Why the study?
Cardio-kidney-metabolic (CKM) diseases share classical risk factors, but the shared and distinct risk factors driving longitudinal changes in CKM indicators and disease progression remain unclear.
Do classical phenotypical, demographic, and lifestyle risk factors (age, sex, education, alcohol and tobacco consumption, BMI, and waist circumference) predict baseline cardio-kidney-metabolic indicators and their 5-year longitudinal changes in a general population cohort?
Cohort (n=2,650)
No
Do classical phenotypical, demographic, and lifestyle risk factors (age, sex, education, alcohol and tobacco consumption, BMI, and waist circumference) predict baseline cardio-kidney-metabolic indicators and their 5-year longitudinal changes in a general population cohort?
Classical cardio-kidney-metabolic risk factors strongly correlate with baseline HbA1c, blood pressure, arterial stiffness, and kidney function cross-sectionally, but have limited utility in predicting 5-year longitudinal changes in these indicators in the general population, with only age and BMI predicting changes in pulse wave velocity.
Background Cardio-kidney-metabolic (CKM) diseases share risk factors, but their shared and distinct risk factors for disease progression remain unclear. We examined whether classical risk factors predict baseline CKM indicators and their longitudinal changes in a population-based German National Cohort (NAKO) sample. Methods In 2,650 NAKO-IMMEDIATE participants selected for deep-phenotyping, baseline values and 5-year changes in — glycated hemoglobin (HbA1c), systolic blood pressure (SBP), pulse wave velocity (PWV), and estimated glomerular filtration rate (eGFR) were linearly regressed on age, sex, education, alcohol and tobacco consumption, body mass index (BMI), and residuals of BMI-adjusted waist circumference (WC) with mutual adjustment. Results Baseline values for HbA1c were 34.6±5.8 mmol/mol, for PWV 8.3±1.5 m/s, for SBP 128.0±15.7 mmHg and for eGFR 96.0±14.6 ml/min/1.73 m². Cross-sectionally, all risk factors were associated with one or more of the CKM indicators, with age and BMI being associated with all four indicators. Over 5 years, HbA1c (1.2±4.2 mmol/mol), PWV (0.5±1.2 m/s) and SBP (0.6± 14.2 mmHg) increased, whereas eGFR (−2.3±9.5 ml/min/1.73 m²) decreased. Age (0.03 m/s per 5 year, 95% CI 0.01, 0.06 m/s) was associated with higher and BMI (−0.02 m/s per 1kg/m2, −0.03, −0.01) with lower PWV changes. No other risk factors were associated with CKM indicator changes. Conclusion Classical risk factors were more frequently related to baseline CKM indicators than to their 5-year changes. Within longitudinal analyses, only age and BMI were related to PWV 5-year changes. Clinical Perspective It is well established that classical risk factors are associated with cardio-kidney and metabolic (CKM) diseases whereas their associations with longitudinal changes in CKM indicators are less well understood. This study examines to what extent age, sex, education, alcohol and tobacco consumption, BMI and waist circumference are associated with glycated hemoglobin, systolic blood pressure, pulse wave velocity and estimated glomerular filtration rate at baseline and their 5-year changes. Only age and BMI were associated with changes in PWV, while other longitudinal associations were non-significant, suggesting that classical CKM risk factors have greater utility for assessing cross-sectional CKM function than for predicting prospective changes in CKM function in the general population.
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Chiappe et al. (2026) conducted a cohort in Cardio-kidney-metabolic (CKM) function transition (type 2 diabetes, cardiovascular disease, and kidney dysfunction) (n=2,650). Classical risk factors (age, sex, education, alcohol and tobacco consumption, body mass index, and BMI-adjusted waist circumference) vs. Lower/reference risk factor levels in mutually adjusted multivariable linear regression was evaluated on 5-year longitudinal change in pulse wave velocity (PWV) and other CKM indicators (HbA1c, SBP, eGFR) (MD 0.03 m/s per 5 years of age (and MD -0.02 m/s per 1 kg/m2 BMI), 95% CI 0.01, 0.06, p=<0.05).
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