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Full-Text Articles in Medicine and Health Sciences
Neighborhood Environment And Type 2 Diabetes Comorbidity In Serious Mental Illness, Ramya Walsan, Xiaoqi Feng, Darren J. Mayne, Nagesh B. Pai, Andrew D. Bonney
Neighborhood Environment And Type 2 Diabetes Comorbidity In Serious Mental Illness, Ramya Walsan, Xiaoqi Feng, Darren J. Mayne, Nagesh B. Pai, Andrew D. Bonney
Illawarra Health and Medical Research Institute
Aim: The aim of this study was to examine the association between neighborhood characteristics and type 2 diabetes (T2D) comorbidity in serious mental illness (SMI). We investigated associations of neighborhood-level crime, accessibility to health care services, availability of green spaces, neighborhood obesity, and fast food availability with SMI-T2D comorbidity. Method: A series of multilevel logistic regression models accounting for neighborhood-level clustering were used to examine the associations between 5 neighborhood variables and SMI-T2D comorbidity, sequentially adjusting for individual-level variables and neighborhood-level socioeconomic disadvantage. Results: Individuals with SMI residing in areas with higher crime rates per 1000 population had 2.5 times …
Exploring The Geography Of Serious Mental Illness And Type 2 Diabetes Comorbidity In Illawarra-Shoalhaven, Australia (2010 -2017), Ramya Walsan, Darren J. Mayne, Nagesh B. Pai, Xiaoqi Feng, Andrew D. Bonney
Exploring The Geography Of Serious Mental Illness And Type 2 Diabetes Comorbidity In Illawarra-Shoalhaven, Australia (2010 -2017), Ramya Walsan, Darren J. Mayne, Nagesh B. Pai, Xiaoqi Feng, Andrew D. Bonney
Illawarra Health and Medical Research Institute
Objectives The primary aim of this study was to describe the geography of serious mental illness (SMI)-type 2 diabetes comorbidity (T2D) in the Illawarra-Shoalhaven region of NSW, Australia. The Secondary objective was to determine the geographic concordance if any, between the comorbidity and the single diagnosis of SMI and diabetes. Methods Spatial analytical techniques were applied to clinical data to explore the above objectives. The geographic variation in comorbidity was determined by Moran's I at the global level and the local clusters of significance were determined by Local Moran's I and spatial scan statistic. Choropleth hotspot maps and spatial scan …