Abstract
Introduction
Cardiovascular disease is the leading cause of death among Mississippi adults. Social determinants of health are significant contributors to cardiovascular disease risk and associated mortality as well as health disparities. The authors examined the association between a summary measure of social determinants of health and cardiovascular disease among Mississippi adults.
Methods
Using the social determinants of health and health equity module data from 3,994 respondents to the 2022 Mississippi Behavioral Risk Factor Surveillance System survey, the authors conducted multivariable logistic regression models to examine the association between cardiovascular disease and a social determinants of health/health equity summary measure.
Results
Participants who received food stamps or were enrolled in the Supplemental Nutrition Assistance Program (AOR=2.28; 95% CI=1.35, 3.86), experienced food insecurity (AOR=1.74; 95% CI=1.08, 2.79), and experienced mental distress (AOR=2.39; 95% CI=1.54, 3.73) had significantly higher odds of cardiovascular disease than their counterparts without any of these factors. Mississippi adults experiencing 4 or more of social determinants of health/health equity risk factors had a 2.56 (AOR=2.56; 95% CI=1.49, 4.41) higher odds of cardiovascular disease than those experiencing no social determinants of health/health equity risk factors.
Conclusions
Mississippi adults with 4 or more social determinants of health/health equity risk factors had significantly higher odds of cardiovascular disease than those with no social determinants of health/health equity risk factors. These findings highlight the importance of social determinants of health/health equity factors in cardiovascular disease burden and suggest that interventions targeted at individuals with multiple social determinants of health/health equity risk factors are needed to reduce the high burden of cardiovascular disease among Mississippi adults.
Keywords: Behavioral Risk Factor Surveillance System, cardiovascular disease, health equity, Mississippi, social determinants of health
HIGHLIGHTS
-
•
Food insecurity and mental distress had higher odds of cardiovascular disease (CVD).
-
•
Mississippians with multiple social determinants of health had higher odds of CVD.
-
•
Findings highlight the importance of social determinants of health in CVD burden.
-
•
Interventions for adults with multiple social determinants of health are warranted.
INTRODUCTION
Cardiovascular disease (CVD) is the leading cause of death1 and a contributor to health disparities in Mississippi.2 In 2022, Mississippi's age-adjusted death rates due to heart disease and stroke were 248.1 (Blacks: 268.0; Whites: 238.4) and 54.2 (Blacks: 69.5; Whites: 47.3) deaths per 100,000 population, respectively.1 In a recent study, the authors found a statistically significant 1.7% average annual increase in the CVD rate from 2011 through 2018 for Mississippi adults aged 55–64 years.2
Social determinants of health (SDOH) are those conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.3 Political, social, and economic factors4 shape SDOH, which include social conditions such as safe housing, transportation, neighborhood characteristics, racism, discrimination, violence, education, access to nutritious foods, and literacy skills.3 SDOH domains include economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social and community contexts.3
SDOH significantly impact CVD risk and outcomes,5, 6, 7, 8 particularly among marginalized communities.6 In a recent review of the influence of SDOH on CVD,6 Teshale et al.6 (2023) reported that lower composite SES, homelessness, household instability, food insecurity, and lifetime perceived racial discrimination were associated with CVD, and poor/lack of social support was associated with an increased risk of myocardial infarction. In 2017, Behavioral Risk Factor Surveillance System (BRFSS) data from 17 states indicated that experiencing food (AOR=1.51) and housing (AOR=1.54) insecurity increased the odds of CVD.9 Massachusetts adult respondents who reported experiencing at least 1 SDOH had increased odds of self-rated fair/poor health compared with those who reported no adverse SDOH.10
Because SDOH risk factors or experiences are highly interrelated, a composite measure of SDOH will be informative and more practical than a focus on individual social risk factors when evaluating the overall impact of SDOH on health outcomes.11 Although prior research has indicated that there are strong associations between social conditions and risk of CVD, data on summary measures of SDOH/health equity (HE) and CVD in Mississippi, a state with persistent CVD-related health disparities,2 are limited. Therefore, in this study, we examined the associations between a summary measure of SDOH/HE and CVD burden among Mississippi adults.
