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Division of Nutritional Sciences, Cornell University, Ithaca, New York 14853
2To whom correspondence should be addressed at Division of Nutritional Sciences, B17 Savage Hall, Cornell University, Ithaca, NY 14853-6301. E-mail: eaf1{at}cornell.edu
| ABSTRACT |
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KEY WORDS: need food insecurity food assistance program impact study design humans
| INTRODUCTION |
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It is essential to assess the effectiveness of food assistance programs, especially among the nutritionally needy elderly persons, and to tailor programs so they are more effective and efficient in service delivery. Research methods for assessing the impact of food assistance programs, however, have been limited in that randomized study designs usually cannot be carried out ethically to evaluate food assistance programs.
From a research design perspective, the ideal way to assess the impact
of food assistance programs would be to compare outcomes between
participants and nonparticipants, where both groups would have equal or
comparable needs for food assistance programs. However, this approach
is difficult in practice because the nutritional needs of elderly
persons for food assistance program participants are not well
characterized. The concept of need is most often understood as the gap
between an existing and a desired nutritional state. This gap, which in
principle is measurable, becomes a need in the context of social policy
when it potentially can be prevented or ameliorated by the use of food
assistance programs (Blum and Stein 1981
). There has not
been a full consensus on the nature and extent of need among elderly
persons because need, as a value judgment, is identified and measured
differently according to the perspective of need chosen (i.e., felt,
expressed, normative and comparative) (Bradshaw 1972
)
and the approaches used in need assessments (i.e., rationalistic,
empirical and relativistic) (Nguyen et al. 1983
).
Therefore, an inherent problem in research on the effectiveness of food
assistance programs is finding a relevant comparison group or norm
against which to judge the impact of a program.
Several approaches to finding the best comparison group have been tried in the past. Ideally, the comparison group would be as similar as possible to the program participants, except for program participation and random variation. Lower economic status measured by comparing household income with the Poverty Index Ratio (PIR) has been conventionally used to define elderly persons who are in need of food assistance programs. The PIR, as a normative concept of need and with the rationalistic approach, may not, however, fully reflect the complex conditions of need for food assistance among elderly persons whose need is determined by the culmination of multiple factors throughout their lives.
Groups have been made more comparable in two ways: through analysis and study design. Statistical control has been widely used in analysis to try to make groups (i.e., participants and eligible nonparticipants) comparable in terms of the needs status. The most commonly used method has been multiple ordinary least squares, which allows statistical control for some observable characteristics that might be different between participants and nonparticipants. Even after control for observed characteristics, however, program participants may still differ systematically from eligible nonparticipants in ways that can confound the estimation of food assistance program impact. In other words, it is probable that some determinants of program participation that are not fully observed are related to the outcomes, resulting in biased estimation of program impacts because of the noncomparable need status of participants and nonparticipants.
Selection models have been extensively used to try to deal with this
issue. The assumption of a selection model is that some identifying
variables affect only participation and not outcome variables. This
assumption, however, does not hold across different studies. Especially
in elderly persons, it has been difficult to identify measures that
have a substantial effect on program participation but do not affect
the outcome. Selection models also have not been capable of achieving
equal or similar need status among groups. As a result, most studies
using these statistical approaches have reported conflicting results
about the impacts of the food programs on nutritional and health status
in low-income elderly persons; whereas previous research has
generally found small positive effects, which are usually not
statistically significant. For example, the Food Stamp Program has been
shown to increase food expenditure, nutrient availability and nutrient
intakes among low-income elderly persons, but the size of this
impact varied greatly regardless of whether multiple ordinary least
squares or a selection model was used (Akin et al. 1985
,
Blanchard 1982
, Butler et al. 1985
,
Emmons 1987
, Hama and Chern 1988
,
Lopez and Habicht 1987a and 1987b
, Posner et al. 1987b
).
The second way, incorporated in study design, has been to match
eligible nonparticipants and participants by sociodemographic, economic
or health characteristics. In the recent national evaluation of ENP, a
comparison group from a Medicare recipient list was matched with
participants in terms of their resident area, age, income and
disability status. Multiple regression techniques, with control for
characteristics that would be related to both program participation and
the outcomes studied, were used. The results showed that ENP
participation had positive impacts on nutrient intakes and social
contacts, although the impacts were only marginally significant
(Ponza et al. 1996
). Even this approach had limitations
that make it impossible to attribute the positive results solely to the
programs. Matching may have improved the comparability between
participants and eligible nonparticipants more than just the use of
statistical control, but without a clear understanding of needs for
food assistance programs, it is not certain whether the characteristics
considered for matching were the best ones. Another study that enhanced
the comparability between comparison groups chose nonparticipants from
those who were on the waiting list. This study showed that
participation in home-delivered meals had significantly positive
impacts on nutrition and health outcomes (Edwards et al. 1993
). These studies suggest that as groups become more
comparable in terms of their needs for food assistance programs, the
impact of food assistance programs among elderly persons can be more
accurately measured.
In an environment of shrinking government resources, it is more important than ever to use convincing research designs and methods to provide evidence that food assistance programs have beneficial impacts on nutritionally needy elderly persons. More careful consideration of the need for food assistance programs among elderly persons and incorporation of these concepts into evaluation of the impacts of food assistance programs is required.
