An excerpt:
Introduction
[..] Although an increasing number of studies have focused on the impact of single cardiometabolic diseases on cognitive aging, only a few have considered the associations between their frequent co-occurrence and the loss of cognitive health. Additionally, previous studies of cardiometabolic multimorbidity and cognitive ageing have been limited to only examining individuals from European regions. These countries have a lower prevalence of individuals with cardiometabolic diseases than some countries in Asia, which could potentially lead to different effect estimations regarding the associations between these types of disease and cognitive ageing. [..]
Methods
This pooled multicohort study utilised data across 14 countries from the Health and Retirement Study (HRS); the English Longitudinal Study of Ageing (ELSA); the Survey of Health, Ageing and Retirement in Europe (SHARE); and the China Health and Retirement Longitudinal Study (CHARLS), which were designed using similar survey protocols to enable cross-regional comparisons. The response rates for the four studies ranged from 67·0% to 88·6%. Additional details for each study have been previously described. To ensure comparable cognitive function scores and consistent time ranges across the four studies, this study analysed data from waves 10–14 of the HRS (2010–19), waves 7–9 of ELSA (2014–19), waves 4–7 of SHARE (2010–18), and waves 1–4 of CHARLS (2011–19). This study included adults aged 50 years and older, as functional decline can begin as early as this age. Specific sex data collected were self-reported and the available options were male and female. Participants who were missing information on exposure and outcomes, or had been diagnosed with dementia or Parkinson’s disease, were excluded. [..]
Cardiometabolic diseases are a group of symptoms that encompass cardiovascular, renal, metabolic, prothrombotic, and inflammatory abnormalities. These symptoms are usually characterised by insulin resistance, impaired glucose tolerance, dyslipidaemia, hypertension, and central adiposity. Among cardiometabolic diseases, we focus on the combination of diabetes, heart disease, and stroke because each type of cardiometabolic disease individually contributes to increased risk of cognitive impairment.The presence of these conditions was determined via self-reported history obtained through an in-person visit with study personnel via a questionnaire. Participants’ cardiometabolic disease status was defined according to the total number of cardiometabolic diseases they had (ie, diabetes, heart diseases, or stroke) and participants were categorised as not having a cardiometabolic disease, having a single cardiometabolic disease, or showing cardiometabolic multimorbidity (having two or three comorbid types of disease).
The primary outcomes were the performance in cognitive function, specifically in three domains: memory, numeracy, and orientation, assessed along all participants with available data. First, memory was measured by immediate and delayed memory tests modified from Rey’s Auditory Verbal Learning Test. These have been shown to have good construct validity and consistency to measure episodic memory. Participants were asked to repeat a ten-word list at 2-sec intervals and then recall as many words as possible after 2–5 min. The immediate and delayed recall scores were added together, with a range of 0–20. Second, numeracy was measured using the Serial Sevens test, which required participants to subtract 7 from 100 up to 5 times. This test measures attention and calculation, and the scores ranged from 0–5. Third, orientation was evaluated by tasks involving naming the month, date, day of the week, and year, and was scored from 0 to 4. Fourth, a global cognitive score was created by summing the individual scores for memory, numeracy, and orientation, with a range of 0–29. Higher scores indicated better cognitive function, and cognitive decline was defined as the difference in these scores over time. [..]
Results
[..] The study population had a mean age of 67·49 years (SD 10·43). 73 846 (46·1%) of 160 147 partipants were men and 86 301 (53·9%) were women. 103 083 (64·4%) of 160 147 individuals did not have a cardiometabolic disease, whereas 57 064 (35·6%) had at least one of these diseases. Compared with people who did not have cardiometabolic diseases, those with cardiometabolic diseases were more likely to be older, male, have hypertension, psychological disorders, arthritis, lung disease, cancer, and obesity, and be currently smoking. The scores for global cognitive function were −0·09 (SD 0·98) in individuals with a single cardiometabolic disease, and −0·31 (0·99) in those with co-occurring cardiometabolic diseases, which were worse than the scores of individuals with no cardiometabolic diseases (0·08 [ 1·01]).
