"We don't separate out these things. Everything is related": Partnerships with Indigenous Communities to Design, Implement, and Evaluate Multilevel Interventions to Reduce Health Disparities

Multilevel interventions (MLIs) are appropriate to reduce health disparities among Indigenous peoples because of their ability to address these communities' diverse histories, dynamics, cultures, politics, and environments. Intervention science has highlighted the importance of context-sensitive MLIs in Indigenous communities that can prioritize Indigenous and local knowledge systems and emphasize the collective versus the individual. This paradigm shift away from individual-level focus interventions to community-level focus interventions underscores the need for community engagement and diverse partnerships in MLI design, implementation, and evaluation. In this paper, we discuss three case studies addressing how Indigenous partners collaborated with researchers in each stage of the design, implementation, and evaluation of MLIs to reduce health disparities impacting their communities. We highlight the following: (1) collaborations with multiple, diverse tribal partners to carry out MLIs which require iterative, consistent conversations over time; (2) inclusion of qualitative and Indigenous research methods in MLIs as a way to honor Indigenous and local knowledge systems as well as a way to understand a health disparity phenomenon in a community; and (3) relationship building, maintenance, and mutual respect among MLI partners to reconcile past research abuses, prevent extractive research practices, decolonize research processes, and generate co-created knowledge between Indigenous and academic communities.

Food Insecurity and Social Policy: A Comparative Analysis of Welfare State Regimes in 19 Countries

We sought to determine whether a country's social policy configuration-its welfare state regime-is associated with food insecurity risk. We conducted a cross-sectional study of 2017 U.N. Food and Agriculture Organization individual-level food insecurity survey data from 19 countries (the most recent data available prior to COVID-19). Countries were categorized into three welfare state regimes: liberal (e.g., the United States), corporatist (e.g., Germany), or social democratic (e.g., Norway). Food insecurity probability, calibrated to an international reference standard, was calculated using a Rasch model. We used linear regression to compare food insecurity probability across regime types, adjusting for per-capita gross domestic product, age, gender, education, and household composition. There were 19,008 participants. The mean food insecurity probability was 0.067 (SD: 0.217). In adjusted analyses and compared with liberal regimes, food insecurity probability was lower in corporatist (risk difference: -0.039, 95% CI -0.066 to -0.011, p  =  .006) and social democratic regimes (risk difference: -0.037, 95% CI -0.062 to -0.012, p  =  .004). Social policy configuration is strongly associated with food insecurity risk. Social policy changes may help lower food insecurity risk in countries with high risk.

Understanding food insecurity risk in the United States: A longitudinal analysis

Background

Food insecurity, lack of consistent access to the food needed for an active, healthy life, harms population health. Although substantial biomedical evidence examines the connections between food insecurity and health, fewer studies examine why food insecurity occurs.

Methods

We propose a conceptual understanding of food insecurity risk based on institutions that distribute income-the factor payment system (income distribution stemming from paid labor and asset ownership), transfers within households, and the government tax-and-transfer system. A key feature of our understanding is 'roles' individuals inhabit in relation to the factor payment system: child, older adult, disabled working-age adult, student, unemployed individual, caregiver, or paid laborer. A second feature is that the roles of others in an individual's household also affect an individual's food insecurity risk. We tested hypotheses implied by this understanding, particularly hypotheses relating to role, household composition, and income support programs, using nationally-representative, longitudinal U.S. Current Population Survey data (2016-2019).

Results

There were 16,884 participants (year 1 food insecurity prevalence: 10.0%). Inhabiting roles of child (Relative Risk [RR] 1.79, 95% Confidence Interval [95%CI] 1.67 to 1.93), disabled working age-adult (RR 3.74, 95%CI 3.25 to 4.31), or unemployed individual (RR 3.29, 95%CI 2.51 to 4.33) were associated with a greater risk of food insecurity than being a paid laborer. Most food insecure households, 74.8%, had members inhabiting roles of child or disabled working age-adult, and/or contained individuals who experienced job loss. Similar associations held when examining those transitioning from food insecurity to food security in year 2.

Conclusions

The proposed understanding accords with the pattern of food insecurity risk observed in the U.S. An implication is that transfer income programs for individuals inhabiting roles, such as childhood and disability, that limit factor payment system participation may reduce food insecurity risk for both those individuals and those in their household.

Examining Changes in Food Security, Perceived Stress, and Dietary Intake in a Cohort of Low-Wage Workers Experiencing an Increase in Hourly Wage

OBJECTIVE

To determine whether an increase in hourly wages was associated with changes in food security and perceived stress among low-wage workers. We also determined whether changes in food security and stress were associated with changes in diet.

SETTING

Wages is a prospective cohort study following 974 low-wage workers in Minneapolis, MN, where an ordinance is incrementally increasing minimum wage to US$15/hr from 2018 to 2022, and a comparison community with no minimum wage ordinance (Raleigh, NC). Interaction models were estimated using generalized estimating equations.

PARTICIPANTS

Analyses used two waves of data (2018 [baseline], 2019) and included 219 and 321 low-wage workers in Minneapolis and Raleigh (respectively).

RESULTS

Average hourly wages increased from US$9.77 (SD US$1.69) to US$11.67 (SD US$4.02). Changes in wages were not associated with changes in food security (odds ratio = 1.05, 95% confidence interval [CI] [0.89, 1.23], p = .57) or stress (β = -0.01, 95% CI [-0.04, 0.03], p = .70) after 1 year of policy implementation. Changes in food security were not associated with changes in diet. However, we found significant changes in the frequency of fruit and vegetable intake across time by levels of stress, with decreased intake from Wave 1 to 2 at low levels of stress, and increased intake at high levels of stress (incidence rate ratio = 1.17, 95% CI [1.05, 1.31], p = .01).

CONCLUSIONS

Changes in wages were not associated with changes in food security or stress in a sample of low-wage workers. Future research should examine whether full implementation of a minimum wage increase is associated with changes in these outcomes.

Social Isolation, Loneliness, and Quality of Life Among Food-Insecure Adults

INTRODUCTION

Food insecurity is associated with adverse health outcomes, but may also have a detrimental effect on social relationships, potentially exacerbating social isolation and loneliness, and consequently affecting health-related quality of life. This study examined the associations of food insecurity with social isolation, loneliness, and health-related quality of life among U.S. adults.

METHODS

A retrospective cohort study was conducted using panel data from the 2020-2021 Medical Expenditure Panel Survey. Regression models were used to assess the associations of food insecurity in 1 year with the outcomes of interest in the subsequent year while adjusting for baseline individual-level characteristics. Analysis was conducted in December 2023.

RESULTS

Experiencing food insecurity in 2020 was significantly associated with increased reports of social isolation (3.1 percentage points [95% CI: 1.2-5.1]) and loneliness (9.7 percentage points [95% CI: 1.0-18.3]) in 2021. Additionally, food insecurity in 2020 was significantly associated with lower self-reported good mental health (-2.9 percentage points [95% CI: -5.1, -0.6]) and mental component summary score from the Short Form-12 Health Survey (-3.3 points [95% CI -3.8, -2.9]) in 2021. However, there were no or small associations with physical health-related quality of life.

CONCLUSIONS

Food insecurity is associated with worse social and mental well-being among U.S. adults. This suggests that food insecurity interventions should not focus too narrowly on nutrition, but instead give holistic consideration to the multiple ways food insecurity harms health-not only via lower quality diets, but through worse mental health and impairing the ability to participate in social life.

Benefits, Challenges, and Opportunities in Addressing Medicaid Beneficiaries' Non-Medical Risks to Health: A Qualitative Analysis

CONTEXT

North Carolina's Healthy Opportunities Pilots (HOP) is a Medicaid 1115 Waiver program that seeks to address nonmedical risks to health for Medicaid beneficiaries through multisector collaboration. Among other stakeholders, HOP involves collaboration between human services organizations that deliver interventions, network leads, which establish and oversee the human services organizations within a region of the state.

OBJECTIVE

To understand how employees at human services organizations and network leads prepared to deliver HOP services.