In this study, in which we used established concepts of human service
needs (Blum and Stein 1981
, Bradshaw 1972
, Nguyen et al. 1983
, Siegel et al. 1978
), we assessed the impact of food assistance programs on
nutritional and health status among the nutritionally needy elderly
persons using the best available cross-sectional and longitudinal
data: Third National Health and Nutrition Examination Survey (NHANES III, 198894), Nutrition Survey of the Elderly in New York State
(NSENY, 1994) and Longitudinal Study of Aging (LSOA, 19841990). Food
insecurity was chosen to specify nutritional need among elderly persons
in addition to the poverty measure, because food insecurity reflects
the need for nutritional services perceived by both elderly persons
themselves and society. In addition, food insecurity has been shown to
have a direct link to poor nutrition and health status and to mediate
the link between risk factors and malnutrition; the income-based
poverty measure may not account for these relations (Institute of Medicine 1996
, Roe 1990
, Rose et al. 1998
, Rose and Oliveira 1997
, Vailas et al. 1998
). Food insecure elderly persons are regarded as having
needs that can be solved by the use of food assistance programs. They
are expected to have higher potential to benefit from food assistance
participation than food secure elderly persons (Institute of Medicine 1996
, Ruel et al. 1996
). Thus, the null
hypothesis was that there are no differences in nutritional and health
status (i.e., nutrient intakes, skinfold thickness, self-reported
health status, nutritional risk, hospitalization and mortality) of
elderly persons regardless of their food insecurity status and food
assistance program participation. The alternative hypotheses of
interest were: 1) food assistance participants have better
nutritional and health status than nonparticipants, and 2)
the benefits of program participation are larger among food insecure
elderly persons than among the food secure.
| MATERIALS AND METHODS |
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NHANES III.
Elderly persons 6090 y old (n = 6596) were
sampled in the NHANES III (198894). The survey conducted by the
National Center for Health Statistics was designed to obtain nationally
representative information on health and nutritional status in U.S.
population through extensive interviews and an examination in a mobile
examination center. Specifically, the NHANES III included the aged and
very old and used a home examination to monitor nonresponse at the time
of data collection to provide reliable estimates in older persons
(McDowell et al. 1991
). More detailed information about
the survey design and operation has been published elsewhere
(U.S. Department of Health and Human Services National Center for Health Statistics 1996
).
NSENY.
The data were taken from elderly persons 6096 y old (n
= 553) who were sampled in the supplemental survey to the NSENY
(April 18 to July 7, 1994). The NSENY was conducted by the New York
State Department of Health in collaboration with the State Office for
the Aging to obtain information to improve the effectiveness of
services provided by the ENP in New York State. This survey included a
wide range of data related to eligibility for home-delivered meals
program, sociodemographic characteristics, nutritional risk, food
insecurity and functional impairment variables. More detailed
information on the survey design, operation and questionnaire has been
published elsewhere (New York State Department of Health and Office of the Aging 1996
).
LSOA.
The LSOA was a prospective survey of 7527 civilian noninstitutionalized
persons aged
70 y who were selected from the 1984 National Health
Interview Survey, Supplement on Aging. Three follow-up interviews
were conducted at 2-y intervals (1986, 1988 and 1990). The LSOA was
designed to provide information on changes in health, social
functioning, functional impairments, health service use and mortality
for a cohort of older Americans. More detailed information on sampling
design, questionnaire and operation has been reported elsewhere
(Kovar et al. 1992
). Due to budget constraints, 2376
individuals were not reinterviewed in 1986. This analysis focused on
the 1984 and 1988 data to ensure the largest possible analytic sample
(n = 7527).
Comparison groups
Food insecurity.
In the NHANES III, the family food insufficiency question was used to
determine food insecurity status. The family food insufficiency
question, defined as "an inadequate amount of food intake due to lack
of resources," was designed to measure individual food insufficiency
based on the reported adequacy of the familys food resources
(Briefel and Woteki 1992
). An elderly person was
classified as "food insecure" if he or she reported that the family
"sometimes or often did not get enough food to eat." Several
studies have confirmed the validity of the food insufficiency question
as a measure of food insecurity, despite some limitations
(Alaimo 1997
, Alaimo et al. 1999
,
Basiotis 1992
, Briefel and Woteki 1992
,
Cristofar and Basiotis 1992
, Frongillo et al. 1997
, Rose and Oliveira 1997
).
In the NSENY survey, three items were used to measure food insecurity
status during the past 6 mo ("Do you have enough money to buy the
food you need most of the time?" "In the past 6 mo, have you
skipped one or more meals because you had no food in the house or you
thought that soon you might not have enough food?" and "In the past
6 mo, have you had to choose between buying food or paying bills or
buying something else you needed?"). Previous research established
content and construct validity of the items (Burt 1993
,
Quandt and Rao 1999
). An elderly person was classified
as "food insecure" if he or she reported affirmative responses to
at least one of the three items.
In the LSOA, a direct question asking food insecurity status was not
available. We chose the question "Do you have difficulty in preparing
your own meals?" to indicate need for food assistance among elderly
persons. Functional impairments including the inability to prepare
meals is significantly associated with food insecurity in elderly
persons (Lee and Frongillo 2001
). This question has been
used to determine food insecurity status in elderly persons in previous
research (Burt 1993
, Quandt and Rao 1999
).
Food assistance program participation. Food assistance program participation indicated whether a respondent took part in food assistance programs available in their community at the present time. Programs for which information was available were the Food Stamp Program and ENP in NHANES III, ENP in NSENY, and ENP and homemaker services (HMS) in the LSOA.
