Using a Social Determinants of Health Summary Measure to Predict General Health Status in the BRFSS

Abstract

Purpose

This study aims to assess the relationship between social determinants of health (SDoH) burden and overall health.

Design

Three years of Behavioral Risk Factor Surveillance System (BRFSS) data (2017–2019) were combined for this cross-sectional study.

Setting

Massachusetts.

Subjects

Out of a possible 21,312 respondents, 16,929 (79%) were eligible for inclusion.

Measures

To create the SDoH summary measure, items assessing social risk experiences including financial instability (1 item), housing instability (2 items), perceptions of neighborhood crime (1 item), and food insecurity (2 items) were summed to create a count of risk experiences. Outcome measures included self-rated general health, days of poor physical health, and days of poor mental health.

Analysis

Multivariable logistic regression was used to evaluate the association between each outcome and the SDoH summary measure, adjusting for demographic confounders.

Results

In adjusted analyses, respondents who reported experiencing 1, 2, 3, or 4+ SDoH had a 1.6 (95% CI: 1.3–2.0), 2.9 (95% CI: 2.3–3.7), 3.2 (95% CI: 2.4–4.3), or 5.3 (95% CI: 4.0–7.0) increased odds (respectively) of self-rated fair/poor health, compared to those who reported zero SDoH. The adjusted relationship between the SDoH summary measure and physical health and mental health was similar in magnitude and statistically significant.

Conclusions

These results demonstrate that the overall burden of risk due to SDoH is an important predictor of health.

Keywords

social determinants of health measurement summary measure general health mental health behavioral risk factor surveillance system

Purpose

The social determinants of health (SDoH) refer to a broad array of social and contextual experiences that influence health, including but not limited to education, healthcare, economic stability, social and community context, and the built environment.¹ Others have included factors such as racial/ethnic discrimination, occupational exposures, social support, and stress as among the many exposures or characteristics that can be considered SDoH.² These experiences are highly inter-related and inter-dependent, and there is ample evidence that the profound influence that the SDoH have on health is not due to one experience vs another but rather the overall burden of risk conferred by SDoH.³ In addition, researchers have begun to consider new approaches to modeling COVID-19 to better include information on SDoH⁴ and assess the role that SDoH plays in vulnerability vs resilience following a disaster.⁵

The Behavioral Risk Factor Surveillance System (BRFSS) is a national system of health-related telephone surveys, funded by the Centers for Disease Control and Prevention (CDC). These surveys collect statewide data on health-related behaviors, chronic diseases, and utilization of preventive services.⁶ While there is a core set of required questions, CDC has offered “optional modules”—standardized sets of questions on special topics. One such optional module collects information on food insecurity, housing insecurity, financial instability, and stress. This module has evolved over time with the first set of questions introduced in 1996. While the specific questions have changed over time and will continue to change as our knowledge about SDoH increases, the goal—to assess the social, occupational, and financial conditions experienced by individual respondents—has remained the same.⁶

Given the importance of the SDoH, combined with the multitude of measures, there is a need to succinctly describe the overall burden of risk due to SDoH. The objective of this study was to create a single measure that summarizes overall SDoH burden (of a subset of SDoH) and assess the relationship between the SDoH measure and overall health.

Methods

Design

Three years of MA BRFSS data (2017–2019) were combined for this cross-sectional study.

Sample

Out of a possible 21,312 respondents, 16,929 (79%) were eligible for inclusion. To be considered eligible for inclusion, respondents must have provided valid responses to (1) all 3 outcome questions; (2) at least 3 of the 6 SDoH items; and (3) items assessing age, education, gender, and race/ethnicity. This study was conducted using de-identified data and was not considered human subjects research by the Massachusetts Department of Public Health IRB.

Measures

The outcome measures included self-rated general health, days of poor physical health, and days of poor mental health. General health was assessed by asking: “Would you say that in general your health is … excellent, very good, good, fair, or poor?” Responses were collapsed into 2 categories: “excellent/very good/good” vs “fair/poor.” Physical health was assessed by asking: “Thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?” Responses were collapsed into 2 categories: “0-14 days/month” vs “15+ days/month.” Mental health was assessed by asking “Thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?” Responses were collapsed: “0-14 days/month” vs “15+ days/month.”

