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The conditions in people's environment that determine risk versus  well-being.

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Social determinants of health are the conditions in which people are born, grow, live, work and age that shape health. This brief provides an overview of social determinants of health and emerging initiatives to address them. It shows:

Social determinants of health include factors like socioeconomic status, education, neighborhood and physical environment, employment, and social support networks, as well as access to health care. Addressing social determinants of health is important for improving health and reducing longstanding disparities in health and health care.

There are a growing number of initiatives to address social determinants of health within and outside of the health care system. Outside of the health care system, initiatives seek to shape policies and practices in non-health sectors in ways that promote health and health equity. Within the health care system, there are multi-payer federal and state initiatives as well as Medicaid-specific initiatives focused on addressing social needs. These include models under the Center for Medicare and Medicaid Innovation, Medicaid delivery system and payment reform initiatives, and options under Medicaid. Managed care plans and providers also are engaged in activities to identify and address social needs. For example, 19 states required Medicaid managed care plans to screen for and/or provide referrals for social needs in 2017, and a recent survey of Medicaid managed care plans found that almost all (91%) responding plans reported activities to address social determinants of health.

Many challenges remain to address social determinants of health, and new directions pursued by the Trump Administration could limit resources and initiatives focused on these efforts. The Trump Administration is pursuing a range of new policies and policy changes, including enforcing and expanding work requirements associated with public programs and reducing funding for prevention and public health. These changes may limit individuals' access to assistance programs to address health and other needs and reduce resources available to address social determinants of health.

Introduction

Efforts to improve health in the U.S. have traditionally looked to the health care system as the key driver of health and health outcomes. However, there has been increased recognition that improving health and achieving health equity will require broader approaches that address social, economic, and environmental factors that influence health. This brief provides an overview of these social determinants of health and discusses emerging initiatives to address them.

What are Social Determinants of Health?

Addressing social determinants of health is important for improving health and reducing health disparities. Though health care is essential to health, it is a relatively weak health determinant. Research shows that health outcomes are driven by an array of factors, including underlying genetics, health behaviors, social and environmental factors, and health care. While there is currently no consensus in the research on the magnitude of the relative contributions of each of these factors to health, studies suggest that health behaviors, such as smoking, diet, and exercise, and social and economic factors are the primary drivers of health outcomes, and social and economic factors can shape individuals' health behaviors. For example, children born to parents who have not completed high school are more likely to live in an environment that poses barriers to health such as lack of safety, exposed garbage, and substandard housing. They also are less likely to have access to sidewalks, parks or playgrounds, recreation centers, or a library. Further, evidence shows that stress negatively affects health across the lifespan and that environmental factors may have multi-generational impacts. Addressing social determinants of health is not only important for improving overall health, but also for reducing health disparities that are often rooted in social and economic disadvantages.

Initiatives to Address Social Determinants of Health

A growing number of initiatives are emerging to address social determinants of health. Some of these initiatives seek to increase the focus on health in non-health sectors, while others focus on having the health care system address broader social and environmental factors that influence health.

Focus on Health in Non-Health Sectors

Policies and practices in non-health sectors have impacts on health and health equity. For example, the availability and accessibility of public transportation affects access to employment, affordable healthy foods, health care, and other important drivers of health and wellness. Nutrition programs and policies can also promote health, for example, by supporting healthier corner stores in low-income communities, farm to school programs and community and school gardens, and through broader efforts to support the production and consumption of healthy foods. The provision of early childhood education to children in low-income families and communities of color helps to reduce achievement gaps, improve the health of low-income students, and promote health equity.

"Health in All Policies" is an approach that incorporates health considerations into decision making across sectors and policy areas. A Health in All Policies approach identifies the ways in which decisions in multiple sectors affect health, and how improved health can support the goals of these multiple sectors. It engages diverse partners and stakeholders to work together to promote health, equity, and sustainability, and simultaneously advance other goals such as promoting job creation and economic stability, transportation access and mobility, a strong agricultural system, and improved educational attainment. States and localities are utilizing the Health in All Policies approach through task forces and workgroups focused on bringing together leaders across agencies and the community to collaborate and prioritize a focus on health and health equity. At the federal level, the Affordable Care Act (ACA) established the National Prevention Council, which brings together senior leadership from 20 federal departments, agencies, and offices, who worked with the Prevention Advisory Group, stakeholders, and the pubic to develop the National Prevention Strategy.

Addressing Social Determinants in the Health Care System

In addition to the growing movement to incorporate health impact/outcome considerations into non-health policy areas, there are also emerging efforts to address non-medical, social determinants of health within the context of the health care delivery system. These include multi-payer federal and state initiatives, Medicaid initiatives led by states or by health plans, as well as provider-level activities focused on identifying and addressing the non-medical, social needs of their patients.

Federal and State Initiatives

Through the CMMI State Innovation Models Initiative (SIM), a number of states are engaged in multi-payer delivery and payment reforms that include a focus on population health and recognize the role of social determinants. SIM is a CMMI initiative that provides financial and technical support to states for the development and testing of state-led, multi-payer health care payment and service delivery models that aim to improve health system performance, increase quality of care, and decrease costs. To date, the SIM initiative has awarded nearly $950 million in grants to over half of states to design and/or test innovative payment and delivery models. As part of the second round of SIM grant awards, states are required to develop a statewide plan to improve population health. States that received Round 2 grants are pursuing a variety of approaches to identify and prioritize population health needs; link clinical, public health, and community-based resources; and address social determinants of health.

