The socioecological correlates of meal skipping in community-dwelling older adults: a systematic review

Prevalence, correlates, and health indicators associated with meal-skipping among middle-aged and older adults in Thailand: A national longitudinal study

AIM

The purpose of this longitudinal study was to evaluate the prevalence and correlates of and the factors contributing to meal-skipping in middle-aged and older adults in Thailand.

METHODS

We examined prospective cohort data from three consecutive waves of the Health, Aging and Retirement in Thailand (HART) study (analytic sample size = 2863) for participants 45 years of age and older. Meal-skipping was assessed with a one- and two-day recall of breakfast, lunch, and dinner. We used generalized estimating equations analysis to evaluate the longitudinal relationships between sociodemographic, lifestyle, and health indicators and meal-skipping between 2015 (wave 1), 2017 (wave 2), and 2020 (wave 3). Furthermore, binary logistic regression was used to establish the longitudinal association between meal-skipping and the incidence of multiple chronic conditions.

RESULTS

The prevalence of meal-skipping was 6.2% in 2015, 16.2% in 2017, and 13.6% in 2020, and across study years the highest proportion of meal skipping was for lunch (6.0%), followed by breakfast (4.6%), and dinner (2.8%). In the final model, sociodemographic factors (higher education, urban residence, and lower subjective economic status), lifestyle factors (high alcohol use, current smoking, and obesity class II), and health indicators (probable depression and wearing dentures) were positively associated with meal-skipping. In the adjusted logistic regression models, compared with no meal-skipping, meal-skipping in 2-3 study waves was associated with incident obesity and incident probable depression.

CONCLUSION

Skipping meals was linked to a number of lifestyle variables and indicators of physical and mental illness. Geriatr Gerontol Int 2024; 24: 1196-1202.

A national cross-sectional study on breakfast skipping-related factors and comparison of nutritional status according to breakfast skipping in older adults based on the 8th Korea National Health and Nutrition Examination Survey (KNHANES, 2020)

OBJECTIVES

This study aimed to compare the distinct socio-ecological characteristics, nutritional status, and nutrient intake quality of the older adults based on breakfast skipping (EBF, eating breakfast vs. SBF, skipping breakfast). This study also investigated the association between breakfast skipping, socioecological features, and quality of nutrient consumption.

METHOD

From the 8th Korea National Health and Nutrition Examination Survey (KNHANES, 2020), data of 92,093 subjects aged ≥ 65 years old (male: 43,910 and female: 48,183) having data with eating habits, such as nutrient intake and skipping breakfast were analyzed.

RESULTS

The average age of SBF was markedly lower than EBF. EBF had a lower employed status, education level, heavy alcohol intake frequency, smoking, and eating out regularly than SBF. Compared to EBF, SBF showed a significantly higher BMI and waist circumference. Moreover, EBF showed a markedly higher average intake in energy, protein, fiber, calcium, and iron compared with SBF, while SBF had a noticeably higher mean intake in fat, saturated fat, and sugar. In addition, SBF had a significantly reduced mean adequacy ratio (MAR, adjusted OR: 0.260 [95% CI: 0.245-0.276]) and the value of index nutritional quality (INQ, adjusted OR: 0.847 [95% CI: 0.799-0.898]) compared with EBF.

DISCUSSION

There were distinct socioecological features and nutritional conditions of older adults relying on breakfast skipping; and a strong association between breakfast skipping, socioecological parameters, and nutrient intake quality. These observations provide the significance of breakfast skipping in the nutritional status of older adults and offer fundamental information for nutritional education and implications for older adults.

Marital status, marital transition and health behaviour and mental health outcomes among middle-aged and older adults in Thailand: A national longitudinal study

OBJECTIVES

The aim of this study was to assess the longitudinal association between marital status, marital transition, mental ill-health, and health risk behaviours among middle-aged and older adults in Thailand.

METHODS

We analyzed prospective cohort data of participants 45 years and older from three consecutive waves in 2015, 2017, and in 2020 (analytic sample, n = 2863) of the Health, Aging and Retirement in Thailand (HART) study. Sociodemographic and health variables were assessed by self-report.

RESULTS

Being single was positively associated with current smoking among men and transitioning to widowed or divorced was associated with incident current smoking among women. Divorced or separated was positively associated with current alcohol use among men and transitioning to marriage was associated with incident alcohol use among women. Being single or widowed was positively associated with underweight and negatively associated with obesity among women. Men who were divorced, single, or widowed had higher odds of having depressive symptoms and among women, transitioning to being widowed or divorced or separated was associated with incident depressive symptoms. Among both men and women, being divorced, single or widowed were positively associated with poor quality of life/happiness, and among men being divorced, single or widowed was positively associated with loneliness, and among women, being single or widowed was positively associated with loneliness. Among men, being single was positively associated with having an emotional or psychiatric disorder.

CONCLUSION

We found among men and/or women that being unmarried was associated with several health risk behaviours and mental-ill health indicators.

Evaluation of health factors on artificial intelligence and the internet of things-based older adults healthcare programmes

Objective

This study evaluates Artificial intelligence and the Internet of Things-based older adults' healthcare programmes (AI·IoT-OAHPs), which offer non-face-to-face and face-to-face health management to older adults for health promotion.

Methods

The study involved 146 participants, adults over 60 who had registered in AI·IoT-OAHPs. This study assessed the health factors as the outcome of pre- and post-health screening and health management through AI·IoT-OAHPs for six months.

Results

Preand post-health screening and management through AI·IoT-OAHPs were evaluated as significant outcomes in 14 health factors. Notably, the benefits of post-cognitive function showed a twofold increase in older female adults through AI·IoT-OAHPs. Adults over 70 showed a fourfold increase in post-walking days, a threefold in post-dietary practice, and a twofold in post-cognitive function in the post-effects compared with pre via AI·IoT-OAHPs.

Conclusions

AI·IoT-OAHPs seem to be an effective program in the realm of face-to-face and non-face-to-face AI·IoT-based older adults' healthcare initiatives in the era of COVID-19. Consequently, the study suggests that AI·IoT-OAHPs contribute to the upgrade in health promotion of older adults. In future studies, the effectiveness of AI·IoT-OAHPs can be evaluated as a continuous project every year in the short term and every two years in the long term.

Correlates of Meal Skipping in Community Dwelling Older Adults: A Cross-Sectional Study

In this cross-sectional analysis of 10,071 community dwelling adults aged ≥70 years, we examined factors associated with meal skipping (self-reported) using multivariable logistic regression. Prevalence of meal skipping in this study was 19.5%. The adjusted odds (aOR [95%CI]) of meal skipping were lower in those 85+ years (vs. 70-74.9 years, 0.56 [0.45-0.70]), and in those in regional areas (vs. urban area, 0.81 [0.72-0.92]). Higher odds of meal skipping were observed for those living alone (vs. living with someone, 1.84 [1.64-2.05]), current smokers (vs. non-smokers, 2.07 [1.54-2.80]), consumers of high amounts of alcohol (vs. abstainers 1.93 [1.35-2.75]), those with poor oral health (vs. excellent oral health, 1.71 [1.07 -2.73]) diabetes (vs. not 1.26 [1.06-1.50]), or frailty (vs. not, 1.63 [1.09-2.43]). This study identified socio-demographic, social, behavioural and biomedical correlates of meal skipping in later life, which may assist in targeting interventions to address meal skipping.