Food-insecurity-and-multidimensional-healthy-aging-across-_2026_Social-Scien.pdf
Food insecurity and multidimensional healthy aging across 31 countries:
pooled longitudinal evidence from four cohorts
Guanghui Cui a,b, Mingzheng Hu c, Kaixuan Tang d, Shaojie Li e,*
a Department of Integrated Traditional Chinese and Western Medicine, Peking University First Hospital, Beijing, China
b Institute of Integrated Traditional Chinese and Western Medicine, Peking University, Beijing, China
c Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
d Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
e School of Public Health, Peking University, Beijing, China
A R T I C L E I N F O
Handling Editor: Social Epidemiology Office
Keywords:
Food insecurity
Healthy aging
Functional limitations
Cognitive impairment
Mental health
A B S T R A C T
Food insecurity is a social determinant of health, yet population level evidence on its relation to multidimen
sional healthy aging across countries remains limited. We pooled harmonized data from four longitudinal studies
conducted in the United States, England, 28 European countries, and Mexico from 2010 to 2019, including
232,228 adults aged 60 years or older. Food insecurity was measured with cohort specific questionnaires.
Healthy aging was operationalized across four domains: absence of major diseases, absence of functional limi
tations, no cognitive impairment, and good mental health. Within cohort associations were estimated using
generalized estimating equations and combined using random effects meta-analysis. Food insecurity prevalence
ranged from 0.1 % in Denmark to 31.8 % in Mexico. In meta-analysis, food insecurity was associated with lower
odds of healthy aging (odds ratio 0.78, 95 % confidence interval 0.72 to 0.85). It was most consistently related to
higher odds of functional limitations (odds ratio 1.29, 95 % confidence interval 1.15 to 1.45) and poor mental
health (odds ratio 1.56, 95 % confidence interval 1.35 to 1.80). Regional heterogeneity was evident, with
stronger associations for cognitive impairment in Europe and for functional limitations in Mexico. Associations
were larger among adults younger than 75 years and among those who were physically inactive. Food insecurity
is linked to worse multidimensional healthy aging. Routine screening and mitigation of food insecurity within
aging and social protection programs, tailored to health system capacity and vulnerable subgroups, may help
sustain healthier aging.
1. Introduction
The global aging population is expanding rapidly, with an increasing
number of individuals reaching older ages across all regions. As pop
ulations age, the focus of public health research has increasingly shifted
towards understanding the factors that contribute to "healthy
aging."(Dogra et al., 2022). The World Health Organization defines
healthy aging as the process of developing and maintaining the func
tional ability that enables wellbeing in older age (World Health Orga
nization, 2021). Among the many determinants of healthy aging, food
insecurity has emerged as a critical yet often overlooked factor that af
fects older adults worldwide (Pooler et al., 2018). The Food and Agri
culture Organization (FAO) defines food insecurity as a situation where
an individual lacks consistent access to sufficient, safe, and nutritious
food to support normal growth, development, and a healthy, active
lifestyle (Food and Agriculture Organization of the United Nations,
2025). Older adults, particularly those in low-income or marginalized
communities, are at heightened risk of experiencing food insecurity
(Neves Freiria et al., 2024), which may exacerbate age-related health
challenges, contribute to chronic diseases, and accelerate activities of
daily living decline (Gundersen and Ziliak, 2015). Despite growing
recognition of food insecurity as a significant health risk, previous
cross-national research has primarily focused on its socioeconomic and
structural determinants (Allee et al., 2021; Reeves et al., 2021), with
relatively few studies examining its associations with aging health out
comes across countries. Most evidence on the aging health effects of food
insecurity comes from the United States (Mavegam Tango Assoumou
et al., 2023), with relatively few from low- and middle-income countries
* Corresponding author. School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
E-mail address: li_shaojie@hsc.pku.edu.cn (S. Li).
Contents lists available at ScienceDirect
Social Science & Medicine
journal homepage: www.elsevier.com/locate/socscimed
https://doi.org/10.1016/j.socscimed.2025.118758
Received 24 July 2025; Received in revised form 19 October 2025; Accepted 5 November 2025
Social Science & Medicine 388 (2026) 118758
Available online 6 November 2025
0277-9536/© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Healthy aging was operationalized across four domains: presence of major diseases, absence of functional limi-
(Neves Freiria et al., 2024). As a result, evidence on whether food
insecurity influences multidimensional healthy aging across global
contexts is still insufficient.
Previous epidemiological studies have found significant differences
in the prevalence of food insecurity among older people in different
countries. While in the United States the prevalence of food insecurity is
often reported to be lower among older adults than among working-age
adults, largely due to the buffering effect of social programs such as the
Supplemental Nutrition Assistance Program (SNAP) and Social Security
benefits (Rabbitt et al., 2023; Ziliak et al., 2023), this pattern is not
universal. Evidence from low-and middle-income countries indicates
that older adults can experience disproportionately high levels of food
insecurity, especially in contexts where incomes are limited, household
savings are scarce, and intergenerational support is weakening (Neves
Freiria et al., 2024). For example, a national survey suggested that
nearly one in three older adults aged 60 years or older living in com
munities in Mexico reports moderate/severe level of food insecurity
(P´erez-Zepeda et al., 2016), compared with less than 10 % among those
aged 65+ years in high-income countries (Gatton and Gallegos, 2023).
Even within high income countries, there is substantial heterogeneity.
For example, the rates are relatively low in Nordic countries (such as
Norway) with strong welfare states, but considerably higher in Eastern
and Southern Europe where social protection systems are more fragile
(Gatton and Gallegos, 2023). Beyond these cross-national prevalence
variations, it is also important to consider why older adults themselves
may be especially vulnerable to the adverse consequences of food
insecurity.
From a life-course perspective, older adults may experience greater
exposure to food insecurity due to economic, health, and social changes
that occur later in life. After retirement, income typically becomes fixed
or declines, leaving less flexibility to maintain adequate and nutritious
diets (Patriota and Marques-Vidal, 2021). Rising healthcare expendi
tures further constrain household budgets, while mobility limitations
and cognitive decline can make food acquisition and preparation more
difficult (Pooler et al., 2018; Wylie et al., 1999). In addition, social
changes such as widowhood, living alone, the loss of family caregivers,
and reduced household size weaken informal support networks that
might otherwise help older adults cope with periods of food scarcity (Lee
et al., 2022; Whitelock and Ensaff, 2018).
