00 

Anchor

Evaluation of the Effect of the Older 

Americans Act Title III-C Nutrition Services 

Program on Participants’ Longer-Term Health 

Care Utilization

Final Report

July 28, 2020

James Mabli, Laura Castner, and Marisa Shenk

Submitted to:

Center for Policy and Evaluation

Administration for Community Living

U.S. Department of Health and Human Services

330 C Street, SW

Washington, DC 20201

Project Officer: Susan Jenkins, Social Science 

Analyst, Office of Performance and Evaluation

Contract Number: HHSP233201500035I/

 HHSP23337001T

Submitted by:

Mathematica

955 Massachusetts Avenue, Suite 801

Cambridge, MA 02139

Telephone: 617.301.8997

Project Director: James Mabli

Reference Number: 50158.01.770.471.001 
Mathematica ii

Table of Contents

Executive Summary ............................................................................................................iv

I. Introduction ................................................................................................................... 1

A. Overview of the Title III-C Nutrition Services Program............................................ 1

B. Evaluation objectives and research questions........................................................ 2

C. Organization of the report....................................................................................... 3

II. Methodology ................................................................................................................. 4

A. Research design .................................................................................................... 4

B. Sources of data...................................................................................................... 4

1. Outcomes survey ........................................................................................... 4

2. Medicare administrative data.......................................................................... 5

3. LSP survey..................................................................................................... 5

4. Neighborhood contextual data from the American Community 

Survey............................................................................................................ 6

5. Urbanicity and geographic food access.......................................................... 6

C. Outcome measures................................................................................................ 6

D. Analytic approach................................................................................................... 8

III. Effects of congregate meal participation on outcomes.................................................10

A. Characteristics of participants ..............................................................................10

B. Impacts of congregate meal participation on health care utilization ......................12

1. Likelihood of a health event by income..........................................................13

2. Frequency and costs of health events ...........................................................16

IV. Characteristics associated with adverse health events................................................18

A. Any adverse health event.....................................................................................18

B. Specific adverse health events.............................................................................19

1. Hospital admissions ......................................................................................20

2. Hospital readmissions ...................................................................................20

3. Emergency department visits leading to hospital admissions ........................20

4. Home health episodes...................................................................................22

5. Skilled nursing facility admissions .................................................................22

6. Long-term care admissions ...........................................................................22

C. Characteristics with limited time associations with adverse health 

events ..................................................................................................................23
Contents

Mathematica iii

V. Conclusion ..................................................................................................................24

A. Effects on health care utilization...........................................................................24

B. Characteristics associated with adverse health events.........................................24

C. Discussion ............................................................................................................25

References ........................................................................................................................28

Appendix A Chapter III supplementary tables.................................................................. A-1

Appendix B Chapter IV supplementary tables ................................................................. B-1

Exhibits

II.1 Outcome measures and data sources ............................................................................................. 7

III.1 Selected characteristics of congregate meal participants.............................................................. 11

III.2 Health and health care utilization of congregate meal participants ............................................... 12

III.3 Regression-adjusted percentages of congregate meal participants and 

nonparticipants who experienced a hospital readmission within 30 days of 

discharge in Years 1, 2, and 3 following the survey ...................................................................... 13

III.4 Regression-adjusted percentages of congregate meal participants and 

nonparticipants who were admitted to a long-term care facility in the three years 

following the survey, by income subgroup..................................................................................... 14

III.5 Regression-adjusted percentages of lower-income congregate meal participants 

and nonparticipants who experienced health events in Years 1, 2, and 3 following 

the survey....................................................................................................................................... 15

III.6 Regression-adjusted percentages of higher-income congregate meal participants 

and nonparticipants who experienced health events in Years 1, 2, and 3 following 

the survey....................................................................................................................................... 16

III.7 Regression-adjusted numbers of events experienced by congregate meal 

participants and nonparticipants, among those who experienced health events in 

Years 1, 2, and 3 following the survey ........................................................................................... 17

IV.1 Odds ratios of participants experiencing adverse health events in the three-year 

period following the survey ............................................................................................................ 19

IV.2 Odds ratios of participants experiencing specific adverse health events in the 

three-year period following the survey ........................................................................................... 21
Mathematica iv

Executive Summary 

As people age, they are more likely to face deteriorating health conditions and adverse health events. 

Adults age 65 and older are much more likely than those ages 45 to 64 to have two or more chronic 

conditions (Buttorff et al. 2017; Ward et al. 2014). Almost one-third of older adults fall each year, and 

more than half of these falls are recurrent (Bergen et al. 2016). Older adults also are at higher risk of 

limitations in activities of daily living, decline in cognitive functioning, social isolation, and depression 

(van der Vorst et al. 2016; Murman 2015; Sözeri-Varma 2012). The predicted increase in the share of the 

population age 65 or older over the next 10 years (Ortman et al. 2014; United States Census Bureau 

2020), coupled with continued increases in health care costs (Keehan et al. 2020; Rama 2019) will have 

profound effects on the ability of federal and state agencies, local community-based service providers, 

and family caregivers to meet the health and social needs of older adults (Kelley et al. 2013; Feinberg and 

Spillman 2019). 

Although many older adults—in particular, those who are frail, disabled, or homebound—receive 

assistance from caregivers and obtain support services from home- and community-based agencies, little 

is known about the effectiveness of these programs on the need for health care services. A recent national 

evaluation of the Older Americans Act (OAA) Title III-C Nutrition Services Program (NSP) showed that 

the program not only promotes older adults’ access to nutritious meals, but also facilitates social contact 

and reduces the likelihood of experiencing adverse health events. These positive program effects were 

generally more pronounced for lower-income individuals than higher-income individuals, and for 

individuals living alone than for those living with other family members. However, studies generally have 

not examined the program’s longer-term success in improving health, reducing the occurrence of adverse 

health events, and helping older adults maintain their independence in their homes and communities. 

This report is the fifth of five reports on findings from a national evaluation of the Title III-C NSP. 

Mathematica conducted this evaluation for the Administration on Aging (AoA) within the Administration 

for Community Living (ACL) of the U.S. Department of Health and Human Services (DHHS), which 

oversees the program. Other reports summarize findings from a process evaluation of program 

administration and service delivery; a cost analysis; an evaluation of effects on program participants’ food 

security, socialization, and diet quality; and an evaluation of effects on participants’ health outcomes. The 

prior reports that examined program impacts (effects) looked at outcomes over a one-year period. This 

report examines impacts over three years using additional data collected from NSP participants and 

nonparticipants. 

Background

The goals of the NSP are to ensure that the health and social needs of older adults are adequately met and 

to rebalance the provision of long-term care away from institutionalization and toward home- and 

community-based services. A core component of the program, and the focus of this report, is the 

provision of group (congregate) meals. NSP congregate meal participants can receive a nutritious meal at 

a senior center or other congregate meal sites. Most sites serve lunch on one or more weekdays, and some 

sites offer breakfast or dinner or provide meals on weekends. Congregate meal sites offer an opportunity 

for older adults to socialize with peers and receive other services, such as nutrition education, screening, 

and counseling. 

Organizations in the National Aging Network, an informal network of home- and community-based care 

providers, administer the NSP. AoA’s central and regional offices provide overall federal coordination; 
Executive Summary

Mathematica v 

however, the State Units on Aging (SUAs) and the Area Agencies on Aging (AAAs) both support key 

aspects of program operations. In turn, local service providers (LSPs) typically provide the direct nutrition 

services.

The NSP is authorized under Title III of the OAA. Through Title III, SUAs implement a system of 

coordinated, community-based services targeted to older adults and receive federal grants from AoA for 

providing congregate nutrition services (authorized under Part C-1), home-delivered nutrition services 

(authorized under Part C-2), meals (authorized under Part A), and support services (authorized under Part 

B). In fiscal year (FY) 2018, the most recent year in which counts of meals and individuals served are 

available, 74 million meals were served to 1.5 million people at congregate sites (ACL 2020). OAA Title 

III-C funding was $311 million for congregate nutrition services in FY 2018 (ACL 2020).

Adults age 60 and older, and their spouses of any age, may participate in the NSP’s congregate meal 

program. In addition, members of the following groups are eligible to receive congregate meals: disabled 

people younger than age 60 who reside in housing facilities occupied primarily by older adults where 

congregate meals are served; disabled people who reside at home with, and accompany, people age 60 

and older to meal sites; and NSP service volunteers. 

The NSP is not an entitlement program. It also does not have a means test, but the program specifically 

targets older adults with the greatest economic or social need, with special attention given to low-income 

older adults, minorities, those living in rural areas, those with limited English proficiency, and those at 

risk of institutional care. Payment for meals is not mandatory, but participants are encouraged to make a 

voluntary contribution toward the total cost of the meal. 

Study objectives

One of the objectives of the evaluation was to determine the impact of NSP meals and nutrition services 

on overall wellness and well-being by comparing outcomes for NSP participants and nonparticipants. The 

research team surveyed a cross-section of NSP participants from October 2015 to April 2016 who had 

been participating in the program for varying lengths of time. Study participants included older adults 

who recently had begun receiving program meals and those who had participated for many years. Using a 

combination of data from this survey and Medicare claims data, the most recent evaluation report (Mabli 

et al. 2018) measured the effect of receiving congregate meals on health care utilization in the nine 

months before the study survey and one year following the survey. 

This report presents findings from an analysis that included two additional years of follow-up. The 

analysis uses a combination of survey data and matched Medicare administrative records to measure 

participants’ patterns of health care utilization, including hospital admissions and readmissions, 

emergency department care, doctor visits, home health episodes, and admissions to long-term care 

facilities (nursing homes) and skilled nursing facilities. The report defines outcomes relative to the date an 

individual completed the survey. One set of outcomes measures health care utilization and Medicare costs 

in each of three one-year periods following the date of the survey, and another set measures 

characteristics associated with utilization in the three-year period following the survey.1

1 For example, if the study participant completed the outcomes survey on December 15, 2015, the one-year set of 

outcomes measured the occurrence of events from December 16, 2015 through December 15, 2016; December 16, 
Executive Summary

Mathematica vi 

Specific research questions include the following:

1. What are the health characteristics and health care utilization profiles of congregate meal 

participants?

2. What is the effect of congregate meal participation on the likelihood of being admitted to a hospital, 

visiting an emergency department, having a primary care physician visit, experiencing a home health 

episode, and being admitted to a skilled nursing facility or a nursing home over a three-year period? 

For older adults who experience these events, what is the effect of the program on the number of 

times they occur? What is the effect of the program on total Medicare expenditures? 

3. What characteristics are associated with experiencing these health events? These factors might 

include individual characteristics related to demographics, economic conditions, and household 

circumstances; geographic, community, and health characteristics; and the types of services offered 

by LSPs that provide congregate meals to program participants.

Study findings

The majority of congregate meal participants were older than 75, were female, were high school 

graduates, and lived alone at the time of the survey interview (Exhibit ES.1). Almost three-quarters of 

congregate meal participants had at least one chronic condition, and 23 percent reported having fallen

during the past three months (Exhibit ES.2). About one-fifth reported being in fair or poor health at the 

time they completed the survey, and more than one-third reported functional impairments and needed 

help performing one or more activities critical to remain in their homes (not shown). Emergency 

department visits not resulting in an inpatient stay were common, with 29 percent of participants having 

at least one such visit in the nine-month period before the survey; about 5 percent had an emergency 

department visit that led to a hospital admission. Some participants (6 percent) experienced a home health 

episode, and few (2 percent) had an admission to a skilled nursing facility. Three-quarters of participants 

visited a primary care physician. More than 9 out of 10 participants (91 percent) had at least some 

Medicare expenses during the nine months before the survey (not shown). The annual average of 

Medicare expenses among all participants, including those with no Medicare expenditures, was $631. 

2016 through December 15, 2017; and December 16, 2017 through December 15, 2018. The three-year set 

measured outcomes from December 16, 2015 through December 15, 2018. 
Executive Summary

Mathematica vii

Exhibit ES.1. Selected characteristics of congregate meal participants

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. Characteristics 

were measured for the nine months prior to the outcomes survey.

Exhibit ES.2. Health and health care utilization of congregate meal participants

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Notes: Estimates are based on an unweighted sample size of 316 congregate meal participants. Health conditions 

and utilization for the nine months prior to the outcomes survey.

ED = Emergency Department.
Executive Summary

Mathematica viii

Overall, there were few statistically significant effects of congregate meal participation on health care 

utilization. One effect that was observed involved hospital readmissions. In two of the three time frames 

the analysis examined—two and three years after the survey—participants were less likely than 

nonparticipants to have a hospital readmission within 30 days of discharge (Exhibit ES.3). About 1 

percent of participants had a readmission in Year 2, compared with 6 percent of nonparticipants; in Year 

3, these percentages were 2 and 8 percent, respectively. This pattern was not observed in Year 1.

Exhibit ES.3. Percentages of congregate meal participants and nonparticipants who experienced a 

hospital readmission within 30 days of discharge in Years 1, 2, and 3 following the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. Percentages were regression-adjusted for observed differences between participants and 

nonparticipants. 

**Difference between participants and nonparticipants is statistically different from zero at the 0.05 level, two-tailed 

test.

*Difference between participants and nonparticipants is statistically different from zero at the 0.10 level, two-tailed 

test.

There were several effects of congregate meal participation on health care utilization for lower-income 

individuals and fewer for higher-income individuals. In both Year 2 and Year 3, lower-income 

participants were less likely than their nonparticipant counterparts to have a hospital readmission within 

30 days of discharge (Exhibit ES.3). The difference between the two groups was 11 percentage points in 

Year 2 (2 versus 13 percent) and 12 percentage points in Year 3 (1 versus 13 percent). Therefore, among 

low-income individuals, hospital readmissions are 7 to 25 times higher for nonparticipants than for 

participants. Among higher-income individuals, participants were less likely than nonparticipants to have 

a hospital readmission in Year 2, but the magnitude was smaller than for lower income participants.

In addition, among lower-income individuals, congregate meal participants were less likely than 

nonparticipants to have an admission to a long-term care facility within three years of the interview (13 
Executive Summary

Mathematica ix

versus 22 percent, Exhibit ES.4). Within one year of the survey, lower-income participants were less 

likely than nonparticipants to have an emergency department visit that led to an admission (14 versus 24 

percent, not shown). In contrast, participants were more likely than nonparticipants to be admitted to a 

skilled nursing facility in Year 2 (23 versus 13 percent, not shown). No effects were found for hospital 

admissions, emergency department visits that did not lead to a hospital admission (outpatient emergency 

department visit), or home health episodes. 

Exhibit ES.4. Percentages of congregate meal participants and nonparticipants who were admitted 

to a long-term care facility in the three years following the survey, by income subgroup

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. Percentages were regression-adjusted for observed differences between participants and 

nonparticipants.

*Difference between participants and nonparticipants is statistically different from zero at the 0.10 level, two-tailed 

test.

The only significant difference between participants and nonparticipants overall was observed for hospital 

readmissions within 30 days of discharge (Exhibit ES.3). However, there were some differences between 

participants and nonparticipants in the frequency of health events. As Exhibit ES.5 shows, among those 

admitted to a skilled nursing facility, participants had significantly more admissions than nonparticipants 

in Year 1 (1.6 vs 1.1) and fewer admissions in Year 3 (1.0 vs 2.1). Among those who experienced specific 

types of events, relative to nonparticipants, participants had 0.8 more emergency department visits that 

did not lead to an admission in Year 1, 0.5 fewer hospital admissions in Year 3, and 0.4 fewer home 

health episodes in Year 2. 
Executive Summary

Mathematica x 

Exhibit ES.5. Regression-adjusted numbers of events experienced by congregate meal 

participants and nonparticipants, among those who experienced specific health events in Years 1, 

2, and 3 following the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

***Difference between participants and nonparticipants is statistically different from zero at the 0.01 level, two-tailed 

test.

**Difference between participants and nonparticipants is statistically different from zero at the 0.05 level, two-tailed 

test.

*Difference between participants and nonparticipants is statistically different from zero at the 0.10 level, two-tailed 

test.

The research team also examined characteristics of congregate meal participants associated with 

experiencing health events in the three years following the survey. The likelihood of experiencing any 

type of adverse health event (a hospital admission, a hospital readmission within 30 days, an emergency 

department visit leading to a hospital admission, a home health event, a skilled nursing facility admission, 

and admission to a long-term care facility) was higher among veterans and those who had had a fall 

during the three months prior to the survey. Having a high school education; being non-Hispanic Black or 

a non-Hispanic individual who reported a race other than White or Black; and receiving meals and 

services from an LSP that offered health promotion activities were all associated with being less likely to 

have an adverse health event. 