METHODS
Study Sample
The authors analyzed data from the 2022 Mississippi BRFSS, including the SDOH/HE module. The BRFSS is a state-based, random-digit-dialed telephone survey of the U.S. non-institutionalized civilian population aged ≥18 years. The survey is conducted in all 50 states, the District of Columbia, and 3 U.S. territories (Puerto Rico, Guam, and the U.S. Virgin Islands). Data from the BRFSS provide reliable and valid assessments of health risk factors.12 The BRFSS was approved by human research review boards at the department of health in each state. Detailed information about BRFSS is available elsewhere (www.cdc.gov/brfss/). Analyses were restricted to respondents who self-identified as either Black or White (N=3,994); these racial groups accounted for 96.6% of the Mississippi population in 2022.1 This study was deemed exempt by the Jackson State University IRB.
Measures
CVD was defined as a yes response to the following question: Has a doctor, nurse, or other health professional ever told you that you had any of the following? 1) a heart attack, also called a myocardial infarction, 2) angina or coronary heart disease, 3) a stroke?
In 2022, 39 states, the District of Columbia, and 2 U.S. territories (Puerto Rico and the U.S. Virgin Islands) collected SDOH/HE data. The authors used responses to 10 questions from the 2022 SDOH/HE module. These questions, which were based on the Center for Medicare and Medicaid Innovation Social Needs Assessment Tool,11 asked about employment/economic stability (In the past 12 months have you lost employment or had hours reduced?), receiving food stamps or Supplemental Nutrition Assistance Program (SNAP) (During the past 12 months, have you received food stamps, also called SNAP, the Supplemental Nutrition Assistance Program on an EBT card?), housing stability and quality (During the last 12 months, was there a time when you were not able to pay your mortgage, rent or utility bills?), food security (During the past 12 months how often did the food that you bought not last, and you didn't have money to get more?), transportation access (During the past 12 months has a lack of reliable transportation kept you from medical appointments, meetings, work, or from getting things needed for daily living?), utilities security (During the last 12 months was there a time when an electric, gas, oil, or water company threatened to shut off services?), social isolation (How often do you feel socially isolated from others?), social and emotional support (How often do you get the social and emotional support that you need?), life satisfaction (In general, how satisfied are you with your life?), and mental well-being (Stress means a situation in which a person feels tense, restless, nervous or anxious or is unable to sleep at night because their mind is troubled all the time. Within the last 30 days, how often have you felt this kind of stress?).11
To create an SDOH/HE summary measure, the authors categorized the responses to each SDOH/HE item as 0 (minimal/no experience) or 1 (experience of the SDOH/HE risk factor) and then summed all scores. The resulting summary SDOH/HE scores range from 0 to 10; the authors then categorized respondents as having 0, 1, 2, 3, or ≥4 social risk factors.11
Statistical Analysis
The authors used chi-square tests to assess the associations between individual SDOH/HE variables and CVD. A logistic regression model was then conducted to estimate AORs and 95% CIs for the associations between each individual measure of SDOH/HE and CVD as well as the association between the summary measure of SDOH/HE and CVD. The logistic regression model included age, race, sex, education, income, smoking, exercise, insurance, BMI, and diabetes status. SAS, Version 9.4 (SAS Institute, Inc.), was used to perform all statistical analyses, accounting for the complex sample design. Results were significant at p<0.05.
