Cognitive frailty in relation to adverse health outcomes independent of multimorbidity: results from the China health and retirement longitudinal study

Characteristics of study participants

Among the 5113 participants at baseline, mean (SD) age was 68.1 (6.5) years, and 49% (n=2479) were women (Table 1). The majority of participants at baseline had less than six years of education (including no formal education, did not finish primary school and elementary school), were currently married, lived in rural areas, and were more likely to be non-smokers and non-drinkers.

At baseline, about 16.0% (n=820) of all participants had cognitive impairment; 6.7% (n=342) had physical frailty; and 1.6% (n=82) had both components, i.e., met criteria for cognitive frailty. As expected, the oldest-old (aged 80+ years) were more likely to have normal cognition and physical frailty (Group 3) or cognitive frailty (Group 4). A higher proportion of women were found in the nonfrail group with cognitive impairment (Group 2) and in the group with cognitive frailty (Group 4), which mainly represent older adults with cognitive impairment. About 44% of all participants had two or more chronic diseases (i.e., multimorbidity). Similarly, about 44% of participants in Group 4 had multimorbidity. A little higher proportion of participants in Group 3 (59%) had multimorbidity. Overall, we did not find obvious differences in the proportion of multimorbidity between the four cognitive frailty groups.

Associations between cognitive frailty and adverse health outcomes

BADL, IADL, and mobility disability

Among the participants without BADL disability at baseline (n=3341), 33.6% (n=1121) reported BADL disability over 4-year follow-up. Similarly, the percentages for incident IADL and mobility disability were 35.2% (n=1136) and 65.3% (n=1101), respectively.

Table 2 shows the individual and combined associations of cognitive impairment and physical frailty with adverse health outcomes, using the normal cognition and nonfrail group (Group 1) as the reference group. After adjusting for age and gender, both cognitive impairment and physical frailty significantly increased the risk of developing BADL, IADL, and mobility disability, with ORs ranging from 1.41 (95% CI: 1.15–1.74) to 2.43 (95% CI: 1.64–3.62). In combined effect analyses, belonging to Group 4 (cognitive frailty) was strongly associated with an increased risk for BADL and IADL disability, with ORs of 2.09 and 3.40, respectively, although the OR for BADL was not statistically significant, due to the small sample size for Group 4. Only four participants were free of mobility disability at baseline, which all developed mobility disability during the follow-up period.

Hospitalization

About 28.5% (n=1075) of the participants who did not report hospitalization at baseline reported a hospitalization during 4-year follow-up. In individual effect analyses, physical frailty (OR: 1.37, 95% CI: 1.02–1.83), but not cognitive impairment (OR: 1.14, 95% CI: 0.94–1.39), was independently associated with incidence of hospitalization. In combined effect analyses, compared with Group 1, the other three groups were all associated with elevated risk for hospitalization, though only Group 3 (Normal cognition and frail; OR: 1.50, 95% CI, 1.08‒2.07, Table 2) met statistical significance.

Death

Over 4-year follow-up, 434 of 5113 (8.5%) participants died. In individual effect analyses, both cognitive impairment and physical frailty were independently associated with an increased risk of death (OR=1.58 and 2.07, respectively). In combined effect analyses, all groups were associated with elevated risk of death (ORs range from 1.42 to 3.89). Compared with Group 1, Group 4 (cognitive frailty) had a nearly four-fold increased risk of death (OR=3.89, 95% CI, 2.25‒6.74, Table 2),

For all (individual and combined) associations above, we did not observe substantial changes of the results when additionally adjusting for education, residence, marital status, smoking status, alcohol consumption, body mass index, and multimorbidity (Table 2, Model 2). Furthermore, additional analyses revealed that for the above individual effect analyses, mutually controlled associations of cognitive impairment and physical frailty with all outcomes in logistic regression models did not affect the main model results (Supplementary Table 2).

Subgroup analyses by multimorbidity

We found that after adjusting for age and gender, multimorbidity significantly increased the risk of the five adverse health outcomes (Supplementary Table 3), which suggested that multimorbidity could play a role as moderator or confounder of the associations between cognitive frailty and adverse health outcomes.

Table 3 presents the associations of cognitive impairment and physical frailty with disability (ADL, IADL, and mobility), hospitalization, and death in older adults without and with multimorbidity. We did not find significant interaction effects between cognitive frailty and multimorbidity for these adverse outcomes (all interaction P values>0.05). As shown in Table 3, we found that in participants without multimorbidity, the risk estimates were similar to those shown in the full sample, where cognitive frailty was a strong predictor for the health outcomes (ORs range from 3.59 to 4.47) except for hospitalization. In participants with multimorbidity, partly due to the small sample size, we did not observe statistically significant associations of cognitive frailty with the health outcomes, but the overall trend suggested that older adults with cognitive frailty were at high risk of IADL disability and death.