Beyond higher exposure, older adults are more vulnerable to the
health effects of food insecurity. Nutritional deficiencies in later life can
exacerbate chronic diseases and accelerate frailty (Shlisky et al., 2017).
Limited physiological reserve and multimorbidity reduce the body’s
capacity to recover from dietary deprivation, while psychosocial stress
linked to food insecurity may worsen mental health and functional
decline (Pooler et al., 2018). Thus, food insecurity in older age not only
occurs more frequently but also may lead to more severe health
consequences.
Previous studies have provided evidence supporting these mecha
nisms, linking food insecurity to a range of adverse health outcomes in
older adults, including chronic diseases (Laraia, 2013), functional lim
itations (Gyasi et al., 2022), brain health (McMichael et al., 2022), and
mental health issues (Elgar et al., 2021). However, most existing
research has focused on single health domains or specific conditions,
and few studies have examined food insecurity in relation to multidi
mensional healthy aging. As a result, the overall understanding of how
food insecurity influences multiple aspects of health and functioning in
later life remains limited.
To address these gaps in the literature, this study utilized data from
four large, longitudinal cohort studies (involving 31 countries in North
America and Europe) to examine the cross-regional association between
food insecurity and healthy aging. Specifically, this study investigated
the associations between food insecurity and healthy aging, focusing on
its four key components: major diseases, functional limitations, cogni
tive impairment, and mental health, across different cohorts. Further
more, this study conducted subgroup analysis to determine which
populations are more susceptible to the effect of food insecurity on
healthy aging. This research not only contributes to our understanding
of food insecurity as a determinant of health in older adults but also
provides essential evidence for policymakers and healthcare pro
fessionals to address the growing issue of food insecurity and its impact
on aging populations.
2. Methods
2.1. Study design and participants
This study utilized data from four longitudinal studies, namely the
Health and Retirement Study (HRS), the English Longitudinal Study of
Ageing (ELSA), the Survey of Health, Ageing and Retirement in Europe
(SHARE), and the Mexican Health and Aging Study (MHAS), to enable
cross-regional comparisons of food insecurity and healthy aging (see
supplementary material, pages 4–5). To ensure temporal comparability,
we analyzed data collected between 2010 and 2019 (supplementary
material pp 4), excluding data from 2020 onward due to the potential
confounding effects of the COVID-19 pandemic. Specifically, the anal
ysis included HRS data from 2010 to 2019 (Waves 10 to 14), ELSA data
from 2010 to 2019 (Waves 5 to 9), SHARE data from 2013 to 2019
(Waves 5 to 8, as Wave 4 in 2011 did not assess food insecurity), and
MHAS data from 2012 to 2018 (Waves 3 to 5). We used the harmonized
dataset developed by Gateway to Global Aging Data Team for four
surveys for analysis (Lee et al., 2021). Our study adheres to the
Strengthening the Reporting of Observational Studies in Epidemiology
(STROBE)Statement guidelines (supplementary material pp 1–3).
Following the United Nations’ age classification for older adults
(United Nations Development Programme, 2017), we included partici
pants aged 60 years and older at baseline. Participants with missing data
on food insecurity, healthy aging, or covariates were excluded to ensure
complete case analysis. The study included 232,228 participants aged
≥60 years in final analysis. The study relied on de-identified, publicly
available datasets from these cohorts. All four studies had received
ethical approval from their respective local ethics committees (supple
mentary material pp 4–5), and participants provided informed consent
prior to enrollment. Supplementary material (pp 6–9) showed the
sample selection process for each cohort.
2.2. The measurements of food insecurity
The primary independent variable in this study was food insecurity,
which was assessed differently across the cohorts due to variations in
survey design and question phrasing. In HRS, it was measured with two
questions: (1) “Since the last interview, have you always had enough
money to buy the food you need?” and (2) “In the past 12 months, did
you ever eat less than you felt you should because there wasn’t enough
money for food?” Participants responding “no” to the first or “yes” to the
second were classified as food insecure; all others were deemed food
secure (Lu et al., 2023). In the ELSA, two items were used: (1) “Have
meals ever had to be cut or skipped due to insufficient money for food?”
and (2) “Does having too little money prevent buying your first choice of
food items?” A “yes” to either question indicated food insecurity
(Purdam et al., 2019).
In SHARE, a previous study (Nie and Sousa-Poza, 2018) combined
the affordability of meat, fish, poultry, fruits, and vegetables to create a
proxy measure of food insecurity. However, fruit and vegetable afford
ability was not consistently assessed across all survey waves, whereas
meat, fish, and poultry affordability were available in every wave be
tween 2013 and 2019. To ensure temporal comparability and maintain a
consistent analytic sample, we relied on the meat-based affordability
measure, although it may underrepresent dietary diversity. In SHARE,
household respondents were first asked, “How often does your house
hold eat meat, fish or chicken?” For those reporting less than three times
per week, a follow-up question inquired about the reason: (1) “Cannot
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
2
afford to eat it more often” or (2) “Other reasons.” Respondents selecting
option 1 were classified as food insecure; all others were deemed food
secure. In the MHAS, food insecurity was evaluated with two questions:
(1) “In the last two years, have you always had enough money to buy the
food that you need?” and (2) “At any time in the last two years, did you
not eat or eat less than you wanted because there was not enough food in
your home?”. A “yes” to the first or “no” to the second identified par
ticipants as food secure, with a “no” to the first item or a “yes” to the
second indicating food insecurity (Saenz et al., 2022). Food insecurity
was dichotomized (1 = insecure, 0 = secure) across all cohorts for
analysis.
2.3. The measurements of healthy aging
The primary outcome, healthy aging, was defined based on prior
studies (Rena et al., 2023; Tessier et al., 2025) as the absence of major
diseases, functional limitations, cognitive impairment, and the presence
of good mental health. Major diseases encompassed diabetes, any cancer
or malignant tumor, heart disease, stroke, and chronic lung disease,
identified through self-reports diagnosed by a physician across cohorts.