RESULTS
The mean age of respondents was 49.0 years. More than one third of sample members (37.6%) were non-Hispanic Black, more than half (53.7%) were women, and 44.0% had an annual household income ≥$50,000 (Table 1). CVD prevalence was 12.4%, and the likelihood of experiencing 0, 1, 2, 3, or ≥4 SDOH/HE risk factors was 38.9% (95% CI=36.7, 41.0), 21.9% (95% CI=20.0, 23.8), 13.8% (95% CI=12.4, 15.3), 8.5% (95% CI=7.3, 9.7), and 16.9% (95% CI=15.3, 18.6), respectively.
Table 1.
Sociodemographic Characteristics of Mississippi Adults, Behavioral Risk Factor Surveillance System, 2022
| Characteristics | na (%)b | 95% CI |
|---|---|---|
| Age, years | ||
| 18–24 | 386 (11.7) | 10.4, 13.0 |
| 25–44 | 1,121 (31.5) | 29.7, 33.3 |
| 45–64 | 1,420 (32.2) | 30.4, 34.0 |
| ≥65 | 1,067 (24.6) | 23.0, 26.3 |
| Race/ethnicity | ||
| Non-Hispanic Black | 1,524 (37.6) | 35.7, 39.5 |
| Non-Hispanic White | 2,470 (62.4) | 60.5, 64.3 |
| Sex | ||
| Male | 1,736 (46.3) | 44.3, 48.3 |
| Female | 2,258 (53.7) | 51.7, 55.7 |
| Education level | ||
| Less than high school graduate | 371 (14.5) | 12.8, 16.2 |
| High school graduate or equivalent | 1,042 (30.5) | 28.6, 32.4 |
| Higher than high school graduate | 2,574 (55.0) | 53.0, 57.0 |
| Annual household income, $ | ||
| <15,000 | 279 (9.2) | 7.9, 10.6 |
| 15,000 to <25,000 | 447 (13.6) | 12.1, 15.1 |
| 25,000 to <35,000 | 507 (16.3) | 14.7, 17.9 |
| 35,000 to <50,000 | 541 (16.9) | 15.3, 18.6 |
| ≥50,000 | 1,495(44.0) | 41.8, 46.2 |
| Current smoking status | ||
| Yes | 595 (17.1) | 15.5, 18.6 |
| No | 3,206 (82.9) | 81.4, 84.5 |
| Physical activity or exercise | ||
| Yes | 2,737 (67.6) | 65.7, 69.5 |
| No | 1,251 (32.4) | 30.5, 34.3 |
| Health insurance | ||
| Yes | 3,497 (90.6) | 89.4, 91.8 |
| No | 317 (9.4) | 8.2, 10.6 |
Unweighted sample.
Weighted percentage.
Among respondents, 6.4% reported being dissatisfied or very dissatisfied with their life, whereas 31.3% reported that they only sometimes or rarely/never received support for their social and emotional needs. One third of respondents (33.4%) reported that they always, usually, or sometimes felt socially isolated, and 10.4% reported that they had lost employment or had their working hours reduced in the past 12 months. Material hardship was common in this cohort: 12.9% reported that they received food stamps or SNAP benefits; 20.7% reported that they always, usually, or sometimes experienced food insecurity; 14.1% reported that they experienced housing insecurity; 9.4% reported that their electric, gas, oil, or water company had threatened to shut off services; and 10.1% reported lacking reliable transportation (all during the past 12 months). In addition, 15.9% of respondents reported being stressed in the past 30 days. Four of the individual SDOH/HE factors—receiving food stamps or SNAP (p=0.0003), food insecurity (p≤0.0001), housing insecurity (p=0.0267), and a lack of reliable transportation (p=0.0015)—as well as the summary measure of SDOH/HE (p=0.0029) were significantly associated with CVD (Table 2).
Table 2.