Sensitivity analyses

In sensitivity analyses, we found that: (1) the results were unchanged after removing 146 participants who reported having memory-related disease (dementia, Parkinson's disease, etc., Supplementary Table 4); (2) accounting for the competing risk of death did not substantially change the associations of cognitive frailty with disabilities and hospitalization appreciably (Supplementary Table 5); (3) the cross-sectional analyses obtained relatively higher risk estimates and further offered supportive evidence for the longitudinal relationships of cognitive impairment, physical frailty, and their combinations with adverse health outcomes (Supplementary Table 6).

Study population

The CHARLS targeted Chinese community-dwelling adults aged 45 years and older and their spouses. The CHARLS used a multistage sampling strategy covering 28 provinces, 150 counties/districts, and 450 villages/urban communities across the country. Participants were first recruited in 2011/2012, and completed two follow-up visits biennially up to 2015/2016. Details of the CHARLS survey have been described elsewhere [31]. The CHARLS study offers a wide range of information on socioeconomic status and health, including demographic characteristics, family structure, health status and functioning, biomarkers, health care and insurance, work, retirement and pension, income and consumption, and assets.

Out of 17,708 participants aged 45 years and older enrolled in the baseline survey (2011/2012), we excluded those with missing data on age (n=26), aged <60 years (n=10229), with missing data on cognition (n=623) and four or more physical frailty components (n=1717), leaving 5113 participants available (Figure 1). Finally, for different adverse health outcomes, we assembled various sets of analytical samples, as shown below:

Sample 1 for BADL disability: restricted to participants without BADL disability at baseline (n=3341);

Sample 2 for IADL disability: restricted to participants without IADL disability at baseline (n=3226);

Sample 3 for mobility disability: restricted to participants without mobility disability at baseline (n=1685);

Sample 4 for hospitalization: restricted to participants without hospitalization occurred at baseline (n=3776);

Sample 5 for death: all participants (n=5113).

Measures

Cognitive impairment

Following prior CHARLS publications [33, 34], we used three assessments of cognition: the Telephone Interview of Cognitive Status (TICS-10), word recall, and figure drawing. The overall cognition score is the sum score of the TICS-10 (orientation and attention, 0-10), word recall (episodic memory, 0-10), and figure drawing (visual spatial abilities, 0-1). The TICS is a well-established measure for assessing mental status [35]. In CHARLS, ten items from TICS were included: date (month, day, and year), day of the week, season of the year, and serial subtraction of 7 from 100 (up to five times). Summing the number of correct answers to these questions resulted in a TICS-10 score, ranging from 0 to 10. TICS-10 primarily assesses the executive functions of orientation to time and attention [36]. For word recall, participants were asked to memorize and immediately recall as many words as they could in any order immediately after interviewers read a list of 10 Chinese nouns (i.e., immediate recall). Four to 10 minutes later, participants were asked to recall as many of the original words as possible (i.e., delayed recall) [34, 35]. The average number of immediate and delayed word recalls ranged from 0 to 10, and is regarded as assessing episodic memory [37]. For figure drawing, participants were shown a picture of two overlapped pentagons and asked to draw a similar figure. Participants who successfully completed the task received a score of 1, and those who failed received a score of 0. This task assessed visuospatial abilities [38]. A summary score of the three parts range from 0 to 21, with higher scores indicating better performance [33, 34]. According to the literature, participants were classified as having cognitive impairment if their summary score fell more than 1 SD below age-appropriate norms; otherwise, they were defined as normal cognition [39].

Physical frailty

Frailty was measured by an adapted version of the Fried physical frailty phenotype approach [40], and has been previously developed and validated in the CHARLS [32]. Five items/criteria are included: shrinking, weakness, exhaustion, slowness, and inactivity. Shrinking was established as self-reported loss of 5 or more kg in the previous year or having a body mass index (BMI) of 18.5 kg/m² or less. Weakness was defined as the lowest quintile on maximum handgrip strength (either hand; two trials for each; measured in a standing position with arm bended at 90 degrees) among the population, adjusting for gender and BMI. Exhaustion was determined according to two questions from the Center for Epidemiological Studies-Depression scale: “I could not get going” and “I felt everything I did was an effort”. Slowness was defined as the lowest quintile on the average of two-timed walk tests over a 2.5-meter course, at usual pace, among the population, adjusting for gender and standing height. Inactivity was determined if participants self-reported that they did not walk 10 or more minutes continuously during a usual week. We modified the original physical frailty phenotype proposed by Fried et al. [40], due to limited availability of data in CHARLS. Participants who met three or more criteria were defined as having physical frailty (frail); otherwise, they were considered as having no physical frailty (nonfrail).