Comparison group construction. In both NHANES III and NSENY, four groups were constructed based on food insecurity and food assistance program participation: 1) food insecure and participant (FIP), 2) food insecure and nonparticipant (FINP), 3) food secure and participant (FSP) and 4) food secure and nonparticipant (FSNP).
In the LSOA, three levels of need status were broken down into four groups each depending on whether or in how many food assistance programs they participated. Among 12 possible groups, 4 were excluded because those groups had either small or no sample; those excluded were nonparticipants with severe difficulty, ENP participants with severe difficulty, HMS participants with no difficulty and participants in both programs with no difficulty.
Nutritional and health status
Nutrient intake.
In NHANES III, detailed nutrient intake information was available based
on one 24-h dietary recall method in the mobile examination center. The
NHANES III incorporated several strategies for improving dietary recall
performance in both healthy and poor/frail older persons, such as
memory enhancement techniques and proxy respondents. Also, data on
drinking water intake, vitamin/mineral supplementation and medication
use were included to estimate total nutrient intake (McDowell et al. 1991
, U.S. Department of Health and Human Services National Center for Health Statistics 1996
).
Energy and 20 nutrients were selected for the analysis based on
previous research reflecting concerns for excessive or deficient intake
in elderly persons (Barrocas et al. 1995
, Ponza et al. 1994
, Schlenker 1998
).
Skinfold thickness. Anthropometric measurements provide information about the adequacy of an individuals energy balance and body composition. Weight, arm circumference and triceps, subscapular, suprailiac and thigh skinfold thicknesses were selected to assess energy stores in NHANES III. To help interpret the results on skinfold thickness, the sum of four skinfold measures was expressed also as percentile values of elders aged 60 y old who were examined in NHANES III.
Nutritional risk.
The NSENY included a nutritional risk scale adopted from the 10-item
Nutritional Screening Initiative Checklist (NSIC). The NSIC was
designed as a brief risk-appraisal questionnaire that could be
self-administered and scored by older persons, family members or
caregivers (Nutrition Screening Initiative 1991
). The
construct and scoring system of NSIC have been validated (Posner 1993
and 1994
), and it has been extensively used to evaluate
nutritional risk across various fields specializing in the care of
elderly persons.
In our study, a modified version of nutritional risk was used after excluding one item ("Do you have enough money to buy the food you need most of the time?") that was also included in food insecurity measurement. The questions that were included are one or less meal per day, consumption of fruits/vegetables/milk everyday, dietary change due to health problems, tooth and mouth problems, unable to shop/cook/feed self, loss/gain weight, use of three or more drugs daily, consumption of three or more alcoholic drinks daily and eating alone. Each item has its own weight score depending on attributable seriousness to nutritional and health risk in elderly persons, and the total score is 17.
Self-reported health status, hospitalization and mortality.
Self-reported health status is known to provide a simple, direct and
global way of capturing perceptions of health criteria that are as
broad and inclusive as the responding individual chooses to make them
(Idler and Benyamini 1997
, Krause and Jay 1994
). The validity of perceived health status has been shown
by its strong predictive power for mortality, disability, survival and
health care service use, especially in elderly persons (Idler and Benyamini 1997
, Kaplan 1988
, Mor et al. 1994
, Mossey and Shapiro 1982
).
Self-reported health status was asked "Would you say your health
in general is excellent, very good, good, fair, or poor?" For
analyses, the response was recoded into two categories:
1) good, including excellent, very good and good, and
2) poor, including fair and poor. This information was
available for both NHANES III and LSOA.
The LSOA had information on the number of short-stay hospital episodes in the past 12 mo. A dichotomous hospitalization variable was constructed to indicate whether elderly persons were hospitalized during last year or not, as indicated in the 1988 survey. Also, the LSOA included the mortality information after the 4-y follow up (1988).
Controlling variables
To assess the relationship between food assistance participation
and nutritional and health status, it was crucial to control for
potential confounding variables. Sociodemographic, economic,
psychological, physical functioning, health and behavioral and adverse
health conditions are known to influence nutrient intakes,
anthropometry, self-reported health status, nutritional risk,
hospitality and mortality (Betts and Vivian 1985
,
Bianchetti et al. 1990
, Garry et al. 1982
, Gilbride et al. 1998
, Gray-Donald et al. 1994
, Idler and Benyamini 1997
,
Johnson and Wolinsky 1993
, Keller et al. 1997
, MacLellan 1997
, Marshall et al. 1999
, Murphy et al. 1990
, Neyman et al. 1996
, Payette et al. 1995
, Posner et al. 1987
a, Ritchie et al. 1997
, Roy et al. 1996
, Schlenker 1998
, Stevens et al. 1992
, Walker and Beauchene 1991
, Weimer 1998
). Based on prior knowledge and/or research about the
relationship of the dependent variable to each possible covariate,
variables known to be reasonably associated with the dependent
variables and available in the data set were considered as potential
confounders.
Physical functioning
The Activities of Daily Living (ADL) and Instrumental Activities
of Daily Living (IADL) have been the most frequently assessed
indicators of disability (Kovar and Lawton 1994
). The
NHANES III included four items of ADL (dressing, eating, getting in or
out of bed and transferring) and two items of nutrition-related
IADL (preparing own meals and managing money). The NSENY included five
items of ADL (getting in/out of chair/bed, feeding self, getting
dressed, taking bath/shower and toileting) and five items of IADL
(getting around by car, using public transportation, doing light
housework, managing money and taking medicine). The LSOA included seven
ADL (bathing, dressing, eating, getting in/out of bed, walking, getting
outside and toileting) and six IADL (preparing meals, shopping,
managing money, using telephone, doing heavy housework and doing light
housework). A three-category indicator of physical function was
constructed in the following way: 1) no problem (having no
difficulty in both ADL and IADL), 2) IADL problem (having at
least one difficulty in IADL) and 3) ADL problem (having at
least one difficulty in ADL).
