong scientific evidence for multiple pathways of human exposure to lead (Pb) in residential settings, particularly for young children; however, less is known about maternal exposure during pregnancy and children's exposure during early lifestages. A robust, multi-faceted secondary analysis was conducted using data collected by the National Institute of Child Health and Human Development in the 2009-2014 National Children's Study Vanguard Studies. Descriptive statistics summarized Pb concentrations of maternal blood, maternal urine, and house dust vacuum samples collected during pregnancy and residence surface wipes collected both during pregnancy and six months post-partum. The maternal blood Pb level geometric mean was 0.44 µg/dL (n = 426), with no women having values ≥ 5 µg/dL; creatinine-adjusted maternal urinary Pb geometric mean was 0.43 µg/g (n = 366). These blood and urine concentrations are similar to those observed for females in the general U.S. population in the National Health and Nutrition Examination Survey 2010-2011 cycle. A modest correlation between maternal blood Pb and surface wipe measurements during pregnancy was observed (Spearman r = 0.35, p < 0.0001). Surface wipe Pb loadings obtained in mother's homes during pregnancy (n = 640) and from areas where children spent the most time at roughly 6 months of age (n = 99) ranged from 0.02 to 71.8 ng/cm2, with geometric means of 0.47 and 0.49 ng/cm2, respectively, which were relatively low compared to other national studies. Survey responses of demographic, lifestyle, and residence characteristics were assessed for associations with blood concentration and surface wipe loading. Demographic (e.g., race/ethnicity, income, education, marital status) and housing characteristics (e.g., year home built, paint condition, own or rent home, attached garage) were associated with both maternal blood and surface wipe loadings during pregnancy. The availability of residential environmental media and extensive survey data provided enhanced understanding of Pb exposure during pregnancy and early life.

A Generalizable Evaluated Approach, Applying Advanced Geospatial Statistical Methods, to Identify High Lead Exposure Locations at Census Tract Scale: Michigan Case Study.

BACKGROUND: Despite great progress in reducing environmental lead (Pb) levels, many children in the United States are still being exposed. OBJECTIVE: Our aim was to develop a generalizable approach for systematically identifying, verifying, and analyzing locations with high prevalence of children's elevated blood Pb levels (EBLLs) and to assess available Pb models/indices as surrogates, using a Michigan case study. METHODS: We obtained ∼1.9 million BLL test results of children <6 years of age in Michigan from 2006-2016; we then evaluated them for data representativeness by comparing two percentage EBLL (%EBLL) rates (number of children tested with EBLL divided by both number of children tested and total population). We analyzed %EBLLs across census tracts over three time periods and between two EBLL reference values (≥5 vs. ≥10µg/dL) to evaluate consistency. Locations with high %EBLLs were identified by a top 20 percentile method and a Getis-Ord Gi* geospatial cluster "hotspot" analysis. For the locations identified, we analyzed convergences with three available Pb exposure models/indices based on old housing and sociodemographics. RESULTS: Analyses of 2014-2016 %EBLL data identified 11 Michigan locations via cluster analysis and 80 additional locations via the top 20 percentile method and their associated census tracts. Data representativeness and consistency were supported by a 0.93 correlation coefficient between the two EBLL rates over 11 y, and a Kappa score of ∼0.8 of %EBLL hotspots across the time periods (2014-2016) and reference values. Many EBLL hotspot locations converge with current Pb exposure models/indices; others diverge, suggesting additional Pb sources for targeted interventions. DISCUSSION: This analysis confirmed known Pb hotspot locations and revealed new ones at a finer geographic resolution than previously available, using advanced geospatial statistical methods and mapping/visualization. It also assessed the utility of surrogates in the absence of blood Pb data. This approach could be applied to other states to inform Pb mitigation and prevention efforts. https://doi.org/10.1289/EHP9705.