Cognitive frailty

In line with the definition by an (I.A.N.A./I.A.G.G.) international consensus group [3], cognitive frailty was defined as the simultaneous presence of both cognitive impairment and physical frailty [3], and has been previously validated [41–43]. Based on the two components—cognitive impairment and physical frailty, we defined four combined groups:

Group 1: normal cognition and nonfrail

Group 2: cognitive impairment and nonfrail

Group 3: normal cognition and frail

Group 4: cognitive impairment and frail (cognitive frailty)

Disability and hospitalization

We considered important patient-centered outcomes: disability and hospitalization, as we did before [23]. Three domains (BADL, IADL, and mobility) of disability were operationalized, including 5 BADL (dressing, bathing, eating, getting in/out of bed, and using the toilet), 5 IADL (managing money, taking medications, shopping for groceries, meal preparation, and cleaning house), and 7-item mobility activities (100m, climbing several flights of stairs, getting up from a chair, stooping or kneeling or crouching, extending arms up, lifting 11 lb, and picking up a small coin). For each task in the three domains, participants were asked, “Do you have difficulty in performing the task?” Those participants who need personal assistance in performing one or more of the corresponding activities in each domain were defined as disability. Hospitalization was derived from the participants’ self-report of whether they received any inpatient care in the past year. Since the timing of developing disability during the follow-up period was not available [44], we defined a binary outcome to denote the occurrence of disability over the 4-year follow-up. For hospitalization, we did a similar definition to denote whether the participant had hospitalization over the 4-year follow-up since baseline in this study.

Death

The death information in CHARLS was collected from the exit interview in 2013 and 2015 waves. Generally, a binary variable representing occurrence of death and a variable representing date of death were provided. However, date of death was only available in the 2013 wave according to the current dataset in the CHARLS website. Therefore, we constructed a binary variable to denote occurrence of death within the 4-year follow-up since baseline in this study.

Covariates

Demographic characteristics including age, gender, residence (urban vs rural), education, and marital status were collected at baseline. Five categories were considered for education: no formal education/illiterate, can read but did not finish elementary school, elementary school/traditional Chinese school, middle school, and high school or above. Marital status was defined as currently married (including partnered), and others (e.g., separated, divorced, widowed). Health behaviors included smoking status (never, ever, and currently smoking), alcohol consumption (yes/no), and body mass index (BMI, kg/m²).

Self-reported comorbidity included ten self-reported chronic diseases by asking “Have you been diagnosed with the following conditions by a doctor”: hypertension; diabetes or high blood sugar; cancer or malignant tumor; chronic lung disease; heart problems; stroke; kidney disease; stomach or other digestive disease; arthritis or rheumatism; and asthma. The total number of chronic diseases was calculated. Multimorbidity was defined as co-existence of two or more chronic diseases within one older adult [18].

Statistical analyses

Characteristics of the study population were presented as means (± standard deviation [SD]) or frequencies (percentage) in the overall sample, and four combined groups (Group 1–4).

Logistic regression models were used to estimate the individual (i.e., cognitive impairment and physical frailty as independent categorical variable respectively) and combined associations (i.e., the I.A.N.A./I.A.G.G. criteria defined four cognitive frailty groups as independent categorical variable, with Group 1 as the reference group) of cognitive impairment and physical frailty with adverse health outcomes. Note that we ran a logistic regression model for each health outcome (e.g., BADL disability) in participants who did not have exposure for that outcome at baseline (e.g., n=3341 participants without BADL disability at baseline). We adjusted for age and gender in model 1 and presented the odds ratios (ORs) and corresponding 95% confidence interval (CI). We further adjusted for other covariates including residence, education, marital status, smoking status, alcohol consumption, BMI, and multimorbidity in model 2.

To evaluate whether the associations of cognitive frailty with health outcomes differed by multimorbidity, we added the interaction terms: the four cognitive frailty groups × multimorbidity in the model 1. We then repeated the above analyses in two subgroups: those with and without multimorbidity and presented the results separately.

Sensitivity analyses were performed to test the robustness of the results. First, as the information on dementia was not available in CHARLS, we used one item—self-reported memory related problem (dementia, Parkinson's disease, etc.) as a proxy for dementia. We excluded participants with a response of “Yes” to this question and rerun the model 1 above to testify whether the individual and combined associations of cognitive impairment and physical frailty with adverse health outcomes changed. Second, to address the concern about the attrition of study participants, particularly due to death, we used a competing risk Cox regression model [45] to re-examine the above individual and combined associations of cognitive impairment and physical frailty with disability and hospitalization. To do so, we assumed that the date of incurring disability, hospitalization, or death was the time of the survey if the participant reported having that disability, hospitalization, or death (exit interview). The follow-up time was calculated from the baseline to the date of incurring disability (hospitalization) or death, whichever came first. Finally, we ran an additional analysis by examining the cross-sectional association of cognitive impairment, physical frailty, and their combinations with the health outcomes, in order to confirm the findings from the majority of the literature on a cross-section study design.

All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). P<0.05 (two-tailed) was considered as statistically significant.