The Development of Social Determinants of Health Outcome Measures: The Role of Multisector Partnerships and Community Validation.

PURPOSE: To develop a set of social determinants of health (SDOH) measurements. PROBLEM: Despite burgeoning interest in addressing both SDOH and health-related social needs, the evidence on what works is limited due in part to the lack of standardized measures for evaluation. METHODS: In 2020, the Centers for Disease Control and Prevention (CDC) National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP) identified 5 SDOH domains related to chronic disease for future programmatic work. These included built environment, community connections to clinical care, tobacco-free policies, social connectedness, and food and nutrition security. Subsequently, NCCDPHP launched an effort to develop a set of SDOH measures for evaluating funded programs in these domains. The approach involved a literature scan and a rating process based on 5 criteria relevant to NCCDPHP's SDOH priorities. A complementary community review by 13 multisector community partnerships (MCPs) applied a real-world public health practice lens to measure development. MCPs' ratings were analyzed to create summary scores for each measure, and open-ended feedback was synthesized using rapid qualitative analysis. RESULTS: The internal workgroup identified 59 measures from the initial 200 measures. Feedback from the MCPs identified issues of relevancy and burden of measures. Their high scores narrowed the 59 measures to 22 covering all 5 domains. In response, CDC is honing the original measures review criteria to include community perspectives. CONCLUSION: Public health measures development is often an academic pursuit. Engaging MCPs lends real-world credibility to the development of common SDOH measures.

Racial and Ethnic Differences in Social Determinants of Health and Health-Related Social Needs Among Adults - Behavioral Risk Factor Surveillance System, United States, 2022.

Social determinants of health (SDOH) are a broad array of social and contextual conditions where persons are born, live, learn, work, play, worship, and age that influence their physical and mental wellbeing and quality of life. Using 2022 Behavioral Risk Factor Surveillance System data, this study assessed measures of adverse SDOH and health-related social needs (HRSN) among U.S. adult populations. Measures included life satisfaction, social and emotional support, social isolation or loneliness, employment stability, food stability/security, housing stability/security, utility stability/security, transportation access, mental well-being, and health care access. Prevalence ratios were adjusted for age, sex, education, marital status, income, and self-rated health. Social isolation or loneliness (31.9%) and lack of social and emotional support (24.8%) were the most commonly reported measures, both of which were more prevalent among non-Hispanic (NH) American Indian or Alaska Native, NH Black or African American, NH Native Hawaiian or other Pacific Islander, NH multiracial, and Hispanic or Latino adults than among NH White adults. The majority of prevalence estimates for other adverse SDOH and HRSN were also higher across all other racial and ethnic groups (except for NH Asian) compared with NH White adults. SDOH and HRSN data can be used to monitor needed social and health resources in the U.S. population and help evaluate population-scale interventions.

The Burden of Chronic Disease.

Chronic diseases like diabetes, heart disease, stroke, and cancer have been and continue to be some of the major causes of worldwide morbidity and mortality. A transition between infectious and noncommunicable diseases occurred in the early 1900s as a result of improved public health and has persisted ever since. Now, as individuals live longer, the prevalence and cost of chronic disease continue to grow. The estimated cost of chronic disease is expected to reach $47 trillion worldwide by 2030. Individual lifestyle and behaviors and community factors play important roles in the development and management of chronic diseases. Many of these conditions (diabetes, heart disease, and respiratory diseases) are preventable, and their leading risk factors are physical inactivity, poor nutrition, tobacco use, and excessive alcohol. Unfortunately, the investment in prevention remains small compared with treatment, both from a lifestyle perspective and a social determinants of health perspective. Given the future trajectory of chronic disease, innovation in technology and pharmaceuticals with a concomitant investment in prevention will be required. Our future depends on it.

Using the Prevention Impacts Simulation Model to Estimate Long-Term Impacts of Multisector Community Partnerships' Efforts to Address Social Determinants of Health.

Public health plays a key role in addressing social determinants of health (SDOH) through multisector community partnerships (MCPs), which contribute to community changes that promote healthy living; however, little is known about the longer-term impact of MCP-driven interventions. We used the Prevention Impacts Simulation Model (PRISM) in a rapid evaluation to better understand the implementation and potential impact of MCPs' SDOH initiatives. Results suggest that, if sustained, initiatives implemented by the 27 included MCPs may prevent 880 premature deaths and avert $125.7 million in medical costs over 20 years. As a validated model that estimates impact by using available implementation data, PRISM is a useful tool for evaluating SDOH initiatives.

Key insights on multisector community partnerships from real-world efforts to address social determinants of health.

