Cardiovascular-kidney-metabolic (CKM) syndrome, recently defined by the American Heart Association (AHA), describes the interplay among obesity, diabetes, chronic kidney disease (CKD), and cardiovascular disease (CVD).¹ To capture the progressive nature of CKM syndrome, the AHA introduced a staging framework ranging from stages 0 to 4.¹ Recent studies indicated that CKM syndrome is highly prevalent among US adults, with approximately 90% meeting the criteria for CKM stage 1 or higher between 2011 and 2020.² Notably, 15% of US adults are classified as having advanced CKM stages (stages 3 or 4), with significant differences in prevalence based on sex and age.² Specifically, men are more likely to have advanced CKM stages than women, while advanced CKM stages are more common in older adults (aged ≥65 years) than younger adults (aged 20-44 years).²

Aims: Cardiometabolic diseases (CMDs), including diabetes, heart disease, and stroke, are established risk factors for dementia, but their combined impact has been investigated only recently. This study aimed to examine the association between mid- and late-life cardiometabolic multimorbidity and dementia and explore the role of genetic background in this association. Methods and results: Within the Swedish Twin Registry, 17 913 dementia-free individuals aged ≥60 were followed for 18 years. CMDs [including age of onset in mid (60) or late (≥60) life] and dementia were ascertained from medical records. Cardiometabolic multimorbidity was defined as having ≥2 CMDs. Cox regression was used to estimate the CMD–dementia association in (i) a classical cohort study design and (ii) a co-twin study design involving 356 monozygotic and dizygotic pairs. By comparing the strength of the association in the two designs, the contribution of genetic background was estimated. At baseline, 3,312 (18.5%) participants had 1 CMD and 839 (4.7%) had ≥2 CMDs. Over the follow-up period, 3,020 participants developed dementia. In the classic cohort design, the hazard ratio (95% confidence interval) of dementia was 1.42 (1.27–1.58) for 1 CMD and 2.10 (1.73–2.57) for ≥2 CMDs. Dementia risk was stronger with mid-life as opposed to late-life CMDs. In the co-twin design, the CMD–dementia association was attenuated among monozygotic [0.99 (0.50–1.98)] but not dizygotic [1.55 (1.15–2.09)] twins, suggesting that the association was in part due to genetic factors common to both CMDs and dementia. Conclusion: Cardiometabolic multimorbidity, particularly in mid-life, is associated with an increased risk of dementia. Genetic background may underpin this association.

Importance: Body mass index (BMI) trajectories before the onset of mild cognitive impairment (MCI) and during the progression from MCI to dementia remain unclear.Objective: To assess the long-term BMI trajectories preceding incident MCI and dementia and explore whether they are associated with brain pathologies.Design, Setting, and Participants: The Rush Memory and Aging Project (MAP) was an ongoing community-based cohort study. This study included cognitively intact participants aged 60 to 90 years at baseline with annual follow-up from October 1997 to December 2020 (maximum follow-up of 22 years). During the follow-up, participants underwent brain autopsies. Data were analyzed from August 2021 to February 2022 using mixed-effect models.Exposures: BMI was calculated using height and weight measured at baseline and follow-ups.Main Outcomes and Measures: Incident MCI and dementia were diagnosed following standard criteria. Neuropathological assessments (including global Alzheimer disease and vascular pathology) were performed for autopsies.Results: A total of 1390 participants (mean [SD] age, 78.4 [6.5] years; 1063 female [76.5%]) were included in the study. In the analysis of BMI trajectories before MCI (n = 939), during the follow-up (median [IQR] duration, 6 [3-9] years), 371 participants (39.5%) developed MCI, of whom 88 (23.7%) progressed to dementia. Those who developed MCI were older (mean [SD] age, 79.6 [5.9] years vs 76.9 [6.6] years), consumed less alcohol (median [IQR] consumption, 0 [0-5.8] g/day vs 1.1 [0-6.9] g/day), had a lower BMI (mean [SD], 27.2 [4.9] vs 28.2 [5.9]), and were more likely to be apolipoprotein E (APOE) ε4 carriers (89 of 371 [24.0%] vs 98 of 568 [17.3%]) compared with those who remained cognitively intact over follow-up. Those who developed dementia were older (mean [SD] age, 81.0 [5.2] years vs 79.1 [6.0] years), had a lower level of physical activity (median [IQR] activity, 1.0 [0-2.5] h/week vs 1.8 [0.2-3.8] h/week), and were more likely to be APOE ε4 carriers than those who were dementia-free (33 of 88 [37.5%] vs 56 of 283 [19.8%]). Compared with participants who remained cognitively intact, in those with incident MCI, BMI tended to decline earlier and faster. From 7 years before diagnosis, people with incident MCI had an associated significantly lower BMI (mean difference, −0.96; 95% CI, −1.85 to −0.07) than those who were cognitively intact. Among people with incident MCI, the slopes of BMI decline did not differ significantly between those who did and did not develop dementia (β, −0.03; 95% CI, −0.21 to 0.15). In the analysis of BMI trajectories before autopsy (n = 358), BMI was associated with a faster declination among participants with a high burden of global Alzheimer disease pathology (β for pathology × time highest vs lowest tertile, −0.14; 95% CI, −0.26 to −0.02) or vascular pathology (β for pathology × time² highest vs lowest tertile, 0.02; 95% CI, 0-0.05).Conclusions and Relevance: Results of this cohort study suggest that among cognitively intact people, significantly lower BMI occurs beginning approximately 7 years before MCI diagnosis. After MCI diagnosis, BMI declines at the same pace in people who develop dementia and those who do not. High brain pathologies may underly the BMI decline preceding dementing disorders.