DESIGN

Qualitative analysis of semistructured interviews. Interviews were conducted between April and June 2022. Interviews were recorded, transcribed verbatim, coded thematically, and analyzed using a conceptual model derived from the consolidated framework for implementation research.

SETTING

Organizations within North Carolina counties participating in HOP.

PARTICIPANTS

Employees of human services and network lead organizations across all 3 HOP regions of North Carolina.

RESULTS

The researchers interviewed 37 participants. Overall, organizations experienced benefits from HOP participation, including capacity-building resources, flexibility in allocating resources, and creating community-wide enthusiasm for addressing nonmedical risks to health. There were also key challenges. These included the time needed to build capacity, adjustments to the work processes and regulations inherent to multisector collaboration, geographic variation in availability of services to offer, and the difficulty of addressing different needs. Finally, participants recognized substantial opportunities that HOP presented, including membership in a more extensive network, exposure to a learning community, and a more sustainable funding source.

CONCLUSIONS

The perspectives of individuals preparing to deliver HOP services offer important lessons for those developing and implementing large-scale programs that can address nonmedical threats to health.

Accuracy of a Single Financial Security Question to Screen for Social Needs

OBJECTIVES

Screening for social needs is recommended during clinical encounters but multi-item questionnaires can be burdensome. We evaluate if a single question about financial stress can be used to prescreen for food insecurity, housing instability, or transportation needs.

METHODS

We use retrospective medical record data from children (<11 years) seen at 45 primary pediatric care offices in 2022. Social needs screening was automated at well child visits and could be completed by the parent/guardian via the patient portal, tablet in the waiting room, or verbally with staff. We report the area under the receiver operating curve for the 5 response options of the financial stress question as well as sensitivity and specificity of the financial stress question ("not hard at all" vs any other response) to detect other reported social needs.

RESULTS

Of 137 261 eligible children, 130 414 (95.0%) had social needs data collected. Seventeen percent of respondents reported a housing, food, or transportation need. The sensitivity of the financial stress question was 0.788 for any one or more of the 3 other needs, 0.763 for food insecurity, 0.743 for housing instability, and 0.712 for transportation needs. Using the financial stress question as the first-step of a screening process would miss 9.7% of the families who reported food insecurity, 22.6% who reported housing instability, and 33.0% who reported transportation needs.

CONCLUSIONS

A single question screener about financial stress does not function well as a prescreen because of low sensitivity to reports of food insecurity, housing instability, and transportation needs.

Multisector Collaboration vs. Social Democracy for Addressing Social Determinants of Health

Policy Points Multisector collaboration, the dominant approach for responding to health harms created by adverse social conditions, involves collaboration among health care insurers, health care systems, and social services organizations. Social democracy, an underused alternative, seeks to use government policy to shape the civil (e.g., civil rights), political (e.g., voting rights), and economic (e.g., labor market institutions, property rights, and the tax-and-transfer system) institutions that produce health. Multisector collaboration may not achieve its goals, both because the collaborations are difficult to accomplish and because it does not seek to transform social conditions, only to mitigate their harms. Social democracy requires political contestation but has greater potential to improve population health and health equity.

Permanent Supportive Housing Receipt and Health Care Use Among Adults With Disabilities

This study assessed whether permanent supportive housing (PSH) participation is associated with health service use among a population of adults with disabilities, including people transitioning into PSH from community and institutional settings. Our primary data sources were 2014 to 2018 secondary data from a PSH program in North Carolina linked to Medicaid claims. We used propensity score weighting to estimate the average treatment effect on the treated of PSH participation. All models were stratified by whether individuals were in institutional or community settings prior to PSH. In weighted analyses, among individuals who were institutionalized prior to PSH, PSH participation was associated with greater hospitalizations and emergency department (ED) visits and fewer primary care visits during the follow-up period, compared with similar individuals who largely remained institutionalized. Individuals who entered PSH from community settings did not have significantly different health service use from similar comparison group members during the 12-month follow-up period.

Association of Unmet Social Needs With Metformin Use Among Patients With Type 2 Diabetes

OBJECTIVE

To evaluate the relationship between social needs and metformin use among adults with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

In a prospective cohort study of adults with T2D (n = 722), we linked electronic health record (EHR) and Surescripts (Surescripts, LLC) prescription network data to abstract data on patient-reported social needs and to calculate metformin adherence based on expected refill frequency using a proportion of days covered methodology.

RESULTS

After adjusting for demographics and clinical complexity, two or more social needs (-0.046; 95% CI -0.089, 0.003), being uninsured (-0.052; 95% CI -0.095, -0.009) and while adjusting for other needs, being without housing (-0.069; 95% CI -0.121, -0.018) and lack of access to medicine/health care (-0.058; 95% CI -0.115, -0.000) were associated with lower use.

CONCLUSIONS

We found that overall social need burden and specific needs, particularly housing and health care access, were associated with clinically significant reductions in metformin adherence among patients with T2D.

Food Is Medicine: A Presidential Advisory From the American Heart Association

Unhealthy diets are a major impediment to achieving a healthier population in the United States. Although there is a relatively clear sense of what constitutes a healthy diet, most of the US population does not eat healthy food at rates consistent with the recommended clinical guidelines. An abundance of barriers, including food and nutrition insecurity, how food is marketed and advertised, access to and affordability of healthy foods, and behavioral challenges such as a focus on immediate versus delayed gratification, stand in the way of healthier dietary patterns for many Americans. Food Is Medicine may be defined as the provision of healthy food resources to prevent, manage, or treat specific clinical conditions in coordination with the health care sector. Although the field has promise, relatively few studies have been conducted with designs that provide strong evidence of associations between Food Is Medicine interventions and health outcomes or health costs. Much work needs to be done to create a stronger body of evidence that convincingly demonstrates the effectiveness and cost-effectiveness of different types of Food Is Medicine interventions. An estimated 90% of the $4.3 trillion annual cost of health care in the United States is spent on medical care for chronic disease. For many of these diseases, diet is a major risk factor, so even modest improvements in diet could have a significant impact. This presidential advisory offers an overview of the state of the field of Food Is Medicine and a road map for a new research initiative that strategically approaches the outstanding questions in the field while prioritizing a human-centered design approach to achieve high rates of patient engagement and sustained behavior change. This will ideally happen in the context of broader efforts to use a health equity-centered approach to enhance the ways in which our food system and related policies support improvements in health.

Protocol for a randomized controlled trial of medically tailored meals compared to usual care among individuals with type 2 diabetes in Australia

BACKGROUND

'Food is medicine' strategies aim to integrate food-based nutrition interventions into healthcare systems and are of growing interest to healthcare providers and policy makers. 'Medically Tailored Meals' (MTM) is one such intervention, which involves the 'prescription' by healthcare providers of subsidized, pre-prepared meals for individuals to prevent or manage chronic conditions, combined with nutrition education.

OBJECTIVE

This study will test the efficacy of an MTM program in Australia among participants with type 2 diabetes (T2D) and hyperglycemia, who experience difficulties accessing and eating nutritious food.

METHODS

This study will be a two-arm parallel trial (goal n = 212) with individuals randomized in a 1:1 ratio to a MTM intervention group or a control group (106 per arm). Over 26 weeks, the intervention group will be prescribed 20 MTM per fortnight and up to 3 sessions with an accredited dietitian. Controls will continue with their usual care. The primary outcome is glycated hemoglobin (HbA1c, %) and secondary outcomes include differences in blood pressure, blood lipids and weight, all measured at 26 weeks. Process and economic data will be analyzed to assess the feasibility, acceptability, scalability, and cost-effectiveness of the intervention. Recruitment commenced in the first quarter of 2023, with analyses and results anticipated to be available by March 2025.

DISCUSSION

Few randomized controlled trials have assessed the impact of MTM on clinical outcomes. This Australian-first trial will generate robust data to inform the case for sustained, large-scale implementation of MTM to improve the management of T2D among vulnerable populations.

ANZCTR

ACTRN12622000852752.

PROTOCOL VERSION

Version 1.1, July 2023.

Potential gaps in income support policies for those in poor health: The case of the earned income tax credit-A cross sectional analysis

Background

The federal Earned Income Tax Credit (EITC) is the primary income support program for low-income workers in the U.S., but its design may hinder its effectiveness when poor health limits, but does not preclude, work.