PURPOSE: To better understand and inform how multisector community partnerships (MCPs) perform meaningful work to prevent chronic disease and advance health equity by addressing social determinants of health (SDOH). METHODS: We conducted a rapid retrospective evaluation of SDOH initiatives implemented within the past three years by 42 established MCPs across the United States. The mixed methods evaluation included document review and coding of available outcomes data, virtual discussions, and Prevention Impacts Simulation Model (PRISM) analysis. RESULTS: All 42 MCPs built community capacity for addressing SDOH through new or strengthened data systems, leveraged resources, or engaged residents, for example. Most MCPs (N = 38, 90%) reported contributions to community changes that promote healthy living. More than half of the MCPs (N = 22) reported health outcomes data for their SDOH initiatives, including improved health behaviors and clinical outcomes. Based on reach data provided by 27 MCPs, PRISM analysis results suggest that sustained initiatives could save over $633 million in productivity and medical costs cumulatively through 20 years. CONCLUSIONS: With sufficient technical assistance and funding resources, MCPs are a key component of the public health strategy to address SDOH.

Health Departments' Role in Addressing Social Determinants of Health in Collaboration With Multisector Community Partnerships.

Multisector community partnerships (MCPs) are key component of the public health strategy for addressing social determinants of health (SDOH) and promoting health equity. Governmental public health agencies are often members or leaders of MCPs, but few studies have examined the role of health departments in supporting MCPs' SDOH initiatives. We engaged 42 established MCPs in a rapid retrospective evaluation to better understand how MCPs' SDOH initiatives contribute to community changes that promote healthy living and improved health outcomes. As part of this work, we gained insights into how health departments support MCPs' SDOH initiatives, as well as opportunities for enhanced collaboration. Results indicate that health departments can support MCPs' SDOH initiatives through the provision of funding and technical assistance, data sharing, and connecting community organizations with shared missions, for example. Findings can be used to inform the development of funding opportunities and technical assistance for MCPs and health department partners.

Changes in Sales of E-Cigarettes, Cigarettes, and Nicotine Replacement Therapy Products Before, During, and After the EVALI Outbreak.

INTRODUCTION: In 2019, an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) occurred in the US. We used Nielsen retail sales data to assess trends in sales of e-cigarettes, cigarettes, and nicotine replacement therapy (NRT) products before, during, and after the EVALI outbreak. METHODS: Monthly unit sales of e-cigarettes, cigarettes, and NRT products overall and by product type were assessed during January 2019 through June 2020 by using an interrupted time series model. Two time points were specified at the period ending July 13, 2019, and the period ending February 22, 2020, to partition before, during, and after the outbreak period. Sales trends by aggregated state-level EVALI case prevalence (low, medium, and high) were assessed to investigate interstate variations in changes of sales coinciding with the EVALI outbreak. RESULTS: Monthly e-cigarette sales increased 3.5% (P < .001) before the outbreak and decreased 3.1% (P < .001) during the outbreak, with no significant changes after the outbreak. Monthly cigarette sales increased 1.6% (P < .001) before the outbreak, decreased 1.8% (P < .001) during the outbreak, and increased 2.7% (P < .001) after the outbreak. NRT sales did not change significantly before or during the outbreak but decreased (2.8%, P = .01) after the outbreak. Sales trends by state-level EVALI case prevalence were similar to national-level sales trends. CONCLUSION: Cigarette and e-cigarette sales decreased during the EVALI outbreak, but no changes in overall NRT sales were observed until after the outbreak. Continued monitoring of tobacco sales data can provide insight into potential changes in use patterns and inform tobacco prevention and control efforts.

Modifiable Risk Factors for Alzheimer Disease and Related Dementias Among Adults Aged ≥45 Years - United States, 2019.

Alzheimer disease,* the most common cause of dementia, affects an estimated 6.5 million persons aged ≥65 years in the United States (1). A growing body of evidence has identified potential modifiable risk factors for Alzheimer disease and related dementias (ADRD) (1-3). In 2021, the National Plan to Address Alzheimer's Disease (National Plan) introduced a new goal to "accelerate action to promote healthy aging and reduce risk factors for Alzheimer's disease and related dementias" to help delay onset or slow the progression of ADRD (3). To assess the status of eight potential modifiable risk factors (i.e., high blood pressure, not meeting the aerobic physical activity guideline, obesity, diabetes, depression, current cigarette smoking, hearing loss, and binge drinking), investigators analyzed data from the cognitive decline module that was administered to adults aged ≥45 years in 31 states and the District of Columbia (DC)† in the 2019 Behavioral Risk Factor Surveillance System (BRFSS) survey. Among the risk factors, prevalence was highest for high blood pressure (49.9%) and lowest for binge drinking (10.3%) and varied by selected demographic characteristics. Adults with subjective cognitive decline (SCD),§ an early indicator of possible future ADRD (4), were more likely to report four or more risk factors than were those without SCD (34.3% versus 13.1%). Prevalence of SCD was 11.3% overall and increased from 3.9% among adults with no risk factors to 25.0% among those with four or more risk factors. Implementing evidence-based strategies to address modifiable risk factors can help achieve the National Plan's new goal to reduce risk for ADRD while promoting health aging.¶,*.