There were also several significant associations between participants’ characteristics and specific types of 

adverse health events during the three years following the survey. Those who recently had a fall were 

more likely than those who had not had a fall to be admitted to a hospital, be readmitted to a hospital 

within 30 days of discharge, have a home health episode, be admitted to a skilled nursing facility, and be 
Executive Summary

Mathematica xi 

admitted to a long-term care facility. Similarly, older adults with less income were more likely to be 

admitted to skilled nursing and long-term care facilities than those with more income. 

Conclusions 

This report examined the effect of the NSP on overall wellness and well-being based on outcomes related 

to health and avoidance of institutionalization. It extended findings from a previous report that examined 

effects over a one-year period by incorporating data collected over two additional years of follow-up. 

Implications for continued program development and additional research include the following:

1. The descriptive findings showed that many NSP participants were in fair or poor health, had 

functional impairments that limited daily activities, and had at least one chronic condition. These and 

other indicators of health and economic need, as well as the extent to which participants experienced 

adverse health outcomes, underscore the vulnerability of the population of older adults the program 

serves. Continuing to monitor participants’ characteristics and circumstances will enable LSPs to 

continue to target meals and services to older adults in greatest need.

2. The lower likelihood of hospital readmission among participants, relative to nonparticipants, 

particularly among those with lower income, might reflect the way in which the NSP serves as a 

primary access point for many home- and community-based services to help older adults meet their 

health and nutrition needs. Those returning home after a hospital stay may require a variety of longterm in-home and community-based supports that may not be available to nonparticipants for 

extended periods of time after discharge. In addition, lower rates of hospital readmission among 

lower-income individuals may reflect the targeting of NSP programs to those with the greatest need, 

which could be due to staff and resource constraints or eligibility for complementary services. 

Learning more about the services LSPs offer to older adults who were recently discharged from the 

hospital will help identify effective strategies for continuing to reduce readmission rates among 

congregate meal participants.

3. The lower rate of admission to a long-term care facility among lower-income participants compared 

with lower-income nonparticipants that was sustained across the three-year study period suggests that 

the program is achieving its goal of improving older adults’ ability to age in place and delay or avoid 

institutionalization, particularly among older adults who have the greatest economic need. More 

research is needed to understand the differences in program effectiveness by income and the 

mechanisms through which the meals and services provided by LSPs ultimately influence 

participants’ risk of institutionalization.

4. The findings from this analysis contribute to the well-documented danger of falls among older adults 

and their attendant detriment to health and well-being. The consistency and strength of these findings 

for the congregate meal participant population underscore the need to learn more about what the 

National Aging Network is doing to expand, enrich, and target its falls prevention programs at meal 

sites. 

5. Veterans were more likely than non-veterans to experience any adverse health event and, specifically, 

a home-health episode. These findings suggest that even after accounting for characteristics of 

veterans (disability, income, and so on) veteran status remains strongly associated with longer-term 

health care utilization. More research is needed to understand the types of services available to 

veterans at congregate meal sites and whether veterans endure specific mental health issues that 

interfere with their ability to use NSP services to improve their health.
Executive Summary

Mathematica xii

6. The likelihood of experiencing an adverse health event was lower among participants who received 

meals from LSPs that offered health promotion activities, relative to those served by LSPs that did not 

offer these activities. More information is needed about the structure of these activities and the 

resources required to offer them across all meal sites. By collecting information from two key 

groups—LSPs, to learn more about the types of health promotion activities they offer, and 

participants, to learn more about which activities they have found to be most useful—the National 

Aging Network can identify the specific types of health promotion activities that are most effective in 

improving participants’ lives.
Mathematica 1 

I. Introduction

As people age, they are more likely to face deteriorating health conditions and experience adverse health 

events. Adults ages 65 and older are much more likely than those ages 45 to 64 to have two or more 

chronic conditions (81 versus 50 percent, Buttorff et al. 2017; 61 versus 32 percent, Ward et al. 2014). 

Nearly 30 percent of older adults fall each year, and more than half of these falls are recurrent (Bergen et 

al. 2016). Older adults also are at higher risk of limitations in activities of daily living, decline in 

cognitive functioning, social isolation, and depression (van der Vorst et al. 2016; Murman 2015; SözeriVarma 2012). U.S. Census predictions indicate that 21 percent of the population will be 65 or older by 

2030, compared with 17 percent in 2020 (Ortman et al. 2014; United States Census Bureau 2020, Table

2;). This shift in the demographic composition of the population coupled with continued increases in 

health care costs (Keehan et al. 2020; Rama 2019) will have profound effects on the ability of federal and 

state agencies, local community-based service providers, and family caregivers to meet the health and 

social needs of older adults (Kelley et al. 2013; Feinberg and Spillman 2019). 

Although many older adults—in particular, those who are frail, disabled, or homebound—receive 

assistance from caregivers and obtain support services from home- and community-based agencies, little 

is known about the effectiveness of these programs on the need for health care services. A recent national 

evaluation of the Title III-C Nutrition Services Program (NSP) showed that the program not only 

promotes older adults’ access to nutritious meals, but also facilitates social contact and reduces the 

likelihood of experiencing adverse health events over the course of one year. These positive program 

effects were generally more pronounced for lower-income individuals than higher-income individuals, 

and for individuals living alone than for those living with other family members. However, studies 

generally have not examined the program’s longer-term success in improving health, reducing the 

occurrences of adverse health events, and helping older adults maintain their independence in their homes 

and communities. 

This report is the fifth of five reports on findings from a national evaluation of the Title III-C NSP. 

Mathematica conducted this evaluation for the Administration on Aging (AoA) within the Administration 

for Community Living (ACL) of the U.S. Department of Health and Human Services (DHHS), which 

oversees the program. Other reports summarize findings from a process evaluation of program 

administration and service delivery (Mabli et al. 2015); a cost analysis (Ziegler et al. 2015); an evaluation 

of effects on program participants’ food security, socialization, and diet quality (Mabli et al. 2017); and 

an evaluation of effects on participants’ health outcomes (Mabli et al. 2018). The prior reports that 

examined program impacts (effects) looked at outcomes over a one-year period. This report examines 

impacts over three years using additional data collected from NSP participants and nonparticipants. The 

remainder of this chapter provides an overview of the NSP, summarizes the research objectives of the 

evaluation, and describes the organization of the report.

A. Overview of the Title III-C Nutrition Services Program

The NSP is authorized under Title III of the Older Americans Act (OAA). Through Title III, State Units 

on Aging (SUAs) implement a system of coordinated, community-based services targeted to older adults 

and receive federal grants from AoA to provide congregate nutrition services (authorized under Part C-1), 

home-delivered nutrition services (authorized under Part C-2), meals (authorized under Part A), and 

support services (authorized under Part B). The goals of the NSP are to ensure that the health and social 
Chapter I. Introduction

Mathematica 2 

needs of older adults are adequately met and to rebalance the provision of long-term care away from 

institutionalization and toward home- and community-based services. 

A core component of the program and the focus of this report is the provision of group (congregate) 

meals. NSP congregate meal participants can receive a nutritious meal at a senior center or other 

congregate meal sites. Most sites serve lunch on one or more weekdays, and some sites offer breakfast or

dinner or provide meals on weekends (Mabli et al. 2015). Congregate meal sites offer older adults an 

opportunity to socialize with peers and receive other services, such as nutrition education, screening, and 

counseling. These services help older adults identify their general and specific needs related to 

maintaining their health and managing individual nutrition-related diseases, such as heart disease, 

hypertension, and diabetes. Participants may also receive non-nutrition services, including transportation, 

case management services, and referrals to Medicare and health promotion and disease prevention 

programs. In fiscal year (FY) 2018, the most recent year in which counts of meals and individuals served 

are available, 74 million meals were served to 1.5 million people at congregate sites (ACL 2020). In FY 

2018, OAA Title III-C funding was $311 million for congregate nutrition services (ACL 2020).

Adults age 60 and older, and their spouses of any age, may participate in the NSP’s congregate meal 

program. In addition, members of the following groups are eligible to receive congregate meals: disabled 

people younger than age 60 who reside in housing facilities occupied primarily by older adults where 

congregate meals are served; disabled people who reside at home with, and accompany, people age 60 

and older to meal sites; and NSP service volunteers. 

The NSP is not an entitlement program. It also does not have a means test, but the program specifically 

targets older adults with the greatest economic or social need, with special attention given to low-income 

older adults, minorities, those living in rural areas, those with limited English proficiency, and those at 

risk of institutional care. Payment for meals is not mandatory, but participants are encouraged to make a 

voluntary contribution toward the total cost of the meal. 

Individuals become aware of NSP programs services through several channels. Many are referred by 

health professionals, health service agencies, and family and friends. Other common referral sources for 

congregate meals include information and assistance systems, such as the OAA national referral system, 

and hospital, health care facility, and discharge planners (Mabli et al. 2015). 

In addition to supporting older adults with their nutritional needs, NSP agencies strive to understand and 

address the numerous non-nutritional needs of program participants that affect overall wellness and wellbeing, including social activities, health promotion and disease prevention, transportation to and from 

meal sites, case management, and chores and housekeeping services. The majority of local service 

providers (LSPs) have a formal process for assessing the non-nutritional needs of congregate participants, 

which includes examining the participants’ paths to the meals program and the needs existing agencies 

are addressing. Many LSPs also refer clients to other programs such as Medicare Parts A and B, Medicare 

Part D, Medicaid waiver programs, and evidence-based health promotion and disease prevention 

programs. 

B. Evaluation objectives and research questions

One of the objectives of the evaluation was to determine the impact of NSP meals and nutrition services 

on overall wellness and well-being by comparing outcomes for NSP participants and nonparticipants. The 

most recent evaluation report (Mabli et al. 2018) addressed this objective by measuring the effect of 
Chapter I. Introduction

Mathematica 3 

receiving congregate meals on health care utilization in the nine months before the study survey and one 

year following the survey, based on Medicare claims data.2

 

This report presents findings from an analysis that included two additional years of follow-up. The 

analysis uses a combination of survey data and matched Medicare administrative records to measure 

participants’ patterns of health care utilization, including hospital admissions and readmissions, 

emergency department care, doctor visits, home health episodes, and admissions to nursing homes and 

skilled nursing facilities. 

Specific research questions include the following:

1. What are the health characteristics and health care utilization profiles of congregate meal 

participants?

2. What is the effect of congregate meal participation on the likelihood of being admitted to a hospital, 

visiting an emergency department, having a primary care physician visit, experiencing a home health 

episode, and being admitted to a skilled nursing facility or a nursing home over a three-year period? 

For older adults who experience these events, what is the effect of the program on the number of 

times they occur? What is the effect of the program on total Medicare expenditures?

3. What characteristics are associated with experiencing these health events? These factors might 

include individual characteristics related to demographics, economic conditions, and household 

circumstances; geographic, community, and health characteristics; and the types of services offered 

by LSPs that provide congregate meals to program participants. 

C. Organization of the report

The remaining chapters of this report describe the methodology used in the analysis and present findings. 

Chapter II provides an overview of the study design and the data and methodology used in the analysis. 

Chapter III describes congregate meal participants’ demographic characteristics, health care utilization, 

and Medicare expenditures and presents estimates of the effect of participating in congregate meal 

programs on health care utilization outcomes. Chapter IV examines the factors that meal site staff and 

program administrators can use to help target congregate meal participants who might be at greatest risk 

of experiencing an adverse health event. Chapter V summarizes findings to inform policy and discusses 

implications for future research. Appendices A and B supplement the Chapter III and IV exhibits, 

respectively, by presenting auxiliary tables.

2 Although Mabli et al. (2018) also examined health care utilization for home-delivered meal participants, only the 

receipt of congregate meals was shown to reduce the likelihood of experiencing adverse health events in the shortrun. The current report examines congregate meals only to assess whether these findings remain significant over a 

longer observation period. 
Mathematica 4 

II. Methodology

This report presents findings based primarily on information the research team obtained from a 

comprehensive survey and linked Medicare administrative data collected from samples of NSP

participants and a matched comparison group of program-eligible nonparticipants. This chapter describes 

these and other data sources used in the analysis; defines the outcome measures examined in the report;

and presents the analytic methods used to address the evaluation’s research objectives.3

 

A. Research design

The evaluation used a multistage clustered sample design to obtain information from congregate meal 

participants and nonparticipants. The stages of sampling were: 

1. Area Agencies on Aging (AAAs) 

2. LSPs within AAAs 

3. Congregate meal sites within LSPs 

4. Congregate meal participants within each congregate meal site 

In addition, the research team obtained a matched sample of congregate meal nonparticipants by 

comparing participants’ Medicare administrative records with all Medicare administrative records in the 

geographic areas in which participants lived. The team identified potential nonparticipants as those who 

had the closest match to participants on a set of demographic, economic, and health characteristics and 

health care utilization measures. These individuals were then screened to assess whether they were 

homebound and were not currently participating in congregate meal programs. The research team asked 

individuals who passed the screener and consented to be part of the evaluation to complete the survey and 

included them in the analysis sample.4

 

B. Sources of data

The research team linked the outcomes survey data to several data sources: Medicare administrative data, 

an LSP survey, the American Community Survey, and food retailer information from the U.S. 

Department of Agriculture (USDA). Details on each source are provided below. 

1. Outcomes survey 

The outcomes survey collected data on a comprehensive set of topics, including demographic 

characteristics, food security, health and well-being, NSP participation history, and participants’ 

impressions of the program and services. A random sample of NSP participants and a matched 

comparison group of program-eligible nonparticipants completed the survey. 

The research team collected data between October 2015 and April 2016 through in-person computerassisted interviews. From late October 2015 through early January 2016, field interviewers collected 

information from congregate meal participants. Data collection in each congregate meal site spanned five 

3 Additional details about data collection, weight construction, outcome measures, and analysis measures are 

available in Mabli et al. (2018).

4 Details about participant and nonparticipant data collection are available in Mabli et al. (2017). 
Chapter II. Methodology

Mathematica 5 

days. Field interviewers randomly selected participants to take part in the study on one day and, over the 

next four days, administered the survey to participants who agreed to participate in the study. From late 

January 2016 through early April 2016, field interviewers returned to the same geographic areas to 

interview a matched comparison group of program-eligible nonparticipants. 

The research team used the American Association for Public Opinion Research’s (2016) Standard 

Definitions, ninth edition, to calculate response rates. The survey response rate was 76.1 percent for 

congregate meal participants. The survey completion rate for congregate meal nonparticipants who were 

recruited from the telephone screener was 79.1 percent.

2. Medicare administrative data 

The research team used Medicare claims and enrollment data obtained through the Centers for Medicare 

and Medicaid Services Research Data Assistance Center to construct outcome measures and define 

Medicare beneficiary characteristics. These data included hierarchical condition category (HCC) scores, 

which capture the risk of subsequent health care expenditures based on prior claims information; the 

original reason for an individual’s Medicare eligibility, which measures whether the beneficiary originally 

qualified for Medicare due to age, disability, or end-stage renal disease; whether the individual had dual 

enrollment in Medicare and Medicaid, which could indicate low socioeconomic status; and whether the 

individual had any chronic health conditions. The team obtained the following files for 2015 through the 

first quarter of 2019: Medicare claims data (inpatient, outpatient, carrier, home health, and skilled nursing 

facility files); the Medicare long-term care Minimum Data Set with comprehensive assessment 

information on residents of long-term care facilities; and the Medicare enrollment database. 

This analysis includes all participants and nonparticipants who were matched to the 2015–2017 Medicare 

data (Mabli et al. 2018). Some participants chose not to provide a full or partial Social Security number, 

which prevented the research team from matching them successfully to the Medicare administrative data. 

Overall, 11 percent of the participants and nonparticipants who completed the outcomes survey were not 

matched to the Medicare data and, thus, were not included in the analysis. Because Medicare claims, 

which identify specific events such as a hospital stay or emergency department visit, are not available for 

beneficiaries enrolled in managed care plans such as Medicare Advantage, the research team limited the 

analysis to those who were enrolled in fee-for-service (FFS) Medicare (known as Original Medicare). 

3. LSP survey

The LSP survey included two parts: a web survey and a separate editable PDF form that respondents 

completed and returned electronically. The web survey contained the majority of the questions, including 

those that a respondent could likely answer without referring to other data sources, such as organizational 

structure. The editable PDF (referred to as a “fax-back” form) included fewer items and was largely 

focused on questions that required respondents to look up data from sources such as financial reports on 

program expenditures. 