Methods

Cross-sectional analysis of nationally-representative U.S. Census Current Population Survey (CPS) data covering 2019. Working-age adults eligible to receive federal EITC were included in this study. Poor health, as indicated by self-report of at least one problem with hearing, vision, cognitive function, mobility, dressing and bathing, or independence, was the exposure. The main outcome was federal EITC benefit category, categorized as no benefit, phase-in (income too low for the maximum benefit), plateau (maximum benefit), phase-out (income above threshold for maximum benefit), or earnings too high to receive any benefit. We estimated EITC benefit category probabilities by health status using multinomial logistic regression. We further examined whether other government benefits provided additional income support to those in poor health.

Results

41,659 participants (representing 87.1 million individuals) were included. 2,724 participants (representing 5.6 million individuals) reported poor health. In analyses standardized over age, gender, race, and ethnicity, those in poor health, compared with those not in poor health, were more likely to be in the no benefit (2.40% vs. 0.30%, risk difference 2.10 percentage points [95%CI 1.75 to 2.46 percentage points]), and phase-in (9.28% vs. 2.74%, risk difference 6.54 percentage points [95%CI 5.82 to 7.26 percentage points]) categories. Differences in resources by health status persisted even after accounting for other government benefits.

Conclusions

EITC program design creates an important gap in income support for those for whom poor health limits work, which is not closed by other programs. Filling this gap is an important public health goal.

Eliminating Food Insecurity in the USA: a Target Trial Emulation Using Observational Data to Estimate Effects on Health-Related Quality of Life

BACKGROUND

Food insecurity is associated with many aspects of poor health. However, trials of food insecurity interventions typically focus on outcomes of interest to funders, such as healthcare use, cost, or clinical performance metrics, rather than quality of life outcomes that may be prioritized by individuals who experience food insecurity.

OBJECTIVE

To emulate a trial of a food insecurity elimination intervention, and quantify its estimated effects on health utility, health-related quality of life, and mental health.

DESIGN

Target trial emulation using longitudinal, nationally representative data, from the USA, 2016-2017.

PARTICIPANTS

A total of 2013 adults in the Medical Expenditure Panel Survey screened positive for food insecurity, representing 32 million individuals.

MAIN MEASURES

Food insecurity was assessed using the Adult Food Security Survey Module. The primary outcome was the SF-6D (Short-Form Six Dimension) measure of health utility. Secondary outcomes were mental component score (MCS) and physical component score (PCS) of the Veterans RAND 12-Item Health Survey (a measure of health-related quality of life), Kessler 6 (K6) psychological distress, and Patient Health Questionnaire 2-item (PHQ2) depressive symptoms.

KEY RESULTS

We estimated that food insecurity elimination would improve health utility by 80 QALYs per 100,000 person-years, or 0.008 QALYs per person per year (95% CI 0.002 to 0.014, p = 0.005), relative to the status quo. We also estimated that food insecurity elimination would improve mental health (difference in MCS [95% CI]: 0.55 [0.14 to 0.96]), physical health (difference in PCS: 0.44 [0.06 to 0.82]), psychological distress (difference in K6: -0.30 [-0.51 to -0.09]), and depressive symptoms (difference in PHQ-2: -0.13 [-0.20 to  -0.07]).

CONCLUSIONS

Food insecurity elimination may improve important, but understudied, aspects of health. Evaluations of food insecurity interventions should holistically investigate their potential to improve many different aspects of health.

Estimated Costs of Intervening in Health-Related Social Needs Detected in Primary Care

Importance

Health-related social needs are increasingly being screened for in primary care practices, but it remains unclear how much additional financing is required to address those needs to improve health outcomes.

Objective

To estimate the cost of implementing evidence-based interventions to address social needs identified in primary care practices.

Design, Setting, and Participants

A decision analytical microsimulation of patients seen in primary care practices, using data on social needs from the National Center for Health Statistics from 2015 through 2018 (N = 19 225) was conducted. Primary care practices were categorized as federally qualified health centers (FQHCs), non-FQHC urban practices in high-poverty areas, non-FQHC rural practices in high-poverty areas, and practices in lower-poverty areas. Data analysis was performed from March 3 to December 16, 2022.

Intervention

Simulated evidence-based interventions of primary care-based screening and referral protocols, food assistance, housing programs, nonemergency medical transportation, and community-based care coordination.

Main Outcomes and Measures

The primary outcome was per-person per-month cost of interventions. Intervention costs that have existing federally funded financing mechanisms (eg, the Supplemental Nutrition Assistance Program) and costs without such an existing mechanism were tabulated.

Results

Of the population included in the analysis, the mean (SD) age was 34.4 (25.9) years, and 54.3% were female. Among people with food and housing needs, most were program eligible for federally funded programs, but had low enrollment (eg, due to inadequate program capacity), with 78.0% of people with housing needs being program eligible vs 24.0% enrolled, and 95.6% of people with food needs being program eligible vs 70.2% enrolled. Among those with transportation insecurity and care coordination needs, eligibility criteria limited enrollment (26.3% of those in need being program eligible for transportation programs, and 5.7% of those in need being program eligible for care coordination programs). The cost of providing evidence-based interventions for these 4 domains averaged $60 (95% CI, $55-$65) per member per month (including approximately $5 for screening and referral management in clinics), of which $27 (95% CI, $24-$31) (45.8%) was federally funded. While disproportionate funding was available to populations seen at FQHCs, populations seen at non-FQHC practices in high-poverty areas had larger funding gaps (intervention costs not borne by existing federal funding mechanisms).

Conclusions and Relevance

In this decision analytical microsimulation study, food and housing interventions were limited by low enrollment among eligible people, whereas transportation and care coordination interventions were more limited by narrow eligibility criteria. Screening and referral management in primary care was a small expenditure relative to the cost of interventions to address social needs, and just under half of the costs of interventions were covered by existing federal funding mechanisms. These findings suggest that many resources are necessary to address social needs that fall largely outside of existing federal financing mechanisms.

Statistically Adjusting for Wear Time in Randomized Trials of Continuous Glucose Monitors as a Complement to Intent-to-Treat and As-Treated Analyses: Application and Evaluation in Two Trials

Background: Randomized trials of continuous glucose monitoring (CGM) often estimate treatment effects using standard intent-to-treat (ITT) analyses. We explored how adjusting for CGM-measured wear time could complement existing analyses by estimating the effect of receiving and using CGM 100% of the time. Methods: We analyzed data from two 6-month CGM trials spanning diverse ages, the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) and CGM Intervention in Teens and Young Adults with Type 1 Diabetes (CITY) Studies. To adjust the ITT estimates for CGM use, as measured by wear time, we used an instrumental variable (IV) approach with the treatment assignment as an instrument. Outcomes included (1) time in range ([TIR] 70-180 mg/dL), time below range ([TBR] ≤70 mg/dL), and time above range ([TAR] ≥250 mg/dL). We estimated outcomes based on CGM use in the last 28 days of the trial and the full trial. Findings: In the WISDM study, the wear time rates over the 28-day window and full trial period were 93.1% (standard deviation [SD]: 20.4) and 94.5% (SD: 11.9), respectively. In the CITY study, the wear time rates over the 28-day window and full trial period were 82.2% (SD: 26.5) and 83.1% (SD: 21.5), respectively. IV-based estimates for the effect of CGM on TIR, TBR, and TAR suggested greater improvements in glycemic management than the ITT counterparts. The magnitude of the differences was proportional to the level of wear time observed in the trials. Interpretation: In trials of CGM use, the effect of variable wear time is non-negligible. By providing adherence-adjusted estimates, the IV approach may have additional utility for individual clinical decision-making.