Chronic disease
This variable reflected the presence (versus absence) of serious health problems in NSENY or at least one of self-reported clinically diagnosed diseases that are highly prevalent and affecting nutritional and health status among elderly persons available in NHANES III and LSOA (arthritis, hypertension, health failure, stroke, cataract, cancer, diabetes mellitus, osteoporosis and emphysema).
Sociodemographic and economic variables
Age was divided into three groups: 1) younger old
(6069 y), 2) older old (7079 y) and 3) oldest
old (
80 y). Race ethnicity was categorized into three groups:
1) non-Hispanic/white, 2) non-Hispanic/black and
3) Hispanic. Marital status and household size questions
were used to create a three-category living arrangement variable:
1) living with spouse, 2) living with others and
3) living alone. Educational status was broken down into two
groups: 1) high school graduate or less (
12 y) and
2) more than high school graduate (>12 y). A social support
variable was made with information about how often the respondent got
together with friends or relatives, such as going out together or
visiting in each others home. Location included two categories:
metropolitan or nonmetropolitan in NHANES III and New York City or
nonNew York City in NSENY. As an economic factor, PIR, computed as
the midpoint of the observed family income category in household
interview divided by the poverty threshold, was divided into five
groups in NHANES III (<50, 50100, 100130, 130200 and >200%)
and two groups in NSENY and LSOA (150 and 100% as cutoffs,
respectively). In addition, dichotomous variables were constructed to
indicate gender (female versus male), dietary change due to health
problems and use of vitamin/mineral supplementation.
Statistical analysis
SAS PROC GLM for linear regression was used to assess the extent to which food assistance program participation was associated with nutritional and health status in food insecure elderly. This analysis compared means of nutrient intake, skinfold thickness and nutritional risk among comparison groups while controlling for other confounding variables. To assess the association of food assistance program participation with self-reported health status, hospitalization and mortality, logistic regression was used with SAS PROC LOGISTIC.
Descriptive statistics were analyzed using sample weights and complex
survey methods that take into account oversampling, noncoverage and
nonresponse among three data sets. The complex sample design was taken
into account when calculating variance estimates using SVY commands in
STATA (Statacorp 1997
). The use of sample weights,
however, made the analysis much less efficient and precise in NHANES
III. The approximate inefficiency of the sample weights calculated with
the equation from DuMouchel and Duncan (1983
) was
56.8%. Our preliminary analysis showed that coefficients of regression
analysis without sample weights were consistently smaller but similar
to coefficients with sample weights. Analysis without sample weights
did not change our results. Thus, unweighted analyses were made while
controlling for the variables related to the design adjustments in the
analysis to maintain its efficiency and precision (Korn and Graubard 1991
). Also, unweighted analyses were made in LSOA,
because previous study using LSOA found that the sampling design of the
LSOA has little impact in variance estimation (Fitti and Kovar 1987
).
| RESULTS |
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Sociodemographic, economic and health characteristics of the study
populations from the three data sets by group are presented in
Tables 1
,
2
and
3
. Of the study population in NHANES III, 1.7% were food insufficient;
8.9% were currently participated in either the Food Stamp Program
(5.0%), Senior Meals Programs (3.3%) or both (0.6%). Program
participants, particularly multiple program participants, were more
likely to be functionally impaired and poor. Food insufficient elderly
persons were more likely to participate in food assistance programs
than were food sufficient elderly persons (45.3% versus 8.3%). Among
the program participants, food insufficient elderly persons were more
likely to participate more in the Food Stamp Program (86.5% versus
53.9%), whereas food sufficient elderly persons were more likely to
participate in Senior Meals Program (39.6% versus 7.0%). The mean age
of the study population was 70.8 ± 0.21 y old (means ± SE); >15% were in their 80s; 57% were female and 11%
were minority.
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The characteristics of study sample from LSOA were similar to those of
the other two study samples (Table 3)
. They were predominantly female
(62.0%) and white (89.1%) and had diseases (78.7%). Almost one tenth
of the study population had problems in preparing their own meals.
Elderly persons who were more likely to have severe difficulty in
preparing their meals were more likely to be poor, less educated,
functionally impaired and in poor health, to live alone and to
participate in food assistance programs.
Analytical results.
Figure 1
shows adjusted nutrient intake as a percentage of RDA among the four
groups in the NHANES III with control for potential confounding
factors: age, gender, race-ethnicity, PIR, education, living
arrangement, disease, physical functioning, dietary change due to
health problems, use of vitamin/mineral supplementation and medication
use. The intakes of energy, protein, calcium, magnesium, zinc and
vitamins A, E and B-6 were lower than 100% of recommended daily
allowance in elderly persons. Overall, food sufficient elderly persons
had higher percentages of recommended daily allowances for most
nutrient intakes than did food insufficient elderly persons. The FSNP
group had higher nutrient intakes than the other three groups. Contrary
to the two specified alternative hypotheses, participants did not have
higher intakes than nonparticipants, regardless of food insufficiency
status. Instead, the FIP group consumed a lower level of energy,
protein, vitamins E and C, thiamin and iron than did the FSNP group.