The research team merged data from the LSP survey to data from the outcomes survey to obtain 

information about whether participants attended LSPs that offered health promotion activities, nutrition 

counseling, nutrition screening, and social activities. For nonparticipants, the team assigned the values of 

variables for the LSPs that served the participant to whom the nonparticipant was matched. 
Chapter II. Methodology

Mathematica 6 

4. Neighborhood contextual data from the American Community Survey 

The research team used data from the American Community Survey to obtain local-area population 

characteristics. To obtain characteristics for small-census geographies, such as census tracts, the Census 

Bureau aggregates data over five years. The research team drew on the 2010–2014 American Community 

Survey summary file to obtain tract-level measures of population, the percentage of families with income 

below 200 percent of the federal poverty threshold, the percentage of the total population that is nonwhite, the percentage of the total population that is Hispanic, and the percentage of housing units without 

access to a vehicle. 

5. Urbanicity and geographic food access 

The research team determined whether an individual lived in an urban or rural area by overlaying the map 

of respondents’ residential locations with a U.S. Census Bureau geographic boundaries file and 

identifying the census tract in which each respondent lived.5

 A binary indicator of urban/rural status was 

created using the census tract identification number. Using the ERS food environment atlas (ERS 2016), 

the research team obtained a variable that indicates whether the population-weighted centroid of a census 

tract is in an urban or rural area. To describe NSP geographic access to food, the research team used the 

address information for each survey respondent, data from the Census Bureau, and address data for food 

retailers from the USDA. The team calculated measures of geographic access to food based on (1) 

distances from each participant to the nearest store in the area and (2) the number of retailers, by type, 

within three distances from each participant’s residential address. In urban areas, the distances are less 

than 0.5 miles, 0.5 to less than 1 mile, and 1 to 2 miles. In rural areas, the distances are less than 5 miles, 

5 to less than 10 miles, and 10 to 20 miles. Mabli et al. (2018) describes the retailer data in more detail.

C. Outcome measures

The research team analyzed three sets of health care utilization outcomes. First, the team analyzed 

whether the following health events occurred in the observation period: hospital admissions, hospital 

readmissions within 30 days of discharge, emergency department visits that resulted in an inpatient stay, 

outpatient emergency department visits, primary care physician visits, home health episodes, admittance 

to a skilled nursing facility, and admittance to a long-term care facility (nursing home) (Exhibit II.1). For 

all outcomes except hospital readmission and nursing home admission, a second set of outcomes counted 

the number of times the event occurred in the observation period. A third set of outcomes consisted of 

total Medicare Part A and Part B costs in the observation period. 

The team defined outcomes relative to the date the outcomes survey was completed (during 2015–2016).

One set of outcomes measured health care utilization and Medicare costs in each of three one-year periods 

following the date of the survey, and another set measured characteristics associated with utilization in the 

three-year period following the survey. For example, if the outcomes survey was completed on December 

15, 2015, the one-year set of outcomes measured the occurrence of events from December 16, 2015 

through December 15, 2016; December 16, 2016 through December 15, 2017; and December 16, 2017 

5 Census tracts are geographic boundaries developed by the U.S. Census Bureau. They are drawn to encompass 

similar population sizes and, thus, vary in spatial size depending on whether they are in a metropolitan or 

nonmetropolitan area. Census tracts are the largest subcounty geographies defined by the Census Bureau; they

generally contain 1,500 to 8,000 people and have a target size of 4,000. In 2010, the United States was divided into 

more than 73,000 census tracts.
Chapter II. Methodology

Mathematica 7 

through December 15, 2018. The three-year set measured outcomes from December 16, 2015 through 

December 15, 2018. These analyses measure outcomes in varying lengths of time relative to the date of 

the survey. The research team administered the survey to a cross-section of NSP participants, including 

those who recently had begun to receive meals and those who had received them for several years. As a 

result, these findings do not represent the effect of an additional two years of participating in the NSP. 

Instead, they allow the research team to measure health care utilization outcomes over a longer period of 

time relative to when older adults are known to have received congregate meals. 

Exhibit II.1. Outcome measures and data sourcesa

Outcome 

measures Data source 

Description of health event 

occurrence variables

Description of number of 

events variables

Hospital 

admissions 

Medicare claims 

data—inpatient 

file 

Binary variable indicating whether the 

individual had an acute care hospital 

admission in the observation period 

Continuous variable equal to the 

number of acute care hospital 

admissions in the observation 

period

Hospital 

readmission

within 30 days of 

discharge 

Medicare claims 

data—inpatient 

file 

Binary variable indicating whether the 

individual was discharged from the 

hospital and had an unplanned 

hospitalization within 30 days of 

discharge in the observation period 

Not included in analysis

Inpatient 

emergency 

department (ED) 

visits 

Medicare claims 

data—inpatient 

files 

Binary variable indicating whether the 

individual had an ED visit and 

observation stay in the observation period

that led to a hospitalization 

Continuous variable equal to the 

number of ED visits and 

observation stays in the 

observation period that led to a 

hospitalization

Outpatient ED 

visits 

Medicare claims 

data—outpatient 

file

Binary variable indicating whether the 

individual had an ED visit and 

observation stay in the observation period 

that did not lead to a hospitalization 

Continuous variable equal to the 

number of ED visits and 

observation stays in the 

observation period that did not 

lead to a hospitalization

Primary care 

physician (PCP) 

visits in all 

settings 

Medicare claims 

data—carrier file 

Binary variable indicating whether the 

individual had a visit to a PCP in the 

observation period 

Continuous variable equal to the 

number of PCP visits in the 

observation period

Home health 

episodes 

Medicare claims 

data—home 

health file 

Binary variable indicating whether the 

individual had a home health episodeb in 

the observation period 

Continuous variable equal to the 

number of home health episodes 

in the observation period

Admittance to a 

skilled nursing 

facility (SNF) 

Medicare claims 

data—SNF 

Binary variable indicating whether the 

individual was admitted to a SNF in the 

observation period 

Continuous variable equal to the 

number of SNF stays in the 

observation period

Admittance to a 

nursing home 

Long-term care 

Minimum Data 

Set 

Binary variable indicating whether the 

individual was admitted to a nursing 

home in the observation periodc 

Not included in analysis

a Observation periods are the three one-year periods following the outcomes survey, unless otherwise noted. 
Chapter II. Methodology

Mathematica 8 

b Home health episodes lasted 60 days and involved at least one or a mix of the following services for homebound 

patients: skilled nursing care, physical or speech therapy, occupational therapy, home health aide, and medical social 

services.

c The observation period for admittance to a nursing home is the three-year period following the outcomes survey.

The Medicare data were at the beneficiary claim level, meaning that each observation corresponded to a 

claim associated with a health event experienced by a beneficiary. The research team aggregated the data 

to the beneficiary level to produce the outcome measures needed for the analysis. For each beneficiary, 

the team aggregated claim information separately over each of the three one-year observation periods or 

for the full three-year period. Health care utilization outcomes measuring whether an event occurred in 

the observation period were defined as binary variables equal to 1 if there was at least one claim in the 

observation period indicating an event occurred, and equal to 0 if not. Health care utilization outcomes 

measuring the number of times an event occurred in the observation period were annualized to reflect the 

number of events an individual experienced over one year (dividing total number of events in observation 

period by the number of FFS eligible months in that period, and multiplying by 12). 

The research team also estimated average Medicare costs per month in the observation period for each 

beneficiary by summing the costs of all claims over the observation period and dividing by the number of 

Medicare FFS months in the observation period. Medicare expenditures included only payments made by 

Medicare for Part A and Part B services as reported in administrative data, and excluded out-of-pocket 

costs, third party payments, and hospice care and durable medical equipment. 

Finally, the research team defined a binary variable for any adverse health event indicating whether the 

individual had an acute care hospital admission, home health episode, or long-term care admittance in

each of the three one-year periods and the full three-year period following the outcomes survey. 

D. Analytic approach

The research team performed descriptive tabular analyses of the characteristics and health care utilization 

of congregate meal participants. For categorical variables, the percentage of participants who responded 

in each category was estimated. For continuous variables, the mean value is presented. 

In estimating the impact of congregate meal participation on the above outcomes, the research team used 

ordinary least squares (OLS) regression analysis for continuous variables: (1) the number of events that 

occurred in a given observation period and (2) average monthly Medicare expenditures. The team used 

logistic regression analysis for binary variables that measured whether a health event occurred in the 

observation period.6

 The results of regression analyses are presented using regression-adjusted tables of 

estimates of program effects. For example, a regression-adjusted table compares the percentages of 

congregate meal participants and nonparticipants who had a hospital admission during an observation 

period after accounting or adjusting for compositional differences between the groups.7

 

With the exception of nursing home admissions, the research team conducted multivariate analyses 

separately for each of the three one-year periods. The team examined nursing home admissions over the 

6 For several subgroup analyses for the binary outcomes, the research team used OLS in place of logistic regression 

analyses due to lack of convergence of the nonlinear model likely attributed to the smaller sample sizes and limited 

variation in the dependent variable.

7 Additional details about the analytic approach are available in Mabli et al. (2018).
Chapter II. Methodology

Mathematica 9 

full three-year period because it was a longer-term outcome and most participants who entered a nursing 

home remained institutionalized and therefore were not at risk of being admitted in subsequent years. 

The team also conducted all analyses separately for two important household and economic subgroups: 

individuals who lived in households with lower or higher incomes, and individuals who lived alone or 

with other family members. The income subgroups were defined by dividing the sample into those 

individuals with household income-to-poverty ratios less than the median value in the sample and those 

with ratios greater than or equal to the median value. Median income as a percentage of the federal 

poverty level was equal to 128 percent for both congregate meal participants and nonparticipants. 

To address the research question examining the characteristics associated with experiencing adverse 

health events, the research team used logistic regression analysis. Analyses were conducted separately by 

year and across the full three-year period, because these analyses focused on longer-term outcomes. Odds 

ratios (ORs) describe the characteristics associated with any adverse health event and specific events (a 

hospital admission, any home health episode, and admission to a long-term care facility). A characteristic 

with an odds ratio below 1 indicates that having that characteristic is associated with (1 – OR) percent 

lower odds of experiencing an adverse health event, while an odds ratio above 1 indicates (OR – 1) 

percent higher odds of experiencing an adverse health event. 

Analysis weights allow one to compute unbiased estimates based on sample survey responses from the 

study population. Weights account for both the probability of selection into the sample and the differential 

response patterns that might exist in the respondent sample. They also account for whether the individual 

had a successful match to the Medicare claims data used to construct outcomes and, if so, whether the 

individual was a Medicare FFS beneficiary. The research team constructed weights separately for 

congregate meal participants and nonparticipants and accounted for the multistage sampling design of the 

outcomes evaluation when estimating standard errors. The team used t-tests to determine whether 

regression-adjusted differences in outcomes between participants and nonparticipants were statistically 

significant at the 0.01, 0.05, and 0.01 levels using a two-tailed test. 

Based on weighted data, the congregate meal participant findings in this report are nationally 

representative of the population of congregate meal participants. This is not true for the nonparticipants, 

however, because, by design, they were not sampled from a frame of nonparticipating older adults. 

Instead, the estimates of the effects of congregate meal participation on outcomes that use weighted 

participant and nonparticipant data are representative of the effects for the population of congregate meal 

participants; that is, the study is meant to assess the effect of the programs on those who choose to 

participate in the program, not on the entire population. For the same reason, Chapter IV presents 

information for congregate meal participants only.
Mathematica 10

III. Effects of congregate meal participation on outcomes 

This chapter discusses findings related to congregate meal participation and health care utilization 

outcomes. The first section describes key characteristics of congregate meal participants.8 It then presents 

estimates of the effects of congregate meal participation on participants’ outcomes. The estimates are 

based on multivariate analyses that account for observed differences between participants and matched 

nonparticipants, referred to as regression-adjusted findings. Except where otherwise noted, this chapter 

presents impact of program participation for three sets of outcomes: (1) whether health events occurred in 

any of the three one-year periods following the survey, (2) the number of events that occurred among 

those individuals who experienced them, and (3) the total Medicare cost associated with the events.

A. Characteristics of participants

The descriptive findings showed that many NSP participants were in fair or poor health, had functional 

impairments that limited daily activities, and had one or more chronic conditions. These and other 

indicators of health and economic need, as well as the extent to which participants experienced adverse 

health outcomes, underscore the vulnerability of the population of older adults the program serves. 

The majority of congregate meal participants were older than 75, were female, were high school 

graduates, and lived alone at the time of the survey (Exhibit III.1).9 Non-Hispanic black individuals 

constituted approximately 14 percent of congregate meal participants, and Hispanic individuals accounted 

for another 14 percent of participants (Appendix A, Table A.1). Just over one-fourth of participants 

resided in rural areas. Although the OAA prohibits financial means tests for participation in the NSP, 

most participants were poor or near poor. 

About one-fifth of congregate meal participants reported being in fair or poor health at the time they 

completed the survey (Exhibit III.2). Almost three-quarters had at least one chronic condition,10 and 23 

percent reported having fallen during the past three months. Over a third of participants reported 

functional impairments and needed help performing one or more activities critical for them to remain in 

their homes (38 percent had difficulty walking or climbing stairs; Appendix A, Table A.2). Emergency 

department visits not resulting in an inpatient stay were common, with 29 percent of participants having 

at least one such visit in the nine-month period before the survey; about 5 percent had an emergency 

department visit leading to a hospital admission. Some participants (6 percent) experienced a home health 

episode, and few (2 percent) had an admission to a skilled nursing facility. Three-quarters of participants 

visited a primary care physician. 

8 Appendix A, Tables A.1 to A.4 provide additional details about characteristics of congregate meal participants.

9 As Chapter II discusses, the research team obtained a matched sample of congregate meal nonparticipants by 

identifying those who had the closest match to participants on a set of demographic, economic, and health 

characteristics, and health care utilization measures. As a result, the characteristics of nonparticipants are statistically 

similar to participants. Because nonparticipants were not sampled from a frame of nonparticipating older adults, this 

chapter presents descriptive information for participants only.

10 The chronic condition information presented in this report is based on Medicare claims and enrollment data and 

may differ from the health condition information in the National Survey of Older American Act Participants 

(https://agid.acl.gov/CustomTables/NPS/Year/) that participants self-report. The classification of conditions also 

differs across the two data sources.
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 11

Exhibit III.1. Selected characteristics of congregate meal participants

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. Characteristics 

were measured for the nine months prior to the outcomes survey.

More than 9 out of 10 participants (91 percent) had at least some Medicare expenses during the nine 

months prior to the survey (Appendix A, Table A.4). The annual average of Medicare expenses among all 

participants, including those with no Medicare expenditures, was $631. 

There were several differences by income and living arrangement in the likelihood of experiencing 

specific health events (Appendix A, Tables A.1 to A.4). The percentage of participants with a hospital 

admission was similar for lower- and higher-income individuals (8 percent), but the percentage with a 

readmission within 30 days after discharge was 2 percent for lower-income individuals and close to 0 

percent for higher-income individuals. Emergency department visits that did not lead to a hospitalization 

were also much more common among lower-income individuals (33 versus 24 percent). Those who lived 

alone were more likely to have an emergency department visit that did not lead to a hospitalization than 

those who lived with other family members (33 versus 23 percent). In contrast, the likelihood of a 

hospital admission or readmission within 30 days of discharge was lower for individuals who lived alone 

than for those who lived with other family members (7 versus 10 percent, and 0 versus 3 percent, 

respectively). 
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 12

Exhibit III.2. Health and health care utilization of congregate meal participants

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Notes: Estimates are based on an unweighted sample size of 316 congregate meal participants. Health conditions 

and utilization for the nine months prior to the outcomes survey.

B. Impacts of congregate meal participation on health care utilization

Overall, there were few statistically significant effects of congregate meal participation on health care 

utilization (Appendix A, Tables A.5 and A.6). One effect that was observed involved hospital 

readmissions. In two of the three time frames the analysis examined—two and three years after the 

survey—participants were less likely than nonparticipants to have a hospital readmission within 30 days 

of discharge (Exhibit III.3). About 1 percent of participants had a readmission in Year 2, compared with 6 

percent of nonparticipants; in Year 3, these percentages were 2 and 8 percent, respectively. This pattern 

was not observed in Year 1. 
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 13

Exhibit III.3. Regression-adjusted percentages of congregate meal participants and 

nonparticipants who experienced a hospital readmission within 30 days of discharge in Years 1, 2, 

and 3 following the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

**Difference between participants and nonparticipants is significantly different from zero at the 0.05 level, two-tailed 

test.

