Purpose: There is limited research on how the relational and generational make-up of household members relates to experiencing food insecurity among older populations. This gap may obscure our understating of the contexts in which older individuals face inadequate food access. We describe the prevalence of experiencing food insecurity in households with at least one member aged 60 or older in the United States.
Methods: We used nationally representative 2020 and 2021 Current Population Survey Food Security Supplement data. Our sample included households with someone age 60+ (n=24,436). We defined household composition as: single person households, partners only, two-generation (e.g., parent, child), three plus generation (e.g., grandparent, parent, child), skipped generation (e.g., grandparents, grandchild), or other arrangements. We also classified households for selected demographic characteristics. We estimated the prevalence of food insecurity for each type of household.
Results: Most households with a member aged 60+ were single person households (36.3%) or partners only (35.9%), while fewer were in two-generation (14.1%), three plus generation (3.4%), skipped generation (1.3%) or other arrangement (9.0%). Households with at least one member belonging to a minoritized racial or ethnic group were more likely to be two-generation, three plus generation, skipped generation, or other arrangement households. Overall, 8.5% [8.0-8.9%] of households experienced food insecurity. The prevalence of food insecurity was lowest for partners only (3.6% [3.2-4.1%]), slightly above the average for single person households (10.6% [9.8-11.4%]) and two generation (10.0% [8.9-11.3%]), and highest for three plus generation (16.7% [13.6-20.4%]) and skipped generation (18.1% [13.6-23.8%]) households.
Conclusion: Households with differing generational and relational compositions also experienced food insecurity at differing rates. Polices and programs designed to support food security among adults aged 60+ should be inclusive of the wide variety of households they live in. For example, Older Americans Act nutrition programs specify that spouses under the age of 60 are eligible to receive meals, but do not have explicit allowances for other family members such as grandchildren. This type of oversight may discourage older adults with the most need, such as those living in skipped and three plus generation households, from accessing food assistance.

Purpose: The interplay between Older Adults’ 24-hour movement behaviors, Well-being, Cognition, and BMI remains largely unexplored. This study aimed to investigate the interdependent relationship of older adults’ daily engagement in physical activity (PA), sedentary behavior (SB), and sleep (S) in the context of a Tai Chi intervention.

Method: A total of 41 healthy older adults participated in a remote Tai Chi program, employing a cross-over design. Participants wore a Fitbit band (Inspire 3) for an average of at least 23 hours a day, five days a week, over six months. The Fitbit device continuously tracked Light PA, Very Active PA, SB, and Sleep durations. Quality of Life and Cognitive flexibility were assessed using the Older People’s Quality of Life Questionnaire and the Dimensional Change Card Sort Test, respectively. BMI was calculated using participants' weight (kg) and height (m) squared. A compositional analysis (CODA) paradigm was used to investigate the codependent associations among these variables.

Result: Linear regression models utilizing CODA indicated significant associations between the outcomes and the relative time spent in the four-movement behaviors. BMI showed a strong relationship (p<0.01), and Quality of Life was also significantly associated (p=0.0024), while cognitive flexibility approached significance (p=0.06), hinting at a potential link with Light PA. The models accounted for a substantial proportion of the variance in BMI (Adj. R2 = 0.977), with the proportion of time in Very Active PA being particularly influential (B=-0.87, p=0.014). Quality of Life models explained a moderate variance (Adj. R2 = 0.295), though no proportional times were significantly linked.

Conclusion: Very Active PA emerges as a key focus for interventions targeting older adults, significantly influencing BMI. Although not statistically significant, a potential positive correlation between light PA and cognitive flexibility in older adults was observed.

Title: Associations of physical activity, sedentary behavior, and sleep patterns with cognitive function among middle-aged and older community-dwelling adults: A latent class analysis

Authors: Yuzi Zhang, Laura F. DeFina, David Leonard, Baojiang Chen, Emily T. Hébert, Harold W. Kohl III

Purpose: The current study aimed to identify movement patterns of physical activity, sitting time (ST), and sleep and examine the association of movement patterns with cognitive function.

Methods: This cross-sectional study included 1,240 participants aged ≥55 years participating in the Cooper Center Longitudinal Study who visited the Cooper Clinic, Dallas (2016-2019) for preventive health care. Four movement behaviors, including leisure-time aerobic activity, muscle-strengthening activity, ST, sleep, and other characteristics, were self-reported. Cognitive function was assessed by the Montreal Cognitive Assessment (MoCA). Four categorical indicators were created for each movement behavior and used to identify latent classes using latent class analysis. Information criterion, relative entropy, and model interpretability were used to determine the optimal number of classes. Participants were assigned to the predicted classes based on their highest posterior probabilities. Multinomial regressions examined the association between movement patterns and each covariate. Linear regression models examined the association of movement patterns and cognitive function. A sensitivity analysis was conducted adjusting for misclassification errors.