Also, intakes of energy, some of the vitamins (thiamin, riboflavin and
vitamins A, E, B-6, B-12 and C), niacin and iron were lower in the FIP
group than in the FINP group. Adjusted means of nutrient intakes of
seven other nutrients (i.e., total fatty acids, saturated fatty acids,
carbohydrate, cholesterol, folate, phosphate and sodium) showed similar
nutrient intake patterns among the four groups (data not shown).
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In the LSOA, contrary to the two alternative hypotheses, elderly
persons with greater difficulty in preparing meals had higher odds of
having poorer self-reported health status, hospitalization rates
and mortality rates (Fig. 2
). Participation in either the ENP or HMS did not make significant
differences in that pattern. Rather, those who participated in either
of the two programs showed higher odds of having poorer
self-reported health status, hospitalization rates and mortality
rates than did their counterparts within the same level of difficulty.
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| DISCUSSION |
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A consistent trend across groups was found in all three data sets. Food
insecure elderly persons were more likely to participate in food
assistance programs available in their community, even though only half
of them used those services in the nationally representative sample.
Contrary to the first alternative hypothesis, food assistance
participants had similar or poorer nutrient intakes, nutritional risk,
self-reported health status, hospitalization rates and mortality
rates and smaller skinfold thickness than did nonparticipants. Also
contrary to the second alternative hypothesis, the benefit of program
participation was not greater for food insecure elderly persons than
for the food secure. These findings are consistent with previous
research using statistical control or selection models that found
nonsignificant and minimal impacts of food assistance programs among
eligible participants compared with eligible nonparticipants
(Akin et al. 1985
, Basiotis and Brown 1987
, Blanchard 1982
, Butler et al. 1985
, Deveney and Moffit 1991
, Emmons 1987
, Hama and Chern 1988
, Lane 1978
, Lopez and Habicht 1987a
and 1987b
,
Posner et al. 1987b
).
Across the three national or statewide representative data sets, either
cross-sectional or longitudinal, program participants were more
likely to be poor, functionally impaired, living alone and at
nutritional risk than nonparticipants. Multiple program participants
tended to have worse sociodemographic, nutritional and health status.
The process of translating the need for food assistance or food
insecurity (i.e., felt needs) into utilization of food assistance
programs (i.e., expressed needs) is influenced by availability,
accessibility of programs and acceptability to elderly persons
(Blanchard 1982
, Hollenbeck and Ohls 1984
, Trela and Simmons 1971
, Wolfe et al. 1996
). In particular, perceptions about the need and
attitudes for services provided by programs targeted toward elderly
persons have been known as important determinants of service use
(Krout 1983
, Wracker et al. 1998
). Not
all elderly persons who feel a need for food assistance programs
participate in programs. Although nonparticipants among food insecure
elderly persons might have greater potential to benefit from food
assistance, they may have problems or concerns that make them reluctant
to participate. For example, lack of information, ineligibility, living
in a nonmetropolitan area, functional impairments and negative
perceptions or stigma toward the program participation may limit
participation. Food assistance program participation implies more than
just receiving nutritional services or different participant
characteristics; it implies selectivity resulting from serious
nutritional need and demand for food assistance programs as well as
complicated decision-making processes by elderly persons. Food
assistance program participants who are food insecure may have been the
most nutritionally needy, and they may have chosen to participate in
programs regardless of all of the constraints of and negative
perceptions toward programs (Ponza and Wray 1990
). These
ideas are consistent with the observation in this study that the FIP
group who are most in need had the similar or worse nutritional and
health status than the FINP group, as was the case for the FSNP and FSP
groups.
At least two interpretations of these results are possible. One interpretation is that food assistance participation may have either no or little impact on the nutritional and health status of food insecure elderly persons. Another more plausible interpretation is that food assistance program participation may protect food insecure elderly persons from further detrimental nutritional and health problems and may contribute to maintaining food security among food secure persons. That is, programs might help participants to maintain nutritional and health status at least similar to that of nonparticipants within the same level of need status. One cannot, however, easily judge which interpretation is likely to be most correct without more extensive information on their needs.
These two possible interpretations illustrate why our approach to incorporate the concept of need is important in trying to accurately assess impacts of food assistance programs. However, limited information on the dynamic nature of needs in relation to program participation in the three data sets, both cross-sectional and longitudinal, did not allow the achievement of comparability of need status across the groups. The two cross-sectional data sets lacked information on the duration and severity of food insecurity, as well as the pattern and period of program participation. Even the longitudinal data containing information at an interval of 4 y were not sufficient to provide better information on dynamic changes in need status and program participation.
This study suggests that direct comparison between participants and nonparticipants is incapable of assessing the impact of program participation, even with the best-available, typical cross-sectional and longitudinal data. This problem likely cannot be corrected by statistical control, selection models or matching. The incorporation of simple categorization of specific needs was also unable to resolve selection bias related to program participation and to facilitate an examination of the impacts of food assistance programs. Careful understanding and identification of the nutritional needs of elderly persons within appropriate time frames are critical to evaluate the impacts of food assistance programs and whether they are of benefit to the most nutritionally needy. Furthermore, close scrutiny on different manifestations of need for food assistance programs among elderly persons, which is greatly specific to an elderly individual, is vital to assess and interpret the impacts of the program.