All 11 states that received Round 2 SIM testing grants plan to establish links between primary care and community-based organizations and social services. For example, Ohio is using SIM funds, in part, to support a comprehensive primary care (CPC) program in which primary care providers connect patients with needed social services and community-based prevention programs. As of December 2017, 96 practices were participating in the CPC program. Connecticut's SIM model seeks to promote an Advanced Medical Home model that will address the wide array of individuals' needs, including environmental and socioeconomic factors that contribute to their ongoing health.

A number of the states with Round 2 testing grants are creating local or regional entities to identify and address population health needs and establish links to community services. For example, Washington State established nine regional "Accountable Communities of Health," which will bring together local stakeholders from multiple sectors to determine priorities for and implement regional health improvement projects. Delaware plans to implement ten "Healthy Neighborhoods" across the state that will focus on priorities such as healthy lifestyles, maternal and child health, mental health and addiction, and chronic disease prevention and management. Idaho is creating seven "Regional Health Collaboratives" through the state's public health districts that will support local primary care practices in Patient-Centered Medical Home transformation and create formal referral and feedback protocols to link medical and social services providers.

The Round 2 testing grant states also are pursuing a range of other activities focused on population health and social determinants. Some of these activities include using population health measures to qualify practices as medical homes or determine incentive payments, incorporating use of community health workers in care teams, and expanding data collection and analysis infrastructure focused on population health and social determinants of health.

Medicaid Initiatives

Delivery System and Payment Reform

In Oregon, each Coordinated Care Organization (or "CCO") is required to establish a community advisory council and develop a community health needs assessment. CCOs receive a global payment for each enrollee, providing flexibility for CCOs to offer "health-related services" - which supplement traditional covered Medicaid benefits and may target the social determinants of health. Early experiences suggest that CCOs are connecting with community partners and beginning to address social factors that influence health through a range of projects. For example, one CCO has funded a community health worker to help link pregnant or parenting teens to health services and address other needs, such as housing, food, and income. Another CCO worked with providers and the local Meals on Wheels program to deliver meals to Medicaid enrollees discharged from the hospital who need food assistance as part of their recovery. An evaluation conducted by the Oregon Health & Science University's Center for Health Systems Effectiveness released in 2017 found CCOs were associated with reductions in spending growth and improvement in some quality domains. According to the evaluation, most CCOs believed health-related flexible services were effective at improving outcomes and reducing costs.

Similarly, in Colorado, the Regional Collaborative Organizations (RCCOs), which are paid a per member per month payment for enrollees, help connect individuals to community services through referral systems as well as through targeted programs designed to address specific needs identified within the community. A study published in 2017 comparing Oregon's CCO program to Colorado's RCCO program found that Colorado's RCCO program generated comparable reductions in expenditures and inpatient care days.

Several other state Medicaid programs have launched Accountable Care Organization (ACO) models that often include population-based payments or total cost of care formulas, which may provide incentives for providers to address the broad needs of Medicaid beneficiaries, including the social determinants of health.

Some state Medicaid programs are supporting providers' focus on social determinants of health through "Delivery System Reform Incentive Payment" (DSRIP) initiatives. DSRIP initiatives emerged under the Obama Administration as part of Section 1115 Medicaid demonstration waivers. DSRIP initiatives link Medicaid funding for eligible providers to process and performance metrics, which may involve addressing social needs and factors. For example, in New York, provider systems may implement DSRIP projects aimed at ensuring that people have supportive housing. The state also has invested significant state dollars outside of its DSRIP waiver in housing stock to ensure that a better supply of appropriate housing is available. In Texas, some providers have used DSRIP funds to install refrigerators in homeless shelters to improve individuals' access to insulin. The California DSRIP waiver has increased the extent to which the public hospital systems focus on coordination with social services agencies and county-level welfare offices. To date, data on the results of DSRIP programs are limited, but a final federal evaluation report is scheduled to for 2019.

Medicaid programs also are providing broader services to support health through the health homes option established by the ACA. Under this option, states can establish health homes to coordinate care for people who have chronic conditions. Health home services include comprehensive care management, care coordination, health promotion, comprehensive transitional care, patient and family support, as well as referrals to community and social support services. Health home providers can be a designated provider, a team of health professionals linked to a designated provider, or a community health team. A total of 21 states report that health homes were in place in fiscal year 2017. A federally-funded evaluation of the health homes model found that most providers reported significant growth in their ability to connect patients to nonclinical social services and supports under the model, but that lack of stable housing and transportation were common problems for many enrollees that were difficult for providers to address with insufficient affordable housing and rent support resources.