Diet and Food and Nutrition Insecurity and Cardiometabolic Disease

Poor nutrition is the leading cause of poor health, health care spending, and lost productivity in the United States and globally, which acts through cardiometabolic diseases as precursors to cardiovascular disease, cancer, and other conditions. There is great interest in how the social determinants of health (the conditions in which people are born, live, work, develop, and age) impact cardiometabolic disease. Food insecurity is an example of a powerful social determinant of health that impacts health outcomes. Nutrition insecurity, a distinct but related concept to food insecurity, is a direct determinant of health. In this article, we provide an overview of how diet in early life relates to cardiometabolic disease and then continue to focus on the concepts of food insecurity and nutrition insecurity. In the discussions herein we make important distinctions between the concepts of food insecurity and nutrition insecurity and provide a review of their concepts, histories, measurement and assessment devices, trends and prevalence, and links to health and health disparities. The discussions here set the stage for future research and practice to directly address the negative consequences of food and nutrition insecurity.

Evaluation of a Produce Prescription Program for Patients With Diabetes: A Longitudinal Analysis of Glycemic Control

OBJECTIVE

Produce prescriptions have shown promise in improving diabetes care, although most studies have used small samples or lacked controls. Our objective was to evaluate the impacts of a produce prescription program on glycemic control for patients with diabetes.

RESEARCH DESIGN AND METHODS

Participants included a nonrandom enrollment of 252 patients with diabetes who received a produce prescription and 534 similar control participants from two clinics in Hartford, Connecticut. The start of the COVID-19 pandemic in March 2020 coincided with program implementation. Produce prescription enrollees received vouchers ($60 per month) for 6 months to purchase produce at grocery retail. Controls received usual care. The primary outcome was change in glycated hemoglobin (HbA1c) between treatment and control at 6 months. Secondary outcomes included 6-month changes in systolic (SBP) and diastolic blood pressure (DBP), BMI, hospitalizations, and emergency department admissions. Longitudinal generalized estimating equation models, weighted with propensity score overlap weights, assessed changes in outcomes over time.

RESULTS

At 6 months, there was no significant difference in change in HbA1c between treatment and control groups, with a difference of 0.13 percentage points (95% CI -0.05, 0.32). No significant difference was observed for change in SBP (3.85 mmHg; -0.12, 7.82), DBP (-0.82 mmHg; -2.42, 0.79), or BMI (-0.22 kg/m2; -1.83, 1.38). Incidence rate ratios for hospitalizations and emergency department visits were 0.54 (0.14, 1.95) and 0.53 (0.06, 4.72), respectively.

CONCLUSIONS

A 6-month produce prescription program for patients with diabetes, implemented during the onset of the COVID-19 pandemic, was not associated with improved glycemic control.

Gaps in the welfare state: A role-based model of poverty risk in the U.S

BACKGROUND

Research clearly demonstrates that income matters greatly to health. However, income distribution and its relationship to poverty risk is often misunderstood.

METHODS

We provide a structural account of income distribution and poverty risk in the U.S., rooted in the 'roles' that individuals inhabit with relation to the 'factor payment system' (market distribution of income to individuals through wages and asset ownership). Principal roles are child, older adult, and, among working-age adults, disabled individual, student, unemployed individual, caregiver, or paid laborer. Moreover, the roles of other members of an individual's household also influence an individual's income level. This account implies that 1) roles other than paid laborer will be associated with greater poverty risk, 2) household composition will be associated with poverty risk, and 3) income support policies for those not able to engage in paid labor are critical for avoiding poverty. We test hypotheses implied by this account using 2019 and 2022 U.S. Census Current Population Survey data. The exposure variables in our analyses relate to roles and household composition. The outcomes relate to income and poverty risk.

RESULTS

In 2019, 40.1 million individuals (12.7% of the population) experienced poverty under the U.S. Census' Supplemental Poverty Measure. All roles other than paid laborer were associated with greater poverty risk (p < .001 for all comparisons). Household composition, particularly more children and disabled working-age adults, and fewer paid laborers, was also associated with greater poverty risk (p < .001 for all comparisons). Five key policy areas-child benefits, older-age pensions, disability and sickness insurance, unemployment insurance, and out-of-pocket healthcare spending-represented gaps in the welfare state strongly associated with poverty risk.

CONCLUSIONS

The role one inhabits and household composition are associated with poverty risk. This understanding of income distribution and poverty risk may be useful for social policy.

Financing Health Care System Interventions Addressing Social Risks

This Viewpoint discusses the benefits and drawbacks of health care involvement in social risk interventions and presents proposals to finance such involvement.

Food Insecurity Was Associated With Greater Family Health Care Expenditures In The US, 2016-17

Food insecurity has been associated with the health care expenditures of individuals, but it can affect the entire family. Evaluating the relationship between food insecurity and family expenditures provides a better understanding of the financial implications of food insecurity interventions. Our primary objective was to evaluate the association between food insecurity in one year (2016) and family health care expenditures-for all members, for children only, and for adults only-in the next year (2017). We also evaluated whether this association varied across types of insurance coverage within families: all private, all public, or mixed (including uninsured). Using nationally representative data, we found that food-insecure families had 20 percent greater total health care expenditures than food-secure families, for an annual difference of $2,456. Food insecurity was associated with greater expenditures across all family insurance patterns, including the 19.1 percent of families with mixed coverage. Our findings suggest that in families with mixed coverage, positive impacts of food insecurity interventions on health care use may accrue to family members other than the targeted beneficiaries and those who have different insurance, benefiting the entire family but potentially discouraging investments on the part of any one payer.

Medically tailored meals for food insecurity and type 2 diabetes: Protocol for the Food as Medicine for Diabetes (FAME-D) trial

BACKGROUND

Food insecurity is associated with worse glycemic management for individuals with type 2 diabetes mellitus (T2DM), but whether medically tailored meals (MTM), a food insecurity intervention, can improve glycemic management is unclear.

OBJECTIVE

To describe the protocol for a trial assessing whether an MTM plus lifestyle intervention improves hemoglobin A1c (HbA1c) and participant-reported outcomes, relative to a food subsidy (money that can be spent on foods participants choose), for adults with both T2DM and food insecurity.

METHODS

The Food as Medicine for Diabetes (FAME-D) randomized clinical trial (goal n = 200) is a pragmatic trial with an active comparator. Participants, who will have T2DM and report food insecurity, will be randomly assigned to a 6-month MTM plus telephone-delivered lifestyle change intervention, or a 6-month food subsidy ($40/month). The primary outcome is HbA1c at 6 months. Secondary outcomes include HbA1c at 12 months to assess whether the intervention effect (if any) is sustained, along with weight, food insecurity, diabetes distress, and health-related quality of life. Qualitative analyses of semi-structured interviews will help understand why, how, and under what circumstances the intervention achieved its observed results.

CONCLUSION

Results from FAME-D will help inform clinical management of food insecurity when it co-occurs with T2DM. Further, results may be useful as healthcare payors are considering coverage for MTM interventions.

CLINICALTRIALS

gov: NCT04828785.

A two-stage super learner for healthcare expenditures

Objective

To improve the estimation of healthcare expenditures by introducing a novel method that is well-suited to situations where data exhibit strong skewness and zero-inflation.

Data Sources

Simulations, and two real-world datasets: the 2016-2017 Medical Expenditure Panel Survey (MEPS); the Back Pain Outcomes using Longitudinal Data (BOLD).

Study Design

Super learner is an ensemble machine learning approach that can combine several algorithms to improve estimation. We propose a two-stage super learner that is well suited for healthcare expenditure data by separately estimating the probability of any healthcare expenditure and the mean amount of healthcare expenditure conditional on having healthcare expenditures. These estimates can then be combined to yield a single estimate of expenditures for each observation. The analytical strategy can flexibly incorporate a range of individual estimation approaches for each stage of estimation, including both regression-based approaches and machine learning algorithms such as random forests. We compare the performance of the two-stage super learner with a one-stage super learner, and with multiple individual algorithms for estimation of healthcare cost under a broad range of data settings in simulated and real data. The predictive performance was compared using Mean Squared Error and R².

Conclusions

Our results indicate that the two-stage super learner has better performance compared with a one-stage super learner and individual algorithms, for healthcare cost estimation under a wide variety of settings in simulations and in empirical analyses. The improvement of the two-stage super learner over the one-stage super learner was particularly evident in settings when zero-inflation is high.