Social Determinants of Health and Health Equity Characteristics and CVD Among Mississippi Adults, BRFSS, 2022
| Characteristics | CVD, %a | 95% CI | p-valueb | |
|---|---|---|---|---|
| Life satisfaction | ||||
| Dissatisfied/very dissatisfied | 17.2 | 11.3, 23.0 | 0.0906 | |
| Satisfied/very satisfied | 12.5 | 11.0, 14.0 | ||
| Social and emotional support | ||||
| Sometimes/rarely/never | 14.6 | 11.8, 17.4 | 0.0873 | |
| Always/usually | 11.6 | 10.2, 13.5 | ||
| Social isolation | ||||
| Always/usually/sometimes | 13.8 | 11.3, 16.4 | 0.3106 | |
| Rarely/never | 12.2 | 10.5, 14.0 | ||
| Lost or reduced hours for employment | ||||
| Yes | 8.8 | 5.2, 12.5 | 0.0536 | |
| No | 13.4 | 11.8, 14.9 | ||
| Receiving food stamps or SNAP | ||||
| Yes | 19.8 | 14.8, 24.9 | 0.0003 | |
| No | 11.7 | 10.2, 13.1 | ||
| Food insecurity | ||||
| Always/usually/sometimes | 18.5 | 14.6, 22.4 | <0.0001 | |
| Rarely/never | 11.1 | 9.6, 12.6 | ||
| Housing insecurity | ||||
| Yes | 16.9 | 12.5, 21.3 | 0.0267 | |
| No | 12.1 | 10.6, 13.6 | ||
| Threatened total shut off of utility services | ||||
| Yes | 15.1 | 9.9, 20.2 | 0.3453 | |
| No | 12.6 | 11.1, 14.1 | ||
| Lack of reliable transportation | ||||
| Yes | 20.2 | 14.3, 26.0 | 0.0015 | |
| No | 12.0 | 10.6, 13.5 | ||
| Mental distress | ||||
| Always/usually | 15.9 | 11.9, 19.6 | 0.0568 | |
| Sometimes/rarely/never | 12.1 | 10.5, 13.6 | ||
| Summary measure of SDOH/HE | ||||
| 0 | 9.9 | 8.0, 11.8 | 0.0029 | |
| 1 | 12.0 | 8.8, 15.3 | ||
| 2 | 13.3 | 9.2, 17.4 | ||
| 3 | 12.9 | 7.8, 18.0 | ||
| ≥4 | 18.6 | 14.2, 23.0 | ||
Note: Boldface indicates statistical significance (p<0.05).
Weighted percentage.
Determined by chi-square test.
BRFSS, Behavioral Risk Factor Surveillance System; CVD, cardiovascular disease; SDOH/HE, social determinants of health and health equity; SNAP, Supplemental Nutrition Assistance Program.
Respondents who received food stamps or SNAP (AOR=2.28; 95% CI=1.27, 4.09), experienced food insecurity (AOR=1.74; 95% CI=1.08, 2.79), and experienced mental distress (AOR=2.39; 95% CI=1.54, 3.73) had significantly higher odds of CVD than their counterparts without any of these factors. Mississippi adults experiencing 4 or more SDOH/HE risk factors had a 2.56 (AOR=2.56; 95% CI=1.49, 4.41) higher odds of CVD than those who experienced no SDOH/HE risk factors (Table 3).
Table 3.