Housing and Employment Supports

Some states are providing housing support to Medicaid enrollees through a range of optional state plan and waiver authorities. While states cannot use Medicaid funds to pay for room and board, Medicaid funds can support a range of housing-related activities, including referral, support services, and case management services that help connect and retain individuals in stable housing. For example, the Louisiana Department of Health formed a partnership with the Louisiana Housing Authority to establish a Permanent Supportive Housing (PSH) program with the dual goals of preventing and reducing homelessness and unnecessary institutionalization among people with disabilities. Louisiana's Medicaid program covers three phases of tenancy support services for Medicaid beneficiaries in permanent supportive housing: pre-tenancy services (housing search assistance, application assistance etc.), move-in services, and ongoing tenancy services. Louisiana reports a 94% housing retention rate since the program began housing tenants in 2008. A preliminary analysis shows statistically significant reductions in hospitalizations and emergency department utilization after the PSH intervention, and an early independent analysis of the PSH program's impact on Medicaid spending found a 24% reduction in Medicaid acute care costs after a person was housed.

Medicaid Managed Care Organizations (MCOs)

Medicaid MCOs are increasingly engaging in activities to address social determinants of health. Data from the Kaiser Family Foundation's 50-state Medicaid budget survey show that a growing number of states are requiring Medicaid MCOs to address social determinants of health as part of their contractual agreements (Box 1). In 2017, 19 states required Medicaid MCOs to screen beneficiaries for social needs and/or provide enrollees with referrals to social services and six states required MCOs to provide care coordination services to enrollees moving out of incarceration, with additional states planning to implement such requirements in 2018. Other data from a 2017 Kaiser Family Foundation survey of Medicaid managed care plans show that almost all responding MCOs (91%) reported activities to address social determinants of health, with housing and nutrition/food security as the top areas of focus. The most common activities plans reported engaging in were working with community -based organizations to link members to social services (93%), assessing members' social needs (91%), and maintaining community or social service resource databases (81%) (Figure 2). Some plans also reported using community health workers (67%), using interdisciplinary community care teams (66%), offering application assistance and counseling referrals for social services (52%), and assisting justice-involved individuals with community reintegration (20%).

Arizona requires coordination of community resources like housing and utility assistance under its managed long-term services and supports (MLTSS) contract. The state provides state-only funding in conjunction with its managed behavioral health contract to provide housing assistance. The state also encourages health plans to coordinate with the Veterans' Administration and other programs to meet members' social support needs.

The District of Columbia encourages MCOs to refer beneficiaries with three or more chronic conditions to the "My Health GPS" Health Home program for care coordination and case management services, including a biopsychosocial needs assessment and referral to community and social support services.

Louisiana requires its plans to screen for problem gaming and tobacco use and requires referrals to Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and the Louisiana Permanent Supportive Housing program when appropriate.

Nebraska requires MCOs to have staff trained on social determinants of health and be familiar with community resources; plans are also required to have policies to address members with multiple biopsychosocial needs.

PROVIDER ACTIVITIES

Some providers have adopted screening tools within their practices to identify health-related social needs of patients. For example, according to a survey of nearly 300 hospitals and health systems conducted by the Deloitte Center for Health Solutions in 2017, nearly 9 in 10 (88%) hospitals screen patients to gauge their health-related social needs, though only 62% report screening target populations in a systematic or consistent way. These hospitals are mostly screening inpatient and high-utilizer populations. The National Association for Community Health Centers, in coordination with several other organizations, developed the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) tool to help health centers and other providers collect data to better understand and act on their patients' social determinants of health. Other organizations and entities have created screening tools, including Health Leads, a non-profit organization funded by the Robert Wood Johnson Foundation, which has developed a social needs screening toolkit for providers and CMMI, which released an Accountable Health Communities screening tool to help providers identify unmet patient needs.

Looking Ahead

The ACA provided a key opportunity to help improve access to care and reduce longstanding disparities faced by historically underserved populations through both its coverage expansions and provisions to help bridge health care and community health. To date, millions of Americans have gained coverage through the coverage expansions, but coverage alone is not enough to improve health outcomes and achieve health equity. With growing recognition of the importance of social factors to health outcomes, an increasing number of initiatives have emerged to address social determinants of health by bringing a greater focus on health within non-health sectors and increasingly recognizing and addressing health-related social needs through the health care system.

Within the health care system, a broad range of initiatives have been launched at the federal and state level, including efforts within Medicaid. Many of these initiatives reflect new funding and demonstration authorities provided through the ACA to address social determinants of health and further health equity. They also reflect a broader system movement toward care integration and "whole-person" delivery models, which aim to address patients' physical, mental, and social needs, as well as a shifts towards payments tied to value, quality, and/or outcomes.

Although there has been significant progress recognizing and addressing social determinants of health, many challenges remain. Notably, these efforts require working across siloed sectors with separate funding streams, where investments in one sector may accrue savings in another. Moreover, communities may not always have sufficient service capacity or supply to meet identified needs. Further, there remain gaps and inconsistencies in data on social determinants of health that limit the ability to aggregate data across settings or to use data to inform policy and operations, guide quality improvement, or evaluate interventions. Within Medicaid, the growing focus on social determinants of health raises new questions about the appropriate role Medicaid should play in addressing non-medical determinants of health and how to incentivize and engage Medicaid MCOs in addressing social determinants of health.