1. Likelihood of a health event by income

For lower-income individuals, the research team identified several effects of congregate meal 

participation and fewer for higher-income individuals. Among lower-income individuals, congregate meal 

participants were less likely than nonparticipants to have a nursing home admission within three years of 

the interview (13 versus 22 percent, Exhibit III.4). In addition, in both Year 2 and Year 3, lower-income 

congregate meal participants were less likely than lower-income nonparticipants to have a hospital 

readmission within 30 days of discharge (Exhibit III.5). The difference between the two groups was 11 

percentage points in Year 2 (2 versus 13 percent) and 12 percentage points in Year 3 (1 versus 13 

percent). Therefore, among low-income individuals, hospital readmissions are 7 to 25 times higher for 

nonparticipants than for participants. Lower-income participants were also less likely to have an 

emergency room visit that led to an admission than lower-income nonparticipants in Year 1 (14 versus 24 

percent, for a difference of 10 percentage points). In contrast, participants were more likely than 

nonparticipants to be admitted to a skilled nursing facility in Year 2 (23 versus 13 percent, for a 

difference of 10 percentage points). There were no effects observed for other outcomes.

Among higher-income individuals, a similar finding was observed for hospital readmissions, but the 

magnitude of the difference between congregate meal participants and nonparticipants was much smaller, 

and the difference was statistically significant only in Year 2 (difference of 2 percentage points, Exhibit 
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 14

III.6). In addition, higher-income participants were more likely than higher-income nonparticipants to 

have a hospital admission in Year 3 (37 versus 19 percent). 

There were generally no significant effects of the program by living arrangement (Appendix A, Table 

A.8). Among individuals who lived with other family members at the time of the survey, congregate meal 

participants were less likely than nonparticipants to be readmitted to a hospital within 30 days of 

discharge in Year 2. There were no other significant outcomes in either of these groups. 

Exhibit III.4. Regression-adjusted percentages of congregate meal participants and 

nonparticipants who were admitted to a long-term care facility in the three years following the 

survey, by income subgroup

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

*Difference between participants and nonparticipants is significantly different from zero at the 0.10 level, two-tailed 

test.
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 15

Exhibit III.5. Regression-adjusted percentages of lower-income congregate meal participants and 

nonparticipants who experienced health events in Years 1, 2, and 3 following the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

**Difference between participants and nonparticipants is significantly different from zero at the 0.05 level, two-tailed 

test.

*Difference between participants and nonparticipants is significantly different from zero at the 0.10 level, two-tailed 

test.
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 16

Exhibit III.6. Regression-adjusted percentages of higher-income congregate meal participants and 

nonparticipants who experienced health events in Years 1, 2, and 3 following the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

***Difference between participants and nonparticipants is significantly different from zero at the 0.01 level, two-tailed 

test.

**Difference between participants and nonparticipants is significantly different from zero at the 0.05 level, two-tailed 

test.

2. Frequency and costs of health events

As previously shown, the only significant difference between all participants and nonparticipants was 

observed for hospital readmissions within 30 days of discharge (Exhibit III.3). However, for some events, 

there were differences between participants and nonparticipants in the number of times they occurred. As 

Exhibit III.7 shows, among those being admitted to a skilled nursing facility, participants transitioned 

from having more admissions than nonparticipants in Year 1 (1.6 vs 1.1 admissions), to no statistical 

difference in Year 2, and to fewer admissions in Year 3 (1.0 vs 2.1 admissions). Among those with an 

emergency room visit that did not lead to an admission, participants had 0.8 more visits in Year 1 than 

nonparticipants. Among those who were admitted to the hospital, participants had 0.5 fewer admissions in 

Year 3. Among those experiencing a home health episode, participants had 0.4 fewer episodes than 

nonparticipants in Year 2. 
Chapter III. Effects of congregate meal participation on outcomes

Mathematica 17

Exhibit III.7. Regression-adjusted numbers of events experienced by congregate meal participants 

and nonparticipants, among those who experienced health events in Years 1, 2, and 3 following 

the survey

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants. 

***Difference between participants and nonparticipants is significantly different from zero at the 0.01 level, two-tailed 

test.

**Difference between participants and nonparticipants is significantly different from zero at the 0.05 level, two-tailed 

test.

*Difference between participants and nonparticipants is significantly different from zero at the 0.10 level, two-tailed 

test.
Mathematica 18

IV. Characteristics associated with adverse health events 

Chapter III showed that for some health utilization outcomes, lower percentages of congregate meal

participants experienced the events relative to nonparticipants. For other outcomes, similar percentages of 

participants and nonparticipants experienced them. In both cases, it is important to learn more about why 

older adults who receive congregate meals continue to experience these events. 

This chapter first examines the characteristics associated with any adverse health event over the threeyear period following the survey. Next, the chapter explores characteristics associated with specific 

adverse effects—a hospital admission, a hospital readmission within 30 days, an emergency department 

visit leading to a hospital admission (inpatient emergency department visits), a home health episode, a 

skilled nursing facility admission, and admission to a long-term care facility.11 Appendix B includes 

supporting tables, including characteristics associated with events in each of the three one-year periods. 

The research team used logistic regression analysis to examine demographic, economic, health, 

community, LSP, and geographic characteristics associated with adverse health events. A characteristic 

with an odds ratio below 1 indicates that having that characteristic is associated with lower odds of 

experiencing the event, while an odds ratio above 1 indicates higher odds of experiencing the event. 

A. Any adverse health event

In the three years following the survey, veteran status and having had a fall in the previous three months 

were associated with higher odds of having an adverse health event. Veterans were more than twice as 

likely (with odds ratio greater than 2) as non-veterans to have an adverse health event (Exhibit IV.1). 

Individuals who had experienced a fall during the previous three months were nearly twice as likely to 

have an adverse health event, relative to individuals who did not report a fall. Furthermore, individuals 

who had experienced a fall were more than five times more likely than individuals who did not report a 

fall to experience an adverse health event in Year 1 (Appendix B, Table B.1). 

Having a high school education; being non-Hispanic Black or a non-Hispanic individual of a race other 

than White or Black; and receiving meals and services from an LSP that offers health promotion activities 

were all associated with lower odds of having an adverse health event. Congregate meal participants who 

had at least a high school education had 60 percent lower odds of experiencing an adverse health event in 

the three-year period than those who had less than a high school education, though the effect appears to 

be largest in Year 1, with 76 percent lower odds; in Years 2 and 3, the odds ratios remained below 1 but 

were not significant (Appendix B, Table B.1). Non-Hispanic Black participants had 58 percent lower 

odds of such an event compared with non-Hispanic White participants, and the effect was also largest in 

Year 1. Non-Hispanic individuals who are neither White nor Black or did not report a race had 85 percent 

lower odds than non-Hispanic White participants, an effect that was significant in both Years 1 and 3. 

Finally, receiving meals and services from an LSP that offers health promotion activities was also 

associated with 57 percent lower odds of experiencing an adverse health event over the three-year period. 

11 Outpatient emergency department visits and primary care physician visits are not always considered adverse 

health events. Unlike outpatient emergency department visits that can sometimes substitute for office-based 

physician visits, hospital admissions and emergency department visits leading to inpatient stays are typically 

regarded as reflecting adverse, acute health events, rather than substitutes for primary care physician visits 

(Aminzadeh and Dalziel 2002).
Chapter IV. Characteristics associated with adverse health events 

Mathematica 19

Exhibit IV.1. Odds ratios of participants experiencing adverse health events in the three-year 

period following the survey

Baseline characteristic Any adverse health event

Demographic, economic, and household characteristics

Age 1.01

Female 1.31

Completed high school 0.40*

Married or living with partner 0.90

Veteran 2.10*

Non-Hispanic black 0.42*

Non-Hispanic othera 0.15**

Hispanic 0.70

Monthly income-to-poverty lower than medianb 1.35

Food insecure 0.76

Living alone 0.79

Health characteristics

HCC score 1.74

High blood pressure/hypertension or diabetes 0.80

Any falls in past three months 2.35**

LSP characteristics

LSP provides health promotion activities 0.43*

LSP provides nutrition counseling 0.79

LSP provides nutrition screening and assessment 1.88

LSP provides social activities 0.82

Geographic characteristics

Share of population non-White is higher than median 0.56

Share of population Hispanic is higher than median 1.21

Share of housing units without access to a vehicle is higher than median 1.07

Share of families below 200% of poverty is higher than median 1.64

Has access to supermarket 1.00

Urban 0.99

Midwest 1.44

Northeast 2.06

West 0.95

Source: Administration on Aging (AoA) Nutrition Services Program outcomes survey, 2015–2016, weighted data; 

AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; HCC = hierarchical condition category. 

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test. 

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander, and races not 

identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 

B. Specific adverse health events

The research team examined the six adverse health events separately in the three years following the 

survey. Overall, few characteristics were associated with multiple types of events with the exception of 

prior falls, which were associated with higher odds of experiencing five of the six events (hospital 

admissions, readmissions, home health episodes, skilled nursing facility admissions, and nursing home 

admissions).
Chapter IV. Characteristics associated with adverse health events 

Mathematica 20

1. Hospital admissions 

Participants who had fallen in the three months before the survey were more than twice as likely to have a 

hospital admission in the three years following the survey (Exhibit IV.2). The association was strongest in 

Year 1, with participants who had fallen being almost four times more likely to have a hospital admission 

relative to those who had not fallen, and decreased over time (Appendix B, Table B.2). 

Education and being a non-Hispanic race other than White or Black race were associated with a lower 

likelihood of having a hospital admission in the three years following the survey (Exhibit IV.2). 

Participants who had at least a high school education were 62 percent less likely to have a hospital 

admission in the three years following the survey, though the finding was most prominent in Year 1, 

where high school graduates were 72 percent less likely to have a hospital admission (Appendix B, Table 

B.2). Participants classified as non-Hispanic other were 85 percent less likely to have a hospital admission 

in the three-year period and even less likely in Years 1 and 3. 

2. Hospital readmissions

Several characteristics were associated with higher likelihoods of experiencing a hospital readmission 

over the three-year period (Exhibit IV.2).12 Hispanic participants were more than six times more likely to 

experience a hospital readmission, compared with non-Hispanic White participants, as were those who 

had nearby access to food. Participants who had a fall were more than five times more likely to 

experience a hospital readmission. Participants who received meals and services from an LSP that offers 

nutrition counseling were also more likely to experience a hospital readmission. Conversely, participants 

who received meals and services from an LSP that offers nutrition screening were 68 percent less likely to 

experience a hospital readmission. Participants who lived in the Western or Midwestern regions were also 

less likely to experience a hospital readmission.

3. Emergency department visits leading to hospital admissions

Congregate meal participants who lived in urban areas were more than twice as likely to have emergency 

department visit leading to a hospital admission (Exhibit IV.2). The association was largest in Year 1, but 

also large and significant in Year 2 (Appendix B, Table B.4). 

Being a non-Hispanic race other than White or Black race and living in the West were associated with 

lower odds (Exhibit IV.2). Being a non-Hispanic individual of a race other than White or Black was 

associated with 82 percent lower odds of experiencing an inpatient emergency department visit in the 

three years following the survey. This association was large in Year 3, but not in Years 1 or 2 (Appendix 

B, Table B.4). Participants who lived in the West had 79 percent lower odds of experiencing an inpatient 

emergency department visit; the effect was significant in Years 1 and 2.

12 Hospital readmissions were assessed only over the three-year period, and not the three one-year periods.
Chapter IV. Characteristics associated with adverse health events 

Mathematica 21

Exhibit IV.2. Odds ratios of participants experiencing specific adverse health events in the threeyear period following the survey

Baseline characteristic

Hospital 

admission

30-day 

hospital

readmission

ED visit 

leading to 

a hospital 

admission

Home 

health 

episode

Skilled 

nursing 

facility 

admission

Nursing 

home 

admission

Demographic characteristics

Age 1.01 1.06 1.02 1.07* 1.06 1.12***

Female 1.17 0.97 1.46 1.67 0.63 0.10***

Completed high school 0.38** 1.59 0.57 0.46 0.59 0.45

Married or living with partner 1.57 1.53 1.46 0.31 0.80 0.17*

Veteran 1.52 0.78 1.34 2.93** 0.89 0.47

Non-Hispanic black 0.43 0.10 0.60 0.69 0.20** 0.00***

Non-Hispanic othera 0.15** 0.18* 0.19 0.42 0.70

Hispanic 0.80 6.77*** 2.49 0.65 0.47 0.63

Monthly income-to-poverty

lower than medianb

1.35 0.34 1.31 1.10 3.38*** 3.90***

Food insecure 0.57 0.30 0.88 1.31 0.71 2.52

Living alone 1.38 2.84 1.45 0.47 2.92** 1.60

Health characteristics

HCC score 1.62 0.22 1.15 1.12 0.58 0.81

High blood 

pressure/hypertension or 

diabetes

0.68 1.55 0.91 2.19* 1.22 2.52

Any falls in past three months 2.24* 5.20*** 1.78 5.67*** 2.74** 3.79***

LSP characteristics

LSP provides health promotion 

activities

0.51 0.35 0.70 0.70 1.49 2.89

LSP provides nutrition 

counseling

0.94 5.91*** 1.48 1.01 1.31 1.80

LSP provides nutrition 

screening and assessment

1.70 0.32** 0.73 1.40 0.59 0.97

LSP provides social activities 0.66 0.42 0.48 0.70 0.45 0.43

Geographic characteristics

Share of population non-White 

is higher than median

0.59 0.66 1.77 0.65 1.26 3.54*

Share of population Hispanic is 

higher than median

0.98 0.65 0.98 0.94 0.86 0.63

Share of housing units without 

access to a vehicle is higher 

than median

0.96 0.58 0.89 1.76 1.54 0.63

Share of families below 200% of 

poverty is higher than median

1.66 1.60 1.59 0.78 1.05 1.04

Has access to supermarket 1.48 7.74** 1.30 0.92 0.81 1.45

Urban 1.19 8.92 2.45* 1.42 0.54 0.62

Midwest 1.31 0.09* 0.81 0.49 0.41 0.68

Northeast 1.23 0.17 0.92 0.99 0.44 1.11

West 0.77 0.03*** 0.21** 0.35 0.28** 0.06*

Source: Administration on Aging (AoA) Nutrition Services Program outcomes survey, 2015–2016, weighted data; 

AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; HCC = hierarchical condition category. 

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander, and races not 

identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Chapter IV. Characteristics associated with adverse health events 

Mathematica 22

4. Home health episodes

Veteran status, having had a fall, hypertension, and age were associated with a higher likelihood of 

experiencing a home health episode (Exhibit IV.2). Veterans were nearly three times more likely than 

non-veterans to have a home health episode in the three years following the survey. The association was 

large and significant in Year 1, but not significant in Years 2 and 3 (Appendix B, Table B.5). Congregate 

meal participants who had a fall were more than five times more likely to have a home health episode in 

the three years following the survey. In each year following the survey, the association was significant 

and large (Appendix B, Table B.5). Participants with hypertension were more than twice as likely as those 

without hypertension to have a home health episode in the three-year period. The association was greater 

than 1 in all three individual years but significant only in Year 2. In addition, one-year increments in age 

were associated with a 7 percent increase in the likelihood of having a home health episode, a finding that 

was also significant and at least 7 percent in both Years 1 and 3. 

5. Skilled nursing facility admissions

Having lower income, living alone, and having had a fall were associated with higher odds of 

experiencing a skilled nursing facility admission (Exhibit IV.2). Participants with lower income were 

more than three times more likely than participants with higher income to be admitted to a skilled nursing 

facility over the three-year period. The association was significant in Year 2 but not significant in Years 1 

and 3 (Appendix B, Table B.6). Living alone was associated with nearly three times higher odds of 

experiencing a skilled nursing admission, an association that was large and significant in Year 1; in Years 

2 and 3, the odds ratios remained above 1 but were not significant. Participants who had fallen in the prior 

three months were more than twice as likely to have a skilled nursing facility admission in the three-year 

period. The effect was largest and significant in Year 1. 

In contrast, being non-Hispanic Black and living in the West were associated with lower odds of 

experiencing a skilled nursing facility admission (Exhibit IV.2). Non-Hispanic Black participants had 80 

percent lower odds of such an event compared with non-Hispanic White participants; the effect was 

significant in Years 1 and 2. Living in the West was associated with 72 percent lower odds of being 

admitted to a skilled nursing facility in the three-year period. The association was significant in Year 2 

(Appendix B, Table B.6).

6. Long-term care admissions

Several characteristics were associated with the likelihood of being admitted to a long-term care facility 

in the three years following the survey (Exhibit IV.2).13 Those who had a fall were nearly four times more 

likely to be admitted to a long-term care facility than those who had not had a fall. Lower income 

participants were almost four times more likely to have an admission to a long-term care facility than 

higher income participants. Participants who lived in communities with a higher percentage of non-White 

individuals (compared with the median across the nation) were more than three times more likely to have 

a long-term care admission. Age was also associated with a higher likelihood of admission to a long-term 

care facility, with each additional year of age being associated with a 12 percent increase in an admission. 

