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Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population.

ABSTRACT: Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies. Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), a local diabetes and chronic disease management program, between October 2013 and September 2018 recruited from a local clinic. The primary outcome was the reduction of hemoglobin A1C (HbA1C) at the last follow-up visit compared to the baseline. In addition to age, gender, insurance status, education level and marital status, we also investigated 15 community (census tract) SDOH using the American Community Survey. Because of the high correlation in the community SDOH, we developed the community-level indices representing different domains. Using Bayesian multilevel spatial models that account for the geographic dependency, we were able to simultaneously investigate the individual- and community-level SDOH that may impact HbA1C reduction. Results: After accounting for the diabetes self-management education classes taken by the participants and their length of stay in the program, we found that older age at baseline, being married (compared to being widowed or divorced) and English speaking (compared to Spanish) were significantly associated with greater HbA1C reduction. Moreover, we found that the community level SDOH were also highly associated with HbA1C reduction. With every percentile rank decrease in the socioeconomic advantage index, we estimated an additional 0.018% reduction in HbA1C [95% CI (-0.028, -0.007)]. Besides the socioeconomic advantage index, urban core opportunity and immigrant's cohesion and accessibility indices were also statistically associated with HbA1C reduction. Conclusion: To our knowledge, our study is the first to utilize Bayesian multilevel spatial models and simultaneously investigate both individual- and community-level SDOH in the context of diabetes management. Our findings suggest that community SDOH play an important role in diabetes control and management, and the need to consider community and neighborhood context in future interventions programs to maximize their overall effectiveness.

SUBMITTER: Zhang K

PROVIDER: S-EPMC7888279 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population.

Zhang Kehe K Reininger Belinda B Lee Miryoung M Xiao Qian Q Bauer Cici C

Frontiers in public health 20210203

Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies. Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), ...[more]

PMID: 33614572

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Project description:Diabetes is a common chronic condition affecting the many spheres of individuals' lives. It can also lead to severe complications without continuous management. Accordingly, this paper describes a study protocol aimed at 1) determining the status and prevalence of diabetes complications in a Northwestern Ontario community; 2) exploring the internal (e.g., demographic and clinical variables) and external factors (e.g., access to services and resources) affecting diabetes outcomes (e.g., complications, emergency room visits, hospitalizations); 3) critically exploring how the social determinants of health affect self-management for individuals living with diabetes; and 4) identifying individuals' needs, concerns, and challenges to monitor and regulate diabetes. The study uses a cross-sectional design and a social constructivist approach based on qualitative data collection. The proposed study will include patients with type 1 and type 2 diabetes with or without diabetes complications who have been attending the Centre for Complex Diabetes Care (CCDC) in Thunder Bay, Ontario, Canada, since January 2019. Quantitative data related to diabetes complications and other outcomes, diabetes management, and demographic and clinical status will be retrieved from patients' charts using a data extraction form. Analyses of the quantitative data will include the prevalence of diabetes complications, rate of hospitalizations, and their associations with diabetes management, access to services, and social determinants of health. Additionally, interviews will occur with at least 10 participants with or without diabetes complications to understand their needs, concerns, and struggle to self-manage diabetes daily. The results of this study will generate evidence to support future research and policy on the development and implementation of an educational program to improve self-care management and outcomes for individuals living with diabetes and its complications in Northwestern Ontario.

Project description:BackgroundWith the increased availability of data, a growing number of studies have been conducted to address the impact of social determinants of health (SDOH) factors on population health outcomes. However, such an impact is either examined at the county level or the state level in the United States. The results of analysis at lower administrative levels would be useful for local policy makers to make informed health policy decisions.ObjectiveThis study aimed to investigate the ecological association between SDOH factors and population health outcomes at the census tract level and the city level. The findings of this study can be applied to support local policy makers in efforts to improve population health, enhance the quality of care, and reduce health inequity.MethodsThis ecological analysis was conducted based on 29,126 census tracts in 499 cities across all 50 states in the United States. These cities were grouped into 5 categories based on their population density and political affiliation. Feature selection was applied to reduce the number of SDOH variables from 148 to 9. A linear mixed-effects model was then applied to account for the fixed effect and random effects of SDOH variables at both the census tract level and the city level.ResultsThe finding reveals that all 9 selected SDOH variables had a statistically significant impact on population health outcomes for ≥2 city groups classified by population density and political affiliation; however, the magnitude of the impact varied among the different groups. The results also show that 4 SDOH risk factors, namely, asthma, kidney disease, smoking, and food stamps, significantly affect population health outcomes in all groups (P<.01 or P<.001). The group differences in health outcomes for the 4 factors were further assessed using a predictive margin analysis.ConclusionsThe analysis reveals that population density and political affiliation are effective delineations for separating how the SDOH affects health outcomes. In addition, different SDOH risk factors have varied effects on health outcomes among different city groups but similar effects within city groups. Our study has 2 policy implications. First, cities in different groups should prioritize different resources for SDOH risk mitigation to maximize health outcomes. Second, cities in the same group can share knowledge and enable more effective SDOH-enabled policy transfers for population health.

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Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population.

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Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population.

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