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FOOD ASSISTANCE PROGRAMS AND REDUCED HOSPITALIZATIONS FOR OLDER ADULTS WITH DIABETES

 

M.L. Johnson1, S.E. Walsh2

 

1. Wayne State University School of Medicine, Detroit, MI, USA; 2. Eastern Michigan University School of Health Sciences, Ypsilanti, MI, USA

Corresponding Author: Sarah E. Walsh, 340 Marshall, School of Health Sciences, Eastern Michigan University, Ypsilanti, MI 48197, Phone 734.487.2364 / Fax 734.487.4095, swalsh8@emich.edu

J Frailty Aging 2022;in press
Published online February 18, 2022, http://dx.doi.org/10.14283/jfa.2022.13

 


Abstract

Diabetes is an increasingly common and costly condition for older adults. Each year, as many as 1 in 3 Medicare dollars is spent to treat and manage diabetes and associated comorbidities for people with diabetes. To control health care spending in the US, it is imperative that we identify factors for reducing hospitalizations for these individuals. The purpose of this cross-sectional study was to identify predictors of hospitalization in the past 12 months for community-dwelling older adults with diabetes. Data from round five of the National Health and Aging Trends Study were analyzed to assess the impact of food assistance programs on the risk of hospitalization in the past 12 months for 1094 Medicare recipients ages 65 and older with diabetes. Previous research on the social determinants of health has demonstrated that social stressors like poverty and exposure to racism are associated with poorer health outcomes overall, but we did not find a statistically-significant association between race, gender, age or Medicare/ Medicaid dual-eligibility and hospitalization for our study population. Notably, receipt of Supplemental Nutrition Assistance Program (SNAP) benefits, Meals on Wheels services or other food assistance was associated with a 43% reduction in the risk of hospitalization in the past 12 months. Food assistance programs appear to be a promising strategy for reducing hospitalizations associated with diabetes and its comorbidities. Primary care providers, diabetes educators and other health professionals should be more proactive in their referrals to food assistance programs and other community supports.

Key words: Diabetes, food assistance, Meals on Wheels, healthcare utilization, hospitalization.


 

Introduction

Diabetes is a common, costly condition and a priority for both prevention efforts (1) and improved disease management. According to the National Health Interview Survey, approximately one in ten Americans have been diagnosed with diabetes, and the prevalence doubles for those over age 65 (2). This study focuses on older adults because individuals over age 65 are developing diabetes three times faster than younger adults (3).
In 2019, the U.S. spent nearly $296 billion on diabetes-related healthcare, with the highest spending levels for older age groups (4). Among the healthcare utilization costs, hospitalizations are especially concerning as stays tend to be longer and average costs are 25% higher for patients with diabetes (5). In recent years, there has been little to no progress in reducing preventable hospitalizations for patients with diabetes (6), suggesting that identifying low-cost interventions to improve diabetes outcomes among older adults is particularly urgent.
A core premise of the American Diabetes Association’s clinical practice guidelines is that diabetes care must be adapted for an individual’s unique social context (7). Adults with diabetes are 58% more likely to face food insecurity than those without a diabetes diagnosis (8) and food insecurity increases the likelihood of adverse outcomes. Specifically, food insecurity is associated with higher average blood glucose levels (9); lower adherence to self-care recommendations, including diet, exercise and medication adherence (10–12); increased risk of emergency department visits and hospitalizations (13, 14); and higher overall healthcare spending (15, 16).
To address food insecurity, there are a number of food assistance programs available in the US with varying eligibility criteria. The Supplemental Nutrition Assistance Program (SNAP) is the US government’s largest nutrition program and provides income-eligible individuals and families – including 4.8 million older adults (17) – with a debit card that can be used to purchase qualifying food items from grocery stores and other retail outlets. Food assistance is also available in the form of prepared meals that are served in congregate settings like senior centers or delivered directly to the homes of participants. The most familiar home-delivered meal program is Meals on Wheels (MOW), which technically refers to a network of more than 5000 independent agencies. Each year, MOW serves more than 2.4 million older Americans.[18] For the general population of older adults, food assistance programs are associated with improved health outcomes. Medicare beneficiaries had fewer hospitalizations and emergency department visits following enrollment in Meals on Wheels services (19). Similarly, the Supplemental Nutrition Assistance Program (SNAP) reduced hospitalizations among a general sample of low-income older adults (20).
It is logical that interventions to reduce food insecurity would improve diabetes-specific outcomes as well, but empirical evidence is limited for this population. For older adults with diabetes, SNAP participation is associated with improved self-care behaviors: specifically, a reduction in the proportion of individuals who reported going without medication due to the cost (21). Previous studies have not found a significant difference in either hospitalization rates or overall healthcare spending for SNAP program participants vs. income-eligible non-participants (22) but this has not been assessed for the broader array of food assistance programs with a large, nationally-representative sample of older adults. The authors hypothesized that receipt of food assistance would decrease the risk of hospitalization specifically for older adults with diabetes and used data from the National Health and Aging Trends Study (NHATS) to address this gap in the literature.