Changes in Food Insecurity and Changes in Patient-Reported Outcomes: a Nationally Representative Cohort Study

BACKGROUND

Cross-sectional studies have found that health-related quality of life and mental health are worse among food-insecure compared with food-secure individuals. However, how these outcomes change as food insecurity changes is unclear.

OBJECTIVE

To evaluate how common patient-reported health-related quality of life and mental health scales change in response to changes in food security.

DESIGN

Retrospective cohort study using data representative of the civilian, adult, non-institutionalized population of the USA.

PARTICIPANTS

Food insecure adults who completed the 2016-2017 Medical Expenditure Panel Survey.

MAIN MEASURES

Mental health, as measured by the mental component score of the Veterans Rand 12-Item Health Survey (VR-12) (primary outcome), along physical health (physical component score of the VR-12), self-rated health status, psychological distress (Kessler 6), depressive symptoms (PHQ2), and the SF-6D measure of health utility. We fit linear regression models adjusted for baseline outcome level, age, gender, race/ethnicity, education, health insurance, and family size followed by predictive margins to estimate the change in outcome associated with a 1-point improvement in food security.

KEY RESULTS

A total of 1,390 food-insecure adults were included. A 1-point improvement in food security was associated with a 0.38 (95%CI 0.62 to 0.14)-point improvement in mental health, a 0.15 (95%CI 0.02 to 0.27)-point improvement in psychological distress, a 0.05 (95%CI 0.01 to 0.09)-point improvement in depressive symptoms, and a 0.003 (95%CI 0.000 to 0.007)-point improvement in health utility. Point estimates for physical health and self-rated health were in the direction of improvement, but were not statistically significant.

CONCLUSIONS

Improvement in food insecurity was associated with improvement in several patient-reported outcomes. Further work should investigate whether similar changes are seen in food insecurity interventions, and the most useful scales for assessing changes in health-related quality of life and mental health in food insecurity interventions.

Association of National Expansion of Insurance Coverage of Medically Tailored Meals With Estimated Hospitalizations and Health Care Expenditures in the US

IMPORTANCE

Medically tailored meals (MTMs) are associated with lower health care utilization among patients with complex diet-related diseases but are not a covered benefit in Medicare or Medicaid. The potential impact of extending insurance coverage for MTMs nationally remains unknown.

OBJECTIVE

To estimate 1- and 10-year potential changes in annual hospitalizations, potential changes in annual health care expenditures, and overall policy cost-effectiveness associated with national MTM coverage for US patients with diet-related disease and limited instrumental activities of daily living who have Medicaid, Medicare, or private insurance.

DESIGN, SETTING, AND PARTICIPANTS

In this economic evaluation, conducted from January 2021 to February 2022, a nationally representative sample from the 2019 Medical Expenditure Panel Survey was used to create a population-level cohort policy simulation model that estimated changes in annual hospitalizations and health care expenditures associated with coverage of MTMs. Participants were 6 309 998 US adults aged 18 years or older who had Medicare, Medicaid, or private payer insurance and at least 1 diet-sensitive condition and 1 limitation in instrumental activities of daily living.

INTERVENTIONS

Ten nutritionally tailored MTMs per week for a mean of 8 months in each year of intervention.

MAIN OUTCOMES AND MEASURES

The main outcomes were total hospitalizations, program costs, health care expenditures, and net policy costs. One thousand Monte Carlo simulations for each of 10 years (2019-2028) jointly incorporated uncertainty in model inputs for effect sizes, hospitalizations, health care expenditures, and program costs.

RESULTS

At the 2019 baseline, an estimated 6 309 998 US adults were eligible to receive MTMs. Mean (SD) age was 68.1 (16.6) years; most were female (63.4%), were non-Hispanic White (66.7%), and had Medicare and/or Medicaid (76.5%). The most common eligibility diagnoses were cardiovascular diseases (70.6%), diabetes (44.9%), and cancer (37.2%). If all eligible individuals received MTMs, an estimated 1 594 000 hospitalizations (95% uncertainty interval [UI], 1 297 000-1 912 000) and $38.7 billion (95% UI, $24.9 billion to $53.9 billion) in health care expenditures could potentially be averted in 1 year. Program costs were $24.8 billion (95% UI, $23.1 billion to $26.8 billion), for an associated net savings of $13.6 billion (95% UI, $0.2 billion to $28.5 billion) from a health care perspective. In 2019 dollars, 10 years of the MTM intervention was anticipated to cost $298.7 billion (95% UI, $279.7 billion to $317.4 billion) and to potentially be associated with 18 257 000 averted hospitalizations (95% UI, 14 690 000-22 109 000) and reductions in health care expenditures of $484.5 billion (95% UI, $310.2 billion to $678.4 billion), for net savings of $185.1 billion (95% UI, $12.9 billion to $377.8 billion). Findings were robust in multiple sensitivity analyses.

CONCLUSIONS AND RELEVANCE

The findings suggest that national implementation of MTMs for patients with diet-sensitive conditions and activity limitations could potentially be associated with approximately 1.6 million averted hospitalizations and net cost savings of $13.6 billion annually. The results may inform US state, federal, and private-payer interest in expanding insurance coverage for MTMs among patients with diet-related chronic illness.

Cross-Sectional Associations: Social Risks and Diabetes Care Quality, Outcomes

INTRODUCTION

Social risks (e.g., food/transportation insecurity) can hamper type 2 diabetes mellitus (T2DM) self-management, leading to poor outcomes. To determine the extent to which high-quality care can overcome social risks' health impacts, this study assessed the associations between reported social risks, receipt of guideline-based T2DM care, and T2DM outcomes when care is up to date among community health center patients.

METHODS

A cross-sectional study of adults aged ≥18 years (N=73,484) seen at 186 community health centers, with T2DM and ≥1 year of observation between July 2016 and February 2020. Measures of T2DM care included up-to-date HbA1c, microalbuminuria, low-density lipoprotein screening, and foot examination, and active statin prescription when indicated. Measures of T2DM outcomes among patients with up-to-date care included blood pressure, HbA1c, and low-density lipoprotein control on or within 6‒12 months of an index encounter. Analyses were conducted in 2021.

RESULTS

Individuals reporting transportation or housing insecurity were less likely to have up-to-date low-density lipoprotein screening; no other associations were seen between social risks and clinical care quality. Among individuals with up-to-date care, food insecurity was associated with lower adjusted rates of controlled HbA1c (79% vs 75%, p<0.001), and transportation insecurity was associated with lower rates of controlled HbA1c (79% vs 74%, p=0.005), blood pressure (74% vs 72%, p=0.025), and low-density lipoprotein (61% vs 57%, p=0.009) than among those with no reported need.

CONCLUSIONS

Community health center patients received similar care regardless of the presence of social risks. However, even among those up to date on care, social risks were associated with worse T2DM control. Future research should identify strategies for improving HbA1c control for individuals with social risks.

TRIAL REGISTRATION

This study is registered at www.

CLINICALTRIALS

gov NCT03607617.

Food Insecurity, Missed Workdays, And Hospitalizations Among Working-Age US Adults With Diabetes

Food insecurity is associated with poor clinical outcomes among adults with diabetes, but associations with nonclinical outcomes, such as missed work, have not been well characterized. Our objective was to assess the associations between food insecurity, health-related missed workdays, and overnight hospitalizations. We pooled National Health Interview Survey data from the period 2011-18 to analyze food insecurity among 13,116 US adults ages 18-65 who had diabetes. Experiencing food insecurity, compared with being food secure, was associated with increased odds of reporting any health-related missed workdays, more than twice the rate of health-related missed workdays, and increased odds of overnight hospitalization within the prior twelve months. There was no significant association between food insecurity and the number of nights spent hospitalized. These findings underscore the broad impacts of food insecurity on health and wellness for working-age adults with diabetes. When weighing the costs and benefits of proposed interventions to address food insecurity, policy makers should consider potential benefits related to productivity in addition to implications for health care use.

