A Visualization Tool to Study Dyadic Caregiving Health Profiles

OBJECTIVES

Guided by a life course perspective and fundamental cause theory, this study aims to visualize co-trajectories of health between partners and examine how changes in one spouse's cognitive status can cohesively impact the health of the other spouse along three dimensions (functional, mental, and cognitive).

METHODS

Drawing longitudinal data from the Health and Retirement Study 2000-2016 (N = 3582), we measure women's health profiles by functional limitation (physical health), depression (mental health), and cognitive function (cognitive health). We use multivariate linear mixed models to summarize these paths in the same visual representation.

RESULTS

The approach provides a visualization tool that depicts data and model in the same spatial representation allowing assessment of model fit and comparison. This study advances the traditional life course studies by representing underlying processes as a multidimensional time vector of health outcomes.

DISCUSSION

The described approach provides a blueprint for studying complex health profiles or trajectories.

Health behaviour change among commercially sexually exploited Israeli youth and young adults in a multi-module program

Commercially sexually exploited youth and young adults (hereafter CSEY) are at high risk for various health adversities, but little is known about interventions that can improve their health outcomes. This study reports changes in health behaviours-positive health behaviours, drug use and risky sexual behaviour-in the first stages of treatment of 122 participants in a comprehensive multi-module program for CSEY in Israel. Data included sociodemographic and background information upon program entry, monthly reports on the treatment the participants received and their status. Data were collected monthly through online questionnaires completed by case managers for each of the CSEY in their care. A three-part analytic strategy assessed changes in repeated measures over time and their contributors. Latent class analysis helped identify differential trajectories of change over time among different participant groups. Findings showed overall significant decrease in risky sexual behaviours and improvement in positive health behaviours among certain CSEY groups. Participants with higher levels of health-risk situations and behaviour at program entry (e.g. more victimisation, less residential safety) were more likely to show improvement in health behaviours during intervention, but less likely to change their moderately risky sexual behaviours. Program participants with high levels of drug use did not show improvement in drug use patterns over time. This study demonstrates that a comprehensive multi-module intervention for CSEY can significantly improve health behaviour outcomes among serviced CSEY, and highlights the value of person-oriented care, and of research that can detect vulnerable subpopulations within CSEY who require uniquely tailored interventions. Personalising treatment to specific differential needs of CSEY, coupled with early detection and intervention, can improve program outcomes. Further research is needed to understand contributors to change and changes in subsequent health outcomes.

Bayesian latent multi-state modeling for nonequidistant longitudinal electronic health records

Large amounts of longitudinal health records are now available for dynamic monitoring of the underlying processes governing the observations. However, the health status progression across time is not typically observed directly: records are observed only when a subject interacts with the system, yielding irregular and often sparse observations. This suggests that the observed trajectories should be modeled via a latent continuous-time process potentially as a function of time-varying covariates. We develop a continuous-time hidden Markov model to analyze longitudinal data accounting for irregular visits and different types of observations. By employing a specific missing data likelihood formulation, we can construct an efficient computational algorithm. We focus on Bayesian inference for the model: this is facilitated by an expectation-maximization algorithm and Markov chain Monte Carlo methods. Simulation studies demonstrate that these approaches can be implemented efficiently for large data sets in a fully Bayesian setting. We apply this model to a real cohort where patients suffer from chronic obstructive pulmonary disease with the outcome being the number of drugs taken, using health care utilization indicators and patient characteristics as covariates.

Trajectories of racial and gender health disparities during later midlife: Connections to personality

OBJECTIVE

We examined race/gender effects on initial levels and trajectories of self-reported physical and mental health, as well as the moderating role of personality. We hypothesized that health disparities would remain stable or decrease over time, and that at-risk personality traits (e.g., neuroticism) would have a more robust negative impact on health for Black participants.

METHOD

Analyses utilized 6 waves of data from a community sample of 1,577 Black and White adults (mean age 60 years), assessed every 6 months for 2.5 years. Using multigroup latent growth curve modeling, we examined initial levels and changes in health among White men, White women, Black men, and Black women.

RESULTS

Black participants reported lower initial physical health than Whites. Women's physical health was stable over time, whereas men's declined. There were no disparities in mental health. Higher agreeableness was associated with higher initial levels of physical health only among Black men and White women. All other personality traits were associated with physical and mental health similarly across race and gender.

CONCLUSIONS

Race and gender influence health trajectories. Most personality- health associations replicated across race and gender, except for agreeableness with physical health. An intersectional framework considering more than one aspect of social identity is crucial for understanding health disparities. Future studies may benefit from including large, diverse samples of participants and further examining the moderating effects of race and gender on personality associations with a variety of health outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Life Course Pathways of Economic Hardship and Mobility and Midlife Trajectories of Health

We utilize over 40 years of prospective data from the Panel Study of Income Dynamics (N = 1,229) and repeated-measures latent class analysis to examine how long-term patterns of stability and change in economic hardship from childhood to adulthood are related to subsequent trajectories of midlife health. We review conceptual and methodological approaches to examining health inequality across the life course and highlight the contribution of a person-centered, disaggregated approach to modeling health and its association with long-term pathways of economic resources, including changing resources associated with mobility. Findings suggest those who experienced early mobility out of economic hardship were less likely than those in persistent economic hardship to experience a high-risk health trajectory, while experiencing later mobility did not lessen this risk. We conclude with a call for further investigation into the role of social mobility and the timing, degree, and direction of change in investigations of health inequality.