Functional limitations were evaluated using five Basic Activities of Daily
Living (BADL), namely dressing, bathing, eating, bed transfer, and toi
leting, to ensure consistency across cohorts. Inability to perform any one
of these activities independently classified a participant as having a
functional limitation. Cognitive function assessment varied across co
horts, prompting a standardized approach. We evaluated cognition
using immediate and delayed recall of 10 words (range 0–20), serial
subtraction of seven (five iterations, range 0–5), and three orientation
items (year, month, day, range 0–3). Recognizing the strong influence of
age and education on cognition, we referred to the aging-associated
cognitive decline framework (Levy, 1994) to define impairment. Based
on previous reports (Han et al., 2021), participants were grouped into
five age categories (60–64, 65–69, 70–74, 75–79, and ≥80 years) and
three education levels (less than high school, high school/GED, college
and above), yielding 15 age-education strata. For each stratum, mean
cognitive scores and standard deviations (SD) were calculated, with
cognitive impairment defined as a score below the stratum-specific
mean minus 1 SD. Mental health was characterized by the absence of
depressive symptoms and self-reported emotional, nervous, or psychi
atric conditions diagnosed by a physician. Depressive symptoms were
measured differently across cohorts. The HRS and ELSA utilized the
8-item Centre for Epidemiologic Studies Depression Scale (Andresen
et al., 1994) (CES-D; range 0–8), with a score ≥3 indicating depressive
symptoms. The Mexican Health and Aging Study (MHAS) employed a
9-item CES-D (range 0–9), with a threshold of ≥5 for depressive symp
toms. The SHARE used the 12-item Euro-Depression Scale (Prince et al.,
1999) (Euro-D; range 0–12), with a score ≥4 denoting depressive
symptoms.
2.4. Covariates
Based on previous studies (Behr et al., 2023; Santamaria-Garcia
et al., 2023), this study selected age, sex, marital status, education level,
family wealth, smoking, alcohol consumption, lack of physical activity,
and self-rated health status as potential confounding factors and cova
riates (supplementary material pp 10). This study used the DAGitty
program to create a theoretical model in a directed acyclic graph (sup
plementary material pp 11) to determine the minimal sufficient
adjustment set (MSAS), including age, sex, marital status, education
level, and family wealth.
2.5. Statistical analysis
We described continuous variables with mean and SD and described
categorical variables with frequencies and percentages. To examine the
association between food insecurity and healthy aging, including its
components, we applied Generalized Estimating Equations (GEE) with a
binomial family, logit link function, and an exchangeable correlation
structure, accounting for repeated measures and their correlations. This
approach accounted for repeated measures and their correlations across
waves. Robust standard errors were estimated using the ′vce(robust)′
option in Stata to ensure reliable inference despite potential hetero
scedasticity. The strength of associations was quantified using odds ra
tios (ORs) and their corresponding 95 % confidence intervals (CIs). We
fitted three models: Model 1 remained unadjusted; Model 2 adjusted for
MSAS; and Model 3 adjusted for all covariates. To synthesize findings
across the four cohorts, we conducted pooled analysis by an inverse
variance-weighted random-effects meta-analysis, which allowed for
between-cohort heterogeneity. The I2 statistic was reported to quantify
the degree of heterogeneity. In addition, we performed subgroup ana
lyses based on covariates to assess variations in associations across
population subgroups. Moreover, to explore heterogeneity within
SHARE, we performed subgroup analyses at the regional level (North
ern, Western, Southern, and Eastern Europe).
To evaluate the robustness of the relationship between food insecu
rity and healthy aging, we conducted several sensitivity analyses. First,
we included wave number as a covariate to address potential time effects
across waves. Second, we scored healthy aging continuously (0–4, with
higher scores indicating better healthy aging) and estimated its associ
ation with food insecurity using GEE with a Poisson distribution,
reporting incidence rate ratios (IRRs) and 95 % CIs. Third, we addressed
potential attrition bias using Inverse Probability Weighting (IPW).
Specifically, we estimated the probability of participants remaining in
the study using a logistic regression model, and then assigned weights to
each participant based on the inverse of their predicted probability.
Fourth, we imputed missing covariate data using multiple imputation by
chained equations (MICE) with 10 imputations, applying multinomial
logistic regression for categorical variables and logistic regression for
binary variables, then re-analyzed the imputed datasets. Fifth, to eval
uate whether heterogeneity in food insecurity measurement influenced
our findings, we repeated the pooled analysis after sequentially
excluding SHARE and ELSA to assess whether the pooled estimates were
disproportionately driven by a single cohort’s measurement approach.
In addition, to assess the validity of the food insecurity measure in
SHARE, we conducted a supplementary analysis using data from Wave 5
(2013), which was the only wave that included additional two-step
questions on the affordability of fruits and vegetables. In this wave,
respondents were first asked how often their household consumed fruits
or vegetables. Those who reported eating them less than three times per
week were then asked for the reason, with one response option being
“Cannot afford to eat it more often.” We then constructed an alternative
indicator of food insecurity that classified respondents as food insecure
if they reported being unable to afford any of the following: meat, fish,
poultry, fruits, or vegetables. This alternative indicator was compared
with the original meat-based measure to examine their level of agree
ment and to test whether associations with healthy aging outcomes and
its components were consistent based on logistic regression models.
Finally, a sensitivity analysis was conducted using data from the SHARE
cohort to examine whether countries with extremely low prevalence of
food insecurity influenced the overall findings. Countries were classified
according to their national prevalence of food insecurity, with those
below 1 % defined as the low-prevalence group (Austria, Germany,
Sweden, the Netherlands, Spain, Denmark, Switzerland, Belgium,
Luxembourg, Portugal, and Finland). GEE models were re-estimated
separately for countries with food insecurity prevalence below 1 %
and those with prevalence ≥1 %, adjusting for the same covariates as in
the main SHARE analysis. We performed all analyses in Stata 17.0,
considering P < 0.05 as statistically significant.