The Trump Administration is pursuing policies that may limit individuals' access to assistance programs to address health and other needs and reduce resources to address social determinants of health. The Administration has begun phasing out DSRIP programs, is revising Medicaid managed care regulations, and has signaled reductions in funding for prevention and public health. It has also announced plans to change the direction of models under the CMMI., , The Administration also is pursuing approaches to enforce and expand work requirements in public programs, including Medicaid. CMS asserts that this policy is designed to "improve Medicaid enrollee health and well-being through incentivizing work and community engagement" and that state efforts to make participation in work or other community engagement a requirement for Medicaid coverage may "help individuals and families rise out of poverty and attain independence." In guidance, CMS has specified that states implementing such programs will be required to describe strategies to assist enrollees in meeting work requirements (e.g., linking individuals to job training, childcare assistance, transportation, and other work supports), but that states may not use federal Medicaid funds for supportive services to help people overcome barriers to work. Data show that most nonelderly Medicaid adults already are working or face significant barriers to work, leaving a small share of adults to whom these policies are directed. However, eligible individuals could lose Medicaid coverage due to difficulty navigating documentation and administrative processes associated with these requirements.

This brief updates an earlier version that was produced with Harry J. Heiman, formerly with the Satcher Health Leadership Institute at the Morehouse School of Medicine.

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Beyond Health Care: The Role of Social Determinants in Promoting Health and Health Equity

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Research demonstrates that improving population health and achieving health equity will require broad approaches that address social, economic, and environmental factors that influence health. This brief provides an overview of the broad factors that influence health and describes efforts to address them, including initiatives within Medicaid.

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Building a more resilient community starts with Knowledge, which leads to Insights and a shift in thinking about self and others. Effective Strategies can then be developed, which eventually lead to Structures and sustainability.
Developing strategies without knowledge and insight may actually increase trauma.

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Recent advances in science and technology have helped us understand the unique biological processes that buffer against the damaging impact of toxic stress.  Protective factors during early childhood provide the greatest long-term benefit, but it is never too late. Protective factors have a positive effect during all stages of life. A community that values and supports the resilience of all its members will be better equipped to deal with various types of adverse events.

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Short for: P ositive C hildhood E xperiences

Findings from Christina Bethell's 2019 research report suggest that PCEs may have lifelong consequences for mental and relational health despite co-occurring adversities, such as ACEs.

The report identified 7 PCEs:
1. Able to talk with my family about my feelings.
2. Felt that my family stood by me during difficult times.
3. Enjoyed participating in community traditions.
4. Felt a sense of belonging in high school.
5. Felt supported by friends.
6. Had at least two non-parent adults who took an interest in me.
7. Felt safe and protected by an adult in my home.

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Associations Across Adverse Childhood Experiences Levels

Christina Bethell, PhD, MBA, MPH, ¹ Jennifer Jones, MSW, ² Narangerel Gombojav, MD, PhD, ¹ Jeff Linkenbach, EdD, ³ and Robert Sege, MD, PhD ⁴

Key Points

Question

Are positive childhood experiences (PCEs) associated with adult depression and/or poor mental health (D/PMH) and adult-reported social and emotional support (ARSES) independent from adverse childhood experiences (ACEs)?

Findings

In this cross-sectional study, adults reporting higher PCEs had lower odds of D/PMH and greater ARSES after accounting for ACEs. The associations of PCEs with D/PMH also remained stable when controlling for ARSES.

Meaning

Positive childhood experiences demonstrate a dose-response association with adult D/PMH and ARSES after adjustment for ACEs; assessing and proactively promoting PCEs may reduce adult mental and relational health problems, even in the concurrent presence of ACEs.

Abstract

Importance

Associations between adverse childhood experiences (ACEs) and risks for adult depression, poor mental health, and insufficient social and emotional support have been documented. Less is known about how positive childhood experiences (PCEs) co-occur with and may modulate the effect of ACEs on adult mental and relational health.

Objective

To evaluate associations between adult-reported PCEs and (1) adult depression and/or poor mental health (D/PMH) and (2) adult-reported social and emotional support (ARSES) across ACEs exposure levels.

Design, Setting, and Participants

Data were from the cross-sectional 2015 Wisconsin Behavioral Risk Factor Survey, a random digit-dial telephone survey of noninstitutionalized Wisconsin adults 18 years and older (n = 6188). Data were weighted to be representative of the entire population of Wisconsin adults in 2015. Data were analyzed between September 2016 and January 2019.

Main Outcomes and Measures

The definition of D/PMH includes adults with a depression diagnosis (ever) and/or 14 or more poor mental health days in the past month. The definition of PCEs includes 7 positive interpersonal experiences with family, friends, and in school/the community. Standard Behavioral Risk Factor Survey ACEs and ARSES variables were used.