A Big Five approach to self-regulation: personality traits and health trajectories in the Hawaii longitudinal study of personality and health

Self-regulatory processes influencing health outcomes may have their origins in childhood personality traits. The Big Five approach to personality was used here to investigate the associations between childhood traits, trait-related regulatory processes and changes in health across middle age. Participants (N = 1176) were members of the Hawaii longitudinal study of personality and health. Teacher assessments of the participants' traits when they were in elementary school were related to trajectories of self-rated health measured on 6 occasions over 14 years in middle age. Five trajectories of self-rated health were identified by latent class growth analysis: Stable Excellent, Stable Very Good, Good, Decreasing and Poor. Childhood Conscientiousness was the only childhood trait to predict membership in the Decreasing class vs. the combined healthy classes (Stable Excellent, Stable Very Good and Good), even after controlling for adult Conscientiousness and the other adult Big Five traits. The Decreasing class had poorer objectively assessed clinical health measured on one occasion in middle age, was less well-educated, and had a history of more lifespan health-damaging behaviors compared to the combined healthy classes. These findings suggest that higher levels of childhood Conscientiousness (i.e. greater self-discipline and goal-directedness) may prevent subsequent health decline decades later through self-regulatory processes involving the acquisition of lifelong healthful behavior patterns and higher educational attainment.

Socioeconomic inequalities in health trajectories in Switzerland: are trajectories diverging as people age?

Do socioeconomic differences in health status increase as people age, reflecting cumulative advantage or disadvantage in health trajectories? Life course research hypothesises that cumulative advantage/disadvantage (CAD) is an important underlying social process that shape inequalities as people age. The objective of this study is to examine whether health trajectories are diverging as people age across socioeconomic positions (education, employment status and income). In a random sample of 3,665 respondents living in Switzerland (Swiss Household Panel 2004-2011), trajectories of self-rated health, body mass index, depression and medicated functioning were examined with multilevel regression models. The results showed that employment status and income were associated with diverging health trajectories among men; however, only a few associations supported the CAD hypothesis. Education was rarely associated with diverging health trajectories. In conclusion, little evidence was found to support the CAD model.

Impact of traditional Chinese medicine on age trajectories of health: evidence from the Taiwan Longitudinal Study on Aging

Although traditional Chinese medicine (TCM) is widely used, its effect on health outcomes is not well understood. This study employed a cohort sequential design to investigate levels and rates of change in health from midlife to older adulthood in TCM users and nonusers. A sample of 1,302 community-dwelling adults aged 53 to 80 was selected from individuals interviewed in the 1999 Taiwan Longitudinal Study on Aging (TLSA) and reinterviewed in 2003 and 2007. TCM users were identified as participants who reported visiting a Chinese medicine clinic in the year before each of the three interviews. Health outcomes included physical function, self-rated health, cognitive function, and depressive symptoms. Approximately one in five adults reported that they used TCM in at least one wave of the 3 interview years, but less than one in twenty across all waves. Controlling for time-varying sociodemographic and health conditions, levels and rates of change in physical and cognitive function did not differ according to TCM use. Although adults who reported using TCM had higher depressive symptoms (βTCM = 0.979, 95% confidence interval (CI) = 0.200-1.758) and poorer self-rated health (βTCM = -0.267, 95% CI = -0.267 to -0.081) at baseline, their rates of change in these outcomes did not differ from those who did not use TCM. Subgroup analyses revealed that TCM use benefited adults with higher depressive symptoms by attenuating worsening depressive symptoms (βTCM ×Age = -0.221, 95% CI = -0.434 to -0.007). Further research aimed at understanding the specific mechanisms by which TCM affects health outcomes is warranted.

Effects of physical function trajectories on later long-term care utilization among the Taiwanese elderly

AIM

The aim of this study was to examine the effects of trajectories of physical function on later long-term care utilization based on longitudinal panel data of older adults.

METHODS

A representative longitudinal sample of older adults during the years 1993 to 2007 was used (n=1232). Trajectories of physical function from 1993 to 2007 were identified by group-based trajectory analysis, and then the relationships of the past trajectories with the use of nursing homes and care assistants, and the amount of utilization used in 2007 were examined.

RESULTS

Four groups of physical function difficulties trajectories were identified: none (38.8%), little (34.1%), late increasing (16.1%) and early increasing (11.0%). The early- and late-increasing difficulty groups were more likely to use and used more nursing homes and care assistants. In particular, a long-term disability is closely related to a larger probability of using nursing homes than using care assistants at home. The utilization of care assistants seems a priority choice at the early-increasing stage of disability. When the disability worsens and lasts a long time, a nursing home is then the next choice.

CONCLUSION

Past physical function trajectories relate to later long-term care utilization.

"Getting sicker quicker": does living in a more deprived neighbourhood mean your health deteriorates faster?

Data from the longitudinal West of Scotland Twenty-07 STUDY: Health in the Community was used to examine whether, over a 20 year period, the self-reported health of people living in deprived areas became poorer faster compared to those living in more affluent areas. Three cohorts (born in the early 1930s, 1950s and 1970s) are included, covering 60 years of the life span. Using multilevel growth curve models, a 40% probability of reporting poor health was predicted among residents of more deprived areas at an earlier age (66) compared to those living in more affluent areas (83). Wider area differences were seen for men than for women. Our findings indicate that attempts to reduce area differences in health should start young but also continue throughout the lifespan.