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Using geographical random forest models to explore spatial patterns in the neighborhood determinants of hypertension prevalence across chicago, illinois, USA

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References

2015Geographical and Temporal Weighted Regression (GTWR)621 cited
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2020Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic259 cited
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2018Neighbourhood walkability and incidence of hypertension: Findings from the study of 429,334 UK Biobank participants94 cited
2010Does the Relationship Between Neighborhood Socioeconomic Status and Health Outcomes Persist Into Very Old Age? A Population-Based Study89 cited
2021Spatial disparity of individual and collective walking behaviors: A new theoretical framework82 cited

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2015The Non-linear Health Consequences of Living in Larger Cities74 cited

2020The impact of housing conditions on health outcomes56 cited

2021Association between neighbourhood deprivation and hypertension in a US-wide Cohort49 cited

Cited by

2025Assessing the impact of walkability indicators on health outcomes using machine learning algorithms: A case study of Michigan10 cited