Neighborhood Social Environment and Patterns of Depressive Symptoms Among Patients with Type 2 Diabetes Mellitus

Abstract

This study sought to examine whether neighborhood social environment was related to patterns of depressive symptoms among primary care patients with type 2 diabetes mellitus (DM). Neighborhood social environment was assessed in 179 patients with type 2 DM. Individual patient residential data at baseline was geo-coded at the tract level and was merged with measures of neighborhood social environment. Depressive symptoms at baseline and at 12-week follow up were assessed using the nine-item Patient Health Questionnaire (PHQ-9). Patients in neighborhoods with high social affluence, high residential stability, and high neighborhood advantage were much less likely to have a persistent pattern of depressive symptoms compared to a pattern of few or no depressive symptoms (adjusted odds ratio (OR) = 0.06, 95% confidence interval (CI) [0.01, 0.36]). Detrimental neighborhood influences may amplify risk for persistent depressive symptoms.

Impact of Demographic, Socioeconomic, and Psychological Factors on Glycemic Self-Management in Adults with Type 2 Diabetes Mellitus

“…Additionally, living in a neighborhood with limited access to healthy food and safe places to exercise can be a significant barrier for diabetes self-care and poorer glycemic control ( 14 , 54 ). O’Donnell et al suggested that patients living in a neighborhood with high social influence, high residential stability, and high neighborhood advantage are much less likely to experience depression ( 55 ).…”

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review

“…With regards to the domain of non-diabetes medical related variables, chronic kidney disease (n = 6, 4.1%) [10,26,56,65,68,132], hypertension (n = 5, 3.4%) [71,102,149,150], and cardiovascular disease related (n = 3, 2.0%) [50,51,102]. Pertaining to the domain of psychiatric / psychological related variables, depression/anxiety related (n = 9, 6.1%) [21,27,29,35,42,46,[154][155][156] and other psychiatric disorders/symptoms related (n = 5, 3.4%) [22,35,42,62,131] variables were most commonly employed. Lastly for the health systems related domain, types of healthcare utilization (n = 2, 1.4%) [160,161] and type/specialty of care providers (n = 2, 1.4%) [64,77] related variables were most frequently used.…”