In contrast, participants who were female, married or with a partner, or living in the West were at least 80 

percent less likely than their counterparts to be admitted to a long-term care facility. 

13 Long-term care admissions were assessed only over the three-year period and not the three one-year periods.
Chapter IV. Characteristics associated with adverse health events 

Mathematica 23

C. Characteristics with limited time associations with adverse health events 

Some characteristics were associated with a higher or lower likelihood of experiencing the events in Year 

1, but these associations were not sustained in the subsequent two years. For example, congregate meal 

participants who lived alone were more than two times as likely to have any adverse event, more than 

three times as likely to have a hospitalization, nearly five times more likely to have a home health episode 

or an inpatient emergency department visit, and nearly 10 times more likely to have a skilled nursing 

facility admission in Year 1 (Appendix B, Tables B.1, B.2, B.4, B.5, and B.6). In each case, the higher 

association was not significant in Years 2 and 3. Hypertension followed a similar pattern for any adverse 

event, hospitalizations, and inpatient emergency department visits; participants with hypertension were 

more than twice as likely to have an adverse event, hospital admission, or emergency department visit 

leading to a hospital admission than those without hypertension in Year 1 but were less likely in Year 3. 

In contrast, participants whose service provider offered nutrition counseling were half as likely as those 

whose provider did not offer nutrition counseling in Year 1 to have any adverse event, but were more than 

three times as likely in Year 3. 
Mathematica 24

V. Conclusion

This chapter summarizes findings on the effects of congregate meal participation on participants’ health 

care utilization. It also presents recommendations for additional research motivated by these findings.

A. Effects on health care utilization

Although there were few statistically significant effects on health care utilization among congregate meal 

participants overall, there were large effects on utilization among lower-income participants. Participants 

were less likely than nonparticipants to have a hospital readmission within 30 days of discharge, with 

sizable differences in readmission rates two and three years after the survey. These effects were 

particularly pronounced among lower-income individuals, with hospital readmission rates of 2 percent for 

participants versus 13 percent for nonparticipants in Year 2 and 0.5 versus 13 percent in Year 3. 

Similarly, while there were no effects on the rate of admission to a long-term care facility for congregate 

meal participants overall, there was an effect among lower-income individuals: in this group of older 

adults, participants were less likely than nonparticipants to be admitted to a long-term care facility in Year 

2 (13 versus 22 percent). 

Among older adults who had an outpatient emergency department visit or an admission to a skilled 

nursing facility, participants had slightly more visits and admissions, on average, than nonparticipants in 

Year 1. However, participants who experienced adverse health events had fewer events in Years 2 and 3 

relative to nonparticipants. In Year 2, among individuals who had a home health episode, participants had 

fewer episodes than nonparticipants. In Year 3, participants had fewer hospital admissions than 

nonparticipants (among individuals with an admission) and had fewer skilled nursing facility admissions 

(among individuals with an admission). 

B. Characteristics associated with adverse health events

Several characteristics of congregate meal participants were associated with experiencing an adverse 

health event in the three years following the survey. The likelihood of experiencing an event was higher 

among veterans and those who had a recent fall and was lower among high school graduates, nonHispanic Black individuals, non-Hispanic individuals who reported a race other than White or Black, and 

participants who received meals from LSPs that offered health promotion activities. 

There were also several significant associations between participants’ characteristics and specific types of 

adverse health events during the three years following the survey, including the following: 

• A hospital admission was more than twice as likely among participants who had recently experienced 

a fall and was less likely among high school graduates and non-Hispanic individuals who reported a 

race other than White or Black. 

• A home health episode was more likely among individuals who were older, were veterans, had 

recently experienced a fall, or had hypertension. 

• An admission to a skilled nursing facility was more likely among participants who had lower income, 

those who lived alone, and those who recently had a fall. 

• Being admitted to a long-term care facility was more likely among individuals who were older, had 

recently experienced a fall, had lower income, or were living in a community with a high percentage 
Chapter V. Conclusion

Mathematica 25

of non-White individuals. It was less likely among those who were female, married or living with a 

partner, or non-Hispanic Black. 

Some characteristics were associated with a higher or lower likelihood of adverse health events in the first 

year following the survey, but these associations were not evident in the subsequent two years. 

Congregate meal participants who lived alone at the time of the interview were more than twice as likely 

to have any adverse event, more than three times more likely to have a hospitalization, and nearly five 

times more likely to have a home health episode in the first year following the survey, but there were 

generally no associations after the first year. Similarly, participants who had hypertension were more 

likely to experience any adverse event and to be admitted to a hospital in the first year, but there were 

generally no associations after that.

C. Discussion 

This report addressed the NSP evaluation’s research objectives to examine overall wellness measured 

using longer-term outcomes related to health and avoidance of institutionalization. Whereas Mabli et al. 

(2018) measured health care utilization outcomes within one year of when older adults were known to 

have received congregate meals, this report measured outcomes within three years of that date. Thus, this 

report extended the findings from a one-year assessment of the effect of receiving congregate meals on 

health care utilization to a three-year assessment. 

The descriptive findings showed that many NSP participants were in fair or poor health, had functional 

impairments that limited daily activities, and had multiple chronic conditions. These and other indicators 

of health and economic need described in this report underscore the vulnerability of the population of 

older adults the program serves. These vulnerabilities were reflected in higher health care needs and the 

extent to which participants experienced adverse health outcomes. For example, many NSP participants 

recently had an emergency department visit, home health episode, or hospital admission before the 

survey. 

The analysis examined the effect of NSP participation on overall health and well-being by comparing 

health care utilization outcomes for participants and nonparticipants. Relative to nonparticipants, 

congregate meal participants had a lower likelihood of being readmitted to a hospital within 30 days of 

discharge but similar likelihoods of experiencing other adverse health events. This finding might reflect 

the way in which the NSP serves as a primary access point for many home- and community-based 

services to help older adults meet their health and nutrition needs. These offerings may be more effective 

among individuals who have been hospitalized because many of these individuals require a variety of 

long-term in-home and community-based supports, such as homemaker and home-health aide services, 

transportation, physical activity and chronic disease self-management programs, home repair and 

modification, and falls prevention programs; these services may not be available to nonparticipants for 

extended periods of time after discharge. 

The lower rate of hospital readmission was particularly pronounced among lower income individuals in 

two of the three years following the survey. There are several possible explanations for stronger effects 

among lower-income older adults. First, although there is no means test for the NSP, the program targets 

older adults with the greatest need. It is possible that LSPs with limited resources and staff availability 

target the provision of services to older adults who need them most. If needs are greater among lowerincome older adults, these individuals may receive more assistance and support after discharge. Second, 

lower-income individuals are more likely than those with higher incomes to be eligible for non-NSP 
Chapter V. Conclusion

Mathematica 26

programs that can help provide stability after a discharge. All older adults in the lower-income group are 

income-eligible for the Supplemental Nutrition Assistance Program (SNAP), for example, but a much 

smaller percentage of those in the higher-income group are. Having access to SNAP and other support 

programs may free up discretionary income to pay for medications, transportation to medical 

appointments, and other basic needs. Third, lower-income individuals may be more closely connected to 

the network of food assistance and care providers from personal history or information sharing among 

peers needing similar services. Learning more about the services LSPs offer to older adults who were 

recently discharged from the hospital will help to identify effective strategies for continuing to reduce 

readmission rates among congregate meal participants. 

One of the main benefits of using a three-year period, as opposed to the one-year period used in the earlier 

report on health care utilization (Mabli et al. 2018), is the ability to examine longer-term effects of 

congregate meal participation on admissions to long-term care facilities. Mabli et al. (2018) found that 

participants were less likely than nonparticipants to have a nursing home admission during the year 

following the survey, and that the effect was especially large for low-income individuals. The analyses 

conducted for this report showed that these findings are sustained over a three-year period. Although 

more research is needed to understand the differences in program effectiveness by income, the lower rate 

of admission to a long-term care facility among lower-income participants compared with lower-income 

nonparticipants suggests that the program is achieving its goal of improving older adults’ ability to age in 

place and delay or avoid institutionalization, particularly among older adults who have the greatest 

economic need. 

Overall, the lower rates of hospital readmissions and nursing home admissions among congregate meal 

participants align with expectations of how the combination of receiving nutritious meals, social support 

from peers and program staff, and LSP services can affect health outcomes. These findings are consistent 

with findings from a previous analysis that found that congregate meal participants had better food 

security, socialization experiences, and diet quality than nonparticipants (Mabli et al. 2017). 

However, this report also found that nontrivial percentages of participants experienced adverse health 

events and were admitted to nursing homes. More research is needed to explore the mechanisms through 

which receiving congregate meals and supportive services leads to lower rates of hospital readmissions 

and nursing home admission but not to impacts on other adverse health events. Obtaining qualitative 

information from program participants and program staff would help identify the mechanisms and explore 

whether they differ by economic circumstances, care received by family members, medical histories, 

geography, length of meal program participation, or other key characteristics. 

The prevalence of adverse health effects among congregate meal participants, even those for which the 

program had a favorable effect, points to the need to examine the characteristics associated with 

congregate meal participants experiencing these events. This report was the first to explore these 

associations, including those with nursing home admissions, among a national sample of congregate meal 

participants. A consistent finding across several analyses in Chapter IV was the strong association 

between an older adult having a recent fall and experiencing an adverse health event such as a 

hospitalization, home health episode, or nursing home admission. Although much research has 

documented the prevalence of falls among older adults and their attendant detriment to health and wellbeing, the consistency and strength of these findings for the congregate meal participant population 

underscore the need to learn more about what the National Aging Network is doing to expand, enrich, and 

target its falls prevention programs at meal sites. 
Chapter V. Conclusion

Mathematica 27

Veterans are more likely than non-veterans to experience any adverse health event and, specifically, a 

home-health episode. Unfortunately, little is known about the relationship between being a veteran and 

experiencing these events. Veterans who use the Veterans Health Administration health care system are 

more likely to be a racial or ethnic minority, poor, or disabled and, thus, are more likely to experience 

adverse health events (Wang et al. 2015). The findings in this report suggest that even after accounting for 

these factors among congregate meal participants, veteran status remains strongly associated with longerterm health care utilization. More research is needed to understand the types of services available to 

veterans at congregate meal sites and whether veterans endure specific mental health issues that interfere 

with their ability to use NSP services to improve their health. 

The likelihood of experiencing an adverse health event was lower among participants who received meals 

from LSPs that offered health promotion activities, relative to those served by LSPs that did not offer 

these activities. More information is needed about the structure of these activities and the resources 

required to offer them across all meal sites. By collecting information from two key groups—LSPs, to 

learn more about the types of health promotion activities they offer, and participants, to learn more about 

which activities they have found to be most useful—the National Aging Network can identify the specific 

types of health promotion activities that are most effective in improving participants’ lives.
Mathematica 28

References

Administration for Community Living. “Aging Integrated Database.” Washington, DC: U.S. Department 

of Health and Human Services, Administration for Community Living, 2020. Profile of State OAA 

Programs: 50 States + DC & Territories, State Profiles. Available at

https://agid.acl.gov/CustomTables/. Accessed April 1, 2020. 

Aminzadeh, Faranak and William Burd Dalziel. “Older Adults in the Emergency Department: A Systemic 

Review of Patterns of Use, Adverse Outcomes, and Effectiveness of Interventions, Annals of 

Emergency Medicine, vol. 39, no. 3, 2005, pp. 978-998. 

Bergen, Gwen, Mark R. Stevens, and Elizabeth R. Burns. “Falls and Fall Injuries Among Adults Aged≥ 

65 Years—United States, 2014.” Morbidity and Mortality Weekly Report, vol. 65, no. 37, 2016, pp. 

993–998. Available at https://www.cdc.gov/mmwr/volumes/65/wr/mm6537a2.htm?s. 

Buttorff, Christine, Teague Ruder, and Melissa Bauman. “Multiple Chronic Conditions in the United 

States.” Santa Monica, CA: Rand, 2017. Available at https://sbgg.org.br/informativos/29-06-

17/1497877975_1_Chronic_Conditions.pdf. 

Economic Research Service, U.S. Department of Agriculture. “Food Access Research Atlas.” 2016. 

Available at http://www.ers.usda.gov/data-products/food-access-research-atlas.aspx. 

Feinberg, Lynn Friss, and Brenda C. Spillman. "Shifts in Family Caregiving—and a Growing Care 

Gap." Generations: Journal of the American Society on Aging, vol. 43, no. 1, 2019, pp. 73–77. 

Keehan, Sean P, Gigi A. Cuckler, John A. Poisal, Andrea M. Sisko, Sheila D. Smith, Andrew J. 

Madison, Kathryn E. Rennie, Jacqueline A. Fiore, and James C. Hardesty. “National Health 

Expenditures Projections, 2019-28: Expected Rebound in Prices Drives Rising Spending Growth.” 

Health Affairs, vol. 39, no. 4, 2020, pp. 704–714. 

Kelley, Amy S., Kathleen McGarry, Sean Fahle, Samuel M. Marshall, Qingling Du, and Jonathan S. 

Skinner. “Out-of-Pocket Spending in the Last Five Years of Life.” Journal of General Internal 

Medicine, vol. 28, 2013, pp. 304–309. doi:10.1007/s11606-012-2199-x. 

Mabli, James, Elizabeth Gearan, Rhoda Cohen, Katherine Niland, Nicholas Redel, Erin Panzarella, and 

Barbara Carlson. “Evaluation of the Effect of the Older Americans Act Title III-C Nutrition Services 

Program on Participants’ Food Security, Socialization, and Diet Quality.” Washington, DC: U.S. 

Department of Health and Human Services, Administration for Community Living, April 21, 2017. 

Available at https://www.mathematica-mpr.com/our-publications-andfindings/publications/evaluation-of-the-effect-of-the-older-americans-act-title-iii-c-nutrition-servicesprogram. Accessed January 23, 2018. 

Mabli, James, Arkadipta Ghosh, Bob Schmitz, Marisa Shenk, Erin Panzarella, Barbara Carlson, and Mark 

Flick. “Evaluation of the effect of the Older Americans Act Title III-C Nutrition Services Program on 

Participants’ Health Care Utilization.” Washington, DC: U.S. Department of Health and Human 

Services, Administration for Community Living, February 1, 2018. 
References 

Mathematica 29

Mabli, James, Nicholas Redel, Rhoda Cohen, Erin Panzarella, Mindy Hu, and Barbara Carlson. “Process 

Evaluation of Older Americans Act Title III-C Nutrition Services Program.” Washington, DC: U.S. 

Department of Health and Human Services, Administration for Community Living, September 30, 

2015. Available at https://www.mathematica-mpr.com/our-publications-andfindings/publications/process-evaluation-of-older-americans-act-title-iiic-nutrition-services-program. 

Accessed October 15, 2016. 

Murman, Daniel L. “The Impact of Age on Cognition.” Seminars in Hearing, vol. 36, no. 3, 2015, pp. 

111–121. Accessed via PubMed March 2, 2018. 

Ortman, Jennifer M., Victoria A. Velkoff, and Howard Hogan, “An Aging Nation: The Older Population 

in the United States.” Current Population Reports, No. P25-1140.” Washington, DC: U.S. Census 

Bureau, 2014.

Rama, Apoorva. “National Health Expenditures, 2017: The Slowdown in Spending Growth Continues.” 

Policy Research Perspectives. American Medical Association. April 2019. Available at

https://www.ama-assn.org/system/files/2019-04/prp-annual-spending-2017.pdf

Sözeri-Varma, Gülfizar. “Depression in the Elderly: Clinical Features and Risk Factors.” Aging and 

Disease. vol. 3, no. 6, 2012, pp. 465–471. 

United States Census Bureau. “2017 National Population Projections Tables: Main Series.” Table 2: 

Projected age and sex composition of the population. Available at

https://www.census.gov/data/tables/2017/demo/popproj/2017-summary-tables.html. 

van der Vorst, Anne, G.A. Rixt Zijlstra, Nico De Witte, Daan Duppen, Andreas E. Stuck, Gertrudis I.J.M. 

Kempen, and Jos M.G.A. Schols. “Limitations in Activities of Daily Living in Community-Dwelling 

People Aged 75 and Over: A Systematic Literature Review of Risk and Protective Factors.” PLoS 

ONE , vol. 11, no. 10, 2016. e0165127. Available at https://doi.org/10.1371/journal.pone.0165127.

Wang, Emily A., Kathleen A. McGinnis, Joseph Goulet, Kendall Bryant, Cynthia Gibert, David A. Leaf, 

et. al. “Food Insecurity and Health: Data from the Veterans Aging Cohort Study.” Public Health 

Reports, vol 130, no. 3, 2015, pp. 261–268. 

