Although medical advances, improved nutrition, and reduced mortality in early life have produced life expectancies extending beyond those of previous generations, recent evidence indicates that baby boomers have higher rates of chronic disease than members of the previous generation (1), suggesting that lifestyle factors affect health in late life. In addition, age of death decreased for women in 42.8% of US counties from 1992 to 2006 (2), and in a nationally representative UK sample, not smoking, engaging in regular physical activity, consuming alcohol moderately, and obtaining adequate vitamin C (an indicator of fruit and vegetable intake) were associated with lower risk of mortality and lowered the all-cause mortality rate by 58% (3). Memory functioning, and especially mild cognitive impairment (MCI) is often not included in survival analyses, but it is an important predictor of mortality. A review of dementia, cognitive impairment, and mortality in international and US community populations found a positive association between increasing levels of severity of cognitive impairment and mortality. Mortality risk increased with mild levels of impairment (4). MCI is associated with increased risk for dementia and mortality, and increased mortality risk in MCI is likely due to dementia and dementia-related illnesses (5). Memory impairment in Alzheimer’s disease (AD) may increase risk for mortality due to the complications such as immobility, swallowing disorders, malnutrition, and pneumonia (6). Rather than being a precursor to AD, age-related memory loss is a distinct process that probably results from changes in neural functioning rather than loss of neurons, as is the case with AD (7). Few studies of mortality in community samples have examined the effect of MCI on mortality (8).

Delayed word recall (DWR) is among the most sensitive measures of memory functioning. In a study of 3,778 older adults without dementia, 3-word DWR predicted mortality at 10 years, with a 52% greater mortality in those who remembered 0 words compared with those who remembered all 3 words (4). High depressive symptoms predicted mortality in older adults after controlling for sociodemographic factors, disease, biological, and behavioral risk factors and suggested that motivational depletion (eg, everything I did was an effort) may help explain the effect of depressive symptoms on mortality (9).

The purpose of this study was to examine demographic, cognitive, behavioral, and biological risk and protective factors of self-rated health and mortality longitudinally in a nationally representative sample. Our research questions were 1) How well do age, education, recall memory, depression, physical activity, sleep, and body mass index (BMI) at time 1 predict self-rated health (SRH) 2 and 4 years later, and 2) How well do education, recall memory, depression, physical activity, sleep, BMI, and smoking predict mortality.

Sample characteristics are presented in Table 1. At baseline, a higher percentage of obese respondents reported chronic pain, high blood pressure, a heart condition, diabetes, and arthritis, stroke, cancer, and lung disease than nonobese participants (P < .05). At times 2 and 3 these differences remained, except that the prevalence of stroke and cancer did not differ between obese and nonobese respondents. Preliminary analyses tested the effects of sex and age on SRH and mortality. Only age was correlated with SRH and mortality. Correlations between the study’s risk and protective factors and SRH and mortality are presented in Table 2.

The total variation in outcomes of SRH at times 1, 2, and 3, with all of the predictors, was calculated with 3 hierarchical multiple regressions. Age and years of education in model 1 accounted for significant variance in SRH at time 1 (9%), time 2 (8%), and time 3 (7%). DWR, depression, sleep, mild activities, smoking, and BMI were entered as a set and accounted for significant incremental variance in SRH at time 1 (20%), time 2 (16%), and time 3 (14%), independent of the effects of age and education. All variables explained unique variance when predicting SRH (Table 3). In the Cox regression analysis, SRH, DWR, depression, sleep, mild activities, smoking, and BMI were entered as a set, controlling for age and education (Table 4). Significant predictors of mortality included age, DWR, depression, smoking, and BMI.

Tests of temporal mediation were conducted. DWR at time 2 mediated the relationship between mild activities at time 1 and SRH at time 3. DWR at time 2 also mediated the relationship between mild activities at time 1 and mortality. Effect sizes were small (κ ² = .03 for SRH and κ ² = .04 for mortality). Because including DWR at time 2 would likely eliminate the sickest participants (who had died by time 2) in the mortality mediation model, we also tested DWR at time 1 as a mediator of mild activities at time 1 and mortality, which was significant. The effect size was stronger than the effect of DWR at time 2, but still small (κ ² = .07). Mild activities at time 2 mediated the relationship between depression at time 1 and time 3 SRH; the effect size was small (K ² = .04). Mild activities at time 2 mediated the relationship between depression at time 1 and mortality; the effect size was small (K ² = .04). Depression at time 2 also mediated the relationship between mild activity at time 1 and SRH at time 3; the effect size was small (K ² = .05) (Table 5).