Results

In the 2015 Wisconsin Behavioral Risk Factor Survey sample of adults (50.7% women; 84.9% white), the adjusted odds of D/PMH were 72% lower (OR, 0.28; 95% CI, 0.21-0.39) for adults reporting 6 to 7 vs 0 to 2 PCEs (12.6% vs 48.2%). Odds were 50% lower (OR, 0.50; 95% CI, 0.36-0.69) for those reporting 3 to 5 vs 0 to 2 PCEs (25.1% vs 48.2%). Associations were similar in magnitude for adults reporting 1, 2 to 3, or 4 to 8 ACEs. The adjusted odds that adults reported "always" on the ARSES variable were 3.53 times (95% CI, 2.60-4.80) greater for adults with 6 to 7 vs 0 to 2 PCEs. Associations for 3 to 5 PCEs were not significant. The PCE associations with D/PMH remained stable across each ACEs exposure level when controlling for ARSES.

Conclusions and Relevance

Positive childhood experiences show dose-response associations with D/PMH and ARSES after accounting for exposure to ACEs. The proactive promotion of PCEs for children may reduce risk for adult D/PMH and promote adult relational health. Joint assessment of PCEs and ACEs may better target needs and interventions and enable a focus on building strengths to promote well-being. Findings support prioritizing possibilities to foster safe, stable nurturing relationships for children that consider the health outcomes of positive experiences.

Introduction

Research demonstrates that both positive and adverse experiences shape brain development and health across the life span.. Understanding human development requires a model that incorporates both risks (factors that decrease the likelihood of successful development) and opportunities (factors that increase the likelihood of successful development). On the positive side, successful child development depends on secure attachment during the first years of life. As the child grows, exposure to spoken language and having the presence of safe, stable, nurturing relationships and environments are important factors for optimal development. On the other hand, children with adverse childhood experiences (ACEs) are at risk for observable changes in brain anatomy, gene expression, and delays in social, emotional, physical, and cognitive development lasting into adulthood.

According to standardized measures, an estimated 61.5% of adults and 48% of children in the United States have been exposed to ACEs, with more than one-third of these having multiple exposures. The wide-ranging negative associations between exposure to multiple ACEs and diminished adult and child health are well documented. Most notable is the especially strong evidence linking ACEs with adult mental health problems including depression. A robust literature also exists regarding the effect of ACEs on adult relational health (often assessed by whether adults report that they get the social and emotional support they need) and how diminished adult social and emotional support contributes to poorer adult physical and mental health.

Beyond the extensive and growing body of research dealing with lifelong correlates of adversity, many prior studies identify resiliency factors and adaptive skills and interventions associated with improved child development and child and adult health outcomes. For example, the Search Institute developed a list of "40 Developmental Assets" and demonstrated associations between the number of assets and both positive and negative outcomes. A national population-based study on child flourishing and resilience shows strong associations with levels of family resilience and parent-child connection for children with exposures to greater ACEs, poverty, and chronic conditions. Similar studies, such as those assessing the US Centers for Disease Control and Prevention (CDC)'s "safe, stable, and nurturing relationships" model, show similar findings.

Despite these advances, standardized measures and the prevalence of positive childhood experiences (PCEs) at the population level for adults or children are still unknown. Yet prior studies, using data from small or nonrepresentative samples, have explored interactions between PCEs and ACEs. For example, 1 study, conducted by Kaiser Permanente and CDC investigators, analyzed a cohort of 4648 women. They found that adult reports of specific positive family experiences in childhood (including closeness, support, loyalty, protection, love, importance, and responsiveness to health needs) were associated with lower rates of adolescent pregnancy across all ACEs exposure levels. The protective effects of reported interpersonal PCEs against mental health problems in adulthood have also been found among pregnant women and young adults exposed to ACEs. Despite these findings, few subsequent studies on ACEs have simultaneously evaluated PCEs.

Collectively, prior studies on child development point to the importance of research focusing on PCEs, especially those associated with parent-child attachment, positive parenting (eg, parental warmth, responsiveness, and support), family health, and positive relationships with friends, in school, and in the community. Knowledge of whether retrospectively reported PCEs co-occur with ACEs and how PCEs interact with ACEs to effect adult mental and relational health is needed to inform the nation's growing focus on addressing early life and social determinants of healthy development and lifelong health.

This study used data from the 2015 Wisconsin Behavioral Risk Factor Survey (WI BRFS), a representative, population-based survey, to assess the prevalence of PCEs in an adult sample and evaluate hypothesized associations with adult mental and relational health across 4 ACEs exposure levels. This study builds on a 2017 Health Outcomes of Positive Experiences report featuring bivariate findings from the 2015 WI BRFS associating individual PCEs with negative adult health outcomes. Here, we construct a PCEs cumulative score measure and use multivariable regression methods to assess the magnitude and significance of associations between this PCEs score and (1) adult depression and/or poor mental health (D/PMH) and (2) adults' reported social and emotional support (ARSES). Separate assessment of associations was conducted for each of 4 ACEs exposure levels.

Methods

Population and Data

Data were from the cross-sectional 2015 WI BRFS, a representative, telephone survey of noninstitutionalized Wisconsin adults 18 years and older who speak English or Spanish (n = 6188). The WI BRFS response rate was 45.0% (weighted American Association of Public Opinion Research median, 47.2%). The cooperation rate was 64.9% (weighted American Association of Public Opinion Research median, 68.0%). The 2015 WI BRFS core and state-added items data sets were linked. Institutional review board (IRB) approval was not required because data are based on a survey conducted by a public agency and do not include personal health information. Respondent oral consent methods and construction of race/ethnicity variables used standard CDC BRFS approved methods.