Ward, Brian W., Jeannine S. Schiller, and Richard A. Goodman. “Multiple Chronic Conditions Among 

US Adults: A 2012 Update.” Preventing Chronic Disease, vol. 11, Article 130389, 2014. Available at

http://dx.doi.org/10.5888/pcd11.130389 . 

Ziegler, Jessica, Nicholas Redel, Linda Rosenberg, and Barbara Carlson. “Older Americans Act Nutrition 

Programs Evaluation: Meal Cost Analysis.” Washington, DC: U.S. Department of Health and Human 

Services, Administration for Community Living, September 30, 2015. 
Appendix A

Chapter III supplementary tables
Appendix A 

Mathematica A-2 

Table A.1. Selected demographic and household characteristics of Nutrition Services Program 

participants at the time of the survey

Characteristic

All 

individuals

Individuals 

in higherincome 

households

Individuals 

in lowerincome 

households

Individuals 

who live 

alone

Individuals 

who live 

with other 

family 

members

Average age (years) 77.3 77.0 77.6 77.7 76.7

Female 66.9 56.4 77.4 68.6 64.4

Veteran 16.1 22.4 9.9 12.3 22.1

High school graduate, GED, or 

equivalent

75.8 87.8 63.8 78.3 72.0

Race/ethnicity

Non-Hispanic Black 13.6 12.1 15.1 14.2 12.6

Non-Hispanic othera 5.0 5.2 4.8 4.2 6.1

Non-Hispanic White 67.7 73.0 62.3 64.6 72.4

Hispanic 13.8 9.7 17.9 17.0 8.9

Marital status

Married or living with partner 23.8 31.9 15.7 0.7 59.2

Widowed 48.8 50.2 47.5 61.6 29.3

Divorced, separated, or never 

married 

27.3 17.8 36.9 37.7 11.4

Monthly income-to-poverty ratiob 162.1 237.7 86.4 166.8 155.0

Lives alone 60.4 60.6 60.1 100.0 0.0

Food insecure 16.5 13.0 20.1 21.3 9.2

LSP provides health promotion 

activities

52.2 51.6 52.7 46.8 60.4

LSP provides nutrition counseling 19.3 23.4 15.2 18.5 20.5

LSP provides nutrition screening 

and assessment

51.6 47.4 55.8 45.9 60.3

LSP provides social activities 62.0 59.8 64.2 59.7 65.6

Share of population non-White is 

higher than median

64.9 63.7 66.0 64.3 65.8

Share of population Hispanic is 

higher than median

61.1 58.1 64.1 62.3 59.2

Share of housing units without 

access to a vehicle is higher than 

median

56.8 48.2 65.3 63.4 46.6

Share of families below 200% of 

poverty is higher than median

50.3 42.0 58.7 55.3 42.7

Has access to supermarket 73.2 78.3 68.0 77.1 67.2

Urban 72.3 71.8 72.8 75.7 67.2

Midwest 23.1 26.1 20.1 21.1 26.2

Northeast 25.8 31.6 19.9 29.6 19.9

West 29.4 27.6 31.2 34.4 21.8

South 21.7 14.7 28.7 14.9 32.1

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data.

Note: All units are percentages, unless otherwise noted. 

Tabulations restricted to survey respondents who had valid matches to Medicare administrative records 

and were not participating in Medicare Advantage for the full year. 

Tabulations are based on unweighted sample sizes of 316 congregate meal participants. Individual 

estimates within the table may have slightly fewer observations due to item nonresponse to individual 

questions.

LSP = local service provider.

a “Other” includes Asian, American Indian, or Alaska native; Native Hawaiian or other Pacific Islander; and races not 

identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Appendix A 

Mathematica A-3 

Table A.2. Selected health characteristics of Nutrition Services Program participants at or before 

the time of the survey

Characteristic

All 

individuals

Individuals in 

higherincome 

households

Individuals in 

lowerincome 

households

Individuals 

who live 

alone

Individuals 

who live with 

other family 

members

General health

Excellent, very good, or 

good

78.7 81.7 75.7 78.7 78.8

Fair or poor 21.3 18.3 24.3 21.3 21.2

Number of prescription 

medications taken every day

0 10.3 8.5 12.0 11.8 7.9

1 or 2 21.5 15.0 28.2 24.7 16.8

3 or more 68.2 76.5 59.7 63.5 75.3

Number of falls in the past 

three months

0 76.8 75.7 78.0 75.2 79.3

1 or more 23.2 24.3 22.0 24.8 20.7

Number of falls in the past 

three months that caused an 

injury

0 83.0 75.4 91.4 80.4 87.8

1 or more 17.0 24.6 8.6 19.6 12.2

Mobility

Able to walk 99.5 99.0 100.0 99.5 99.6

Able to walk but has 

difficulty walking or 

climbing stairs

37.9 41.1 34.8 39.8 35.1

Mean HCC Score 0.8 0.8 0.8 0.8 0.8

Dual enrollment status 29.8 7.3 52.3 35.6 20.8

Chronic conditions

0 26.4 26.5 26.3 25.5 27.8

1 or more 73.6 73.5 73.7 74.5 72.2

Mean number of chronic 

conditions

1.7 1.5 1.8 1.7 1.6

Source: Medicare claims and enrollment data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: All units are percentages, unless otherwise noted. Tabulations restricted to survey respondents that had 

valid matches to Medicare administrative records and were not participating in Medicare Advantage for the 

full year. 

Incidence of chronic conditions measured at the end of 2014 before the 2015–2016 survey was conducted. 

Tabulations are based on unweighted sample sizes of 316 congregate meal participants. Individual 

estimates within the table may have slightly fewer observations due to item nonresponse to individual 

questions.

HCC = hierarchical conditional category score.
Appendix A 

Mathematica A-4 

Table A.3. Health care utilization among Nutrition Services Program participants in the nine 

months before the survey

All 

individuals

Individuals 

in higherincome 

households

Individuals 

in lowerincome 

households

Individuals 

who live 

alone

Individuals 

who live 

with other 

family 

members

Experienced the event (%) 

Hospital admission 7.9 7.9 8.0 6.6 9.9

30-day hospital readmission 1.2 0.2 2.2 0.2 2.7

Emergency department visit leading 

to a hospital admission

5.3 6.4 4.1 5.1 5.6

Outpatient emergency department 

visit

28.5 24.1 32.9 32.5 22.5

Primary care physician visit in any 

setting

76.0 76.1 75.8 75.1 77.3

Home health episode 6.3 5.9 6.7 6.0 6.7

Nursing home admission 1.5 1.4 1.6 1.4 1.7

Skilled nursing facility admission 2.0 2.3 1.8 2.1 1.9

Number of times the event occurred 

among those that experienced the 

event

Hospital admission 1.7 1.8 1.7 1.7 1.7

Emergency department visit leading 

to a hospital admission

1.9 1.8 2.0 1.7 2.1

Outpatient emergency department 

visit

2.1 2.3 2.0 2.1 2.1

Primary care physician visit in any 

setting

6.8 6.5 7.1 7.3 6.1

Home health episode 1.7 1.4 2.0 1.7 1.7

Skilled nursing facility admission 1.6 1.3 1.9 1.3 2.0

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data.

Note: Utilization was measured in the nine months preceding the survey for each participant.

Tabulations are based on unweighted sample sizes of 316 congregate meal participants. 
Appendix A 

Mathematica A-5 

Table A.4. Monthly Medicare expenditures among Nutrition Services Program participants

All 

individuals

Individuals 

in higherincome 

households

Individuals 

in lowerincome 

households

Individuals 

who live 

alone

Individuals 

who live 

with other 

family 

members

Total Medicare expenditures 

Percentage of participants with 

non-zero expenditures 

91.4 90.8 92.0 90.3 93.1

Average among those with 

non-zero expenditures 

$690 $641 $739 $727 $637

Average among all participants $631 $582 $680 $657 $593

Inpatient

Percentage of participants with 

non-zero expenditures 

8.0 8.0 8.0 6.9 9.5

Average among those with 

non-zero expenditures 

$2,314 $2,531 $2,097 $2,345 $2,280

Average among all participants $184 $202 $167 $163 $217

Outpatient

Percentage of participants with 

non-zero expenditures 

72.0 70.4 73.6 72.8 70.7

Average among those with 

non-zero expenditures 

$287 $233 $340 $340 $206

Average among all participants $207 $164 $250 $247 $145

Skilled nursing facility

Percentage of participants with 

non-zero expenditures 

2.0 2.3 1.8 2.1 1.9

Average among those with 

non-zero expenditures 

$1,129 $940 $1,367 $1,073 $1,223

Average among all participants $23 $21 $24 $22 $23

Home health

Percentage of participants with 

non-zero expenditures 

6.3 5.9 6.7 6.0 6.7

Average among those with 

non-zero expenditures 

$340 $295 $379 $313 $377

Average among all participants $21 $17 $25 $19 $25

Physician services

Percentage of participants with 

non-zero expenditures 

91.1 90.5 91.7 90.2 92.4

Average among those with 

non-zero expenditures 

$215 $197 $233 $228 $197

Average among all participants $196 $178 $214 $205 $182

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Expenditures were measured in the nine months preceding the survey for each participant. 

Tabulations are based on unweighted sample sizes of 316 congregate meal participants. 
Appendix A 

Mathematica A-6 

Table A.5. Regression-adjusted percentages of congregate meal participants and nonparticipants 

who experienced health events in Years 1, 2, and 3 following the survey 

 Participants Nonparticipants Difference

Outcome Percentage

Standard 

error Percentage

Standard 

error Percentage

Standard 

error

Hospital admission

Year 1 25.1 (2.9) 22.6 (2.9) 2.5 (3.8)

Year 2 23.2 (2.4) 22.9 (3.7) 0.2 (4.5)

Year 3 29.9 (3.3) 26.2 (3.6) 3.7 (4.9)

30-day hospital readmission

Year 1 3.0 (0.9) 3.6 (1.0) -0.7 (1.4)

Year 2 1.3 (0.8) 5.5 (1.5) -4.1** (1.8)

Year 3 2.4 (0.9) 8.3 (1.8) -5.9*** (2.1)

Emergency department visit 

leading to a hospital 

admission

Year 1 14.9 (2.0) 18.2 (2.7) -3.3 (2.8)

Year 2 15.8 (1.9) 16.2 (3.2) -0.4 (3.9)

Year 3 20.7 (2.7) 20.0 (3.7) 0.7 (4.4)

Outpatient emergency 

department visit

Year 1 34.0 (3.1) 32.5 (3.0) 1.4 (4.3)

Year 2 34.1 (3.0) 32.8 (3.6) 1.3 (4.8)

Year 3 38.9 (3.5) 36.2 (4.4) 2.8 (5.4)

Primary care physician visit in 

any setting

Year 1 85.8 (2.5) 80.8 (2.6) 5.1 (3.5)

Year 2 82.2 (2.3) 81.7 (2.6) 0.6 (3.2)

Year 3 81.9 (3.1) 85.7 (2.5) -3.8 (3.9)

Home health episode

Year 1 13.5 (1.7) 12.5 (1.9) 1.0 (3.1)

Year 2 14.3 (2.2) 19.4 (3.0) -5.1 (3.6)

Year 3 15.4 (2.2) 15.6 (3.0) -0.1 (4.3)

Skilled nursing facility 

admission

Year 1 8.7 (1.8) 8.3 (1.9) 0.4 (2.9)

Year 2 14.4 (2.4) 10.2 (2.0) 4.2 (3.3)

Year 3 10.2 (1.7) 8.4 (1.7) 1.8 (2.2)

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test.
Appendix A 

Mathematica A-7 

Table A.6. Regression-adjusted percentages of congregate meal participants and nonparticipants 

who experienced nursing home admissions in the three-year period following the survey

 Participants Nonparticipants Difference

Outcome Percentage

Standard 

error Percentage

Standard 

error Percentage

Standard 

error

All individuals 11.7 (1.6) 13.8 (2.0) -2.0 (2.9)

Individuals in 

higher-income 

households 10.4 (2.0) 9.6 (2.0) 0.9 (3.3)

Individuals in 

lower-income 

households 13.0 (2.0) 21.8 (3.6) -8.7* (4.4)

Individuals who 

live alone 15.1 (2.4) 18.2 (3.2) -3.0 (4.2)

Individuals who 

live with other 

family members 7.5 (1.9) 9.3 (2.2) -1.8 (3.2)

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test.
Appendix A 

Mathematica A-8 

Table A.7. Regression-adjusted percentages of individuals who experienced health events in 

Years 1, 2, and 3 following the survey, by congregate meal participation status and household 

income

Individuals in lower-income 

households

Individuals in higher-income 

households

Outcome Participants

Nonparticipants Difference ParticipantsNonparticipants Difference

Hospital admission

Year 1 23.6 25.2 -1.7 26.0 20.9 5.1

Year 2 29.7 24.2 5.5 18.4 19.9 -1.5

Year 3 23.9 32.5 -8.7 36.5 19.2 17.3***

30-day hospital readmission

Year 1 3.4 1.9 1.5 4.2 4.7 -0.6

Year 2 2.0 13.4 -11.4** 0.0 2.4 -2.4**

Year 3 0.5 12.6 -12.1** 3.2 4.5 -1.3

Emergency department visit 

leading to a hospital 

admission

Year 1 13.7 23.5 -9.8* 17.1 13.4 3.7

Year 2 20.5 18.1 2.5 12.7 12.8 -0.1

Year 3 20.1 26.6 -6.5 22.6 13.7 8.9

Outpatient emergency 

department visit

Year 1 43.2 35.3 7.9 29.6 29.8 -0.2

Year 2 32.3 37.3 -5.0 36.8 28.6 8.2

Year 3 43.8 42.3 1.5 36.3 29.2 7.0

Primary care physician visit in 

any setting

Year 1 89.2 80.7 8.5 82.4 81.2 1.2

Year 2 82.9 81.6 1.3 82.4 80.8 1.6

Year 3 81.7 86.3 -4.6 82.7 83.2 -0.5

Home health episode

Year 1 16.5 16.3 0.2 10.5 9.6 0.9

Year 2 16.5 23.6 -7.1 12.8 15.0 -2.3

Year 3 13.7 22.1 -8.4 17.3 10.2 7.1

Skilled nursing facility 

admission

Year 1 9.4 9.4 0.0 13.4 8.0 5.4

Year 2 22.5 12.9 9.6* 11.3 8.0 3.3

Year 3 14.9 12.6 2.3 7.1 4.6 2.5

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test. 
Appendix A 

Mathematica A-9 

Table A.8. Regression-adjusted percentages of individuals who experienced health events in 

Years 1, 2, and 3 following the survey, by congregate meal participation status and living 

arrangement

Individuals who live alone

Individuals who live with other 

family members

Outcome Participants

Nonparticipants Difference ParticipantsNonparticipants Difference

Hospital admission

Year 1 28.2 27.3 0.9 21.8 18.6 3.1

Year 2 25.0 25.0 0.0 20.9 21.2 -0.4

Year 3 30.8 28.8 2.1 30.5 21.3 9.2

30-day hospital readmission

Year 1 5.4 6.7 -1.3 1.1 4.2 -3.1

Year 2 2.2 4.6 -2.5 0.0 5.5 -5.6***

Year 3 1.6 8.3 -6.7* 4.9 5.3 -0.4

Emergency department visit 

leading to a hospital 

admission

Year 1 18.9 25.2 -6.3 12.8 10.8 2.0

Year 2 16.6 22.1 -5.5 15.2 10.5 4.7

Year 3 23.9 22.6 1.3 19.4 15.8 3.6

Outpatient emergency 

department visit

Year 1 36.5 34.9 1.6 33.7 30.4 3.3

Year 2 36.6 30.6 5.9 33.2 34.2 -1.1

Year 3 41.0 39.9 1.1 37.2 30.4 6.7

Primary care physician visit in 

any setting

Year 1 85.1 80.0 5.1 87.0 80.7 6.4

Year 2 83.0 81.2 1.7 80.9 81.8 -0.9

Year 3 79.6 85.9 -6.3 83.7 86.0 -2.3

Home health episode

Year 1 15.7 13.0 2.7 10.1 12.4 -2.3

Year 2 13.6 20.9 -7.2 14.8 19.0 -4.2

Year 3 15.2 15.3 0.0 18.8 14.0 4.7

Skilled nursing facility 

admission

Year 1 13.3 11.0 2.3 5.5 3.7 1.8

Year 2 18.6 12.5 6.1 9.2 8.5 0.7

Year 3 12.8 8.8 3.9 7.9 8.0 -0.1

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test.
Appendix A 

Mathematica A-10

Table A.9. Regression-adjusted numbers of events experienced by congregate meal participants 

and nonparticipants who experienced health events in Years 1, 2, and 3 following the survey