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
3
3. Results
3.1. Participants characteristics
Table 1 shows the characteristics of participants across the four co
horts: HRS (N = 64,749), ELSA (N = 33,462), SHARE (N = 106,609),
and MHAS (N = 27,408). The mean ages of participants in HRS, ELSA,
SHARE, and MHAS were 72.7, 71.2, 71.6, and 70.6 years, respectively.
Females comprised 54.8 %–58.2 % of participants across cohorts. Edu
cation levels varied widely, with 88.8 % of MHAS participants having
less than high school education compared to 19.6 % in HRS; college
education was highest in HRS (22.4 %) and lowest in MHAS (8.7 %). The
proportion of food insecurity and healthy aging varied significantly
across the 31 countries studied (Fig. 1 and supplementary material pp
12). Food insecurity ranged from as low as 0.1 % in Denmark to as high
as 31.8 % in Mexico. Healthy aging varied from 19.4 % in Lithuania to
50.0 % in Slovakia. The overall proportion of food insecurity was 2.4 %
in SHARE, 4.6 % in ELSA, and 7.7 % in HRS. The overall proportion of
healthy aging was 24.9 % in HRS, 34.2 % in ELSA, 32.7 % in SHARE, and
31.2 % in MHAS. For the components of healthy aging, major diseases
were reported by 45.0 % (MHAS) to 61.4 % (HRS), functional limita
tions by 12.6 % (SHARE) to 20.4 % (HRS), and cognitive impairment by
14.0 % (HRS) to 16.7 % (MHAS). Good mental health was reported by
66.4 % (SHARE) to 73.8 % (ELSA).
3.2. Association between food insecurity and healthy aging
Table 2 shows the results of the association between food insecurity
and healthy aging across four cohort studies. In HRS, food insecurity was
associated with lower odds of healthy aging (fully-adjusted model: OR
= 0.78, 95 % CI: 0.73–0.84), with similar findings in ELSA (fully-
adjusted model: OR = 0.88, 95 % CI: 0.79–0.98). SHARE showed the
strongest association (fully-adjusted model OR = 0.67, 95 % CI:
0.60–0.75), while MHAS indicated a slightly weaker but significant link
(fully-adjusted model OR = 0.81, 95 % CI: 0.76–0.85). Pooled analysis
across cohorts confirmed a consistent inverse relationship (Model 3: OR
= 0.78, 95 % CI: 0.72–0.85), though significant heterogeneity was
observed (I2 = 77.1 %, p = 0.004), suggesting variability across
populations.
The associations between food insecurity and four components of
healthy aging were displayed in Fig. 2. In HRS, food insecurity was
significantly associated with increased odds of having major diseases
(OR = 1.10, 95 % CI: 1.05–1.14), functional limitations (OR = 1.47, 95
% CI: 1.37–1.58), and poor mental health (OR = 1.32, 95 % CI:
1.25–1.39), but not with cognitive impairment. Similarly, in ELSA, food
insecurity was associated with higher odds of functional limitations (OR
= 1.26, 95 % CI: 1.11–1.43) and poor mental health (OR = 1.52, 95 %
CI: 1.38–1.69), while no significant associations were observed for
major diseases or cognitive impairment. In SHARE, food insecurity was
strongly associated with cognitive impairment (OR = 1.41, 95 % CI:
1.28–1.55) and poor mental health (OR = 1.81, 95 % CI: 1.66–1.98),
while associations with major diseases and functional limitations were
not statistically significant. In MHAS, food insecurity was significantly
associated with functional limitations (OR = 1.35, 95 % CI: 1.27–1.44),
cognitive impairment (OR = 1.25, 95 % CI: 1.17–1.34), and poor mental
health (OR = 1.65, 95 % CI: 1.56–1.74), with no significant association
observed for major diseases. In the pooled analysis, food insecurity was
significantly associated with higher odds of functional limitations (OR
= 1.29, 95 % CI: 1.15–1.45) and poor mental health (OR = 1.56, 95 %
CI: 1.35–1.80). The associations with major diseases and cognitive
impairment did not reach statistical significance. Substantial heteroge
neity was observed across cohorts for all outcomes (I2 ranging from 83.7
% to 94.1 %, all p < 0.001).
Table 1
Characteristics of participants in four longitudinal studies.
Variables
HRS (N =
64749)
ELSA (N =
33462)
SHARE (N =
106609)
MHAS (N =
27408)
Age, mean (sd)
72.7 (8.9)
71.2 (7.8)
71.6 (8.0)
70.6 (7.6)
Sex, n (%)
Females
37708
(58.2 %)
18339
(54.8 %)
59196 (55.5
%)
15260
(55.7 %)
Males
27041
(41.8 %)
15123
(45.2 %)
47413 (44.5
%)
12148
(44.3 %)
Education, n (%)
Less than high
school or GED
12677
(19.6 %)
10150
(30.3 %)
44289 (41.5
%)
24326
(88.8 %)
High-school or
GED
37565
(58.0 %)
17544
(52.4 %)
39247 (36.8
%)
703 (2.6 %)
College and
above
14507
(22.4 %)
5768 (17.2
%)
23073 (21.6
%)
2379 (8.7
%)
Marital status, n (%)
Others
29050
(44.9 %)
11873
(35.5 %)
34433 (32.3
%)
10097
(36.8 %)
Married
35699
(55.1 %)
21589
(64.5 %)
72176 (67.7
%)
17311
(63.2 %)
Family wealth, n (%)
Q1
13311
(20.6 %)
7802 (23.3
%)
27027 (25.4
%)
6392 (23.3
%)
Q2
15317
(23.7 %)
8505 (25.4
%)
27305 (25.6
%)
6683 (24.4
%)
Q3
17263
(26.7 %)
8600 (25.7
%)
26423 (24.8
%)
6943 (25.3
%)
Q4
18858
(29.1 %)
8555 (25.6
%)
25854 (24.3
%)
7390 (27.0
%)
Self-rated health, n (%)
Poor
5441 (8.4
%)
2724 (8.1
%)