Odds of Individual and Summary Measure of SDOH/HE and CVD Among Mississippi Adults, BRFSS, 2022
| Characteristics | Model 1 |
Model II |
||
|---|---|---|---|---|
| ORa | 95% CI | AORb | 95% CI | |
| SDOH/HE characteristics | ||||
| Life satisfaction | 1.45 | 0.94, 2.23 | 1.35 | 0.67, 2.67 |
| Social and emotional support | 1.27 | 0.97, 1.68 | 1.25 | 0.87, 1.82 |
| Social isolation | 1.15 | 0.88, 1.51 | 1.31 | 0.90, 1.89 |
| Lost or reduced hours for employment | 0.63 | 0.39, 1.01 | 1.13 | 0.60, 2.14 |
| Receiving food stamps or SNAP | 1.88 | 1.33, 2.65 | 2.28 | 1.27, 4.09 |
| Food insecurity | 1.82 | 1.35, 2.47 | 1.74 | 1.08, 2.79 |
| Housing insecurity | 1.47 | 1.04, 2.07 | 1.34 | 0.05, 2.27 |
| Threatened total shut off of utility services | 1.23 | 0.80, 1.88 | 1.48 | 0.86, 2.56 |
| Lack of reliable transportation | 1.85 | 1.26, 2.73 | 1.62 | 0.95, 2.76 |
| Mental distress | 1.38 | 0.99, 1.92 | 2.39 | 1.54, 3.73 |
| Summary measure of SDOH/HE | ||||
| 0 (ref) | 1.00 | 1.00 | ||
| 1 | 1.25 | 0.86, 1.81 | 1.09 | 0.67, 1.77 |
| 2 | 1.40 | 0.92, 2.12 | 1.42 | 0.83, 2.47 |
| 3 | 1.35 | 0.82, 2.23 | 1.71 | 0.87, 4.41 |
| ≥4 | 2.08 | 1.45, 2.98 | 2.56 | 1.49, 4.41 |
Note: Boldface indicates statistical significance (p<0.05).
Unadjusted.
Adjusted for age, race, sex education, income, smoking, exercise, insurance, BMI, and diabetes.
BRFSS, Behavioral Risk Factor Surveillance System; CVD, cardiovascular disease; SODH/HE, social determinant of health and health equity; SNAP, Supplemental Nutrition Assistance Program.
DISCUSSION
Among Mississippi adults, 3 individual measures and a summary measure of SDOH/HE risk factors were associated with CVD. Mississippi adult respondents who reported receipt of food stamps or SNAP, food insecurity, and mental distress had significantly higher odds of CVD than their counterparts without any of these factors. In addition, Mississippi adults who reported experiencing 4 or more SDOH/HE risk factors had significantly higher odds of CVD than those experiencing no SDOH/HE risk factors.
These results align with the findings of a 2017 BRFSS study on the basis of data from 17 states, which demonstrated that food insecurity and financial insecurity were associated with increased odds of CVD.9 Similarly, a recent systematic review of 19 epidemiologic studies showed that food insecurity was associated with multiple CVD complications, including mortality, frequent hospitalizations, and readmissions.13 Paralleling our finding that among Mississippi adults, receipt of food stamps or SNAP was associated with increased odds of CVD, an analysis of data from the National Health Interview Survey documented that respondents who participated in SNAP had higher total and CVD mortality than SNAP-eligible nonparticipants.14
The authors also found that experiencing a higher number of SDOH/HE risk factors was associated with increased CVD burden in Mississippi adults. Among adults residing in Massachusetts, those who reported experiencing at least 1 SDOH risk factor had significantly increased odds of fair or poor health compared with those who reported 0 SDOH/HE factors.10 An analysis of data from the 2017 BRFSS from 17 states showed that respondents who reported experiencing 4 or more social risk factors had nearly twice the odds of having arthritis as those with no risk factors.15 In the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study, a high burden of SDOH was associated with a gradual increase in the risk of incident coronary heart disease.16
Targeted scaled-up evidence-based interventions at the intersection of public health and community development are crucial to addressing SDOH-associated health inequities.17 Interventions that provide support in a variety of SDOH domains significantly improve population health and advance health equity.17,18 The U.S. HHS Office of Health Policy documented successful evidence-based strategies for addressing SDOH.18 The HHS-recommended neighborhood-level strategies include supportive housing to individuals with chronic diseases and access to healthy food environments and affordable transportation options.18 Programs that help facilitate access to resources and provide financial incentives for low-income individuals and those with disabilities have also been shown to improve quality of life and desirable health outcomes.17,18 Finally, high-quality care coordination and well-integrated healthcare and support services are central to efforts to identify unmet needs in the interest of informing treatment priorities for individuals negatively impacted by multiple SDOH.18
Limitations
The findings are subject to 3 significant limitations. First, the BRFSS data on SDOH/HE measures were self-reported and thus are subject to recall and social desirability bias.19 Second, the analysis of SDOH/HE module data was limited to certain SDOH/HE items. Data constraints prevented the researchers from considering other SDOH/HE domains, including early childhood development, neighborhood and built environment, and discrimination. The authors acknowledge the importance of assessing these domains in relation to CVD risk in future studies. Finally, the associations were cross-sectional and thus do not permit causal inferences.