There were 18.1% to 21.1% missing cases for state-added ARSES, ACEs, and PCEs items. "Don't know/refused" responses to these questions were 0.2% to 0.9%. A 10% missing value rate for the WI BRFS state-added items is expected and is attributed to the administration of the core WI BRFS survey by another state to Wisconsin residents who have out-of-state cellular phones. In these cases, the WI BRFS state-added items were not available to be administered. The remainder of missing cases were nearly all owing to respondent dropoffs prior to administering the ARSES, ACEs, and PCEs questions after administration of the core WI BRFS. Differences in D/PMH prevalence rates between respondents and missing cases were not notable. See eTable 1 in the Supplement for additional details.

Key Measures

Positive Childhood Experiences Score

The PCEs score included 7 items asking respondents to report how often or how much as a child they: (1) felt able to talk to their family about feelings; (2) felt their family stood by them during difficult times; (3) enjoyed participating in community traditions; (4) felt a sense of belonging in high school (not including those who did not attend school or were home schooled); (5) felt supported by friends; (6) had at least 2 nonparent adults who took genuine interest in them; and (7) felt safe and protected by an adult in their home. The PCEs score items were adapted from 4 subscales included in the Child and Youth Resilience Measure-28 : (1) 4 items from the Psychological, Caregiving subscale (see PCEs items 1, 2, 7, and 6 listed previously); (2) 1 from the Education subscale (PCEs item 4); (3) 1 from the Culture subscale (PCEs item 3), and (4) 1 from the Peer Support subscale (PCEs item 5). Items were designed in the Child and Youth Resilience Measure-28 for cultural sensitivity, and their validity was supported by associations with improved resilience. Psychometric analyses confirmed use of a PCEs cumulative score. See eTable 2 in the Supplement for details.

Adverse Childhood Experiences

We used data from the standardized ACEs survey items defined by the CDC. The ACEs measure included 11 ACEs items assessing recollections of childhood experiences of physical or emotional abuse or neglect, sexual abuse, and household dysfunctions such as substance abuse, parental incarceration, and divorce. As recommended by the CDC, items were coded using cumulative score groupings of 0, 1, 2 to 3, or 4 to 8 ACEs. Subjective reports of experiences in childhood are the intended construct for assessment of both PCEs and ACEs and not whether what is reported would be validated using objective assessments.

Adult-Reported Social and Emotional Support

Adult-reported social and emotional support is assessed using a standardized single item, "How often do you get the social and emotional support you need?" Response choices were "always," "usually," "sometimes," "rarely," or "never." Based on previous research and analysis of this ARSES variable, this study separately evaluated "always" and "usually" responses and created a combined "sometimes/rarely/never" response category.

Depression/Poor Mental Health

The D/PMH category was constructed using (1) the single item on depression asking whether a physician or other health professional "ever told you that you have a depressive disorder, including depression, major depression, dysthymia, or minor depression?"; and (2) a score of 14 or higher on the single item validated as an indicator of current poor mental health that asked, "Now 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?" Adults reporting either or both of these outcomes were included in the D/PMH variable.

Other Covariates

Demographic covariates included age (18-34 years, 35-54 years, 55-64 years, and 65 years or older), race/ethnicity (nonwhite or white/non-Hispanic), and annual income (less than $25 000, $25 000-$49 999, $50 000-$74 999, and $75 000 or more). Sample size and statistical power analysis findings required combining race/ethnicity subgroups into 2 categories for purposes of statistical analysis.

Analytic Methods

Prevalence rates for all variables were computed, and bivariate associations between individual PCE items and PCEs cumulative score groups and all other variables were evaluated using χ ² tests. Iterative and recursive analyses confirmed independent variable construction and focused on confirmation of assumptions on the linearity and comparability of associations with study outcomes when ordinal (count) or cumulative score groupings of PCEs and ACEs were used. Cumulative score groups of 0 to 2, 3 to 5, and 6 to 7 PCEs and 0, 1, 2 to 3, and 4 to 8 ACEs were also selected to ensure adequate statistical power to detect meaningful associations. Such score groups also simplify reporting of results by narrowing the number of comparative groups requiring reporting. Interaction variables crossing PCEs by ACEs and PCEs by ARSES were also analyzed for each study outcome and supported decisions to assess PCEs, ACEs, and ARSES as independent (vs interacting) variables in regression models.

As noted, multivariable logistic regression analyses evaluated 2 association pathways between PCEs items and cumulative score groups and 2 outcome variables: (1) meeting criteria for D/PMH and (2) reports of "always" on ARSES. Regression models were adjusted for age, sex, race/ethnicity, income, and ACEs. Separate models were evaluated for each ACEs exposure level (0, 1, 2-3, and 4-8) to examine stability of associations across ACEs exposure levels. We further assessed the stability of associations between D/PMH and PCEs when ARSES were or were not controlled for in regression models. This was done to further understand more nuanced association pathways between PCEs and ARSES and their individual or interacting association with D/MPH. Additional sensitivity analyses of PCEs associations when ACEs were or were not included in models were also conducted. The survey data were weighted to be representative of the Wisconsin population. We used SPSS Complex Samples, version 24 (IBM Corporation) for data analysis. A P value of .05 or less was used to determine statistical significance.