These results emphasize the importance of having more extensive
information on the complex and dynamic nature of need for nutrition
services among elderly persons. Different study designs and approaches
to sort out need status and its change within each older individual
across an appropriate time frame are necessary to assess unbiased
impacts of food assistance programs. In the absence of the ability to
conduct randomized intervention trials, time-intensive event
history designs may be most able to provide the information required to
assess the impacts of programs for elderly persons (Blossfeld and Rohwer 1995
, Tuma and Hannan 1984
). An event
history design study transitions across a set of discrete states,
including the length of time intervals between entry into and exit from
specific states. The transitions in states are studied in relation to
other discrete events and changes in continuous states. These designs
hold advantages for causal inference over both cross-sectional and
traditional longitudinal designs and are particularly suited for
research with elderly persons because of the highly dynamic nature of
factors in their lives that affect their well-being.
In the era of population aging, understanding the dynamic needs along with social psychological dynamics of help-seeking behavior among elderly persons is fundamental to assessing the impact of food assistance programs. Theory and knowledge to understand what, how and why nutritional needs are manifested within the context of food assistance program delivery and to develop study designs are required to examine the impact of food assistance programs and to make food assistance programs a more effective and beneficial intervention for elderly persons.
| ACKNOWLEDGMENTS |
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| FOOTNOTES |
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3 Abbreviations used: ADL, Activities of Daily Living; ENP, Elderly Nutrition Program; FINP, food insecure and program nonparticipant; FIP, food insecure and program participant; FSNP, food secure and program nonparticipant; FSP, food secure and program participant; HMS, homemaker services; IADL, Instrumental Activities of Daily Living; LSOA, Longitudinal Study on Aging; NHANES III, Third National Health and Nutrition Examination Survey; NSENY, Nutrition Survey of the Elderly in New York State; NSIC, Nutritional Screening Initiative Checklist; PIR, Poverty Index Ratio. ![]()
Manuscript received March 31, 2000. Initial review completed July 1, 2000. Revision accepted November 28, 2000.
| REFERENCES |
|---|
|
|
|---|
1. Akin J. S., Guilkey D. K., Popkin B. M., Smith K. M. The impact of federal transfer programs on the nutrient intake of elderly individuals. J. Hum. Resources 1985;20:383-404
2. Alaimo K. Food Insecurity, Hunger, and Food Insufficiency in the United States: Cognitive Testing of Questionnaire Items and Prevalence Estimates from the NHANES III 1997 Cornell University Ithaca, NY.
3. Alaimo K., Olson C. M., Frongillo E. A., Jr Importance of cognitive testing for survey items: an example from food security questionnaires. J. Nutr. Educ. 1999;31:269-275
4. Barrocas A., Belcher D., Champagne C., Jastram C. Nutrition assessment practical approaches. Clin. Geriatr. Med. 1995;11:675-713
5. Basiotis, P. P. (1992) Validity of the Self-Reported Food Sufficiency Status Item in the US Department of Agriculture Food Consumption Surveys, Toronto, Ontario, Canada.
6. Basiotis P. P., Brown M. Nutrient availability, food costs, and food stamps. Am. Agric. Econ. Assoc. 1987;65:685-693
7. Betts N. M., Vivian V. M. Factors related to the dietary adequacy of noninstitutionalized elderly. J. Nutr. Elder. 1985;4:3-14
8. Bianchetti A., Rozzini R., Carabellese C., Zanetti O., Trabucchi M. Nutritional intake, socioeconomic conditions, and health status in a large elderly population. J. Am. Geriatr. Soc. 1990;38:521-526
9. Blanchard L. Food Stamp SSI/Elderly Cashout Demonstration Evaluation 1982 U.S. Department of Agriculture Food and Nutrition Service.
10. Blossfeld H., Rohwer G. Techniques of Event History Modeling: New Approaches to Causal Analysis 1995 Lawrence Erlbaum Association Manhwa, NJ.
11. Blum H. L. Stein S. L. eds. Assessment: Measurement of Where We Are, Where We Are Likely to Be, and Where We Want to Be 2nd ed. 1981:88-164 Human Sciences Press New York.
12. Bradshaw J. The concept of social need. New Society 1972;19:640-643
13. Briefel R. R., Woteki C. E. Development of the food sufficiency questions for the Third National Health and Nutrition Examination Survey. J. Nutr. Educ. 1992;24:24S-28S
14. Burt M. R. Hunger among the Elderly: Local and National Comparison 1993 The Urban Institute Washington, D.C.
15. Butler J. S., Ohls J. C., Posner B. The effect of the Food Stamp Program on the nutrient intake of the eligible elderly. J. Hum. Resources 1985;20:405-420
16. Cristofar S. P., Basiotis P. P. Dietary intakes and selected characteristics of women ages 1950 years and their children ages 15 years by reported perception of food sufficiency. J. Nutr. Educ. 1992;24:53-58
17. Deveney B., Moffit R. Dietary effects of the Food Stamp program. Am. Agric. Econ. Assoc. 1991;:202-211
18. DuMouchel W. H., Duncan G. J. Using sample survey weights in multiple regression analysis of stratified samples. J. Am. Stat. Assoc. 1983;78:535-543
19. Frongillo E. A., Jr, Rauschenbach B. S., Olson C. M., Kendall A., Colmenares A. G. Questionnaire-based measures are valid for the identification of rural households with hunger and food insecurity. J. Nutr. 1997;127:699-705
20. Edwards D. L., Frongillo E. A., Rauschenbach B., Roe D. A. Home-delivered meals benefit the diabetic elderly. J. Am. Diet. Assoc. 1993;93:585-587
21. Emmons L. Relationship of participation in food assistance programs to the nutritional quality of diets. Am. J. Public Health. 1987;77:856-858
22. Fitti J., Kovar M. The Supplement on Aging to the 1984 National Health Interview Survey 1987 U.S. Government Printing Office, U.S. Department of Health and Human Services Washington, D.C.