Permanent Supportive Housing Tenure Among a Heterogeneous Population of Adults with Disabilities

People with disabilities can face substantial barriers to living stably in community settings. Evidence shows that permanent supportive housing (PSH), which combines subsidized housing with individualized support services, can improve housing stability among subpopulations of people with disabilities, including those with behavioral health conditions. PSH has also been shown to improve some health outcomes among people with severe mental illness or substance use disorder, but effects varied by participants' program tenure. This study assessed retention in a PSH program serving a broad population of adults with disabilities and identified factors associated with program tenure. Administrative data from 2093 individuals who began participating in a North Carolina PSH program between 2015 and 2018 were analyzed. Participants' unadjusted probability of remaining in a PSH placement at specific time points was estimated, with censoring due to death or the end of the study period (July 2020). Using Cox regression, program tenure was modeled as a function of participant and PSH placement location characteristics. Participants had a 71% probability of remaining in PSH after 2 years. Older age, female gender, and non-Hispanic Black race/ethnicity were associated with lower hazard of PSH departure. Having a severe mental illness diagnosis was associated with greater departure hazard. Level of socioeconomic deprivation and rurality of the PSH placement ZIP code were not associated with departure hazard. PSH programs may be able to successfully retain a heterogeneous population of adults with disabilities, although tenure may vary by participant demographic and clinical characteristics.

Evaluating A Nonemergency Medical Transportation Benefit For Accountable Care Organization Members

Nonemergency medical transportation benefits, often using smartphone application-based ridesharing services, are increasingly being offered as part of population health management programs. However, the impact of these programs on health care use and costs remains understudied. We conducted a mixed-methods evaluation of a nonemergency medical transportation benefit offered to members of a Medicare accountable care organization (ACO) within a large academic health system, the UNC Health Alliance ACO. Participation in the transportation program was associated with a greater number of per person per year outpatient visits (9.2) and higher outpatient spending ($4,420) than in a comparison group. However, there was no difference in inpatient admissions or emergency department visits, and the program was not cost saving. Qualitative analyses revealed that participants were highly satisfied with the program, reporting that it eased financial burdens and made them feel safer, more empowered, and better able to take control of their health. These findings suggest that although transportation programs are commonly introduced as ways to contain health care spending, it may be better to think of them as programs to improve health care access for people facing difficult circumstances.

North Carolina's Healthy Opportunities Pilots Focus Attention on Housing as a Health Care Intervention

The social conditions in which people live, including their housing, can have a profound impact on their health. The North Carolina Healthy Opportunities Pilots aim to address housing problems and other social needs to improve health. The results from the Pilots' evaluation will have important implications for health policy and practice.

Supplemental Nutrition Assistance Program Participation and Health Care Use in Older Adults : A Cohort Study

BACKGROUND

Older adults dually eligible for Medicare and Medicaid have particularly high food insecurity prevalence and health care use.

OBJECTIVE

To determine whether participation in the Supplemental Nutrition Assistance Program (SNAP), which reduces food insecurity, is associated with lower health care use and cost for older adults dually eligible for Medicare and Medicaid.

DESIGN

An incident user retrospective cohort study design was used. The association between participation in SNAP and health care use and cost using outcome regression was assessed and supplemented by entropy balancing, matching, and instrumental variable analyses.

SETTING

North Carolina, September 2016 through July 2020.

PARTICIPANTS

Older adults (aged ≥65 years) dually enrolled in Medicare and Medicaid but not initially enrolled in SNAP.

MEASUREMENTS

Inpatient admissions (primary outcome), emergency department visits, long-term care admissions, and Medicaid expenditures.

RESULTS

Of 115 868 persons included, 5093 (4.4%) enrolled in SNAP. Mean follow-up was approximately 22 months. In outcome regression analyses, SNAP enrollment was associated with fewer inpatient hospitalizations (-24.6 [95% CI, -40.6 to -8.7]), emergency department visits (-192.7 [CI, -231.1 to -154.4]), and long-term care admissions (-65.2 [CI, -77.5 to -52.9]) per 1000 person-years as well as fewer dollars in Medicaid payments per person per year (-$2360 [CI, -$2649 to -$2071]). Results were similar in entropy balancing, matching, and instrumental variable analyses.

LIMITATION

Single state, no Medicare claims data available, and possible residual confounding.

CONCLUSION

Participation in SNAP was associated with fewer inpatient admissions and lower health care costs for older adults dually eligible for Medicare and Medicaid.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Pathways by Which Food Insecurity Is Associated With Atherosclerotic Cardiovascular Disease Risk

Background Food insecurity (FI) has been associated with an increased atherosclerotic cardiovascular disease (ASCVD) risk; however, the pathways by which FI leads to worse cardiovascular health are unknown. We tested the hypothesis that FI is associated with ASCVD risk through nutritional/anthropometric (eg, worse diet quality and increased weight), psychological/mental health (eg, increased depressive symptoms and risk of substance abuse), and access to care pathways. Methods and Results We conducted a cross-sectional study of adults (aged 40-79 years) using the 2007 to 2016 National Health and Nutrition Examination Survey. Our primary exposure was household FI, and our outcome was 10-year ASCVD risk categorized as low (<5%), borderline (≥5% -<7.5%), intermediate (≥7.5%-<20%), and high risk (≥20%). We used structural equation modeling to evaluate the pathways and multiple mediation analysis to determine direct and indirect effects. Of the 12 429 participants, 2231 (18.0%) reported living in a food-insecure household; 5326 (42.9%) had a low ASCVD risk score, 1402 (11.3%) borderline, 3606 (29.0%) intermediate, and 2095 (16.9%) had a high-risk score. In structural models, we found significant path coefficients between FI and the nutrition/anthropometric (β, 0.130; SE, 0.027; P<0.001), psychological/mental health (β, 0.612; SE, 0.043; P<0.001), and access to care (β, 0.110; SE, 0.036; P=0.002) pathways. We did not find a significant direct effect of FI on ASCVD risk, and the nutrition, psychological, and access to care pathways accounted for 31.6%, 43.9%, and 15.8% of the association, respectively. Conclusions We found that the association between FI and ASCVD risk category was mediated through the nutrition/anthropometric, psychological/mental health, and access to care pathways. Interventions that address all 3 pathways may be needed to mitigate the negative impact of FI on cardiovascular disease.

Transporting experimental results with entropy balancing

We show how entropy balancing can be used for transporting experimental treatment effects from a trial population onto a target population. This method is doubly robust in the sense that if either the outcome model or the probability of trial participation is correctly specified, then the estimate of the target population average treatment effect is consistent. Furthermore, we only require the sample moments of the effect modifiers drawn from the target population to consistently estimate the target population average treatment effect. We compared the finite-sample performance of entropy balancing with several alternative methods for transporting treatment effects between populations. Entropy balancing techniques are efficient and robust to violations of model misspecification. We also examine the results of our proposed method in an applied analysis of the Action to Control Cardiovascular Risk in Diabetes Blood Pressure trial transported to a sample of US adults with diabetes taken from the National Health and Nutrition Examination Survey cohort.

Association of a Fruit and Vegetable Subsidy Program With Food Purchases by Individuals With Low Income in the US

IMPORTANCE

Food insecurity is associated with a less healthy diet. The Supplemental Nutrition Assistance Program (SNAP) is associated with reduced food insecurity, but benefit levels may be insufficient for beneficiaries to afford healthy foods.

OBJECTIVE

To evaluate whether participation in SuperSNAP, a program that provides an additional $40 per month for the purchase of fruits and vegetables with no added sugar, sodium, or fat to SNAP beneficiaries, is associated with changes in food purchasing.

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal cohort study used data from transaction records of a large supermarket chain with approximately 500 stores located across North Carolina from October 2019 to April 2020. Participants were SNAP beneficiaries.

EXPOSURE

SuperSNAP participation.

MAIN OUTCOMES AND MEASURES

Monthly spending on all fruits, vegetables, legumes, and nuts (primary outcome); spending on less healthy food categories; and spending on sugar-sweetened beverages as 1 category of less healthy foods. Monthly data on purchases by SNAP beneficiaries before and during SuperSNAP participation were compared with data from SNAP beneficiaries not enrolled in the program who shopped at the same stores. Overlap weighting (a propensity score-based method) was used to account for confounding, and linear mixed-effects models were fitted with random effects to account for repeated measures and clustering by store.