 Participants Nonparticipants Difference

Outcome Number

Standard 

error Number

Standard 

error Number

Standard 

error

Hospital admission

Year 1 1.4 (0.1) 1.7 (0.1) -0.3 (0.2)

Year 2 1.8 (0.1) 1.9 (0.2) -0.1 (0.3)

Year 3 1.5 (0.1) 2.0 (0.2) -0.5** (0.2)

Emergency department visit 

leading to a hospital 

admission

Year 1 1.4 (0.1) 1.5 (0.1) -0.1 (0.1)

Year 2 1.8 (0.2) 1.8 (0.3) 0.0 (0.3)

Year 3 1.5 (0.1) 2.1 (0.3) -0.6 (0.3)

Outpatient emergency 

department visit

Year 1 2.7 (0.2) 1.9 (0.2) 0.8** (0.3)

Year 2 2.7 (0.3) 1.7 (0.4) 1.0 (0.7)

Year 3 2.2 (0.3) 1.9 (0.2) 0.3 (0.4)

Primary care physician visit in 

any setting

Year 1 6.8 (0.3) 7.0 (0.6) -0.2 (0.7)

Year 2 8.9 (0.7) 7.4 (0.6) 1.5 (0.9)

Year 3 8.5 (0.7) 8.0 (0.7) 0.5 (0.9)

Home health episode

Year 1 1.6 (0.1) 1.9 (0.2) -0.3 (0.3)

Year 2 1.7 (0.1) 2.1 (0.1) -0.4* (0.2)

Year 3 1.8 (0.2) 2.0 (0.2) -0.3 (0.3)

Skilled nursing facility 

admission

Year 1 1.6 (0.1) 1.1 (0.1) 0.4* (0.2)

Year 2 1.8 (0.1) 2.1 (0.3) -0.4 (0.3)

Year 3 1.0 (0.1) 2.1 (0.2) -1.2*** (0.3)

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test.
Appendix A 

Mathematica A-11

Table A.10. Regression-adjusted average total Medicare spending of congregate meal participants 

and nonparticipants in the three years following the survey

 Participants Nonparticipants Difference

Outcome Dollars

Standard 

error Dollars

Standard 

error Dollars

Standard 

error

Average total Medicare 

expenditures a ($) 

Year 1 999 (142) 1,008 (145) -9 (215)

Year 2 1,363 (190) 994 (149) 369 (247)

Year 3 1,304 (260) 1,289 (220) 14 (273)

Source: Medicare claims data matched to AoA NSP outcomes survey, 2015–2016, weighted data. 

Note: Estimates are based on an unweighted sample size of 683 congregate meal participants and 

nonparticipants.

***/**/* Significantly different from zero at the 0.01/0.05/0.10 level, two-tailed test. 

a Total expenditures exclude expenditures for durable medical equipment and hospice care.
Appendix B

Chapter IV supplementary tables
Appendix B 

Mathematica B-2 

Table B.1. Odds ratios of participants experiencing any adverse health event in the three-year period following the survey

Baseline characteristic

Year 1

OR (95% CI)

Year 2

OR (95% CI)

Year 3

OR (95% CI)

Years 1 to 3 

OR (95% CI)

Age 1.06* (1.00 - 1.12) 1.02 (0.95 - 1.08) 1.03 (0.97 - 1.10) 1.01 (0.94 - 1.09)

Female 1.46 (0.47 - 4.58) 1.07 (0.42 - 2.71) 0.57 (0.21 - 1.55) 1.31 (0.49 - 3.48)

Completed high school 0.24** (0.08 - 0.70) 0.71 (0.27 - 1.86) 0.76 (0.33 - 1.75) 0.40* (0.16 - 1.03)

Married or living with partner 1.56 (0.54 - 4.53) 0.89 (0.25 - 3.17) 0.45 (0.06 - 3.21) 0.90 (0.25 - 3.24)

Veteran 1.42 (0.49 - 4.13) 1.62 (0.42 - 6.28) 1.03 (0.30 - 3.50) 2.10* (0.87 - 5.09)

Non-Hispanic Black 0.29* (0.08 - 1.01) 0.55 (0.16 - 1.91) 0.75 (0.20 - 2.87) 0.42* (0.15 - 1.15)

Non-Hispanic othera 0.02*** (0.00 - 0.23) 0.41 (0.08 - 2.05) 0.13* (0.01 - 1.36) 0.15** (0.03 - 0.79)

Hispanic 0.26 (0.05 - 1.43) 0.43 (0.09 - 2.12) 2.74 (0.32 - 23.71) 0.70 (0.17 - 2.88)

Monthly income-to-poverty lower than medianb 1.00 (0.53 - 1.90) 2.45** (1.16 - 5.18) 0.71 (0.31 - 1.63) 1.35 (0.69 - 2.65)

Food insecure 0.52 (0.15 - 1.79) 0.59 (0.22 - 1.59) 1.14 (0.40 - 3.31) 0.76 (0.27 - 2.14)

Living alone 2.40* (0.89 - 6.48) 1.35 (0.47 - 3.84) 0.41 (0.09 - 1.83) 0.79 (0.24 - 2.57)

HCC score 0.76 (0.38 - 1.53) 1.49 (0.51 - 4.31) 1.54 (0.52 - 4.55) 1.74 (0.77 - 3.93)

High blood pressure/hypertension or diabetes 2.07* (0.94 - 4.57) 1.26 (0.58 - 2.73) 0.40** (0.20 - 0.82) 0.80 (0.43 - 1.46)

Any falls in past three months 5.19*** (2.14 - 12.59) 2.63** (1.11 - 6.24) 2.41 (0.83 - 7.05) 2.35** (1.04 - 5.32)

LSP provides health promotion activities 0.88 (0.28 - 2.73) 0.65 (0.23 - 1.88) 0.40** (0.19 - 0.85) 0.43* (0.17 - 1.10)

LSP provides nutrition counseling 0.45* (0.19 - 1.08) 1.08 (0.49 - 2.41) 3.18** (1.08 - 9.36) 0.79 (0.38 - 1.65)

LSP provides nutrition screening and assessment 1.61 (0.59 - 4.42) 1.34 (0.67 - 2.69) 0.83 (0.28 - 2.50) 1.88 (0.85 - 4.15)

LSP provides social activities 0.57 (0.21 - 1.53) 0.85 (0.35 - 2.06) 0.61 (0.21 - 1.76) 0.82 (0.33 - 2.05)

Share of population non-White is higher than median 0.75 (0.24 - 2.37) 1.11 (0.42 - 2.98) 1.28 (0.52 - 3.15) 0.56 (0.23 - 1.37)

Share of population Hispanic is higher than median 0.98 (0.38 - 2.56) 0.79 (0.27 - 2.35) 0.63 (0.25 - 1.58) 1.21 (0.51 - 2.86)

Share of housing units without access to a vehicle is higher 

than median 0.89 (0.42 - 1.87) 2.54* (0.92 - 7.00) 0.62 (0.22 - 1.71) 1.07 (0.49 - 2.33)

Share of families below 200% of poverty is higher than median 0.67 (0.26 - 1.75) 0.59 (0.21 - 1.70) 2.98 (0.78 - 11.37) 1.64 (0.68 - 3.93)

Has access to supermarket 2.37* (0.85 - 6.64) 0.83 (0.33 - 2.07) 0.76 (0.27 - 2.14) 1.00 (0.39 - 2.56)

Urban 3.60** (1.06 - 12.18) 0.89 (0.35 - 2.27) 0.74 (0.24 - 2.29) 0.99 (0.42 - 2.33)

Midwest 0.43 (0.11 - 1.66) 0.55 (0.18 - 1.68) 1.93 (0.68 - 5.48) 1.44 (0.54 - 3.89)

Northeast 0.32 (0.08 - 1.28) 1.21 (0.34 - 4.31) 4.01** (1.09 - 14.75) 2.06 (0.64 - 6.69)

West 1.02 (0.23 - 4.54) 0.42 (0.11 - 1.62) 0.38 (0.11 - 1.35) 0.95 (0.34 - 2.65)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Appendix B 

Mathematica B-3 

Table B.2. Odds ratios of participants experiencing a hospital admission in the three-year period following the survey

Baseline characteristic

Year 1

OR (95% CI)

Year 2

OR (95% CI)

Year 3

OR (95% CI)

Years 1 to 3 

OR (95% CI)

Age 1.03 (0.98 - 1.09) 1.00 (0.94 - 1.06) 1.02 (0.96 - 1.08) 1.01 (0.95 - 1.08)

Female 1.52 (0.42 - 5.47) 1.09 (0.40 - 2.98) 0.66 (0.25 - 1.76) 1.17 (0.41 - 3.30)

Completed high school 0.28** (0.10 - 0.75) 1.11 (0.46 - 2.69) 0.96 (0.41 - 2.22) 0.38** (0.15 - 0.98)

Married or living with partner 2.67 (0.81 - 8.82) 1.19 (0.33 - 4.38) 0.68 (0.09 - 5.25) 1.57 (0.46 - 5.41)

Veteran 1.16 (0.33 - 4.16) 1.28 (0.31 - 5.29) 1.01 (0.28 - 3.65) 1.52 (0.63 - 3.66)

Non-Hispanic Black 0.35 (0.08 - 1.41) 0.82 (0.26 - 2.55) 0.48 (0.11 - 2.02) 0.43 (0.15 - 1.19)

Non-Hispanic othera 0.02*** (0.00 - 0.24) 0.40 (0.07 - 2.38) 0.07* (0.00 - 1.16) 0.15** (0.03 - 0.87)

Hispanic 0.42 (0.08 - 2.22) 0.72 (0.16 - 3.24) 3.79 (0.52 - 27.68) 0.80 (0.19 - 3.37)

Monthly income-to-poverty lower than medianb 0.79 (0.41 - 1.51) 2.62** (1.26 - 5.45) 0.75 (0.35 - 1.62) 1.35 (0.67 - 2.69)

Food insecure 0.45 (0.11 - 1.92) 0.20** (0.05 - 0.70) 0.78 (0.25 - 2.44) 0.57 (0.21 - 1.50)

Living alone 3.60** (1.24 - 10.40) 1.61 (0.58 - 4.48) 0.58 (0.13 - 2.58) 1.38 (0.46 - 4.13)

HCC score 0.79 (0.38 - 1.64) 1.91 (0.60 - 6.13) 1.45 (0.50 - 4.21) 1.62 (0.77 - 3.38)

High blood pressure/hypertension or diabetes 2.32** (1.03 - 5.22) 0.85 (0.35 - 2.03) 0.41** (0.19 - 0.88) 0.68 (0.37 - 1.25)

Any falls in past three months 3.70*** (1.55 - 8.83) 2.50** (1.19 - 5.26) 2.37 (0.81 - 6.96) 2.24* (0.97 - 5.17)

LSP provides health promotion activities 0.84 (0.26 - 2.75) 0.69 (0.27 - 1.77) 0.45** (0.21 - 0.95) 0.51 (0.21 - 1.25)

LSP provides nutrition counseling 0.55 (0.23 - 1.30) 1.52 (0.68 - 3.41) 3.04* (1.00 - 9.27) 0.94 (0.46 - 1.93)

LSP provides nutrition screening and assessment 1.35 (0.47 - 3.86) 0.96 (0.51 - 1.82) 0.77 (0.25 - 2.38) 1.70 (0.76 - 3.81)

LSP provides social activities 0.51 (0.17 - 1.55) 0.66 (0.27 - 1.62) 0.56 (0.19 - 1.69) 0.66 (0.25 - 1.70)

Share of population non-White is higher than median 0.68 (0.21 - 2.19) 1.32 (0.52 - 3.35) 1.37 (0.58 - 3.26) 0.59 (0.25 - 1.42)

Share of population Hispanic is higher than median 0.75 (0.29 - 1.95) 0.97 (0.31 - 2.97) 0.59 (0.23 - 1.52) 0.98 (0.41 - 2.34)

Share of housing units without access to a vehicle is higher 

than median 1.07 (0.46 - 2.48) 1.99 (0.75 - 5.31) 0.62 (0.22 - 1.74) 0.96 (0.42 - 2.21)

Share of families below 200% of poverty is higher than median 0.87 (0.29 - 2.61) 0.59 (0.22 - 1.62) 3.32* (0.90 - 12.18) 1.66 (0.71 - 3.90)

Has access to supermarket 3.82** (1.20 - 12.10) 0.76 (0.33 - 1.73) 0.77 (0.27 - 2.26) 1.48 (0.59 - 3.72)

Urban 3.23* (0.87 - 11.93) 0.73 (0.29 - 1.88) 1.02 (0.31 - 3.43) 1.19 (0.52 - 2.73)

Midwest 0.53 (0.14 - 2.08) 0.49 (0.17 - 1.40) 2.29 (0.82 - 6.39) 1.31 (0.45 - 3.76)

Northeast 0.30 (0.07 - 1.33) 0.94 (0.28 - 3.11) 5.01** (1.35 - 18.60) 1.23 (0.39 - 3.94)

West 1.10 (0.25 - 4.84) 0.46 (0.15 - 1.42) 0.42 (0.11 - 1.56) 0.77 (0.27 - 2.19)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines).
Appendix B 

Mathematica B-4 

Table B.3. Odds ratios of participants experiencing a 30-day hospital readmission in the three-year 

period following the survey

Baseline characteristic

Years 1 to 3 

OR (95% CI)

Age 1.06 (0.95 - 1.17)

Female 0.97 (0.23 - 4.16)

Completed high school 1.59 (0.11 - 23.59)

Married or living with partner 1.53 (0.01 - 394.30)

Veteran 0.78 (0.08 - 7.85)

Non-Hispanic Black 0.10 (0.00 - 4.02)

Non-Hispanic othera 

Hispanic 6.77*** (1.68 - 27.20)

Monthly income-to-poverty lower than medianb 0.34 (0.09 - 1.31)

Food insecure 0.30 (0.03 - 2.65)

Living alone 2.84 (0.06 - 135.41)

HCC score 0.22 (0.03 - 1.37)

High blood pressure/hypertension or diabetes 1.55 (0.22 - 10.97)

Any falls in past three months 5.20*** (1.78 - 15.23)

LSP provides health promotion activities 0.35 (0.07 - 1.82)

LSP provides nutrition counseling 5.91*** (2.20 - 15.90)

LSP provides nutrition screening and assessment 0.32** (0.12 - 0.87)

LSP provides social activities 0.42 (0.07 - 2.56)

Share of population non-White is higher than median 0.66 (0.15 - 2.83)

Share of population Hispanic is higher than median 0.65 (0.07 - 6.05)

Share of housing units without access to a vehicle is higher than median 0.58 (0.08 - 4.09)

Share of families below 200% of poverty is higher than median 1.60 (0.44 - 5.81)

Has access to supermarket 7.74** (1.09 - 55.23)

Urban 8.92 (0.60 - 133.71)

Midwest 0.09* (0.01 - 1.42)

Northeast 0.17 (0.01 - 2.15)

West 0.03*** (0.00 - 0.22)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data

matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not 

identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Appendix B 

Mathematica B-5 

Table B.4. Odds ratios of participants experiencing an emergency department visit leading to a hospital admission in the three-year 

period following the survey

Baseline characteristic

Year 1

OR (95% CI)

Year 2

OR (95% CI)

Year 3

OR (95% CI)

Years 1 to 3 

OR (95% CI)

Age 1.02 (0.95 - 1.09) 0.99 (0.92 - 1.06) 1.02 (0.97 - 1.08) 1.02 (0.96 - 1.08)

Female 0.93 (0.24 - 3.53) 0.96 (0.34 - 2.77) 1.09 (0.41 - 2.88) 1.46 (0.56 - 3.78)

Completed high school 0.43 (0.16 - 1.19) 1.16 (0.40 - 3.39) 0.84 (0.32 - 2.20) 0.57 (0.22 - 1.53)

Married or living with partner 1.83 (0.34 - 9.82) 1.82 (0.48 - 6.91) 0.61 (0.07 - 5.32) 1.46 (0.36 - 5.95)

Veteran 1.57 (0.31 - 7.97) 0.51 (0.13 - 2.06) 2.53 (0.61 - 10.48) 1.34 (0.55 - 3.26)

Non-Hispanic Black 0.60 (0.18 - 1.98) 0.78 (0.20 - 3.03) 0.49 (0.10 - 2.39) 0.60 (0.21 - 1.76)

Non-Hispanic othera 0.51 (0.06 - 4.54) 0.05** (0.00 - 0.75) 0.18* (0.03 - 1.27)