Results/findings: Participants were predominantly non-Hispanic White (95%), male (71%), with an average age of 62 years. A 3-class model fit the data best, comprising class-1: active long sleepers, class-2: very active short sleepers, class-3: moderately active short sleepers, representing 11%, 62%, and 27% of the sample. Compared to class-2, class-1 was more likely to be older and female, while class-3 was more likely to be female, had less education, were overweight and obese, and had chronic conditions. Compared to class-2, class-3 was associated with a lower MoCA total score (β=-0.28, SE=0.14, p=0.045), adjusting for sociodemographic factors. When further controlling for health behaviors and indicators, there were no differences in MoCA total scores between classes. Sensitivity analysis suggested that class-3 had a significantly lower average MoCA total score than class-2 (Difference in means=-0.42, p=0.025).

Conclusions: The current study identified three distinct movement patterns and found different sociodemographic and health characteristics, and cognitive functions correlated with classes. Findings highlight that less active, more sedentary, and shorter sleep adults were associated with worse cognitive function, especially among females, those with less education, and with chronic diseases.

Purpose: Low levels of physical activity place adults with stroke-related disability and their caregivers at risk for cardiovascular, cardiometabolic, and mental health conditions. There are no existing interventions that aim to address stroke survivors’ and caregivers’ shared physical activity needs. The duoABLE intervention combines behavioral activation and social interdependence to build physically active lifestyles (reduced sedentary behavior, increased daily step count) among stroke survivor-caregiver dyads. The purpose of this study is to assess the feasibility of delivering duoABLE to stroke survivor-caregiver dyads.

Methods: Community-dwelling ambulatory stroke survivors (≥6 months post-stroke) and their caregivers (age≥18 years, face-to-face interaction more than once per week) were recruited to a descriptive case series. Each dyad member completed descriptive measures and wore an activPAL micro4 for 7 days at week 0 and week 8. Dyads participated in 12 duoABLE sessions over 6 weeks (2x/week). Feasibility metrics included: participant retention, session attendance, and satisfaction (Client Satisfaction Questionnaire-8). Individual change over time in sedentary time and step count were examined.

Results/findings: Dyads (N=4) with spousal (75%) and parent-adult child (25%) relationships enrolled in this study. Stroke survivors ranged in age (58 to 63 years), chronicity (11 to 25 months post-stroke) and were predominantly white (100%) and male (75%). Caregivers ranged in age (28 to 62 years) and were predominantly white (75%) and female (100%). Stroke survivors (100%) and caregivers (75%) were retained in the study. 3 of 4 dyads completed all intervention sessions. The mean satisfaction score was 3.9 out of 4.0 (range: 3.7 to 4) among stroke survivors and 3.8 out of 4 (range: 3.6 to 4.0) among caregivers. PA results are being analyzed and will be available at the time of the conference presentation.

Conclusions: Delivering a sedentary behavior and physical activity intervention that addresses stroke survivor-caregiver dyads’ shared goals appears acceptable to both dyad members. Strategies to enhance retention of dyads should be explored.

Purpose: We have offered a program in which elderly individuals learn about health. This program is conducted over a period of 10 months annually for individuals >65 years of age residing in Kiyosu City, Aich, Japan. It helps participants learn about exercise, nutrition, elderly health issues, and health promotion. We investigated participants’ physical activity before and after joining the program. The aim is to reveal the association between increased physical activity among elderly individuals and participation in the program.

Methods: A total of 139 elderly individuals participated in the health education program from 2017 to 2022. The program was held from May to February each year. Participants completed the International Physical Activity Questionnaire before and after the program. We analyzed total physical activity, light, moderate, and vigorous activity levels, and sedentary time. Additionally, we calculated physical activity levels at work, transportation, domestic, and leisure. Statistical analysis was conducted using the Wilcoxon signed-rank test to compare physical activity levels before and after the program.

Results: The median total physical activity before and after the program was 3132 and 2829 METs*min/week, respectively. Prior and subsequent total physical activity were not significant. Similarly, light, moderate, and vigorous activity levels and sedentary periods were not significantly different before and after the program. The median physical activity in leisure time before and after joining the program was 1181 and 1274 METs*min/week, respectively. Leisure time physical activity after the program was significantly greater than before joining the program. Activity levels in work, transportation, and domestic settings were not significant before and after joining the program.

Conclusions: The findings suggest that participation in the health education program leads to an increase in leisure time physical activity among elderly individuals. However, other aspects of physical activity did not show significant changes. Participation in this program is voluntary. Therefore, it is possible that individuals who are already physically active may be more inclined to enroll.

Purpose: The relationship between physical activity (PA) and functional status (FS) is well established. Information on how health determinants (HD) such as sleep, nutrition, oral health and loneliness interact with this relationship is scarce. We investigated how sleep, nutrition, oral health and loneliness affect the association between PA and FS.