The MA BRFSS included 6 of the 7 items in the CDC-created SDoH module. The response categories were dichotomized (0 = minimal/no experience vs 1 = experience of the SDoH risk factor). The following items were included: (1) housing instability (2 items): “During the last 12 months, was there a time when you were not able to pay your mortgage, rent or utility bills?” (no/yes) and “In the last 12 months, how many times have you moved from one home to another?” (0–1/2+ moves); (2) perceptions of neighborhood crime: “How safe from crime do you consider your neighborhood to be?” (safe/unsafe); (3) food insecurity (2 items): “The food that I bought just didn't last, and I didn't have money to get more” (never vs often/sometimes) and “I couldn't afford to eat balanced meals” (never vs often/sometimes); (4) financial instability: “In general, how do your finances usually work out at the end of the month?” (money left over or just enough vs not enough). Demographic covariates included age, education, annual income, gender, and race/ethnicity. Due to a large number of missing responses, annual income included a “missing” category (see Table 1).

Table 1.

Massachusetts BRFSS 2017–2019. Sample Characteristics and Global Health Outcome Measures. N = 16,929.

	Weighted % (95% CI)
Demographic characteristic Age 18–24	12.1% (11.3–12.9)
25–34	15.2% (14.4–16.0)
35–44	15.5% (14.7–16.3)
45–54	16.4% (15.6–17.1)
55–64	18.4% (17.7–19.2)
65–74	13.3% (12.7–13.9)
75+	9.2% (8.6–9.7)
Education Less than high school	10.0% (9.2–10.8)
High school	25.5% (24.5–26.4)
College 1–3 years	26.9% (25.9–27.8)
College graduate or more	37.7% (35.8–38.7)
Annual income ≤ $25k	13.3% (12.6–14.1)
$25k–$34,999	6.1% (5.6–6.6)
$35k–$49,999	8.8% (8.2–9.4)
$50k–$74,999	11.2% (10.5–11.8)
$75k+	39.6% (38.5–40.6)
Missing	21.0% (20.1–21.9)
Gender Female	52.8% (51.7–53.8)
Race/Ethnicity White, non-Hispanic	74.8% (73.9–75.8)
Black, non-Hispanic	6.7% (6.2–7.3)
Hispanic	10.5% (9.8–11.1)
Asian	6.7% (6.0–7.4)
Other	1.2% (1.0–1.4)

Analysis

The SDoH summary measure was created by summing the responses to the dichotomized SDoH items, resulting in a count of SDoH risk factors. If half or fewer were missing, missing responses were counted as “0” and included in the summary measure. The final SDoH summary measure was truncated to range from 0 to 4 or more.

Multivariable logistic regression was used to evaluate the association between each outcome and the SDoH summary measure. Unadjusted and adjusted models were created. Adjusted models included the following demographic covariates: age, education, gender, annual income, and race/ethnicity. All analyses were conducted using SAS software, v. 9.1 (SAS Institute Inc, Cary, NC, USA) and adjusted for the sampling design by using SAS procedure “surveylogistic.” This procedure allows adjustment for the sampling design, both geographic stratification and weighting (based on demographic characteristics). Stratification and weighting of the data was completed by the CDC as part of the cooperative agreement with states conducting the BRFSS. To account for the inclusion of 3 years of data in this analysis, we adjusted the sampling weights to reflect the different sample size in each year, as recommended by CDC.⁷

Results

Fourteen percent of respondents rated their health as fair or poor, 10% reported 15+ days of poor physical health in the last month, and 12% reported 15+ days of poor mental health in the past month (see Table 1 for demographic characteristics).

The prevalence of any single SDoH was low. The number of respondents reporting aspects of housing instability ranged from 8% (unable to pay mortgage, rent, utility bills) to 3% (2+ moves in past year), 4% of respondents reported that their neighborhood was unsafe or extremely unsafe, 14% reported that they often or sometimes could not afford balanced meals, 12% ran out of food often or sometimes, and 9% ran out of money at the end of each month. The number of respondents who refused any single item was highest in the question about finances (4%). The other questions were refused by less than 1% of respondents.

The SDoH summary measure revealed that most respondents (75%) did not experience any of the SDoH risks, while 11% reported one, 6% reported two, 4% reported three, and 4% reported four or more. An increase in the burden of SDoH risk experiences was associated with an increase in the likelihood of fair or poor health, after controlling for demographic confounders. In adjusted analyses, those who reported experiencing 1, 2, 3, or 4+ SDoH had 1.6-, 2.9-, 3.2-, or 5.3-fold odds (respectively) of fair or poor health, compared to those who reported zero SDoH. Respondents who reported experiencing 1, 2, 3, or 4+ SDoH had 1.6-, 2.2-, 3.3-, or 4.7-fold odds (respectively) of 15+ days/month of poor physical health. Finally, respondents who reported experiencing 1, 2, 3, or 4+ SDoH had 1.7-, 2.4-, 4.8-, or 6.5-fold odds (respectively) of reporting poor mental health days (Table 2).

Table 2.