CONCLUSIONS
Mississippi adults who experienced 4 or more SDOH/HE risk factors had 2.5-fold higher odds of CVD than those with no SDOH/HE risk factors. Addressing individual measures of SDOH/HE in isolation is unlikely to significantly reduce CVD burden.6 Rather, reducing the impact of SDOH/HE may require a broad range of actions that entail collaboration between multiple sectors, including education; the justice system; employment; and local, state, and federal governments.20,21 Interventions aimed at improving a summary measure of SDOH/HE risk factors will help reduce CVD burden among Mississippi adults.
CRediT authorship contribution statement
Vincent L. Mendy: Conceptualization, Methodology, Formal analysis, Writing – original draft. Tawandra L. Rowell-Cunsolo: Writing – review & editing. Byambaa Enkhmaa: Writing – review & editing.
ACKNOWLEDGMENTS
Disclaimers: The content is solely the responsibility of the authors and does not represent the official views of the NIH.
Funding: Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities of the NIH under Award Number 5U4MD015929-04 and by the Department of Education, Historically Black Graduates Institutes Grant Number P031K190018.
Declaration of interest: none.
REFERENCES
- 1.The Mississippi STatistically Automated Health Resource System (MSTAHRS). Mississippi State Department of Health, Office of Vital Records & Public Health Statistics. https://mstahrs.msdh.ms.gov/. Updated November 17, 2022. Accessed January 24, 2024.
- 2.Mendy VL, Rowell-Cunsolo T, Bellerose M, Vargas R, Enkhmaa B, Zhang L. Cardiovascular disease mortality in Mississippi, 2000–2018. Prev Chronic Dis. 2022;19:E09. doi: 10.5888/pcd19.210385. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Social Determinants of Health. Healthy People 2030, HHS, Office of Disease Prevention and Health Promotion. https://health.gov/healthypeople/priority-areas/social-determinants-health. Updated July 24, 2024. Accessed January 24, 2024.
- 4.WHO . WHO; Geneva, Switzerland: 2008. Closing the gap in a generation: health equity through action on the social determinants of health - final report of the Commission on Social Determinants of Health.https://www.who.int/publications/i/item/9789241563703 PublishedAccessed January 24, 2024. [DOI] [PubMed] [Google Scholar]
- 5.Powell-Wiley TM, Baumer Y, Baah FO, et al. Social determinants of cardiovascular disease. Circ Res. 2022;130(5):782–799. doi: 10.1161/CIRCRESAHA.121.319811. https://DOI.ORG/10.1161/CIRCRESAHA.121.319811 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Teshale AB, Htun HL, Owen A, et al. The role of social determinants of health in cardiovascular diseases: an umbrella review. J Am Heart Assoc. 2023;12(13) doi: 10.1161/JAHA.123.029765. https://DOI.ORG/10.1161/JAHA.123.029765 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Martin SS, Aday AW, Almarzooq ZI, et al. 2024 Heart disease and stroke statistics: a report of U.S. and global data from the American Heart Association. Circulation. 2024;149(8):e347–e913. doi: 10.1161/CIR.0000000000001209. https://DOI.ORG/10.1161/CIR.0000000000001209 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kershaw KN, Magnani JW, Diez Roux AV, et al. Neighborhoods and cardiovascular health: a scientific statement from the American Heart Association. Circ Cardiovasc Qual Outcomes. 2024;17(1) doi: 10.1161/HCQ.0000000000000124. https://DOI.ORG/10.1161/HCQ.0000000000000124 [DOI] [PubMed] [Google Scholar]