RESULTS

The study included 667 SuperSNAP participants and 33 246 SNAP beneficiaries who did not use SuperSNAP but shopped in the same stores; 436 SuperSNAP participants had preintervention data and were included in the main analysis. SuperSNAP participation was associated with increased monthly purchases of fruits, vegetables, nuts, and legumes ($31.84; 95% CI, $31.27-$32.42; P < .001; 294.52 oz; 95% CI, 288.84-300.20 oz; P < .001). Only a small increase in spending on less healthy food categories compared with the SNAP beneficiaries who did not use SuperSNAP ($1.60; 95% CI, $0.67-$2.53; P < .001) was observed. As total spending increased, the proportion of total food and beverage spending on less healthy foods significantly decreased (difference, 4.51%; 95% CI, 4.27%-4.74%; P < .001). Monthly spending on sugar-sweetened beverages decreased (difference, $1.83; 95% CI, $1.30-$2.36; P < .001).

CONCLUSIONS AND RELEVANCE

In this cohort study, participation in SuperSNAP was associated with meaningful increases in healthy food purchasing. Subsequent studies should investigate whether healthy food incentive programs improve health outcomes.

Estimated Effect on Life Expectancy of Alleviating Primary Care Shortages in the United States

BACKGROUND

Prior studies have reported that greater numbers of primary care physicians (PCPs) per population are associated with reduced population mortality, but the effect of increasing PCP density in areas of low density is poorly understood.

OBJECTIVE

To estimate how alleviating PCP shortages might change life expectancy and mortality.

DESIGN

Generalized additive models, mixed-effects models, and generalized estimating equations.

SETTING

3104 U.S. counties from 2010 to 2017.

PARTICIPANTS

Children and adults.

MEASUREMENTS

Age-adjusted life expectancy; all-cause mortality; and mortality due to cardiovascular disease, cancer, infectious disease, respiratory disease, and substance use or injury.

RESULTS

Persons living in counties with less than 1 physician per 3500 persons in 2017 had a mean life expectancy that was 310.9 days shorter than for persons living in counties above that threshold. In the low-density counties (n = 1218), increasing the density of PCPs above the 1:3500 threshold would be expected to increase mean life expectancy by 22.4 days (median, 19.4 days [95% CI, 0.9 to 45.6 days]), and all such counties would require 17 651 more physicians, or about 14.5 more physicians per shortage county. If counties with less than 1 physician per 1500 persons (n = 2636) were to reach the 1:1500 threshold, life expectancy would be expected to increase by 56.3 days (median, 55.6 days [CI, 4.2 to 105.6 days]), and all such counties would require 95 754 more physicians, or about 36.3 more physicians per shortage county.

LIMITATION

Some projections are based on extrapolations of the actual data.

CONCLUSION

In counties with fewer PCPs per population, increases in PCP density would be expected to substantially improve life expectancy.

PRIMARY FUNDING SOURCE

None.

Food Insecurity and Cardiometabolic Conditions: a Review of Recent Research

Purpose of Review

To understand recent literature that examines associations between food insecurity and cardiometabolic conditions and risk factors. We included original research, systematic reviews, and meta-analyses on the topic of food insecurity and cardiometabolic risk published from January 1, 2017, to December 31, 2020. Editorials, perspectives, and case reports were excluded. After the initial search, 3 reviewers selected studies for inclusion based on relevance and methods. Ultimately, fifty studies were included.

Recent Findings

We included 35 studies of adults (20 cross-sectional observational studies, 5 longitudinal observational studies, 5 interventional studies, and 5 meta-analyses/reviews). In adults, food insecurity is associated with greater prevalence of overweight/obesity (especially for women). It is also associated with hypertension, diabetes (including worse glycemic control and more diabetes complications), coronary heart disease, congestive heart failure, stroke, and chronic kidney disease. We included 15 studies of children (11 cross-sectional observational studies and 4 longitudinal observational studies). In children, findings were more nuanced, and in particular, many studies did not find an association between food insecurity and overweight/obesity. However, authors noted that these conditions may not have had time to develop. With notable exceptions, many studies were cross-sectional, and there were few interventions.

Summary

There is a robust association between food insecurity and cardiometabolic conditions and risk factors in adults, but the picture is less clear in children. Overt cardiometabolic clinical conditions develop more rarely in children, but childhood experiences may set a trajectory for worse health later in life. Detailed life course epidemiologic studies are needed to better understand this relationship. Future interventions should examine how to reduce the prevalence of food insecurity, and how best to improve health for those who experience food insecurity.

Association between Food Insecurity and Health-Related Quality of Life: a Nationally Representative Survey

BACKGROUND

Food insecurity, limited or uncertain access to enough food for an active, healthy life, affected over 37 million Americans in 2018. Food insecurity is likely to be associated with worse health-related quality of life (HRQoL), but this association has not been measured with validated instruments in nationally representative samples. Given growing interest understanding food insecurity's role in health outcomes, it would be useful to learn what HRQoL measures best capture the experience of those with food insecurity.

OBJECTIVE

To determine the association between food insecurity and several validated HRQoL instruments in US adults.

DESIGN

Cross-sectional.

PARTICIPANTS

US adults (age ≥ 18), weighted to be nationally representative.

MAIN MEASURES

Food insecurity was assessed with three items derived from the USDA Household Food Security Survey Module. HRQoL was assessed using PROMIS-Preference (PROPr), which contains 7 PROMIS domains, self-rated health (SRH), Euroqol-5D-5L (EQ-5D), Health Utilities Index (HUI), and Short Form-6D (SF-6D).

KEY RESULTS

In December 2017, 4142 individuals completed at least part of the survey (31% response rate), of whom 4060 (98.0%) reported food security information. Of survey respondents, 51.7% were women, 12.5% self-identified as black, 15.8% were Hispanic, and 11.0% did not have a high school diploma. 14.1% of respondents reported food insecurity. In adjusted analyses, food insecurity was associated with worse HRQoL across all instruments and PROMIS domains (p < .0001 for all). The magnitude of the difference between food-insecure and food-secure participants was largest with the SF-6D, EQ-5D, and PROPr; among individual PROMIS domain scores, the largest difference was for ability to participate in social roles.

CONCLUSIONS

Food insecurity is strongly associated with worse HRQoL, with differences between food-secure and food-insecure individuals best measured using the SF-6D, EQ-5D, and PROPr. Future work should develop a specific instrument to measure changes in HRQoL in food insecurity interventions.

Unemployment Insurance, Health-Related Social Needs, Health Care Access, and Mental Health During the COVID-19 Pandemic

This cross-sectional study assesses whether receiving unemployment insurance is associated with lower health-related social needs, better health care access, and better mental health during the COVID-19 pandemic.

Federal Nutrition Programs after the Pandemic: Learning from P-EBT and SNAP to Create the Next Generation of Food Safety Net Programs

It is thought that childhood food insecurity rates increased to 18 million impacted children in 2020. In response, innovative policy solutions from the Supplemental Nutrition Assistance Program (SNAP) and the Pandemic Electronic Benefit Transfer (P-EBT) were swiftly implemented. These innovations must serve as catalysts to create the next generation of food safety net programs. These include the removal of administrative barriers to enrollment, the use of streamlined procedures to access food, the expansion of P-EBT to daycare and childcare centers, and the uncoupling of receipt of benefits from physical presence in schools. Critical gaps also remain. SNAP benefit amounts are often too low, leaving many families ineligible. More realistic benefit amounts are needed, such as those used in the USDA’s Moderate Cost Food Plan. Eligibility cut-offs exclude many food insecure families. Better alignment of SNAP eligibility with income levels that substantially increase food insecurity risk are critical. Lastly, creating slower phase-out periods for benefits as incomes rise is essential. Additionally, food insecurity continues to disproportionately impact racial and ethnic minority populations and low-income households. These deeply rooted inequalities in access to nutrition play an important role in driving health disparities, including obesity, hypertension, diabetes, and other chronic comorbidities and must be further examined. Changes to SNAP and the P-EBT program illustrate how innovative, broad-scale policy solutions can expeditiously support the nutritional needs of families with children. While pandemic-inspired innovation offers critical lessons for designing the next generation of nutrition assistance, there remain gaps that can perpetuate disparities in access to food and health. As a community of medical providers, we must advocate for broader, more inclusive policies to support those facing food insecurity. The future depends on it.