11852 (11.1
%)
592 (2.2 %)
Fair
14436
(22.3 %)
6704 (20.0
%)
32132 (30.1
%)
978 (3.6 %)
Good
44872
(69.3 %)
24034
(71.8 %)
62625 (58.7
%)
25838
(94.3 %)
Current smoking, n (%)
No
58182
(89.9 %)
30260
(90.4 %)
88488 (83.0
%)
24653
(89.9 %)
Yes
6567 (10.1
%)
3202 (9.6
%)
18121 (17.0
%)
2755 (10.1
%)
Current drinking, n (%)
No
31961
(49.4 %)
7456 (22.3
%)
55370 (51.9
%)
21380
(78.0 %)
Yes
32788
(50.6 %)
26006
(77.7 %)
51239 (48.1
%)
6028 (22.0
%)
Physical inactivity, n (%)
No
20549
(31.7 %)
8950 (26.7
%)
46078 (43.2
%)
8959 (32.7
%)
Yes
44200
(68.3 %)
24512
(73.3 %)
60531 (56.8
%)
18449
(67.3 %)
Food insecurity, n (%)
No
59758
(92.3 %)
31917
(95.4 %)
104045 (97.6
%)
18700
(68.2 %)
Yes
4991 (7.7
%)
1545 (4.6
%)
2564 (2.4 %)
8708 (31.8
%)
Major diseases, n (%)
No
24976
(38.6 %)
17972
(53.7 %)
55070 (51.7
%)
15069
(55.0 %)
Yes
39773
(61.4 %)
15490
(46.3 %)
51539 (48.3
%)
12339
(45.0 %)
Functional limitations, n (%)
No
51547
(79.6 %)
27218
(81.3 %)
93206 (87.4
%)
22031
(80.4 %)
Yes
13202
(20.4 %)
6244 (18.7
%)
13403 (12.6
%)
5377 (19.6
%)
Cognitive impairment, n (%)
No
55716
(86.0 %)
28501
(85.2 %)
90276 (84.7
%)
22840
(83.3 %)
Yes
9033 (14.0
%)
4961 (14.8
%)
16333 (15.3
%)
4568 (16.7
%)
Mental health, n (%)
Yes
44787
(69.2 %)
24679
(73.8 %)
70757 (66.4
%)
18531
(67.6 %)
(continued on next page)
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
4
Characteristics of participants in seven longitudinal studies.
3.3. Subgroup and sensitivity analyses
Fig. 3 presents the associations between food insecurity and healthy
aging across different subgroups. Subgroup analyses revealed substan
tial heterogeneity in these associations. Notably, consistent findings
across the four cohorts indicated that the associations were more pro
nounced among individuals aged below 75 years and those with insuf
ficient physical activity. In additional subgroup analyses within SHARE,
countries were classified into four European regions. Food insecurity
was consistently associated with lower odds of healthy aging across
regions, with ORs ranging from 0.61 in Southern Europe to 0.79 in
Eastern Europe. Associations with mental health were strong in all re
gions, particularly in Southern Europe. Cognitive impairment was also
associated with food insecurity in Northern and Eastern Europe,
whereas major diseases showed mixed results across regions. More
specific results of subgroup analysis can be found in supplementary
material (pp 13–15).
In the first sensitivity analysis, the associations between food inse
curity and healthy aging remained significant across all four cohorts
after adjusting for time effects. When using a continuous healthy aging
score as the outcome variable, food insecurity was associated with lower
healthy aging index values. Furthermore, applying IPW in the GEE
models yielded consistent results, with food insecurity still significantly
associated with healthy aging. Lastly, results after multiple imputation
were in line with those of the main analysis. In addition, we conducted
sensitivity analyses on food insecurity and four healthy aging compo
nents, which is consistent with the results in Fig. 2. Finally, to address
heterogeneity in food insecurity measurement, we repeated the pooled
analysis after excluding SHARE and ELSA. The pooled association be
tween food insecurity and healthy aging was robust (OR 0.80, 95 % CI
0.76–0.83), and associations with functional limitations and mental
health remained evident (Table S10). A supplementary validation
analysis based on SHARE Wave 5, the only wave that included addi
tional questions on fruit and vegetable affordability, showed that the
extended definition of food insecurity produced slightly higher preva
lence estimates than the original meat-based measure (Table S11). The
two measures demonstrated almost perfect agreement (κ = 0.92; SE =
0.0047; p < 0.001; Table S12). Logistic regression models using both
Table 1 (continued)
Variables
HRS (N =
64749)
ELSA (N =
33462)
SHARE (N =
106609)
MHAS (N =
27408)
No
19962
(30.8 %)
8783 (26.2
%)
35852 (33.6
%)
8877 (32.4
%)
Healthy aging, n (%)
No
48642
(75.1 %)
22014
(65.8 %)
71734 (67.3
%)
18850
(68.8 %)
Yes
16107
(24.9 %)
11448
(34.2 %)
34875 (32.7
%)
8558 (31.2
%)
Note: GED = General Educational Development.
Fig. 1. The proportion of food insecurity and healthy aging across the 31 countries in four longitudinal studies.
Table 2
Association between food insecurity and healthy aging.
Cohorts/
Outcomes
Model 1
Model 2
Model 3
OR (95 %CI)
OR (95 %CI)
OR (95 %CI)
HRS
0.80 (0.76–0.85)
0.77 (0.72–0.82)
0.78 (0.73–0.84)
ELSA
0.86 (0.79–0.94)
0.83 (0.75–0.91)
0.88 (0.79–0.98)
SHARE
0.52 (0.48–0.57)
0.59 (0.53–0.65)
0.67 (0.60–0.75)
MHAS
0.79 (0.75–0.83)
0.80 (0.76–0.85)
0.81 (0.76–0.85)
Pooled analysis
0.73 (0.61–0.88)
0.74 (0.66–0.84)
0.78 (0.72–0.85)
Heterogeneity
I2 = 96.6 %, p <
0.001
I2 = 90.0 %, p <
0.001
I2 = 77.1 %, p =
0.004
Note: Model 1 remained unadjusted; Model 2 adjusted for MSAS; and Model 3
adjusted for all covariates.
