Trends and geographical variation in population thriving, struggling and suffering across the USA, 2008-2017: a retrospective repeated cross-sectional study

Building local decision-making competencies during COVID-19: Accelerating the transition from learning healthcare systems to learning health communities

Introduction

The persisting and evolving COVID-19 pandemic has made apparent that no singular policy of mitigation at a regional, national or global level has achieved satisfactory and universally acceptable results. In the United States, carefully planned and executed pandemic policies have been neither effective nor popular and COVID-19 risk management decisions have been relegated to individual citizens and communities. In this paper, we argue that a more effective approach is to equip and strengthen community coalitions to become local learning health communities (LLHCs) that use data over time to make adaptive decisions that can optimize the equity and well-being in their communities.

Methods

We used data from the North Carolina (NC) county and zip code levels from May to August 2020 to demonstrate how a LLHC could use statistical process control (SPC) charts and simple statistical analysis to make local decisions about how to respond to COVID-19.

Results

We found many patterns of COVID-19 progression at the local (county and zip code) levels during the same time period within the state that were completely different from the aggregate NC state level data used for policy making.

Conclusions

Systematic approaches to learning from local data to support effective decisions have promise well beyond the current pandemic. These tools can help address other complex public health issues, and advance outcomes and equity. Building this capacity requires investment in data infrastructure and the strengthening of data competencies in community coalitions to better interpret data with limited need for advanced statistical expertise. Additional incentives that build trust, support data transparency, encourage truth-telling and promote meaningful teamwork are also critical. These must be carefully designed, contextually appropriate and multifaceted to motivate citizens to create and sustain an effective learning system that works for their communities.

Trends and Variation in the Gap Between Current and Anticipated Life Satisfaction in the United States, 2008-2020

Objectives. To describe national- and county-level trends and variation in a novel measure of hope. Methods. Using data from the Gallup National Health and Well-Being Index (n = 2 766 728), we summarized the difference between anticipated life satisfaction (ALS) and current life satisfaction (CLS), measured by the Cantril Self-Anchoring Scale, for each year from 2008 to 2020 and by county over two 5-year periods in the United States. Results. Across all years, there was a significant positive trend in the difference between ALS and CLS for the nation (P = .024), which remained positive but not significant when we excluded 2020. Maintenance of ALS with a decrease in CLS drove the 2020 increase. From 2008-2012 to 2013-2017, 14.5% of counties with 300 or more responses (n = 599) experienced an increase in the difference of more than 1 SD, whereas 13.9% experienced a more than 1 SD decrease. Fifty-two counties experienced decreases in ALS and CLS. Conclusions. Responding to trends in the gap between ALS and CLS at national and local levels is essential for the collective well-being of our nation, especially as we navigate and emerge from crisis.

Can a collective-impact initiative improve well-being in three US communities? Findings from a prospective repeated cross-sectional study

INTRODUCTION

Communities are seeking to learn if and how they can improve the well-being of their residents. We therefore examined the impact of a community-led, collective-impact initiative, deployed through Blue Zones Project by Sharecare, aimed at improving health and well-being in one set of US communities.

METHODS

We used data from cross-sectional surveys of the Well-Being Index (2010-2017) to assess how the Life Evaluation Index (LEI) in Hermosa Beach, Manhattan Beach and Redondo Beach in California (Beach Cities) changed over time and how this change compares with change for similar cities (Beach Cities-like) and for the USA as a whole. We examined types of interventions, perceived impacts, and relationships between intervention type and change in LEI.

RESULTS

The Beach Cities experienced greater increases in LEI than Beach Cities-like communities and the nation. The entire portfolio of interventions was positively associated with change in LEI in the Beach Cities (+1.12, p=0.012), with process-oriented interventions most closely associated with improvement.

CONCLUSIONS

Community-led collective action that leverages community engagement and activation, strategic use of programming and large-scale built-environment and policy change can improve health and well-being at scale.