Faculty Bibliography

OBJECTIVE:To explore associations among twenty formal and informal, societal and individual-level factors and quality of life (QOL) among people living with congestive heart failure (CHF) in two settings with different healthcare and social care systems and sociocultural contexts. SETTING AND PARTICIPANTS:We recruited 367 adult patients with CHF from a single heart failure clinic within two countries with different national social to healthcare spending ratios: Minneapolis, Minnesota, United States (US), and Nijmegen, Netherlands (NL). DESIGN:Cross-sectional survey study. We adapted the Social Quality Model (SQM) to organize twenty diverse factors into four categories: Living Conditions (formal-societal: e.g., housing, education), Social Embeddedness (informal-societal: e.g., social support, trust), Societal Embeddedness (formal-individual: e.g., access to care, legal aid), and Self-Regulation (informal-individual: e.g., physical health, resilience). We developed a survey comprising validated instruments to assess each factor. We administered the survey in-person or by mail between March 2017 and August 2018. OUTCOMES:We used Cantril's Self-Anchoring Scale to assess overall QOL. We used backwards stepwise regression to identify factors within each SQM category that were independently associated with QOL among US and NL participants (p<0.05). We then identified factors independently associated with QOL across all categories (p<0.05). RESULTS:367 CHF patients from the US (32%) and NL (68%) participated. Among US participants, financial status, receiving legal aid or housing assistance, and resilience were associated with QOL, and together explained 49% of the variance in QOL; among NL participants, financial status, perceived physical health, independence in activities of daily living, and resilience were associated with QOL, and explained 53% of the variance in QOL. CONCLUSIONS:Four formal and informal factors explained approximately half of the variance in QOL among patients with CHF in the US and NL.

OBJECTIVE:To evaluate the association between community well-being, a positively framed, multidimensional assessment of the health and quality of life of a geographic community, and hospitalisation rates. DESIGN:Cross-sectional study SETTING: Zip codes within six US states (Florida, Iowa, Nebraska, New York, Pennsylvania and Utah) MAIN OUTCOME MEASURES: Our primary outcome was age-adjusted, all-cause hospitalisation rates in 2010; secondary outcomes included potentially preventable disease-specific hospitalisation rates, including cardiovascular-related, respiratory-related and cancer-related admissions. Our main independent variable was the Gallup-Sharecare Well-Being Index (WBI) and its domains (life evaluation, emotional health, work environment, physical health, healthy behaviours and basic access). RESULTS:Zip codes with the highest quintile of well-being had 223 fewer hospitalisations per 100 000 (100k) residents than zip codes with the lowest well-being. In our final model, adjusted for WBI respondent age, sex, race/ethnicity and income, and zip code number of hospital beds, primary care physician density, hospital density and admission rates for two low-variation conditions, a 1 SD increase in WBI was associated with 5 fewer admissions/100k (95% CI 4.0 to 5.8; p<0.001). Results were similar for cardiovascular-related and respiratory-related admissions, but no association remained for cancer-related hospitalisation after adjustment. Patterns were similar for each of the WBI domains and all-cause hospitalisations. CONCLUSION AND RELEVANCE:Community well-being is inversely associated with local hospitalisation rates. In addition to health and quality-of-life benefits, higher community well-being may also result in fewer unnecessary hospitalisations.

OBJECTIVE:To determine if preterm birth, defined as gestational age <37 weeks, is lower for women living in counties with higher well-being, after accounting for known individual risk factors. DESIGN:Cross-sectional study of all US births in 2011. PARTICIPANTS:We obtained birth data from the National Center for Health Statistics which included 3 938 985 individuals. MAIN OUTCOMES MEASURES:Primary outcome measure was maternal risk of preterm delivery by county; primary independent variable was county-level well-being as measured by the Gallup-Sharecare Well-Being Index (WBI). RESULTS:Women living in counties with higher population well-being had a lower rate of preterm delivery. The rate of preterm birth in counties in the lowest WBI quintile was 13.1%, while the rate of preterm birth in counties in the highest WBI quintile was 10.9%. In the model adjusted for maternal risk factors (age, race, Hispanic ethnicity, smoking status, timing of initiation of prenatal visits, multiparity, maternal insurance payer), the association was slightly attenuated with an absolute difference of 1.9% (95% CI 1.7% to 2.1%; p<0.001). CONCLUSIONS:Pregnant women who live in areas with higher population well-being have lower risk of preterm birth, even after accounting for individual risk factors.

