Inequalities in glycemic and multifactorial cardiovascular control of type 2 diabetes: The Heart Healthy Hoods study

Modifying effect of urban parks on socioeconomic inequalities in diabetes prevalence: a cross-sectional population study of Madrid City, Spain

BACKGROUND

Evidence has shown contradicting results on how the density of urban green spaces may reduce socioeconomic inequalities in type 2 diabetes (equigenic hypothesis). The aim of this study is to test whether socioeconomic inequalities in diabetes prevalence are modified by park density.

METHODS

We designed a population-wide cross-sectional study of all adults registered in the primary healthcare centres in the city of Madrid, Spain (n=1 305 050). We obtained georeferenced individual-level data from the Primary Care Electronic Health Records, and census-tract level data on socioeconomic status (SES) and park density. We modelled diabetes prevalence using robust Poisson regression models adjusted by age, country of origin, population density and including an interaction term with park density, stratified by gender. We used this model to estimate the Relative Index of Inequality (RII) at different park density levels.

FINDINGS

We found an overall RII of 2.90 (95% CI 2.78 to 3.02) and 4.50 (95% CI 4.28 to 4.74) in men and women, respectively, meaning that the prevalence of diabetes was three to four and a half times higher in low SES compared with high SES areas. These inequalities were wider in areas with higher park density for both men and women, with a significant interaction only for women (p=0.008).

INTERPRETATION

We found an inverse association between SES and diabetes prevalence in both men and women, with wider inequalities in areas with more parks. Future works should study the mechanisms of these findings, to facilitate the understanding of contextual factors that may mitigate diabetes inequalities.

Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions

Background

Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality.

Methods

We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes.

Discussion

Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

The role of neighborhood inequalities on diabetes prevention care: a mini-review

An emerging research niche has focused on the link between social determinants of health and diabetes mellitus, one of the most prevalent non-communicable diseases in modern society. The aim of the present mini-review is to explore and summarize current findings in this field targeting high-income countries. In the presence of disadvantaged neighborhood factors (including socioeconomic status, food environment, walkability and neighborhood aesthetics), diabetes prevention and care are affected at a multidimensional level. The vast majority of the included studies suggest that, besides individual risk factors, aggregated neighborhood inequalities should be tackled to implement effective evidence-based policies for diabetes mellitus.