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Can data science inform environmental justice and community risk screening for type 2 diabetes?

ABSTRACT: BACKGROUND:Having the ability to scan the entire country for potential "hotspots" with increased risk of developing chronic diseases due to various environmental, demographic, and genetic susceptibility factors may inform risk management decisions and enable better environmental public health policies. OBJECTIVES:Develop an approach for community-level risk screening focused on identifying potential genetic susceptibility hotpots. METHODS:Our approach combines analyses of phenotype-genotype data, genetic prevalence of single nucleotide polymorphisms, and census/geographic information to estimate census tract-level population attributable risks among various ethnicities and total population for the state of California. RESULTS:We estimate that the rs13266634 single nucleotide polymorphism, a type 2 diabetes susceptibility genotype, has a genetic prevalence of 56.3%, 47.4% and 37.0% in Mexican Mestizo, Caucasian, and Asian populations. Looking at the top quintile for total population attributable risk, 16 California counties have greater than 25% of their population living in hotspots of genetic susceptibility for developing type 2 diabetes due to this single genotypic susceptibility factor. CONCLUSIONS:This study identified counties in California where large portions of the population may bear additional type 2 diabetes risk due to increased genetic prevalence of a susceptibility genotype. This type of screening can easily be extended to include information on environmental contaminants of interest and other related diseases, and potentially enables the rapid identification of potential environmental justice communities. Other potential uses of this approach include problem formulation in support of risk assessments, land use planning, and prioritization of site cleanup and remediation actions.

SUBMITTER: Davis JA

PROVIDER: S-EPMC4396977 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Can data science inform environmental justice and community risk screening for type 2 diabetes?

Davis J Allen JA Burgoon Lyle D LD

PloS one 20150414 4

<h4>Background</h4>Having the ability to scan the entire country for potential "hotspots" with increased risk of developing chronic diseases due to various environmental, demographic, and genetic susceptibility factors may inform risk management decisions and enable better environmental public health policies.<h4>Objectives</h4>Develop an approach for community-level risk screening focused on identifying potential genetic susceptibility hotpots.<h4>Methods</h4>Our approach combines analyses of p ...[more]

PMID: 25875676

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Project description:ObjectiveCurrent studies lack a comprehensive understanding of the environmental factors influencing type 2 diabetes, hindering an in-depth grasp of the overall etiology. To address this gap, we utilized network science tools to highlight research trends, knowledge structures, and intricate relationships among factors, offering a new perspective for a profound understanding of the etiology.MethodsThe Web of Science database was employed to retrieve documents relevant to environmental risk factors in type 2 diabetes from 2012 to 2024. Bibliometric analysis using Microsoft Excel and OriginPro provided a detailed scientific production profile, including articles, journals, countries, and authors. Co-occurrence analysis was employed to determine the collaboration state and knowledge structures, utilizing social network tools such as Gephi, Tableau, and R Studio. Additionally, theme evolutionary analysis was conducted using SciMAT to offer insights into research trends.ResultsThe publications and themes related to environmental factors in type 2 diabetes have consistently risen, shaping a well-established research domain. Lifestyle environmental factors, particularly diet and nutrition, stand out as the most represented and rapidly growing topics. Key focal hotspots include sedentary and digital behavior, PM2.5, ethnicity and socioeconomic status, traffic and greenspace, and depression. The theme evolutionary analysis revealed three distinct paths: (1) oxidative stress-air pollutants-PM2.5-air pollutants; (2) calcium-metabolic syndrome-cardiovascular disease; and (3) polychlorinated biphenyls (PCBs)-persistent organic pollutants (POPs)-obesity.ConclusionsDigital behavior signifies a novel approach for preventing and managing type 2 diabetes. The influence of PM2.5 and calcium on oxidative stress and abnormal vascular contraction is intricately linked to microvascular diabetes complications. The transition from PCBs and POPs to obesity underscores the disruption of endocrine function by chemicals, elevating the risk of diabetes. Future studies should explore the connections between environmental factors, microvascular complications, and long-term outcomes in diabetes.

Project description:BackgroundDespite indoor home environments being where people spend most time, involving residents in testing those environments has been very limited, especially in marginalized communities. We piloted participatory testing and reporting that combined relatively simple tests with actionable reporting to empower residents in Main South/Piedmont neighborhoods of Worcester, Massachusetts. We answered: 1) How do we design and implement the approach for neighborhood and household environments using participatory methods? 2) What do pilot tests reveal? 3) How does our experience inform testing practice?MethodsThe approach was designed and implemented with community partners using community-based participatory research. Residents and researchers tested fourteen homes for: lead in dust indoors, soil outdoors, paint indoors and drinking water; radon in basement air; PM2.5 in indoor air; mold spores in indoor/outdoor air; and drinking water quality. Monitoring of neighborhood particulates by residents and researchers used real-time data to stimulate dialogue.ResultsGiven the newness of our partnership and unforeseen conflicts, we achieved moderate-high success overall based on process and outcome criteria: methods, test results, reporting, lessons learned. The conflict burden we experienced may be attributable less to generic university-community differences in interests/culture, and more to territoriality and interpersonal issues. Lead-in-paint touch-swab results were poor proxies for lead-in-dust. Of eight units tested in summer, three had very high lead-in-dust (>1000 microg/ft2), six exceeded at least one USEPA standard for lead-in-dust and/or soil. Tap water tests showed no significant exposures. Monitoring of neighborhood particulates raised awareness of environmental health risks, especially asthma.ConclusionsTimely reporting back home-toxics' results to residents is ethical but it must be empowering. Future work should fund the active participation of a few motivated residents as representatives of the target population. Although difficult and demanding in time and effort, the approach can educate residents and inform exposure assessment. It should be considered as a core ingredient of comprehensive household toxics' testing, and has potential to improve participant retention and the overall positive impact of long-term environmental health research efforts.

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Can data science inform environmental justice and community risk screening for type 2 diabetes?

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Can data science inform environmental justice and community risk screening for type 2 diabetes?

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