Results

Population Characteristics and Prevalence of Study Outcomes by PCEs

Demographic characteristics for the 2015 WI BRFS mirrored the state population: 50.7% women and 84.9% white. About half (52.3%) reported 6 to 7 PCEs, more than half (56.7%) reported ACEs, 21.2% met D/PMH criteria, and more than half (55.1%) reported "always" to getting the social and emotional support they needed (ARSES). Nonwhite, younger, and lower-income adults reported fewer levels of PCEs (). Compared with those reporting 6 to 7 PCEs, adults reporting 0 to 2 PCEs had nearly 4 times higher prevalence of D/PMH (48.2% vs 12.6%) and were half as likely to report "always" to getting the social and emotional support they needed (33.0% vs 67.9%) (). Similar variations in prevalence were observed when each of the 7 PCEs items were separately evaluated for each study outcome ( and and eTable 5 in the Supplement). As hypothesized and shown in these Figures, stronger associations emerged for cumulative PCEs scores.

Table 1.

Table 2.

The lowest adult D/PMH prevalences were observed for respondents reporting both 6 to 7 PCEs and either no ACEs (10.5%) or "always" on the ARSES variable (8.5%). Highest D/PMH prevalences were for those reporting 0 to 2 PCEs and either 4 to 8 ACEs (59.7%) or "sometimes/ rarely/never" on the ARSES variable (61.7%). Yet, even among those reporting always getting needed social and emotional support, a subset reported 0 to 2 PCEs, and this group had 4 times greater prevalence of D/PMH compared with those reporting 6 to 7 PCEs (33.8% vs 8.5%). Likewise, 21.2% of those with 4 to 8 ACEs and 26.6% of those reporting "sometime/rarely/never" to the ARSES item nonetheless also reported 6 to 7 PCEs. (, , and eTable 3 in the Supplement).

Table 3.

Categories by ACEs and PCEs

Meets D/PMH Criteriaa

Reports of "Always" to Getting Needed Social and Emotional Support (ARSES)

Unweighted No.

Weighted %

Adjusted Odds Ratiob (95% CI)

Unweighted No.

Weighted %

Adjusted Odds Ratiob (95% CI)

Association Pathway 1: PCEs and D/PMH

After controlling for ACEs, the adjusted odds of D/PMH were 72% lower (odds ratio [OR], 0.28; 95% CI, 0.21-0.39) for adults with the highest vs lowest PCEs scores (12.6% vs 48.2%). Odds were 50% lower (OR, 0.50; 95% CI, 0.36-0.69) for those reporting intermediate PCEs scores of 3 to 5 (25.1% vs 48.2%) (). Associations were similar in magnitude for adults reporting 1, 2 to 3, or 4 to 8 ACEs ().

Association Pathway 2: PCEs and ARSES

The adjusted odds of "always" reports on the ARSES item were 3.53 times (95% CI, 2.60-4.80) greater for adults with the highest vs lowest PCEs scores. Adjusted odds of reports of "always" on the ARSES variable were not significant for adults with intermediate PCEs of 3 to 5 (adjusted OR, 1.31; 95% CI, 0.97-1.78) (). Findings were similar across all ACEs exposure level subgroups (). Because PCEs and ARSES were strongly associated as hypothesized, we further examined whether each variable demonstrated an independent association with D/PMH and whether associations of PCEs with D/PMH remained stable when ARSES was included in regression models. Results showed that PCEs associations with D/PMH remained significant and changed only modestly when ARSES was included. Associations between ARSES and D/PMH also remained stable when PCEs were or were not included. See eTable 4 in the Supplement for details.

Discussion

This study examined the prevalence of adult reports of both PCEs and ACEs in a statewide sample and found that PCEs both co-occur with and operate independently from ACEs in their associations with the adult health outcomes evaluated here. Findings also confirm the hypotheses that PCEs may exert their association with D/PMH through their association with ARSES. However, PCEs maintained an association with D/PMH independent from ARSES. Findings are both consistent with prior research showing that relational experiences in childhood are associated with adult social and relational skills and health and also point to enduring effects of PCEs on D/PMH separate from their influence on adult ARSES.

While PCEs associations with D/PMH were substantial and similar for adults reporting ACEs, associations were not statistically significant for those reporting no ACEs. Insignificant findings may be owing to low sample sizes for respondents with no ACEs and fewer PCEs. Results still raise questions for further exploration. We hypothesize that PCEs may have a greater influence in promoting positive health, such as getting needed social and emotional support or flourishing as an adult. In turn, these positive health attributes may reduce the burden of illness even if the illness is not eliminated. This is consistent with prior research demonstrating a dual continuum of health whereby flourishing is found to be present for many adults despite concurrent mental health conditions.