Methods: PA was measured using seven days of accelerometry data from 53 community-dwelling older adults (79.8 ± 6.1 yrs, 71.7% females) and was quantified using the AX6 sensor on the lower back. Volume, pattern and variability of walking, upright, sitting and lying bouts were extracted. Measures include: NEADL for FS, PSQI for sleep, SCREENII for nutritional risk, OHIP-14 for oral health and UCLA 3-item for loneliness. Linear regression models investigated the direct association between FS (dependent variable) and PA. The impact of HD on the direct relationship between PA with FS was investigated by entering each HD as a covariate and an interaction term.

Results: FS was associated with daily total walk duration (p = 0.008), number of daily walking bouts (p = 0.010), number of daily steps (p = 0.007) and pattern of upright bouts (p = 0.010). Those who reported poorer nutrition (SCREENII < 50) had higher FS when they spent more time on their feet (p = 0.046, partial eta-squared (ηp²) = 0.09). Those who reported less loneliness (UCLA < 5) had higher FS with greater number of daily walks (p = 0.025, ηp² = 0.11). Neither the quality of sleep nor oral health affected the association between FS and PA.

Conclusion: Nutritional status and loneliness affect the relationship between PA and FS. A nuanced and comprehensive understanding of how these HDs impact PA in older people will help us better plan resources to identify the onset of functional loss and push back the progression of change. Older adults, particularly those with higher nutrition risk or loneliness, may benefit from more walking activities.

Lieke J.E. Duijsens*, Catherine A.W. Bolman, Alissa S. Paas, Trijntje Völlink, Denise A. Peels, and Lilian Lechner

* Presenting author and author to whom correspondence should be addressed; E-mail: lieke.duijsens@ou.nl; Tel. +31 (0)45 576 2487.

Purpose
This qualitative study is part of an extensive research project aimed at developing an integral approach to promote healthy ageing among older adults with a low socioeconomic status (SES). As part of a large-scale Needs-and-Assets assessment, this study investigates the requirements and resources for healthy ageing among older adults in community settings, acknowledging the multidimensional nature of health and the complex interplay of personal, social, and environmental factors. Its findings will guide intervention development by identifying priority issues and local resources to support healthy ageing in place.
Methods
A generic qualitative study design, with a constructivist naturalistic approach, was performed in five Dutch neighbourhoods with varying levels of urbanisation and a predominantly low SES. A semi-structured interview was conducted with 37 community-dwelling older adults (65 years and over) to examine three important aspects of healthy ageing: physical activity, social connectedness, and digital literacy. All conversations were thematically analysed using Braun and Clarke's (2006) six-step approach.
Results
The majority of participants were female (61.2%), lower educated (56.8%), and residing in a rural neighbourhood (73.0%). Their primary motivators for healthy ageing were to remain independent, maintain their social network, and keep up with modern society, including digitalisation. In addition to the numerous individual determinants at play, many factors that promote or impede healthy ageing were attributed to local activities, support services, facilities, and environmental characteristics. The main facilitators were diverse and affordable opportunities for recreation, sufficient and accessible local facilities, nature and green spaces, and municipal support. The most influential impediments were an inadequate provision of information, individualisation of society, growing digitalisation of support services, and, consequently, shutting down local facilities. Although facilities were generally more satisfactory in urban compared to rural areas, other barriers such as criminality and feelings of insecurity prevailed.
Conclusions
This study underscores the multifaceted nature of healthy ageing among older adults with a low SES, emphasising the importance of addressing individual and environmental determinants in fostering well-being. Proceeding forward, interventions should prioritise enhancing access to recreational opportunities and addressing digitalisation and societal changes in ways that resonate with the needs and capabilities of older adults.

The purpose of this study was to investigate associations between handgrip strength with components of metabolic syndrome (MetS) among elderly Indonesians. This was a cross-sectional study using secondary data of the Indonesia Family Life Survey (IFLS)-5. The participants was placed into elderly. Handgrip Components of MetS including central obesity, hypertension, high blood pressure, high glucose (diabetes treatment), and dyslipidemia (cholesterol treatment). Analysis of covariance was used to examine the differences and multivariate with logistic regression analysis of the odds of handgrip strength. This study found that central obesity was less likely to be associated with handgrip strength in elderly Indonesians in the model multivariate both of male (OR) 1.81, 95% (CI) 1.27~2.60, p=0.001), and female (OR) 1.47, 95% (CI) 1.04~2.07, p=0.026) with (OR adjusted for age and cognitive impairment. The proportion of females had metabolic syndrome and low handgrip strength was 61.1% more than males. The presence of MetS was not significantly related to handgrip strength. The conclusion of this study was Handgrip strength is independently associated with an increase in central obesity in both male and female respondents. Therefore, the routine use of hand grip measurement is strongly recommended in clinical practice for identifying elderly individuals at risk of poor health status to prevent metabolic disorders