 

Materials and Methods

For this study, a secondary analysis of data from NHATS Round 5 was completed (23). NHATS is a nationally-representative longitudinal panel study of Medicare beneficiaries ages 65 and older, the methods for which have been described previously (24). Round 5 data were collected in 2015. Of the 8,334 completed interviews included in the Round 5 dataset, analysis was limited to the 1,099 community-dwelling individuals who reported being told by a doctor that they had diabetes. An additional five individuals who did not know if they had been hospitalized during the preceding year were excluded from the analysis. This resulted in a final sample size of 1,094.
Receipt of food assistance was derived from three different NHATS items. In a section on household activities, participants were asked, “In the last month, when you had hot meals, how often were they from Meals on Wheels or other food assistance programs?” This frequency scale was re-coded as dichotomous (ever/never). Participants were also asked, “There are several state and federal programs that help people in need. In the last year, did you receive help from any of these programs? a. Food stamps (also called the Supplemental Nutrition Assistance Program, or SNAP)? b. Other food assistance such as Meals-on-Wheels?” Individuals who answered affirmatively to any of these questions were coded as having received food assistance in the past year. While all participants were Medicare recipients, dual-eligibility for both Medicare and Medicaid was used as a proxy for poverty. Race was reported by NHATS as a four-category variable: non-Hispanic White, non-Hispanic Black, Hispanic and other.
All statistical analyses were completed using IBM SPSS Statistics 27. The original NHATS dataset includes an oversampling of African Americans and individuals ages 90+, and as such, NHATS provides sampling weights (25) to ensure that results are representative of the total population of adults over age 65 in the US. These sampling weights were applied to produce descriptive statistics and cross-tabs. Binary logistic regression was used to test the primary study hypothesis by calculating the odds ratio and confidence interval for the predictor variables’ impact on the binary dependent outcome of a hospitalization in the past year. The main predictor variable was receipt of food assistance. Gender, race, age and poverty status were included in the model for their potential impact as confounding variables on the outcome of interest.

 

Results

Descriptive statistics for the weighted study population are provided in Table 1. When weighted to the total population of Medicare recipients, the 1,094 individuals included in this study represent 7,372,474 older adults with diabetes in the United States. The majority of study participants were male (51.6%), non-Hispanic white (68.4%) and younger than age 80 (81.9%). Approximately one in six were Medicare/ Medicaid dual-eligible (16.4%) and one in ten reported receiving some form of food assistance (11.5%). Participants who received some form of food assistance were more likely to be female, less likely to be non-Hispanic white, more likely to be non-Hispanic Black or Hispanic, more likely to be Medicare/ Medicaid dual-eligible, and these differences were statistically significant. A quarter of those studied (25.2%) reported at least one hospital stay in the preceding twelve months.

Table 1. Demographic characteristics of study sample (unweighted n / weighted %)

a. SNAP, Meals on Wheels, or other food assistance; ***Χ2 for unweighted sample is statistically significant, p < 0.01

 

Because Medicaid and certain food assistance programs have income-eligibility requirements, there is potential overlap between these variables. A Pearson Chi-Square test was statistically significant (Χ2 =205.683, df=1, p<.001) indicating that Medicare/ Medicaid dual eligibility and receipt of food assistance are not independent. However, additional testing of collinearity indicated the assumptions of logistic regression were not violated so both variables were retained in our final model (VIF = 1.0).
Multivariate binary logistic regression (Table 2) indicated that food assistance was associated with the likelihood of having a hospital stay in the preceding year. Relative to those who did not receive any assistance, recipients of food assistance had an odds ratio of 0.57 for hospitalization in the previous 12 months (p< 0.01). Gender, age and Medicare/ Medicaid dual eligibility were not significantly associated with the likelihood of a hospital stay in the final model.
Relative to non-Hispanic Whites, non-Hispanic Black and Hispanic individuals had greater odds of a hospital stay in the past year, but these results were not significant. Race categorized as “other” – that is neither non-Hispanic White, non-Hispanic Black or Hispanic – was associated with lower odds of a hospital stay compared to non-Hispanic Whites, and this difference was statistically significant (OR = 0.58, p<0.05).

