ArticleHuman geographies2012
An Introduction to Macro- Level Spatial Nonstationarity: a Geographically Weighted Regression Analysis of Diabetes and Poverty.
Article in Human geographies, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Mortality from type 2 diabetes mellitus across municipalities in Mexico.Archives of public health = Archives belges de sante publique · 2024Article
- Spatial nonstationarity and the role of environmental metal exposures on COVID-19 mortality in New Mexico.Applied geography (Sevenoaks, England) · 2024Article
- Geospatial Modeling Methods in Epidemiological Kidney Research: An Overview and Practical Example.Kidney international reports · 2024Review
- Article
- Age-based spatial disparities of COVID-19 incidence rates in the United States counties.PloS one · 2023Article
- Historical redlining and the epidemiology of present-day firearm violence in the United States: A multi-city analysis.Preventive medicine · 2022Article
- Exploring regional and sociodemographic disparities associated with unenrollment for the disease management program for type 2 Diabetes Mellitus using Bayesian spatial modelling.Research in health services & regions · 2022Article
- Spatial epidemiology of diabetes: Methods and insights.World journal of diabetes · 2021Review
- Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.Scientific reports · 2021Article
- Article
- Geographical clustering and socioeconomic factors associated with hypoglycemic events requiring emergency assistance in Andalusia (Spain).BMJ open diabetes research & care · 2021Article
- Small-scale spatial analysis of intermediate and definitive hosts of Angiostrongylus cantonensis.Infectious diseases of poverty · 2018Article
- Racial differences in spatial patterns for poor glycemic control in the Southeastern United States.Annals of epidemiology · 2018Article
- Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany.BMC public health · 2018Article
- Article
- Do the risk factors for type 2 diabetes mellitus vary by location? A spatial analysis of health insurance claims in Northeastern Germany using kernel density estimation and geographically weighted regression.International journal of health geographics · 2016Article
- Spatial analysis and correlates of county-level diabetes prevalence, 2009-2010.Preventing chronic disease · 2015Review
Corrections and comments
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Authors and funding
3 authors.
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Abstract
Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity-variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes.
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Registered trials
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