The presence of a single cardiometabolic disease was associated with a greater decline in global cognitive function score (unadjusted β −0·15 [95% CI −0·17 to −0·13]). Furthermore, as the number of cardiometabolic diseases increased, a faster decline in the global cognitive function score was observed (two cardiometabolic diseases, unadjusted β −0·37 [95% CI −0·40 to −0·34]; three cardiometabolic diseases, unadjusted β −0·57 [−0·64 to −0·50]). Similar patterns were observed in the scores for memory, numeracy, and orientation. These patterns remained significant even after adjusting for covariates. Results of sensitivity analyses using a participant sample with missingness addressed by imputation were similar to those obtained from complete case analysis. Results of the subgroup analysis indicated a significant correlation between cardiometabolic disease status and cognitive function in the older group (aged 65 years and older), but not in the younger group (aged 50–64 years). The associations were not present in the group with tertiary education, but were significant in the groups with lower levels of education. [..]
Discussion
[..] The present study suggests that the combination of cardiometabolic conditions might act synergistically to accelerate cognitive function decline and there may be a modifying effect from unhealthy lifestyles. According to the WHO Innovative Care for Chronic Conditions Framework, a health systems roadmap is proposed for multiple chronic physical and mental conditions, but it does not incorporate the complexity related to multimorbidity. Our study supports that the key to prevention of cognitive decline in old age could be to strengthen a multidisciplinary approach by simultaneously developing targeted interventions on lifestyles and integrated treatments for cardiometabolic comorbidities. It is worth noting that the secondary effects between morbidity and lifestyles should be considered a limiting factor of possible interventions. For example, history of heart diseases and stroke might prohibit rigorous exercise. Future studies are warranted to investigate the extent of the burden of cognitive decline that could be counteracted by modifiable lifestyle factors in older adults with cardiometabolic diseases. [..]
Several limitations of the current study warrant consideration. First, the observational nature of the study hampered our ability to investigate the effect of lifestyle factors and cardiometabolic multimorbidity on cognitive decline. The consistent results in this study across different cohorts underscore the need for further research to examine the potential benefits of promoting lifestyle behaviours to reduce cognitive decline related to cardiometabolic multimorbidity. Second, self-reported disease diagnoses could underestimate the measurement of disease prevalence; while at the same time, multimorbidity might be affected by detection biases (ie, one disease is detected and then others are tested for because of it). However, our supplementary analysis using cardiometabolic diseases defined by biomarkers (fasting plasma glucose for diabetes) were consistent with those obtained from self-reported measurements. To further build on our findings of a dose-dependent association between the increasing number of cardiometabolic diseases and cognitive function score, future studies should explore subtypes of cardiometabolic multimorbidity and cognitive aging in different settings and consider different approaches to defining and diagnosing disease. Third, the exposure was a self-reported measure of unhealthy lifestyle factors at one point in time, which cannot capture the cumulative effects of lifestyle factors and might contribute to an underestimation of the association between unhealthy lifestyles factors and cognitive decline associated with cardiometabolic disease. However, we observed that this type of cognitive decline was greater with an increasing number of unhealthy lifestyle factors, which could potentially be used to detect the cumulative role of lifestyle factors. Future longitudinal studies are warranted to investigate the cumulative effect of lifestyle factors in early life to delay cognitive decline in older age, using a life-course approach to healthy ageing. Fourth, the excluded participants with missing values tended to be older, were more often female, and be of a lower socioeconomic status, which might have led to an underestimation of the effect of cardiometabolic diseases on cognitive function decline. However, we performed sensitivity analyses using a participant sample with missingness addressed by imputation using the MICE method, and results were similar to those obtained from complete case analysis. Nonetheless, future studies with more complete data should verify our findings. Fifth, this study did not involve consideration of race and ethnicity differences due to unavailable data, which should be further analysed in future studies.
Full article, Y Jin, J Liang, C Hong et al., The Lancet Healthy Longevity, 2023.5.4