23. Garry P. J., Goodwin J. S., Hunt W. C., Hooper E. M., Leonard A. G. Nutritional status in a health elderly population: dietary and supplemental intakes. Am. J. Clin. Nutr. 1982;36:319-331
24. Gilbride J. A., Amella E. J., Breines E. B., Mariano C., Mezey M. Nutrition and health status assessment of community-residing elderly in New York City: a pilot study. J. Am. Diet. Assoc. 1998;98:554-558
25. Gray-Donald K., Payette H., Boutier V., Page S. Evaluation of the dietary intake of homebound elderly and the feasibility of dietary supplementation. J. Am. Coll. Nutr. 1994;13:277-284
26. Hama M. Y., Chern W. S. Food expenditure and nutrient availability in elderly households. J. Consum. Affairs 1988;22:3-19
27. Hollenbeck D., Ohls J. Participation among the elderly in the Food Stamps Program. Gerontologist 1984;24:616-621
28. Idler E. L., Benyamini Y. Self-reported health and mortality: a review of twenty-seven community studies. J. Health. Soc. Behav. 1997;38:21-37
29. Institute of Medicine WIC Nutrition Risk Criteria: A Scientific Assessment 1996 National Academic Press Washington, D.C.
30. Johnson R. J., Wolinsky F. D. The structure of health status among older adults: disease, disability, functional limitation, and perceived health. J. Health Soc. Behav. 1993;34:105-121
31. Kaplan G. A. Subjective state of health and survival in elderly adults. J. Gerontol. 1988;50B:S191-S193
32. Keller H. H., Ostbye T., Bright-See E. Predictors of dietary intake in Ontario seniors. Can. J. Public Health. 1997;88:305-309
33. Korn E. L., Graubard B. I. Epidemiologic studies utilizing surveys: accounting for the sampling design. Am. J. Public Health. 1991;81:1166-1173
34. Kovar, M. G., Fitti, J. E. & Chyba, M. M. (1992) Vital Health Statistics (10): The Longitudinal Study of Aging: 19841990. U.S. Department of Health and Human Services, Washington, D.C., Report No. PHS 92-1304.
35. Kovar M. G. Lawton M. P. eds. Functional Disability: Activities and Instrumental Activities of Daily Living 1994 Springer New York.
36. Krause N. M., Jay G. M. What do global self-rated health items measure?. Med. Care 1994;32:930-942
37. Krout J. A. Knowledge and use of services by the elderly. Int. J. Aging Hum. Dev. 1983;17:153-167
38. Lane S. Food distribution and Food Stamp Program effects on food consumption and nutritional "achievement" of low income persons in Kern County, California. Am. Agric. Econ. Assoc. 1978;:108-116
39. Lee, J. & Frongillo, E. A., Jr. (2001) Factors associated with food insecurity among US elderly persons: importance of functional impairments. J. Gerontol. (In press.)
40. Lopez A. M., Habicht J.-P. Food stamps and the energy status of the U.S. elderly poor. J. Am. Diet. Assoc. 1987a;87:1020-1024
41. Lopez L. M., Habicht J.-P. Food stamps and the iron status of the U.S. elderly poor. J. Am. Diet. Assoc. 1987b;87:598-603
42. MacLellan D. L. Contribution of home-delivered meals to the dietary intake of the elderly. J. Nutr. Elder. 1997;16:17-32
43. Marshall J. A., Lopez T. K., Shetterly S. M., Morgenstern N. E., Baer K., Swenson C., Baron A., Bazter J., Hamman R. F. Indicators of nutritional risk in a rural elderly Hispanic and non-Hispanic White population: San Luis Valley Health and Aging Study. J. Am. Diet. Assoc. 1999;99:315-322
44. McDowell M. A., Harris T. B., Briefel R. R. Dietary surveys of older persons. Clin. Appl. Nutr. 1991;1:51-60
45. Mor V., Wilcoz V., Rakowski W., Hiris J. Functional transitions among the elderly: patterns, predictors, and related hospital use. Am. J. Public Health. 1994;84:1274-1280
46. Mossey J. M., Shapiro E. Self-reported health: a predictor of mortality among the elderly. Am. J. Public Health. 1982;72:800-808
47. Murphy S. P., Davis M. A., Neuhaus J. M., Lein D. Factors influencing the dietary adequacy and energy intake of older Americans. J. Nutr. Educ. 1990;22:284-291
48. New York State Department of Health and Office for the Aging Nutrition Survey of the Elderly in New York State 1996 Albany NY.
49. Neyman M. R., Zidenberg-Cherr S., McDonald R. B. Effect of participation in congregate-site meal programs on nutritional status of the healthy elderly. J. Am. Diet. Assoc. 1996;96:475-483
50. Nguyen T. D. Attkisson C. C. Bottino M. J. eds. The Definition and Identification of Human Service Needs in a Community 1983:88-110 Human Sciences Press New York.
51. Nutrition Screening Initiative Nutrition Screening Manual for Professionals Caring for Older Americans 1991 Washington D.C.