Hispanic 2.35 (0.54 - 10.25) 3.82* (0.78 - 18.65) 4.18 (0.59 - 29.66) 2.49 (0.55 - 11.32)

Monthly income-to-poverty lower than medianb 0.96 (0.44 - 2.09) 2.61* (0.98 - 6.93) 1.51 (0.58 - 3.94) 1.31 (0.62 - 2.76)

Food insecure 0.45 (0.09 - 2.24) 0.22** (0.06 - 0.79) 1.13 (0.28 - 4.62) 0.88 (0.28 - 2.74)

Living alone 4.74** (1.19 - 18.91) 1.23 (0.44 - 3.45) 0.61 (0.15 - 2.49) 1.45 (0.53 - 3.94)

HCC score 0.61 (0.21 - 1.79) 2.02 (0.54 - 7.48) 1.23 (0.35 - 4.38) 1.15 (0.45 - 2.90)

High blood pressure/hypertension or diabetes 2.33* (0.88 - 6.17) 1.55 (0.57 - 4.20) 0.96 (0.34 - 2.66) 0.91 (0.45 - 1.87)

Any falls in past three months 3.12* (0.90 - 10.87) 5.92*** (2.65 - 13.19) 1.71 (0.60 - 4.90) 1.78 (0.75 - 4.22)

LSP provides health promotion activities 1.67 (0.53 - 5.19) 0.51 (0.15 - 1.69) 0.33** (0.12 - 0.91) 0.70 (0.24 - 2.04)

LSP provides nutrition counseling 0.60 (0.27 - 1.33) 1.15 (0.40 - 3.34) 5.59*** (1.91 - 16.38) 1.48 (0.69 - 3.15)

LSP provides nutrition screening and assessment 0.22*** (0.08 - 0.63) 0.88 (0.36 - 2.13) 0.56 (0.16 - 1.92) 0.73 (0.31 - 1.71)

LSP provides social activities 0.42 (0.12 - 1.45) 0.72 (0.21 - 2.44) 0.75 (0.17 - 3.32) 0.48 (0.15 - 1.56)

Share of population non-White is higher than median 3.23** (1.05 - 9.92) 0.61 (0.21 - 1.82) 2.88* (0.83 - 9.94) 1.77 (0.57 - 5.53)

Share of population Hispanic is higher than median 0.39 (0.13 - 1.23) 1.60 (0.45 - 5.71) 0.57 (0.20 - 1.63) 0.98 (0.31 - 3.07)

Share of housing units without access to a vehicle is higher 

than median 1.30 (0.41 - 4.14) 1.35 (0.39 - 4.68) 0.54 (0.15 - 1.96) 0.89 (0.31 - 2.61)

Share of families below 200% of poverty is higher than median 1.79 (0.44 - 7.31) 1.67 (0.40 - 6.99) 2.62 (0.70 - 9.77) 1.59 (0.52 - 4.88)

Has access to supermarket 1.93 (0.67 - 5.55) 1.21 (0.55 - 2.69) 0.66 (0.18 - 2.41) 1.30 (0.50 - 3.39)

Urban 4.53** (1.15 - 17.88) 3.16* (0.99 - 10.09) 1.59 (0.29 - 8.80) 2.45* (0.94 - 6.38)

Midwest 0.54 (0.16 - 1.88) 0.22** (0.06 - 0.78) 1.49 (0.41 - 5.42) 0.81 (0.25 - 2.59)

Northeast 0.12*** (0.03 - 0.59) 0.80 (0.23 - 2.82) 8.47*** (1.82 - 39.48) 0.92 (0.24 - 3.46)

West 0.08*** (0.01 - 0.49) 0.06*** (0.01 - 0.27) 0.60 (0.11 - 3.19) 0.21** (0.05 - 0.80)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/*Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test. 

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Appendix B 

Mathematica B-6 

Table B.5. Odds ratios of participants experiencing a home health episode in the three-year period following the survey

Baseline characteristic

Year 1

OR (95% CI)

Year 2

OR (95% CI)

Year 3

OR (95% CI)

Years 1 to 3 

OR (95% CI)

Age 1.13*** (1.04 - 1.23) 1.04 (0.97 - 1.11) 1.08** (1.01 - 1.16) 1.07* (0.99 - 1.15)

Female 1.32 (0.31 - 5.67) 0.93 (0.26 - 3.26) 1.82 (0.64 - 5.18) 1.67 (0.60 - 4.60)

Completed high school 0.14** (0.03 - 0.64) 1.07 (0.18 - 6.25) 0.73 (0.23 - 2.32) 0.46 (0.15 - 1.37)

Married or living with partner 0.06** (0.01 - 0.69) 0.73 (0.18 - 3.04) 0.24 (0.03 - 1.81) 0.31 (0.06 - 1.76)

Veteran 19.01*** (2.15 - 168.20) 0.49 (0.10 - 2.37) 1.65 (0.39 - 7.10) 2.93** (1.18 - 7.30)

Non-Hispanic Black 0.08*** (0.01 - 0.46) 0.91 (0.27 - 3.10) 4.52** (1.20 - 16.98) 0.69 (0.25 - 1.90)

Non-Hispanic othera 0.43 (0.04 - 5.17) 0.51 (0.02 - 10.65) 0.19 (0.02 - 1.73)

Hispanic 0.35 (0.05 - 2.32) 0.47 (0.03 - 6.31) 1.78 (0.13 - 25.10) 0.65 (0.14 - 2.99)

Monthly income-to-poverty lower than medianb 2.34 (0.68 - 8.12) 1.30 (0.42 - 4.10) 0.56 (0.20 - 1.57) 1.10 (0.45 - 2.67)

Food insecure 0.80 (0.14 - 4.57) 0.77 (0.29 - 2.01) 1.69 (0.31 - 9.17) 1.31 (0.47 - 3.67)

Living alone 4.95* (0.94 - 26.15) 0.69 (0.21 - 2.22) 0.24** (0.06 - 0.92) 0.47 (0.13 - 1.76)

HCC score 0.07*** (0.01 - 0.51) 1.78 (0.40 - 7.88) 0.67 (0.32 - 1.41) 1.12 (0.42 - 2.98)

High blood pressure/hypertension or diabetes 1.62 (0.46 - 5.74) 3.89** (1.32 - 11.51) 2.26 (0.57 - 8.88) 2.19* (0.95 - 5.05)

Any falls in past three months 13.46*** (3.46 - 52.38) 4.43*** (1.53 - 12.82) 4.90** (1.47 - 16.33) 5.67*** (2.42 - 13.28)

LSP provides health promotion activities 3.94** (1.16 - 13.39) 0.67 (0.29 - 1.55) 0.29* (0.07 - 1.11) 0.70 (0.25 - 1.95)

LSP provides nutrition counseling 0.80 (0.19 - 3.41) 1.01 (0.33 - 3.05) 1.71 (0.60 - 4.82) 1.01 (0.42 - 2.46)

LSP provides nutrition screening and assessment 0.64 (0.20 - 2.12) 2.44 (0.79 - 7.56) 1.01 (0.27 - 3.78) 1.40 (0.50 - 3.89)

LSP provides social activities 0.17*** (0.05 - 0.54) 0.48 (0.18 - 1.32) 1.09 (0.14 - 8.45) 0.70 (0.22 - 2.24)

Share of population non-White is higher than median 1.55 (0.50 - 4.79) 0.48 (0.16 - 1.45) 1.14 (0.26 - 4.92) 0.65 (0.19 - 2.24)

Share of population Hispanic is higher than median 0.30* (0.07 - 1.17) 0.79 (0.23 - 2.67) 0.67 (0.23 - 2.00) 0.94 (0.31 - 2.90)

Share of housing units without access to a vehicle is higher 

than median 0.92 (0.23 - 3.61) 3.51* (0.87 - 14.20) 0.92 (0.25 - 3.45) 1.76 (0.65 - 4.74)

Share of families below 200% of poverty is higher than 

median 0.65 (0.20 - 2.16) 0.47 (0.12 - 1.80) 0.73 (0.14 - 3.82) 0.78 (0.30 - 2.01)

Has access to supermarket 2.20 (0.76 - 6.37) 0.92 (0.37 - 2.29) 1.54 (0.52 - 4.57) 0.92 (0.35 - 2.44)

Urban 1.26 (0.37 - 4.25) 1.53 (0.54 - 4.35) 0.92 (0.27 - 3.16) 1.42 (0.54 - 3.73)

Midwest 0.06*** (0.01 - 0.41) 0.42 (0.10 - 1.76) 0.72 (0.14 - 3.58) 0.49 (0.14 - 1.67)

Northeast 0.10** (0.01 - 0.69) 0.86 (0.22 - 3.30) 1.08 (0.26 - 4.49) 0.99 (0.25 - 3.98)

West 0.12** (0.02 - 0.75) 0.42 (0.10 - 1.81) 0.35 (0.09 - 1.29)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/*Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Appendix B 

Mathematica B-7 

Table B.6. Odds ratios of participants experiencing a skilled nursing facility admission in the three-year period following the survey

Baseline characteristic

Year 1

OR (95% CI)

Year 2

OR (95% CI)

Year 3

OR (95% CI)

Years 1 to 3 

OR (95% CI)

Age 1.05 (0.97 - 1.14) 1.09** (1.02 - 1.16) 1.05 (0.96 - 1.14) 1.06 (0.99 - 1.13)

Female 0.49 (0.14 - 1.77) 0.29* (0.07 - 1.14) 0.72 (0.28 - 1.80) 0.63 (0.18 - 2.18)

Completed high school 0.26** (0.08 - 0.85) 0.86 (0.33 - 2.24) 1.72 (0.31 - 9.41) 0.59 (0.25 - 1.42)

Married or living with partner 0.81 (0.04 - 15.92) 0.34 (0.06 - 1.98) 1.39 (0.13 - 15.39) 0.80 (0.17 - 3.74)

Veteran 2.09 (0.34 - 12.91) 0.23* (0.05 - 1.04) 0.62 (0.12 - 3.29) 0.89 (0.21 - 3.70)

Non-Hispanic Black 0.13* (0.01 - 1.48) 0.06** (0.00 - 0.69) 1.80 (0.18 - 18.31) 0.20** (0.05 - 0.85)

Non-Hispanic othera 1.00 (0.14 - 6.92) 0.38 (0.01 - 25.40) 0.42 (0.05 - 3.26)

Hispanic 3.28 (0.79 - 13.69) 0.01*** (0.00 - 0.11) 0.47 (0.10 - 2.24)

Monthly income-to-poverty lower than medianb 0.83 (0.29 - 2.36) 4.67*** (1.73 - 12.61) 2.63 (0.56 - 12.33) 3.38*** (1.45 - 7.88)

Food insecure 0.18 (0.01 - 2.89) 1.17 (0.41 - 3.34) 2.45 (0.58 - 10.35) 0.71 (0.24 - 2.11)

Living alone 9.70* (0.68 - 138.32) 2.02 (0.46 - 8.78) 3.02 (0.71 - 12.86) 2.92** (1.05 - 8.14)

HCC score 0.66 (0.17 - 2.50) 0.55 (0.15 - 2.06) 0.55 (0.14 - 2.23) 0.58 (0.20 - 1.62)

High blood pressure/hypertension or diabetes 2.05 (0.46 - 9.25) 0.70 (0.23 - 2.13) 2.98* (1.00 - 8.94) 1.22 (0.47 - 3.18)

Any falls in past three months 3.27** (1.16 - 9.18) 1.79 (0.69 - 4.63) 2.15 (0.66 - 7.04) 2.74** (1.11 - 6.80)

LSP provides health promotion activities 2.23 (0.49 - 10.24) 1.29 (0.38 - 4.39) 0.49 (0.12 - 2.00) 1.49 (0.51 - 4.31)

LSP provides nutrition counseling 0.48 (0.10 - 2.26) 3.65** (1.24 - 10.79) 6.18* (0.78 - 49.11) 1.31 (0.47 - 3.70)

LSP provides nutrition screening and assessment 0.24*** (0.10 - 0.58) 0.58 (0.22 - 1.54) 3.29 (0.39 - 27.66) 0.59 (0.25 - 1.40)

LSP provides social activities 1.04 (0.23 - 4.61) 0.41 (0.11 - 1.58) 0.06*** (0.01 - 0.40) 0.45 (0.16 - 1.23)

Share of population non-White is higher than median 4.29 (0.71 - 25.81) 1.36 (0.32 - 5.83) 0.68 (0.08 - 5.93) 1.26 (0.37 - 4.35)

Share of population Hispanic is higher than median 0.88 (0.27 - 2.91) 0.67 (0.19 - 2.38) 0.71 (0.17 - 3.05) 0.86 (0.33 - 2.27)

Share of housing units without access to a vehicle is higher 

than median 2.97 (0.53 - 16.75) 2.74* (0.84 - 9.01) 0.42 (0.09 - 2.03) 1.54 (0.65 - 3.65)

Share of families below 200% of poverty is higher than median 1.53 (0.52 - 4.52) 0.25* (0.06 - 1.06) 0.61 (0.06 - 5.93) 1.05 (0.36 - 3.07)

Has access to supermarket 0.41 (0.11 - 1.49) 1.45 (0.51 - 4.14) 1.03 (0.24 - 4.38) 0.81 (0.32 - 2.06)

Urban 0.16** (0.03 - 0.88) 0.92 (0.28 - 3.01) 1.73 (0.25 - 12.20) 0.54 (0.23 - 1.24)

Midwest 1.89 (0.33 - 10.91) 0.11*** (0.03 - 0.50) 0.47 (0.02 - 10.45) 0.41 (0.10 - 1.62)

Northeast 1.01 (0.14 - 7.32) 0.16** (0.03 - 0.77) 0.89 (0.06 - 12.42) 0.44 (0.12 - 1.54)

West 0.35 (0.07 - 1.73) 0.15** (0.02 - 0.97) 0.28** (0.08 - 0.98)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/*Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines).
Appendix B 

Mathematica B-8 

Table B.7. Odds ratios of participants experiencing a nursing home admission in the three-year 

period following the survey

Baseline characteristic

Years 1 to 3 

OR (95% CI)

Age 1.12*** (1.05 - 1.20)

Female 0.10*** (0.02 - 0.53)

Completed high school 0.45 (0.12 - 1.74)

Married or living with partner 0.17* (0.02 - 1.21)

Veteran 0.47 (0.08 - 2.62)

Non-Hispanic Black 0.00*** (0.00 - 0.07)

Non-Hispanic othera 0.70 (0.05 - 10.41)

Hispanic 0.63 (0.08 - 5.28)

Monthly income-to-poverty lower than medianb 3.90*** (1.80 - 8.46)

Food insecure 2.52 (0.60 - 10.63)

Living alone 1.60 (0.41 - 6.21)

HCC score 0.81 (0.19 - 3.52)

High blood pressure/hypertension or diabetes 2.52 (0.75 - 8.45)

Any falls in past three months 3.79*** (1.44 - 9.97)

LSP provides health promotion activities 2.89 (0.74 - 11.26)

LSP provides nutrition counseling 1.80 (0.52 - 6.20)

LSP provides nutrition screening and assessment 0.97 (0.39 - 2.42)

LSP provides social activities 0.43 (0.10 - 1.89)

Share of population non-White is higher than median 3.54* (0.98 - 12.69)

Share of population Hispanic is higher than median 0.63 (0.24 - 1.67)

Share of housing units without access to a vehicle is higher than median 0.63 (0.14 - 2.78)

Share of families below 200% of poverty is higher than median 1.04 (0.24 - 4.49)

Has access to supermarket 1.45 (0.46 - 4.59)

Urban 0.62 (0.13 - 3.05)

Midwest 0.68 (0.15 - 3.18)

Northeast 1.11 (0.19 - 6.53)

West 0.06* (0.00 - 1.17)

Source: AoA NSP outcomes survey, 2015–2016, weighted data; AoA LSP process survey, 2014, weighted data

matched to outcome survey data records. 

Note: Estimates are based on an unweighted sample size of 316 congregate meal participants. 

LSP = local service provider; CI = confidence interval.

***/**/* Significantly different from one at the 0.01/0.05/0.10 level, two-tailed test.

a “Other” includes Asian, American Indian, or Alaska Native; Native Hawaiian or other Pacific Islander; and races not 

identified by respondents in the survey.

b Income-to-poverty based on DHHS poverty guidelines (https://aspe.hhs.gov/2015-poverty-guidelines). 
Mathematica

Princeton, NJ • Ann Arbor, MI • Cambridge, MA 

Chicago, IL • Oakland, CA • Seattle, WA

Tucson, AZ • Woodlawn, MD • Washington, DC 

EDI Global, a Mathematica Company

Bukoba, Tanzania • High Wycombe, United Kingdom

mathematica.com