Provider perceptions of medication for opioid used disorder (MOUD): A qualitative study in communities with high opioid overdose death rates.

BACKGROUND: Medication for Opioid Use Disorder (MOUD) has been shown to be a safe, cost-effective intervention that successfully lowers risk of opioid overdose. However, access to and use of MOUD has been limited. Our objective was to explore attitudes, opinions, and beliefs regarding MOUD among healthcare and social service providers in a community highly impacted by the opioid overdose epidemic. METHODS: As part of a larger ethnographic study examining neighborhoods in Allegheny County, PA, with the highest opioid overdose death rates, semi-structured qualitative in-person and telephone interviews were conducted with forty-five providers treating persons with opioid use disorders in these communities. An open coding approach was used to code interview transcripts followed by thematic analysis. RESULTS: Three major themes were identified related to MOUD from the perspectives of our provider participants. Within a variety of health and substance use service roles and settings, provider reflections revealed: (1) different opinions about MOUD as a transition to abstinence or as a long-term treatment; (2) perceived lack of uniformity and dissemination of accurate information of MOUD care, permitting differences in care, and (3) observed barriers to entry and navigation of MOUD, including referrals as a "word-of-mouth insider system" and challenges of getting patients MOUD services when they need it. CONCLUSIONS: Even in communities hard hit by the opioid overdose epidemic, healthcare providers' disagreement about the standard of care for MOUD can be a relevant obstacle. These insights can inform efforts to improve MOUD treatment and access for people with opioid use disorders.

Comparison of Census Tract-Level Chronic Disease Prevalence Estimates From 500 Cities and Local Health Claims Data.

OBJECTIVES: To compare city and census tract-level diabetes and hypertension prevalence using 500 Cities Project modeled estimates from the Centers for Disease Control and Prevention (CDC) and insurance claims data. METHODS: Insurance claims by census tract were collected from 3 local health plans for the city of Pittsburgh, Pennsylvania, for 2015-2016; conditions were defined using International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes. Crude prevalence estimates with 95% confidence intervals were downloaded from the CDC 500 Cities Web site to obtain modeled estimates by census tract. Confidence intervals were calculated for claims and compared with modeled estimates; nonoverlapping intervals were considered significant. Pearson correlation coefficients were generated for census tract-level comparison. RESULTS: City-level model-based and claims estimates were 9% versus 10% for diabetes and 31% versus 21% for hypertension. At the census tract level, model-based and insurance claims estimates were more concordant for diabetes (r = 0.366) than for hypertension (r = 0.220). Modeled estimates were significantly higher than claims estimates for 89% of census tracts for hypertension and 35% for diabetes. CONCLUSIONS: Modeled estimates from the 500 Cites Project were significantly higher than insurance claims estimates for hypertension but were more consistent for diabetes. Utilization of multiple data sources to understand local-level chronic disease burden requires consideration of the strengths and limitations of each.

Change in self-reported health: A signal for early intervention in a medicare population.

BACKGROUND: Health plans and risk-bearing provider organizations seek information sources to inform proactive interventions for patients at risk of adverse health events. Interventions should take into account the strong relationship between social context and health. This retrospective cohort study of a Medicare Advantage population examined whether a change in self-reported health-related quality of life (HRQOL) signals a subsequent change in healthcare needs. METHODS: A retrospective longitudinal analysis of administrative claims data was conducted for participants in a Medicare Advantage plan with prescription drug coverage (MAPD) who responded to 2 administrations of the Centers for Disease Control and Prevention 4-item Healthy Days survey within 6-18 months during 2015-2018. Changes in HRQOL, as measured by the Healthy Days instrument, were compared with changes in utilization and costs, which were considered to be a reflection of change in healthcare needs. RESULTS: A total of 48,841 individuals met inclusion criteria. Declining HRQOL was followed by increases in utilization and costs. An adjusted analysis showed that every additional unhealthy day reported one year after baseline was accompanied by an $8 increase in monthly healthcare costs in the subsequent six months for the average patient. CONCLUSIONS: Declining HRQOL signaled subsequent increases in healthcare needs and utilization. IMPLICATIONS: Findings suggest that HRQOL assessments in general, and the Healthy Days instrument in particular, could serve as a leading indicator of the need for interventions designed to mitigate poor health outcomes and rising healthcare costs. LEVEL OF EVIDENCE: III.