Links between life-course SES and frailty trajectory moderated by community environment resources: Person-environment Fit perspective

Association of childhood and adulthood socioeconomic status with frailty index trajectories: Using five-wave panel data from the China Health and Retirement Longitudinal Study (CHARLS)

BACKGROUND

The relationship between childhood and adulthood socioeconomic status (SES) and long-term frailty trajectories is unclear. We aimed to assess the frailty index (FI) dynamic trajectories and examine the associations between childhood and adulthood SES and frailty trajectories.

METHODS

We included 7321 participants aged 45 and older from the 2011-2020 China Health and Retirement Longitudinal Study (CHARLS). Six childhood SES factors and four adulthood SES factors were included. Group-based trajectory modelling was used to identify frailty trajectories and multinomial logistic regression was used to assess the association between SES and frailty trajectories.

RESULTS

Three frailty trajectory groups were identified: low-increase trajectory (LT, 59.9 %), moderate-increase trajectory (MT, 31.7 %) and high-increase trajectory (HT, 8.4 %). With the LT group as reference, for childhood SES, participants with an illiterate mother (relative-risk radio [RRR]=1.67, 95 % confidence interval [CI]: 1.10-2.52), having not enough food (1.67, 1.34-2.09), with family's financial situation (2.35, 1.61-3.42) and childhood health status (2.72, 2.09-3.53) worse than others had higher odds of being in the HT group. For adulthood SES, rural residence (1.86, 1.50-2.31), with an educational level of less than middle school (2.75, 1.83-4.15), had higher odds of being in the HT group. Similar results were found for people of different ages, genders, and residences.

CONCLUSIONS

Participants with lower SES, including maternal and self- low education, childhood hunger, worse family financial and childhood health status are more likely to experience a high-increase FI trajectory, i.e. aging faster. Attention should be paid to reduce early-life social inequalities thus to promote later-time healthy aging.

The combined effects of heatwaves, air pollution and greenery on the risk of frailty: a national cohort study

The associations between heatwaves and frailty, as well as the joint effects of heatwaves with air pollution and greenery, are currently unknown. This study leverages data from the China Health and Retirement Longitudinal Study (CHARLS), which collected information from 6,400 older adults between 2011 and 2018. Our outcome variable was frailty, as measured by the frailty index (FI > 0.21). Heatwaves were defined based on maximum temperature, incorporating four thresholds (≥ 97.5%, 97.5%, 92.5%, and 90%) and three durations (≥ 2, 3, and 4 days). These variables were considered as time-varying variables, representing the one-year exposure preceding survival events. Fine particulate matter (PM2.5) and greenery (normalized difference vegetation index (NDVI)) were utilized as indicators of air pollution and greenery exposure, respectively, and were treated as time-varying indicators concurrent with heatwaves.Time-varying Cox proportional hazards models were employed to assess the independent effects, as well as the multiplicative and additive interactions of heatwaves, air pollution, and greenery on the risk of frailty. These effects were quantified using hazard ratios (HRs), a traditional product term representing the ratio of HRs, and the relative excess risk due to interaction (RERI). Our findings indicate that heatwaves are associated with an increased risk of frailty, with HRs ranging from 1.035 (95% CI: 1.006-1.064) to 1.063 (95% CI: 1.028-1.101). We observed both a positive multiplicative interaction (HRs > 1) and an additive interaction (RERI > 0) between high level PM2.5 concentration, lack of greenery, and heatwaves. This study reveals that the combined effects exacerbate the adverse impact of heatwaves on the risk of frailty. Moreover, the combined effects of heatwaves, air pollution, and greenery exposure on frailty risk vary across age, gender, and educational attainment.

Exposure to early-life adversity and long-term trajectories of multimorbidity among older adults in China: analysis of longitudinal data from the China Health and Retirement Longitudinal Study

OBJECTIVES

This study aimed to identify long-term distinct trajectories of multimorbidity with ageing from 50 to 85 years among Chinese older adults and examine the relationship between exposure to early-life adversity (ELA; including specific types of adversity and accumulation of different adversities) and these long-term multimorbidity trajectories.

DESIGN

The group-based trajectory models identified long-term multimorbidity trajectories. Multinomial logistic regression models were used to examine the relationship between ELA and the identified multimorbidity trajectories.

SETTING

This study used data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018) and the 2014 Life History Survey.

PARTICIPANTS

We used data from 9112 respondents (aged 60 and above) of the 2018 wave of CHARLS.

OUTCOME MEASURES

Each respondent's history of chronic conditions and experiences of ELA were collected from the 2011-2018 waves of CHARLS and the 2014 Life History Survey.

RESULTS

Four heterogeneous long-term trajectories of multimorbidity development were identified: 'maintaining-low' (19.1%), 'low onset-rapidly increasing' (23.3%), 'middle onset-moderately increasing' (41.5%) and 'chronically-high' (16.2%). Our findings indicated that the heterogeneity can be explained by ELA experiences. Across various types of different ELA experiences, exposure to food insufficiency (relative risk ratios from 1.372 (95% CI 1.190 to 1.582) to 1.780 (95% CI 1.472 to 2.152)) and parental quarrel/divorce (relative risk ratios from 1.181 (95% CI 1.000 to 1.394) to 1.262 (95% CI 1.038 to 1.536)) had the most prominent associations with health deterioration. The accumulation of more different ELA experiences was associated with a higher relative risk of developing more severe multimorbidity trajectories (relative risk ratio for five to seven ELAs and chronically high trajectory: 7.555, 95% CI 4.993 to 11.431).

CONCLUSIONS

There are heterogeneous long-term trajectories of multimorbidity in Chinese older adults, and the risk of multimorbidity associated with ELA accumulates over the lifespan. Our findings highlight the role of a supportive early-life family environment in promoting health development across the lifespan, advocating for the integration of life-course approaches to implementing health disparity interventions.