The American Heart Association defined cardiovascular-kidney-metabolic (CKM) syndrome as a novel multi-stage disorder. We examined the associations of CKM stages with premature mortality and the role of social determinants of health (SDOHs). A prospective cohort study. A nationally representative sample of US adults from NHANES 1999-2018. CKM included 5 stages (stages 0-4), reflecting progressive pathophysiology. Premature mortality (deaths before 75 years) were ascertained via linkage to the National Death Index with follow-up until 2019. Cox proportional-hazards models adjusted for age, sex, race/ethnicity, medical history, and other confounding factors were used to calculate the hazard ratios (HR) and 95% CIs for CKM-mortality associations. Among 27,909 participants (mean age 49.7 years, 49.0% females), 1762 premature deaths occurred over a median follow-up of 8.3 years. Compared with stage 0, the adjusted HRs for all-cause premature mortality at CKM stages 1-4 were 0.88 (95% CI 0.66-1.17), 1.31 (0.99-1.73), 1.94 (1.31-2.87), and 2.19 (1.61-2.98), respectively. For CVD premature mortality, the adjusted HRs for CKM stages 1-4 were 1.12 (0.46-2.72), 1.74 (0.71-4.28), 3.93 (1.53-10.12), and 6.48 (2.95-14.20), respectively. Among adults at CKM stages 3-4, unfavorable SDOHs, particularly not living with a partner, low family income, lack of private health insurance, unemployment, or ≥2 cumulative SDOHs (4.16, 95% CI 3.35-5.18) were associated with increased all-cause premature mortality. Among those at CKM stages 0-2, unfavorable SDOHs were also related to increased premature mortality. CKM stages 3-4, but not stages 1-2, were associated with increased risks of premature mortality compared with stage 0. The risks were increased by unfavorable SDOHs across CKM stages.

Cardiovascular health (CVH) has been associated with cognitive decline and dementia, but the extent to which CVH affects brain health remains unclear. We investigated the association of CVH, assessed using Life's Essential 8 (LE8), with neuroimaging-based brain age and brain-predicted age difference (brain-PAD). This longitudinal community-based study was based on UK Biobank participants aged 40-69 years who were free from dementia and other neurologic diseases at baseline. LE8 score at baseline was assessed with 8 measures and tertiled as low, moderate, and high CVH. Structural and functional brain MRI scans were performed approximately 9 years after baseline, and 1,079 measures from 6 neuroimaging modalities were used to model brain age. A Least Absolute Shrinkage and Selection Operator regression model was trained in 4,355 healthy participants and then used to calculate brain age and brain-PAD in the whole population. Data were analyzed using linear regression models. The study included 32,646 participants (mean age at baseline 54.74 years; 53.44% female; mean LE8 score: 71.90). In multivariable-adjusted linear regression, higher LE8 score was associated with younger brain age (β [95% CI] -0.037 [-0.043 to -0.031]) and more negative brain-PAD (β [95% CI] -0.043 [-0.048 to -0.038]) (brain looks younger for chronological age). Compared with high CVH, low/moderate CVH was associated with older brain age (β [95% CI] 1.030 [0.852-1.208]/0.475 [0.303-0.647]) and increased brain-PAD (β [95% CI] 1.193 [1.029-1.357]/0.528 [0.370-0.686]). The associations between low CVH and older brain age/brain-PAD remained similar and significant in both middle-aged (β [95% CI] 1.199 [0.992-1.405]/1.351 [1.159-1.542]) and older adults (β [95% CI] 0.764 [0.417-1.110]/0.948 [0.632-1.263]). Low CVH is associated with older brain age and greater brain-PAD, even among middle-aged adults. Our findings suggest that optimizing CVH could support brain health. The main limitation of our study is that the study sample was healthier than the general population, thus caution is required when generalizing our findings to other populations.