Table 2. Binary logistic regression analysis to identify variables associated with hospitalization for older adults with diabetes

Hospitalization rate analyses were adjusted for gender, race & ethnicity, age, and Medicaid/Medicare dual-eligibility. The independent variable categories that received Odds Ratios of 1.00 are reference categories. ** Statistically significant at p<0.05

 

Discussion

Older adults with diabetes who receive food assistance are demographically different than non-recipients: they are more likely to be female, non-white and low-income. This is a group that is expected to have high rates of healthcare utilization and indeed they did: 37% of food assistance recipients reported a hospitalization in the past twelve months. However, they had lower odds of hospitalization, indicating the rate of hospitalization was not as high as might be expected for this group in the absence of food assistance. Receipt of food assistance (including SNAP benefits, Meals on Wheels services and other programs) was associated with a reduced risk of hospitalizations for older adults with diabetes, and this aligns with our study hypothesis. Specifically, individuals who reported receiving food assistance were 43% less likely to have been hospitalized in the preceding year than was expected given their other demographic characteristics.
Demographic characteristics (gender, race, age, Medicare/ Medicaid dual eligibility) were not generally predictive of hospitalizations in the study model. With the exception of the “Other Race” category, none of the study variable were significantly different than the reference category. Older adults with diabetes in the “Other Race” category were 42% less likely to be hospitalized than Non-Hispanic Whites. Further study is needed to explore how this reduction in hospitalizations is distributed among the various racial and ethnic groups included in this category and the implications of those findings.
As with any self-reported data, this study has certain limitations. Hospital stays were selected as a particularly salient adverse outcome but may underestimate utilization[26] and not reflect total healthcare spending. Additionally, the absence of a hospital stay is not necessarily indicative of well-managed disease. The NHATS dataset does not include information on the frequency or duration of food assistance services, so the impact of the “dose” of SNAP, MOW or other food assistance cannot be evaluated. Further study is warranted in each of these areas.
Despite these limitations, this study extends the available literature in several ways. By using an inclusive definition of food assistance, this study provides a more holistic view of the types of nutritional supports that are available to older adults with diabetes. While Nicholas (22) found similar hospitalization rates for SNAP program participants and non-participants, presumably because SNAP participation did not lead individuals to make better nutrition choices, these results are worth revisiting. In more recent years, diet quality has improved for people with diabetes overall (27) and food insecure SNAP recipients have been shown to have better glucose control than food insecure individuals who did not receive SNAP (28). Further, Nicholas’s results do not include MOW services which provide meals aligned with daily nutrition recommendations for older adults. By focusing specifically on older adults with diabetes, this study explores the impact of food assistance on those most likely to have high levels of healthcare utilization. In general, MOW home-delivered meal clients have been shown to have higher rates of hospitalization than non-users (29), but further research is needed to understand the impact on subgroups of users.
Helping people access community resources to ensure their basic needs are met is part of the “problem solving” professional competency for diabetes care and education specialists.[30] In this regard, older adults facing severe food insecurity are likely to receive referrals to food assistance programs if they participate in formal diabetes self-management education. However, this may not be enough as previous research has shown that food insecure individuals face complex barriers and benefit from more hands-on enrollment assistance (31). Food assistance is a sufficiently promising strategy to reduce hospitalizations for older adults with diabetes that enrollment should be encouraged and supported for all who are eligible. Further, it is a cost-efficient strategy: typical hospital expenses for a single inpatient day (32) exceed the average annual SNAP benefit for households with an older adult (17) and are comparable to the average annual cost of five home-delivered meals per week from Meals on Wheels (33). Primary care providers, specialists and allied health professionals should be more proactive in their referrals to food assistance programs and other community supports for older patients with diabetes. Further, policymakers should work to expand these programs so that more older adults could benefit from food assistance services.

 

Financial Support: MLJ’s work was supported in part by an Honors Undergraduate Research Fellowship from Eastern Michigan University. No other funding source was used to produce this work and no financial disclosures were reported by the authors of this paper.

Acknowledgements: We thank Dr. Grigoris Argeros for valuable feedback on our analysis plan and Dr. Heather Hutchins-Wiese for critical discussions leading to the design of this project. This work was supported in part by an Honors Undergraduate Research Fellowship from Eastern Michigan University.

Conflict of interest : The authors declare that they have no conflict of interest.

Ethical standard: The Eastern Michigan University Human Subjects Review Committee affirms that this study does not constitute human subjects research under the Common Rule.

 

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