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
5
definitions yielded consistent associations with healthy aging outcomes
(Table S13), supporting the validity of the single-item indicator applied
across other waves. In the SHARE sensitivity analysis, the mean preva
lence of food insecurity was 0.5 % among the 11 low-prevalence coun
tries and 4.2 % among the remaining 17 countries. The associations
between food insecurity and healthy aging outcomes were consistent
across both groups (Table S14). These results suggest that inclusion of
countries with minimal food insecurity did not materially affect the
overall associations observed in SHARE. More detailed findings from the
sensitivity analyses are presented in the supplementary material (pp
16–23).
4. Discussion
This study was the first to explore the association between food
insecurity and healthy aging among older adults using four large sample
population surveys from diverse regions. In this study, we provided
evidence that food insecurity is significantly associated with lower odds
of healthy aging. Our analysis revealed that food insecurity was
consistently linked to negative outcomes in key components of healthy
aging, particularly functional limitations and poor mental health. These
findings suggested that food insecurity may play a significant role in
exacerbating age-related declines in physical and mental well-being,
underscoring the importance of addressing food insecurity in older
populations.
The prevalence of food insecurity varied widely across the 31
countries included in this study. In the United States, 7.7 % of older
adults were food insecure, a level considerably higher than that
observed in most European countries. England reported a prevalence of
4.6 %, which was lower than the United States but higher than many
Fig. 2. Associations between food insecurity and four components of healthy aging.
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
6
Western European countries. Within continental Europe, Northern and
Western countries generally had very low prevalence, often below 1 %,
as seen in Denmark, Sweden, the Netherlands, Germany, and Austria. In
contrast, Southern and Eastern Europe showed higher levels, with
Greece at 9.6 %, Lithuania at 8.2 %, Romania at 8.0 %, and Slovakia at
10.8 %. Mexico recorded the highest prevalence, with nearly one in
three older adults classified as food insecure. These variations partly
reflect differences in economic resources, welfare systems, and social
safety nets, but they are also connected to the instruments applied in
each cohort. HRS and MHAS focused on financial barriers and hunger
experiences, capturing the sufficiency of quantity and episodes of
deprivation (Norwood and Wunderlich, 2006). ELSA emphasized coping
strategies such as meal skipping and restricted food choice, which
identify earlier stages of constrained food access (Maxwell, 1996).
SHARE relied on affordability of meat, fish, and poultry, which reflects
access to protein-rich foods and dietary diversity but may also be
influenced by cultural or health-related dietary preferences (Penne and
Goedem´e, 2021; Walker and Baum, 2022). These conceptual differences
imply that very low prevalence rates in some countries may not only
represent favorable conditions but also the narrower dimension of food
insecurity assessed by the instrument. These results mean that direct
comparison of prevalence rates across countries should be made with
caution, as the instruments do not capture identical domains of food
insecurity. The lack of harmonized measures limits the extent to which
prevalence estimates can be interpreted as reflecting equivalent expe
riences across settings. Future research would benefit from the devel
opment and application of standardized instruments that incorporate
both quantity sufficiency and dietary quality, which would allow for
more consistent monitoring and more reliable cross-national compari
sons of food insecurity among older adults.
The pooled analysis from the four cohorts demonstrated that food
insecurity is associated with a reduced likelihood of healthy aging. A
previous study, from the perspective of biological aging, supports the
findings of our study, indicating that food insecurity may lead to alter
ations in DNA methylation across the entire genome and result in
accelerated biological aging (Tamargo and Cruz-Almeida, 2024). While
the strength of this association in our analysis varied by region, the
overall trend of food insecurity negatively impacting aging was clear.
Our finding suggested food insecurity can be considered a key driver of
poor healthy aging. Several potential mechanisms can explain these
associations. The most direct pathway may be through economic stress,
where the anxiety and worry about not having enough money to pur
chase adequate food can increase physiological stress (Ciciurkaite and
Brown, 2022). Chronic stress is well-documented to negatively affect
both physical and mental health, leading to elevated long-term risk of
mental and physical morbidity, weakened immune function, and
accelerated aging (Agorastos and Chrousos, 2022; Hansen et al., 2025;
Klopack et al., 2022), all of which contribute to a decline in healthy
aging. Previous evidence from the United States has provided direct
support for our finding that food insecurity is associated with higher
allostatic loads and higher levels of inflammation and immune
dysfunction (Aljahdali et al., 2024; Pak and Kim, 2021). Additionally,
nutritional deficiencies are a central consequence of food insecurity.
Older adults are particularly vulnerable to poor nutrition, which can
exacerbate existing health conditions or accelerate the onset of
age-related diseases (Dent et al., 2023). Inadequate intake of essential
nutrients, such as vitamins and minerals, can impair cognitive function,
muscle strength, and bone density, leading to functional limitations and
increased frailty (Artaza-Artabe et al., 2016; Fekete et al., 2023).
Another significant factor is the lack of access to healthcare. Food
insecurity often overlaps with other social determinants of health, such
as low socioeconomic status, limited healthcare access, and unstable
housing (Pirrie et al., 2020). Older adults in food-insecure households
may struggle to access regular medical care, preventive services, or
necessary medications, which can delay healthcare and result in poorer
health outcomes (Ostrer and Seligman, 2025).
Subgroup analyses indicated that this association was more pro
nounced among individuals aged under 75 years and those with insuf
ficient physical activity. The stronger association observed in
individuals aged under 75 years may reflect age-related differences in
resilience and compensatory mechanisms (Harvanek et al., 2021).
Younger older adults (under 75) likely retain greater metabolic flexi
bility and adaptive capacity compared to their older counterparts,
making them more responsive to both nutrient sensing and nutritional
deficiencies (Martemucci et al., 2022). While this group may not yet
exhibit advanced chronic conditions, food insecurity could accelerate
subclinical pathological processes, such as chronic inflammation or
oxidative stress, which are strongly linked to functional decline
(Aljahdali et al., 2024; Wells et al., 2020). Conversely, adults ≥75 years
may experience accumulated health deficits with aging, where cumu
lative comorbidities mask the specific effects of food insecurity (Tan
et al., 2025). In addition, the amplified association between food
Fig. 3. Associations between food insecurity and healthy aging across different subgroups.