- 9.Parekh T, Desai R, Pemmasani S, Cuellar A. Impact of social determinants of health on cardiovascular diseases. J Am Coll Cardiol. 2020;75(11):1989. doi: 10.1016/S0735-1097(20)32616-4. (suppl 2) [DOI] [Google Scholar]
- 10.Nelson CC. Using a social determinants of health summary measure to predict general health status in the BRFSS. Am J Health Promot. 2022;36(2):301–304. doi: 10.1177/08901171211044994. [DOI] [PubMed] [Google Scholar]
- 11.Centers for Disease Control and Prevention . Centers for Disease Control and Prevention; Atlanta, GA: 2023. Statistical brief on the social determinants of health and health equity module, behavioral risk factor surveillance system, 2022.https://www.cdc.gov/brfss/data_documentation/pdf/SDOH-Module-Statistical-Brief-508c.pdf Published August 15Accessed January 24, 2024. [Google Scholar]
- 12.Pierannunzi C, Hu SS, Balluz L. A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS), 2004–2011. BMC Med Res Methodol. 2013;13:49. doi: 10.1186/1471-2288-13-49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Parekh T, Xue H, Cheskin LJ, Cuellar AE. Food insecurity and housing instability as determinants of cardiovascular health outcomes: a systematic review. Nutr Metab Cardiovasc Dis. 2022;32(7):1590–1608. doi: 10.1016/j.numecd.2022.03.025. [DOI] [PubMed] [Google Scholar]
- 14.Conrad Z, Rehm CD, Wilde P, Mozaffarian D. Cardiometabolic mortality by supplemental nutrition assistance program participation and eligibility in the United States. Am J Public Health. 2017;107(3):466–474. doi: 10.2105/AJPH.2016.303608. https://DOI.ORG/10.2105/AJPH.2016.303608 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Rethorn ZD, Rethorn TJ, Cook CE, Sharpe JA, Hastings SN, Allen KD. Association of burden and prevalence of arthritis with disparities in social risk factors, findings from 17 U.S. states. Prev Chronic Dis. 2022;19:E08. doi: 10.5888/pcd19.210277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Safford MM, Reshetnyak E, Sterling MR, et al. Number of social determinants of health and fatal and nonfatal incident coronary heart disease in the REGARDS study. Circulation. 2021;143(3):244–253. doi: 10.1161/circulationaha.120.048026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Thornton RL, Glover CM, Cené CW, Glik DC, Henderson JA, Williams DR. Evaluating strategies for reducing health disparities by addressing the social determinants of health. Health Aff (Millwood) 2016;35(8):1416–1423. doi: 10.1377/hlthaff.2015.1357. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Whitman A, De Lew N, Chappel A, Aysola V, Zuckerman R, Sommers BD. Addressing social determinants of health: examples of successful evidence-based strategies and current federal efforts. Washington, DC: Office of the Assistant Secretary for Planning and Evaluation. Office of Health Policy, HHS. https://aspe.hhs.gov/sites/default/files/documents/e2b650cd64cf84aae8ff0fae7474af82/SDOH-Evidence-Review.pdf. Published April 1, 2022. Accessed August 20, 2024.
- 19.Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211–217. doi: 10.2147/jmdh.s104807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Andermann A, CLEAR Collaboration Taking action on the social determinants of health in clinical practice: a framework for health professionals. CMAJ. 2016;188(17–18):E474–E483. doi: 10.1503/cmaj.160177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Satcher D. Include a social determinants of health approach to reduce health inequities. Public Health Rep. 2010;125(suppl 4):6–7. doi: 10.1177/00333549101250S402. [DOI] [PMC free article] [PubMed] [Google Scholar]