52. Payette H., Gray-Donald K., Cyr R., Boutier V. Predictors of dietary intake in a functionally dependent elderly population in the community. Am. J. Public Health. 1995;85:677-683
53. Ponza M., Ohls J. C., Millen B. E. Elderly Nutrition Program evaluation literature review 1994 Mathematica Policy Research, Inc Princeton, NJ.
54. Ponza M., Ohls J. C., Millen B. E., McCool A. M., Needels K. E., Rosenberg L., Chu D., Daly C., Quatromoni P. A. Serving Elders at Risk the Older American Act Nutrition Programs: National Evaluation of the Elderly Nutrition Program 19931995 1996 U.S. Department of Health and Human Services Washington, D.C.
55. Ponza, M. & Wray, L. (1990) Evaluation of the Food Assistance Needs of the Low-Income Elderly and Their Participation in USDA Programs (Elderly Programs Study). Mathematica Policy Research, Princeton, NJ., Report No. MPR reference 7834.
56. Posner B.E.M., Smigelski C. G., Krachenfels M. M. Dietary characteristics and nutrient intake in an urban homebound population. J. Am. Diet. Assoc. 1987a;87:452-456
57. Posner B. M., Ohls J.C., Morgan J. C. The impact of Food Stamps and other variables on nutrient intake in the elderly. J. Nutr. Elder. 1987b;6:3-16
58. Posner B. M., Jette A. M., Smith K. W., Miller D. R. Nutrition and health risks in the elderly: the Nutrition Screening Initiative. Am. J. Public Health. 1993;83:972-978
59. Posner B. M., Jette A. M., Smigelsky C., Miller D. R., Mitchell P. Nutritional risk in New England elders. J. Gerontol. 1994;49:M123-M132
60. Quandt S. A., Rao P. Hunger and food security among older adults in a rural community. Hum. Organs 1999;58:28-35
61. Ritchie C. S., Burgio K., Locher J. L., Cornwell A., Thomas D., Hardin M., Redden D. Nutritional status of urban homebound older adults. Am. J. Clin. Nutr. 1997;66:815-818
62. Roe D. A. In-home nutritional assessment of inner-city elderly. J. Nutr. 1990;120(suppl 11):1538-1543
63. Rose D., Gunderson C., Oliveira V. Socio-economic Determinants of Food Insecurity in the United States: Evidence from the SIPP and CSFII Data Sets. Washington, D.C. 1998 U.S. Department of Agriculture, Economic Research Service Report No. 20036-5831
64. Rose D., Oliveira V. Nutrient intakes of individuals from food-insufficient household in the United States. Am. J. Public Health. 1997;87:1956-1961
65. Roy A. W., Fitzgibbon P. A., Haug M. M. Social support, household composition, and health behaviors as risk factors for four-year mortality in an urban elderly cohort. J. Appl. Gerontol. 1996;15:73-86
66. Ruel M. T., Habicht J.-P., Rasmussen K. M., Martorell R. Screening for nutrition interventions: the risk or the differential-benefit approach. Am. J. Clin. Nutr. 1996;63:671-677
67. Rush D. Nutrition screening in old people. Annu. Rev. Nutr. 1997;17:101-125
68. Schlenker E. D. Nutrition in Aging 1998 McGraw-Hill Boston, MA.
69. Siegel L. M., Attkisson C. C., Carson L. G. Need identification and program planning in the community context. Attkisson C. C. Hargreaves W. A. Horowitz M. J. Sorensen J. E. eds. Evaluation of Human Service Programs 1978 Academic Press New York.
70. Statacorp Stata Statistical Software 1997 Stata Corporation College Station, TX.
71. Stevens D. A., Grivetti L. E., McDonald R. B. Nutrient intake of urban and rural elderly receiving home-delivered meals. J. Am. Diet. Assoc. 1992;92:714-718
72. Trela J., Simmons L. Health and other factors affecting membership and attrition in a senior center. J. Gerontol. 1971;26:46-51
73. Tuma N., Hannan M. Social Dynamics: Models and Methods 1984 Academic Press San Diego, CA.
74. U.S. Department of Health and Human Services Healthy People 2010 2000 Office of Disease Prevention and Health Promotion Washington, D.C.
75. U.S. Department of Health and Human Services National Center for Health Statistics Third National Health and Nutrition Examination Survey 1996:1988-1994 U.S. Department of Health and Human Services National Center for Health Statistics Hyattsville, MD Public Use Data File Documentation No. 76200
76. Vailas L. I., Nitzke S. A., Becker M., Gast J. Risk indicators for malnutrition are associated inversely with quality of life for participants in meal programs for older adults. J. Am. Diet. Assoc. 1998;98:548-553
77. Walker D., Beauchene R. E. The relationship of loneliness, social isolation, and physical health to dietary adequacy of independently living elderly. J. Am. Diet. Assoc. 1991;91:300-304
78. Weimer J. Factors Affecting Nutrient Intake of the Elderly 1998 Food and Rural Economics Division, Economic Research Service, U.S. Department of Agriculture Washington, D.C. Report No. AER-769
79. Wolfe W. S., Olson C. M., Kendall A., Frongillo E. A., Jr Understanding food insecurity in the elderly: a conceptual framework. J. Nutr. Educ. 1996;28:92-100
80. Wracker R. Roberto K. Linda E. eds. Community Resources for Older Adults: Programs and Services in an Era of Change 1998 Pine Forge Press Thousands Oak, CA.
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