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
7
insecurity and healthy aging in those with physical inactivity likely
stems from bidirectional pathophysiological interactions. Physical
inactivity exacerbates metabolic dysregulation (e.g., insulin resistance,
reduced lipid clearance), which may synergize with nutritional de
ficiencies from food insecurity to accelerate biological aging (Shur et al.,
2021; Tamargo and Cruz-Almeida, 2024). This vicious cycle mirrors
findings that food-insecure populations are more likely to engage in low
physical activity (Maia et al., 2023), which in turn compounds over
lapping socioeconomic barriers (e.g., limited access to exercise facil
ities). These barriers further exacerbate food access difficulties, creating
a series of disadvantage. These subgroups heightened vulnerability un
derscores the need for integrated food insecurity interventions targeting
both nutritional support and mobility promotion. Subgroup analyses
within SHARE further indicated regional variation. Although food
insecurity was associated with reduced odds of healthy aging across all
European regions, the magnitude differed, with stronger associations in
Southern and Northern Europe and weaker associations in Eastern and
Western Europe. Mental health outcomes were consistently affected,
with particularly strong associations in Southern Europe, while re
lationships with major diseases and functional limitations varied across
regions. These patterns suggest that both contextual conditions and the
measurement dimension captured by SHARE influence the observed
associations, reinforcing the need for caution when generalizing find
ings across diverse welfare and cultural settings. In addition, a supple
mentary subgroup analysis based on a 1 percent prevalence threshold
showed consistent results across countries with lower and higher na
tional levels of food insecurity. This suggests that the observed associ
ations are robust and not driven by countries where food insecurity is
nearly absent.
In healthy aging components, this association was particularly strong
in relation to functional limitations and mental health issues, which
were the most consistently affected outcomes by food insecurity across
all cohorts. Food insecurity’s strong association with functional limita
tions is consistent with prior research (Gyasi et al., 2022). Functional
limitations in older adults are a key indicator of poor health and
increased dependency, leading to diminished quality of life (Gyasi et al.,
2022). Food insecurity may exacerbate these limitations by contributing
to nutritional deficiencies, and increasing vulnerability to diseases that
impair mobility and daily activities (Awuviry-Newton et al., 2022).
Similarly, a previous systematic review and meta-analysis also found
that food insecurity is related to poor mental health, including depres
sive symptoms and stress (Pourmotabbed et al., 2020). The psycholog
ical stress of not having enough food to meet basic needs can exacerbate
feelings of hopelessness and loneliness, significantly diminishing an in
dividual’s mental well-being (Gyasi et al., 2024). Food insecurity was
also linked to cognitive decline, as shown in the SHARE and MHAS
cohorts, where food insecurity was strongly associated with cognitive
impairment, although there was no statistical significance in the pooled
analysis. A previous systematic review supported our finding, that is,
food insecurity is associated with cognitive function across the life
course (Royer et al., 2021).
The heterogeneity observed across cohorts is an important aspect of
the study’s findings. Although the food insecurity measurements in four
cohorts emphasized distinct aspects, including financial constraints,
hunger experiences, coping behaviors, and affordability of protein-rich
foods, the adverse association with healthy aging was observed in all
cohorts. Sensitivity analyses confirmed the robustness of these findings.
The association between food insecurity and healthy aging remained
significant after adjusting for time effects, when using a continuous
healthy aging score, when applying inverse probability weighting, and
after multiple imputation. Analyses of food insecurity with the four
components of healthy aging produced results consistent with the main
analysis. In addition, repeating the pooled analysis while excluding
SHARE or ELSA yielded similar estimates, indicating that the overall
conclusions were not driven by the measurement approach of a single
cohort. In a supplementary validation analysis using SHARE Wave 5,
where additional information on fruit and vegetable affordability was
available, the extended definition of food insecurity produced slightly
higher prevalence estimates but yielded consistent associations with
healthy aging outcomes. This finding supports the validity and robust
ness of the single-item measure applied in other SHARE waves. The
robustness of the findings across SHARE countries with different food
insecurity prevalence supports the stability of the observed associations.
These results suggest that despite heterogeneity in measurement, the
relationship between food insecurity and healthy aging is stable across
alternative specifications. This suggests that food insecurity is a global
issue with widespread implications for aging populations, though the
severity of its impact may vary depending on local contexts.
The findings from this study carry important implications for public
health policy and practice, particularly in countries with high rates of
food insecurity among older adults, such as Mexico. Recently, the US
Preventive Services Task Force (USPSTF) provided new recommenda
tions and evidence regarding the prevention of food insecurity, and
noted that the evidence for screening in healthcare settings remains
insufficient (O’Connor et al., 2025; US Preventive Services Task Force,
2025). While the USPSTF’s stance on screening remains cautious, our
research suggests that targeted interventions for older adults at risk of
food insecurity could have a positive impact on aging outcomes.
Moreover, as the USPSTF points out, food insecurity is intricately tied to
social determinants of health such as poverty and housing instability,
factors that extend beyond the healthcare system. Therefore, public
health policies should focus on addressing these broader social de
terminants in addition to increasing access to nutritious food. This aligns
with the findings of our study, which suggests that interventions must be
multifaceted, targeting not just food access, but also the social and
economic factors contributing to food insecurity, particularly in regions
like Mexico where these issues are more pronounced. In light of the
USPSTF’s recommendations, we propose that healthcare systems inte
grate food insecurity screening into routine assessments for older adults
at risk, while simultaneously prioritizing collaboration with community
organizations and social services to ensure holistic care. One potential
policy recommendation is to expand food assistance programs, such as
subsidized grocery schemes or community-based food programs, that
target older adults at risk of food insecurity (O’Connor et al., 2025).
These programs could be particularly impactful in countries with large
low-income populations, where food insecurity is often a direct result of
economic hardship.
This study benefits from a longitudinal design, allowing for the ex
amination of the long-term effects of food insecurity on healthy aging.
