This study examined whether and how trajectory group memberships for PCIs’ physical functioning and general health status predict mortality risks. Using group-based trajectory modeling, we identified six distinct trajectory groups for physical functioning and four groups for general health status among PCIs. We found that trajectory group memberships for both physical functioning and general health status significantly predicted mortality. For physical functioning, except for Group 4 (“medium-low start, early fast decrease”), group memberships were largely reflective of the average levels across time among PCIs, and worse trajectories (i.e., lower baselines and faster declines) were associated with higher odds of death. However, although Group 4 (“medium-low start, early fast decrease”) had a higher average level across time than Group 6 (“low start, stable”), the former had much higher mortality. For general health status, we observed two groups with comparable average levels across time, but the one with convex-shape trajectories had higher mortality risks compared to the one with concave-shape trajectories. For both health outcomes, the patterns largely persisted after the inclusion of various sociodemographic and health characteristics.
Our findings on physical functioning highlight the importance of considering trajectories, capturing information on both the general level of physical functioning and the rate of change over time. The results provide examples in which the shape of health deterioration is more predictive of mortality than are the average levels across time. For example, Group 4 (“medium low start, early fast decrease”) had higher mortality risks than Group 6 (“low start, stable”), which had lower average levels across time. Group 4 also had substantially higher mortality risks than Group 5 (“medium low start, moderate decrease”). There are several explanations to consider. One is that the declining function of Group 4 (“medium low start, early fast decrease”) is a consequence of worsening chronic conditions, which is responsible for increased mortality risks. Alternatively, it is possible that there is a negative feedback loop for some individuals. In this case, declining functioning decreases resilience, causing worsening of chronic conditions, which in turn further decreasing functioning. In any case, these findings suggest that rapidly declining functioning is robust indicator of increased mortality risks. The clinical challenge requiring additional research is understanding when interventions can change this trajectory and when these trajectories are irreversible and should trigger consideration of a more palliative approach to care.
Results for general health status similarly highlight the importance of examining trajectories. For example, despite comparable average levels across time, Group 2 (“high start, convex”) had higher mortality risks than Group 3 (“low start, concave”). It is possible that improving general health status (mostly self-rated, so their actual health may even have declined but was perceived to have improved) earlier after developing cognitive impairment, despite a relatively lower baseline value, leads to positive psychological consequences, which reduce mortality risks. In general, the relationship between respondent- or proxy-reported general health status and mortality is more complex than the one for assessment-based physical functioning. Future research is needed to determine the mechanism by which different trajectories are associated with differential risks.
We also found that being female, Black, or Hispanic, and having MCI rather than dementia were significantly predictive of lower mortality whereas smoking regularly was significantly predictive of higher mortality, conditional on physical functioning trajectories. Conditional on general health status trajectories, being Blacks or Hispanics, having at least 4 children, self-report, having MCI rather than dementia, and not smoking regularly were significantly predictive of lower mortality. Other covariates were not significant likely because trajectories largely mediated the relationship between them and mortality. One explanation for the lower mortality risks among Blacks and Hispanics is mortality selection: Blacks and Hispanics disproportionately die early before entering our sample, and therefore the ones left in our sample are positively selected in terms of health. The finding that persons with MCI had lower mortality risks than those with dementia, conditional on trajectory group memberships, adds to the literature demonstrating associations between declining cognition and increased mortality (31, 32).
Our findings may add to the literature in several ways. First, we found that physical functioning trajectory group memberships were highly predictive of mortality, especially when we compared the magnitudes of the coefficients to those for general health status. Indeed, the predictive power was so strong that physical functioning trajectories might have overpowered the many other known risk factors in the models. The comparison between Groups 4 (“medium-low start, early fast decrease”) and 6 (“low start, stable”) further confirms the notion that the shape of trajectories matters to mortality risks on top of the average levels across time. Therefore, clinicians should pay particular attention to the mortality risks of those who experienced sharp declines in physical functioning in a relatively short period of time.
Second, prior literature has shown that general health status is associated with mortality in the general population (33, 34) but such association was not found among PCIs (35). Nielsen, Siersma (35) raised an explanation that general health status is not a valid health indicator among PCIs due to “loss of insight”. However, alternatively, the lack of predictive power of general health status to mortality may be driven by the lack of information on changes of general health status over time, and no previous studies have explored whether and how its trajectories predict mortality among PCIs. Our results suggest that trajectories of general health status are a robust predictor of mortality among PCIs because they capture both the average health level across time and the shape of health deterioration. Therefore, our findings underscore the need to collect general health status trajectory data, rather than cross-sectional ones, for policymakers to better estimate mortality risks for the PCI population.
Third, our results on general health status without adjusting for covariates also suggest that those who perceived their health to be declining over time were at about the same risk for mortality as those with persistently poor general health status, while those who perceived their health to be improving were not statistically different from those who had persistently high general health status. Therefore, previous studies that only measured general health status at the baseline when predicting mortality can lead to misleading results. For example, the baseline value for Group 2 (“high start, convex”) was much higher than that for Group 3 (“high start, concave”), but the former had higher mortality risks than the latter due to differential shapes in the trajectories. When comparing these two groups (see Appendix Table S8), the former tended to be White and have relatively higher socioeconomic status and fewer comorbidities compared to the latter. Future studies are needed to examine what determines the differential shapes of trajectories between these two groups. Perhaps mental health is a determinant here, as Black Americans tended to be happier than Whites (36).
Our study has several limitations. First, although we controlled for a variety of individual sociodemographic and health characteristics when predicting mortality, we may still have missed some important characteristics, such as living arrangements. Second, our sample restriction criteria may lead to unhealthy individuals less likely being included in our sample. Our investigation shows that individuals excluded because of having less than two rounds of cognitive impairment were a mix of high- and low-socioeconomic subgroups (see Appendix Table S9), but individuals excluded because of having fewer than three rounds of data were more likely to have low socioeconomic statuses (see Appendix Table S10).
Despite these limitations, this study suggests several avenues for future research and policy making. Our findings highlighted that health trajectories predicted mortality among PCIs, because of both the general levels and the shapes of declines. Close monitoring health deterioration of PCIs is crucial to understand the health burden of this population and to make subsequent actions.