The purpose of this study was to examine predictors of perceived health and mortality in a nationally representative sample of older adults. This study measured self-rated health with a single item that is correlated with multiple physical health indicators (15) and is a quick and economical way to assess physical health. One-item, global self-ratings of health that ask people to rate their health as poor, fair, good, very good, or excellent are frequently used in medical and research settings and by the Centers for Disease Control and Prevention as a global self-rating of health-related quality of life in the annual Behavioral Risk Factor Surveillance System (18). A global self-rating of health may predict mortality independent of other medical, behavioral, or psychosocial factors (19). The rating is effective for assessing physical health and is highly predictive of mortality, perhaps partly because people evaluate their health using information about bodily sensations that are related to important physiological functions, such as inflammation (20).

Depression was the strongest predictor of SRH at time 1 and remained strong at all points. Older adults may not recognize symptoms of depression or may assume that there are physical causes for them, which may lead them to seek treatment from a primary health provider rather than a mental health professional (21,22). In addition to encouraging regular physical activity as part of prevention efforts in older adults, health providers should screen older adults for depression and refer them for further evaluation or treatment to prevent declining health.

BMI at time 1 was strongly correlated with SRH at each point. In regression analyses, BMI was also a significant predictor of mortality. The prevalence of chronic health conditions (pain, high blood pressure, heart condition, diabetes, and arthritis) differed between obese and nonobese participants at all points.

In mortality analyses, smokers were more likely to die than nonsmokers, which is consistent with previous research (3). DWR was another important predictor, which highlights the importance of assessing memory difficulties and creating effective interventions. Recent evidence indicates that cognitive training improved memory for 5 years or more in healthy individuals (23). More research is needed to test the effectiveness for people with memory impairments. We found that education, BMI, smoking, and mild activities helped explain variance in DWR, which is consistent with research indicating the importance of education and lifestyle factors for cognitive health. A review of predictors of cognitive change identified education, hypertension, health, cardiovascular disease, and the APOE e4 gene as significant predictors; however, effects of physical activity on cognitive change were inconclusive (24). Recent evidence suggests that memory may be malleable in late life. Higher levels of cognitive activity over the lifetime are associated with less cognitive decline, independent of neuropathologic burden (25), and a growing body of evidence indicates that aerobic exercise may increase hippocampal volume, lead to better memory function (26), slow cognitive decline, and reduce the risk of dementia (16). Cognitive training and cognitive stimulation have demonstrated improved attention, learning, and memory functioning in healthy older adults and those with dementia (27,28), and preliminary findings suggest that transcranial direct current stimulation (29) and deep brain stimulation may sustain or even improve memory functioning in early AD (30). Whether these efforts will translate to reduced mortality is unknown. These results suggest that health providers should screen for cognitive impairment, refer patients to mental health professionals for further evaluation, and recommend behaviors that promote cognitive health.

Tests of temporal mediation indicated that DWR at time 2 mediated the relationship between time 1 mild activities and time 3 SRH and between time 1 mild activities and mortality, suggesting that exercise positively influences memory, which then influences health and longevity. The mediating effect of DWR at time 1 was stronger, suggesting that the effects of exercise on memory may lessen with time. Mild activities mediated the relationship between depression and SRH, and between depression and mortality. Depression also mediated the relationship between mild activity and SRH. Together these results suggest a bidirectional causal relationship between exercise, depression, and health, such that activity reduces depression, which positively influences health. Similarly, depression may inhibit physical activity, which may then diminish health. Thus, it is important to assess and encourage frequent physical activity and to assess and treat depression (22), as these efforts may offer benefits on health through separate causal pathways.

Limitations of this study include the lack of genetic information and lack of corroboration with objective behavioral indicators. Future studies should consider experimental tests, daily experience sampling, and longer longitudinal follow-ups of risk and protective factors. Researchers should better understand the processes by which these risk and protective factors affect health. Additional longitudinal tests of mediation and moderation of risk and protective factors may help explain the specific causes of physical health and mortality. Overall, researchers should integrate demographic, biological, cognitive, and behavioral findings from multiple comprehensive longitudinal studies of aging to better understand the risk and protective factors for health and mortality. This integration in turn could lead to the development of more effective screening and interventions.