The use of repeated measures across multiple waves enables us to better
understand the dynamic relationship between food insecurity and aging
outcomes over time. The inclusion of four geographically distinct co
horts, which represent the United States, the England, Europe, and
Mexico, enhances the generalizability of the findings and provides
valuable cross-cultural insights into the relationship between food
insecurity and aging. The study also employed rigorous statistical
methods, including Generalized Estimating Equations and random-
effects meta-analysis, which ensure robust and reliable estimates of
the associations between food insecurity and healthy aging. Sensitivity
analyses, such as inverse probability weighting and multiple imputation,
further strengthen the validity of the results by addressing potential
biases and missing data.
This has several limitations that should be acknowledged. First, food
insecurity was measured differently across cohorts, which reduces
comparability. Although each food insecurity measurement has validity
within its own context, they capture different domains of food insecu
rity, and the pooled estimates should therefore be interpreted as
reflecting a broad vulnerability rather than the same construct across
cohorts. In addition, the validation of the food insecurity measure in the
SHARE data was limited to Wave 5, which was the only wave that
included additional questions on fruit and vegetable affordability.
Although the two definitions showed almost perfect agreement, this
G. Cui et al.
Social Science & Medicine 388 (2026) 118758
8
European regions, the magnitude differed, with weaker associations in Preventive Services Task Force (USPSTF) provided new recommenda-
validation was based on a single cross-sectional wave and may not fully
reflect measurement consistency across other waves or contexts.
Second, although this study controlled for several important cova
riates, there may be residual confounding from unmeasured factors. For
instance, information on the quality of the diet and healthcare access
was not available across all cohorts, which could influence both food
insecurity and health outcomes. The cohorts included in this study are
representative of specific countries or regions but may not fully capture
the experiences of food insecure older adults in other settings, particu
larly in low-income countries without large-scale cohort studies. The
generalizability of the findings to non-Western or non-industrialized
regions remains an important area for further research. Moreover,
another limitation is the aggregation of all 28 SHARE countries.
Although this improved statistical power, it inevitably masked between-
country heterogeneity. We did not conduct country-specific analyses
because in several countries the prevalence of food insecurity was
extremely low, leading to insufficient case numbers for stable model
estimation of associations with healthy aging and its components. To
address this concern, we instead conducted analyses at the regional level
(Northern, Western, Southern, and Eastern Europe), which offered a
balance between statistical stability and cross-national comparability. In
addition, although a sensitivity analysis within the SHARE cohort using
a 1 % prevalence threshold suggested that the inclusion of countries
with very low food insecurity did not materially affect the results, dif
ferences in social and welfare contexts across countries may still limit
direct comparability. Finally, the exclusion of data from 2020 onward
due to the COVID-19 pandemic may limit the applicability of these
findings to the current situation. The pandemic likely exacerbated food
insecurity and health disparities, and future research should examine
how the COVID-19 crisis has affected food insecurity and healthy aging
in older populations.
5. Conclusion
This study demonstrates that food insecurity is a significant predictor
of poor health outcomes in older adults, including functional limitations,
cognitive impairment, and poor mental health. Despite regional differ
ences in food insecurity prevalence and the social contexts in which
these cohorts are situated, the negative association between food inse
curity and healthy aging holds across diverse populations. These find
ings underscore the importance of addressing food insecurity as a public
health priority, especially as the global population continues to age.
Policymakers and healthcare providers should consider food insecurity
as a crucial determinant of health and take steps to ensure that older
adults have access to sufficient, nutritious food to support their aging
process. Future research should continue to explore the pathways
through which food insecurity affects aging and investigate in
terventions that can improve the health and well-being of older adults.
CRediT authorship contribution statement
Guanghui Cui: Writing – original draft, Methodology, Formal
analysis, Conceptualization. Mingzheng Hu: Writing – review & edit
ing. Kaixuan Tang: Writing – review & editing. Shaojie Li: Writing –
review & editing, Validation, Conceptualization.
Ethics approval
The study relied on de-identified, publicly available datasets from
these cohorts. All four studies had received ethical approval from their
respective local ethics committees, and participants provided informed
consent prior to enrollment.
The Health and Retirement Study (HRS) has received ethical
approval from the University of Michigan Institutional Review Board
(IRB Protocol: HUM0061128).
The English Longitudinal Study of Ageing (ELSA) received ethical
approvals from various committees, including the Berkshire Research
Ethics Committee and the South Central – Berkshire Research Ethics
Committee. The specific ethical approval for ELSA is as follows.
ELSA Wave 9 received ethical approval from the South Central –
Berkshire Research Ethics Committee on May 10, 2018 (17/SC/0588).
ELSA Wave 8 received ethical approval from the South Central –
Berkshire Research Ethics Committee on September 23, 2015 (15/SC/
0526).
ELSA Wave 7 received ethical approval from the NRES Committee
South Central - Berkshire on November 28, 2013 (13/SC/0532).
ELSA Wave 6 received ethical approval from the NRES Committee
South Central - Berkshire on November 28, 2012 (11/SC/0374).
ELSA Wave 5 received ethical approval from the Berkshire Research
Ethics Committee on December 21, 2009 (09/H0505/124).
The Survey of Health, Ageing and Retirement in Europe (SHARE) has
been reviewed and approved by the Ethics Committee of the University
of Mannheim and the Ethics Council of the Max Planck Society, with
additional approvals from respective national ethics committees.
The Mexican Health and Aging Study (MHAS) study c had received
ethical approval from the Institutional Review Board of the University of
Texas Medical Branch, the Instituto Nacional de Estadística y Geografía
(INEGI) in Mexico, and the Instituto Nacional de Salud Pública (INSP) in
Mexico.
Funding
This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.
Declaration of interest statement
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgments
We acknowledge the Gateway to Global Aging Data for providing
harmonized data. We are also grateful to the participants, investigators,
and staff involved in the Health and Retirement Study, the English
Longitudinal Study of Ageing, the Survey of Health, Ageing and
Retirement in Europe, and the Mexican Health and Ageing Study.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.socscimed.2025.118758.
Data availability
All original data used in the study can be obtained from the Gateway
to Global Aging Data (https://g2aging.org).
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