Comparison of Fruit and Vegetable Intake Among Urban Low-Income US Adults Receiving a Produce Voucher in 2 Cities

Importance

Fruit and vegetable vouchers have been implemented by cities and counties across the US to increase fruit and vegetable intake and thereby improve overall nutritional quality.

Objective

To determine whether and why use of fruit and vegetable vouchers are associated with varied nutritional intake across different populations and environments.

Design, Setting, and Participants

In a population-based pre-post cohort study of 671 adult participants with low income before and during (6 months after initiation) participation in a 6-month program, fruit and vegetable vouchers were distributed for redemption at local San Francisco and Los Angeles neighborhood grocery and corner stores between 2017 and 2019. A transportability analysis was performed to identify factors that may explain variation in voucher use between cities.

Exposure

Receipt of $20 per month in produce vouchers for 6 months from 2017 to 2019.

Main Outcomes and Measures

Change in total fruits and vegetables (as defined by the US Department of Agriculture) consumed per person per day (change in cup-equivalents between month 6 and month 0).

Results

A total of 671 adults (median age, 54.9 years [interquartile range, 45.0-65.0 years]; 61.7% female; 30.9% Black; 19.7% Hispanic) were enrolled. An increase in fruit and vegetable intake of 0.22 cup-equivalents per day overall (95% CI, 0.14-0.31 cup-equivalents; P < .001) was observed. However, the observed increase was larger in Los Angeles compared with San Francisco (0.64 cup-equivalents per day; 95% CI, 0.41-0.88 cup-equivalents vs 0.10 cup-equivalents per day; 95% CI, 0.01-0.19 cup-equivalents). When the concurrently sampled San Francisco group (n = 157) was weighted in transportability analysis to demographically match the Los Angeles group (n = 155) in observed covariates, the weighted San Francisco group had an estimated increase of 0.53 fruit and vegetable cup-equivalents per day (95% CI, 0.27- 0.79 cup-equivalents, P = .03), with income being the variable needed to allow the 95% confidence intervals to overlap between the weighted San Francisco and unweighted Los Angeles populations.

Conclusions and Relevance

In this study, the use of fruit and vegetable vouchers appeared to be associated with greater benefit among those with lower incomes, suggesting that further investigation of flat-rate rather than income-scaled benefits is warranted.

Unmet Social Needs And Worse Mental Health After Expiration Of COVID-19 Federal Pandemic Unemployment Compensation

Federal Pandemic Unemployment Compensation (FPUC) provided unemployment insurance beneficiaries an extra $600 a week during the unprecedented economic downturn during the coronavirus disease 2019 (COVID-19) pandemic, but it initially expired in July 2020. We applied difference-in-differences models to nationally representative data from the Census Bureau's Household Pulse Survey to examine changes in unmet health-related social needs and mental health among unemployment insurance beneficiaries before and after initial expiration of FPUC. The initial expiration was associated with a 10.79-percentage-point increase in risk for self-reported missed housing payments. Further, risk for food insufficiency, depressive symptoms, and anxiety symptoms also increased among households that reported receiving unemployment insurance benefits, relative to the period when FPUC was in effect. As further unemployment insurance reform is debated, policy makers should recognize the potential health impact of unemployment insurance.

Opportunities for Interventions That Address Socioeconomic Barriers to Type 2 Diabetes Management: Patient Perspectives

PURPOSE

The purpose of the study was to explore patient perspectives on socioeconomic barriers related to diabetes self-management and interventions to address these barriers.

METHODS

Focus groups (n = 8) were conducted with a diverse sample of adults with type 2 diabetes (T2D; n = 53). Researchers used a semistructured moderator guide; focus groups were audio recorded and transcribed verbatim. Researchers employed the constant comparison method for qualitative content analysis and utilized Atlas.ti (Version 8.1.1) to digitalize the analytic process.

RESULTS

Findings revealed 3 primary themes: (1) Existing food and nutrition resources are insufficient to support healthy eating for diabetes; (2) healthy eating is critical for diabetes management, but socioeconomic circumstances make doing so challenging; and (3) participants supported several broad categories of preferred intervention strategies. First, they endorsed lifestyle intervention informed by socioeconomic status (SES; eg, focusing on food resource management, sensitive health coaching and nutritional counseling). Next, they expressed enthusiasm for group-based learning opportunities, such as cooking classes and support groups with similar SES peers. Finally, they suggested healthy food access resources.

CONCLUSIONS

Participant suggestions should be incorporated into intervention development. Ultimately, these interventional strategies should be tested and refined to help improve health for individuals with type 2 diabetes.

Examining the bidirectional relationship between food insecurity and healthcare spending

OBJECTIVE

To improve food insecurity interventions, we sought to better understand the hypothesized bidirectional relationship between food insecurity and health care expenditures.

DATA SOURCE

Nationally representative sample of the civilian noninstitutionalized population of the United States (2016-2017 Medical Expenditure Panel Survey [MEPS]).

STUDY DESIGN

In a retrospective longitudinal cohort, we conducted two sets of analyses: (a) two-part models to examine the association between food insecurity in 2016 and health care expenditures in 2017; and (b) logistic regression models to examine the association between health care expenditures in 2016 and food insecurity in 2017. We adjusted for demographic and socioeconomic variables as well as 2016 health care expenditures and food insecurity.

DATA COLLECTION

Health care expenditures, food insecurity, and medical condition data from 10 886 adults who were included in 2016-2017 MEPS.

PRINCIPAL FINDINGS

Food insecurity in 2016, compared with being food secure, was associated with both a higher odds of having any health care expenditures in 2017 (OR 1.29, 95% CI: 1.04 to 1.60) and greater total expenditures ($1738.88 greater, 95% CI: $354.10 to $3123.57), which represents approximately 25% greater expenditures. Greater 2016 health care expenditures were associated with slightly higher odds of being food insecure in 2017 (OR 1.007 per $1000 in expenditures, 95% CI: 1.002 to 1.012, P =0.01). Exploratory analyses suggested that poor health status may underlie the relationship between food insecurity and health care expenditures.

CONCLUSIONS

A bidirectional relationship exists between food insecurity and health care expenditures, but the strength of either direction appears unequal. Higher health care expenditures are associated with a slightly greater risk of being food insecure (adjusted for baseline food insecurity status) but being food insecure is associated with substantially greater subsequent health care expenditures (adjusted for baseline health care expenditures). Interventions to address food insecurity and poor health may be helpful to break this cycle.

Use of Machine Learning Approaches in Clinical Epidemiological Research of Diabetes

PURPOSE OF REVIEW

Machine learning approaches-which seek to predict outcomes or classify patient features by recognizing patterns in large datasets-are increasingly applied to clinical epidemiology research on diabetes. Given its novelty and emergence in fields outside of biomedical research, machine learning terminology, techniques, and research findings may be unfamiliar to diabetes researchers. Our aim was to present the use of machine learning approaches in an approachable way, drawing from clinical epidemiological research in diabetes published from 1 Jan 2017 to 1 June 2020.

RECENT FINDINGS

Machine learning approaches using tree-based learners-which produce decision trees to help guide clinical interventions-frequently have higher sensitivity and specificity than traditional regression models for risk prediction. Machine learning approaches using neural networking and "deep learning" can be applied to medical image data, particularly for the identification and staging of diabetic retinopathy and skin ulcers. Among the machine learning approaches reviewed, researchers identified new strategies to develop standard datasets for rigorous comparisons across older and newer approaches, methods to illustrate how a machine learner was treating underlying data, and approaches to improve the transparency of the machine learning process. Machine learning approaches have the potential to improve risk stratification and outcome prediction for clinical epidemiology applications. Achieving this potential would be facilitated by use of universal open-source datasets for fair comparisons. More work remains in the application of strategies to communicate how the machine learners are generating their predictions.