Limitations

First, this study is cross-sectional and cannot confirm causal effects. Second, the 2015 Wisconsin adult population is less diverse than the United States as a whole. Third, PCEs focused on the domain of positive emotional experiences in interpersonal relationships. Other types of positive experiences, (eg, safe and supportive environments, nature or spiritual experiences, participation in activities, or accomplishment) require further study, highlighting the need to develop and test additional measures of PCEs. Fourth, we were not able to directly examine bias in reporting of PCEs among adults with depression, although studies show an absence of such biases for reports of ACEs. Finally, the WI BRFS did not assess overall well-being or flourishing. As such, we were not able to assess whether PCEs affect positive adult health outcomes as hypothesized. Sample size limitations may have resulted in false-negative findings in some cases.

Conclusions

Overall, study results demonstrate that PCEs show a dose-response association with adult mental and relational health, analogous to the cumulative effects of multiple ACEs. Findings suggest that PCEs may have lifelong consequences for mental and relational health despite co-occurring adversities such as ACEs. In this way, they support application of the World Health Organization's definition of health emphasizing that health is more than the absence of disease or adversity. The World Health Organization's positive construct of health is aligned with the proactive promotion of positive experiences in childhood because they are foundational to optimal childhood development and adult flourishing. Including PCEs as well as positive health outcomes measures in routinely collected public health surveillance systems, such as the National Survey of Children's Health and state Behavioral Risk Factor Surveillance Surveys, may advance knowledge and allow the nation to track progress in promoting flourishing despite adversity or illness among children and adults in the United States.

Even as society continues to address remediable causes of childhood adversities such as ACEs, attention should be given to the creation of those positive experiences that both reflect and generate resilience within children, families, and communities. Success will depend on full engagement of families and communities and changes in the health care, education, and social services systems serving children and families. A joint inventory of ACEs and PCEs, such as the positive experiences assessed here, may improve efforts to assess needs, target interventions, and engage individuals in addressing the adversities they face by leveraging existing assets and strengths. Initiatives to conduct broad ACEs screening, such as those ensuing in California's Medicaid program, may benefit from integrated assessments including PCEs.

Recommendations and practice guidelines included in the National Bright Futures Guidelines for Health Supervision of Infants, Children, and Adolescents and the CDC's Essentials for Childhood initiative encourage policies and initiatives to help child-serving professionals and programs to adopt effective approaches to promote the type of PCEs evaluated in this study. The Health Outcomes of Positive Experiences framework and the Prioritizing Possibilities national agenda for promoting child health and addressing ACEs each seek to advance existing and emerging evidence-based approaches that promote a positive construct of health in clinical, public health, and human services settings. This study adds to the growing evidence that childhood experiences have profound and lifelong effects. Results hold promise for national, state, and community efforts to achieve positive child and adult health and well-being by promoting the largely untapped potential to promote positive experiences and flourishing despite adversity.

Notes

Supplement.

eTable 1. Prevalence of Depression/Poor Mental Health (D/PMH) and Demographic Characteristics Among Adults With or Without Missing Values for Positive Childhood Experiences (PCEs), Adult Reported Social and Emotional Support (ARSES) and Adverse Childhood Experiences (ACEs) WI BRFS State Added Items

eTable 2. Summary of Findings From Psychometric Analyses a Conducted on Positive Childhood Experiences (PCEs) Seven Item Measure

eTable 3. Prevalence of Adult Depression and/or Poor Mental Health (D/PMH) by Adult Reported Social and Emotional Support (ARSES) and Positive Childhood Experiences (PCEs)

eTable 4. Adjusted Odds Ratios of Adult Depression and/or Poor Mental Health (D/PMH) by Adult Reported Social and Emotional Support (ARSES) and Positive Childhood Experiences (PCEs) Under Alternative Model Configurations

eTable 5. Prevalence of Depression and/or Poor Mental Health (D/PMH) and Adult Reporting "Always" Receiving Needed Social Emotional Support (ARSES), By Positive Childhood Experiences (PCEs) Cumulative Scores and Single Items

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# data[].attributes.attachment_link.title
Positive Childhood Experiences and Adult Mental and Relational Health in a Statewide Sample: Associations Across Adverse Childhood Experiences Levels

# data[].attributes.attachment_link.description
Associations Across Adverse Childhood Experiences Levels Christina Bethell, PhD, MBA, MPH, 1 Jennifer Jones, MSW, 2 Narangerel Gombojav, MD, PhD, 1 Jeff Linkenbach, EdD, 3 and Robert Sege, MD, PhD 4 Are positive childhood experiences (PCEs) associated with adult depression and/or poor mental health (D/PMH) and adult-reported social and emotional support (ARSES) independent from adverse childhood experiences (ACEs)?

# data[].attributes.body
Risk factors are characteristics, conditions or behaviors at the individual, family or community level that increase a person's likelihood of negative health outcomes.

Examples:
Behavioral: substance abuse, physical inactivity, poor diet, etc.
Genetic/physiological: age, family and medical history, etc.
Environment/culture: poverty, institutional racism, poor working conditions, lack of access to healthcare, etc.

# data[].attributes.body
Protective factors are characteristics, conditions or behaviors at the individual, family or community level that increase a person's likelihood of positive health outcomes.

Examples:

Socioeconomic stability

Access to healthcare

Supportive relationships

Willingness to help and seek help

Healthy coping and problem-solving skills