Objective:To describe the rationale and design of a prospective study of ambulatory blood pressure measurement (ABPM) combined with measurement of contextual factors to identify hypertensive phenotypes in a Caribbean population with high rates of HTN and cardiovascular disease. Design:Prospective, multi-center sub-study. Setting:Eastern Caribbean Health Outcomes Research Network Cohort (ECHORN) Study, with study sites in Puerto Rico, the US Virgin Islands, Trinidad and Tobago, and Barbados. Participants:Community-residing adults without a diagnosis of HTN and not taking antihypertensive medication. Intervention:Ambulatory BP patterns are assessed using 24-hour ABPM. Contextual factors are assessed with: ecological momentary assessment (7-item survey of experiences, exposures and responses associated with daytime BP measurements); actigraphy (capturing physical activity and sleep quality); and self-report surveys (assessing physical and social health, environmental and social stressors and supports). Main Outcome Measures:Phenotypes of contextual factors associated with hypertensive BP patterns (sustained HTN, masked HTN, and nocturnal non-dipping). Methods and Results:This study will enroll 500 participants; assessments of blood pressure and contextual factors will be conducted during Waves 2 and 3 of the ECHORN parent study, occurring 2 years apart. In Wave 2, we will assess the association between contextual factors and ABPM patterns. Using advanced analytic clustering methods, we will identify phenotypes of contextual factors associated with hypertensive ABPM patterns. We will then test the stability of these phenotypes and their ability to predict change in ABPM patterns between Waves 2 and 3. Conclusions:Assessment of ABPM, and the contextual factors influencing ABPM, can identify unique phenotypes of HTN, which can then be used to develop more precision-based approaches to the prevention, detection and treatment of HTN in high-risk populations.

Chronic stress is a risk factor for incident cardiovascular (CV) disease. Emotion regulation is the ability to modulate one's state or behavior in response to a given situation or stressor, and may mitigate the effect of chronic stress on CV disease risk. Data from a cohort of 754 community-dwelling young to middle-aged adults who were assessed between 2007 and 2012 on stress, emotion regulation, and CV risk measures were used to test the hypothesis that emotion regulation mitigates the effect of chronic stress on CV risk. Emotion regulation was measured using the Difficulties in Emotion Regulation Scale (DERS). We created a composite stress score using data from the Cumulative Adversity Interview and the Perceived Stress Scale. Our outcomes included blood pressure, body mass index, and insulin resistance separately and combined into a composite CV risk score. Covariates included age, sex, race, years of education, and smoking status. We used multivariable logistic regression to evaluate associations between stress measures and CV risk among participants and the impact of emotion regulation (DERS scores) on this association. We found that composite stress interacted significantly with the DERS score to affect CV risk (p = .007). A median split of the DERS scores indicated that CV risk was associated with the composite stress score in the fully adjusted model (ß = 0.206; p = .005) among participants with low emotion regulation, but not among those with high emotion regulation (ß = 0.048; p = .59). Chronic stress was associated with CV risk only among participants with poor emotion regulation. Emotion regulation is a teachable skill, and may play a role in preventing CV disease.Lay summaryEmotion regulation is the ability to modify one's reaction to a negative or stressful event, and is a teachable skill. Effective emotion regulation dampens the negative effect of chronic stress on the body, which may reduce risk for cardiovascular disease.

OBJECTIVES:To propose collective well-being as a holistic measure of the overall "health" of a community. To define collective well-being as a group-level construct measured across 5 domains (vitality, opportunity, connectedness, contribution, and inspiration) and introduce an actionable model that demonstrates how community characteristics affect collective well-being. To review the literature describing each domain's association with health outcomes and community characteristics' associations with collective well-being. METHODS:We came to consensus on topics describing each component of our conceptual model. Because "well-being" is not indexed in MEDLINE, we performed topic-specific database searches and examined bibliographies of papers retrieved. We excluded articles that were limited to narrow subtopics or studies within small subpopulations. Preference was given to quasi-experimental or randomized studies, systematic reviews, or meta-analyses. Consensus was reached on inclusion or exclusion of all articles. RESULTS:Reviewed literature supported each of the proposed domains as important aspects of collective well-being and as determinants of individual or community health. Evidence suggests a broad range of community characteristics support collective well-being. CONCLUSIONS:The health and quality of life of a community may be improved by focusing efforts on community characteristics that support key aspects of well-being. Future work should develop a unified measure of collective well-being to evaluate the relative impact of specific efforts on the collective well-being of communities.