Massachusetts BRFSS 2017–2019. Multivariate Logistic Regression—Social Determinants of Health Summary Measure to Predict General Health, Physical Health, and Mental Health. Unadjusted and Adjusted Results. N = 16,929.

	Unadjusted OR (95% CI)	Adjusted OR* (95% CI)
General health-rated as fair or poor
0 SDoH (ref)	1	1
1 SDoH	1.9 (1.6–2.4)	1.6 (1.3–2.0)
2 SDoH	3.9 (3.2–4.8)	2.9 (2.3–3.7)
3 SDoH	5.0 (4.0–6.4)	3.2 (2.4–4.3)
4+ SDoH	7.6 (6.0–9.7)	5.3 (4.0–7.0)
15+ days/Month of poor physical health
0 SDoH (ref)	1	1
1 SDoH	1.6 (1.3–2.0)	1.6 (1.2–2.0)
2 SDoH	2.6 (2.0–3.3)	2.2 (1.7–3.0)
3 SDoH	4.1 (3.1–5.3)	3.3 (2.4–4.5)
4+ SDoH	5.9 (4.6–7.6)	4.7 (3.5–6.4)
15+ days/Month of poor mental health
0 SDoH (ref)	1	1
1 SDoH	2.1 (1.7–2.6)	1.7 (1.4–2.2)
2 SDoH	3.3 (2.6–4.2)	2.4 (1.8–3.2)
3 SDoH	6.2 (4.9–8.0)	4.8 (3.6–6.3)
4+ SDoH	9.0 (7.0–11.6)	6.5 (4.9-8.6)

*Adjusted for: age, education, annual income, gender, and race/ethnicity

Discussion

Summary

The results of this study indicate that as the number of SDoH risk experiences increases, the odds of experiencing poor mental and physical health increases. Importantly, rather than reporting on one risk experience vs another, these results demonstrate that the overall burden of risk due to SDoH is an important predictor of health, over and above the contribution of demographic characteristics alone. Previous research using the BRFSS SDoH optional module supports these findings. Dormer and colleagues found that people who worry about having enough money for food and housing are more likely to report poor health.⁸ Similarly, others have found that food and housing insecurity are related to physical and mental health, independent of demographic characteristics.⁹ Another study demonstrated interrelationships between SDoH risk experiences and demographic characteristics, providing evidence for disparities in both food and housing insecurity by age, sex, education, and race/ethnicity, which persisted across levels of educational achievement.¹⁰

Limitations

An important limitation of this study is the cross-sectional design, as it is difficult to determine the potential direction of causation. Missing data may also be an important source of bias, as the average income may be lower or higher or the total burden of SDoH may be higher.

The SDoH summary measure is not an exhaustive measure and does not include important aspects of the SDoH such as healthcare access, working conditions, or social networks—to name but a few. Additionally, the summary measure provides more information about some SDoH aspects (food and housing insecurity) than others (financial instability and neighborhood safety). Rather, this study is intended to provide a first look at succinctly summarizing the effect of social factors on health, and demonstrating, in addition to their individual effects, there may also be an important combined effect.

Significance

Important strengths of this study include the large, representative sample and the use of BRFSS, which uses validated questions and has a high response rate. As the body of work investigating the health impact of adverse childhood experiences has so elegantly demonstrated, it is not simply one risk experience vs another that matters for health, but rather the overall burden of experience.¹¹ Similarly, the findings of this study indicate that the overall burden of SDoH, such as financial instability, housing instability, perceptions of neighborhood crime and food insecurity, is an important predictor of health, over and above the contribution of demographic characteristics. Current and planned research to investigate opportunities to include SDoH in COVID-19 models has outlined the problems in including SDoH measures.^4,5 The approach to quantifying SDoH burden utilized in this study may be helpful in modeling approaches, as it quantifies the vulnerability conferred by SDoH experiences.

“SO WHAT?”

What is already known on this topic?

Social determinants of health have a profound influence on health and health-related behaviors.

What does this article add?

There is evidence that the SDoH are inter-dependent and may work together to affect health. This article demonstrates how a summary of SDoH “exposure” relates to general health outcomes and provides evidence that SDoH “exposure burden” is an important facet of SDoH.

What are the implications for health promotion practice or research?

This study demonstrates that a succinct SDoH summary measure from the BRFSS is associated with general health measures in a strong and graded fashion.

Footnotes

Author Contributions

Dr. Nelson is the sole author of this work and conceptualized the study, conducted the analysis, interpreted the results, and wrote the report. She is accountable for all aspects of this report.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Centers for Disease Control and Prevention Cooperative Agreement #1 NU58DP006851-01-00.

Ethical Approval

This study was conducted using de-identified data and was not considered human subjects research by the Massachusetts Department of Public Health IRB.

ORCID iD

Candace C. Nelson

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