📄 medicine

Intensity of Physical Activity and the Trajectory of Cardiovascular-Kidney-Metabolic Multimorbidity: A Multistate Analysis of Two Population-Based Cohorts

This multistate analysis of two large population-based cohorts demonstrates that higher-intensity physical activity significantly reduces the risk of cardiovascular-kidney-metabolic multimorbidity onset, progression, and mortality, with the most pronounced protective effects observed during early disease onset and the transition from metabolic to cardiovascular-metabolic disease.

Original authors: Wei Zhao, Qing Yan, Chuan Mou

Published 2026-08-20

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Wei Zhao, Qing Yan, Chuan Mou

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The human body is a complex machine where the heart, the kidneys, and the systems that manage sugar and fat in the blood do not work in isolation. When one of these systems begins to struggle, it often puts extra strain on the others, creating a chain reaction that can lead to a cluster of chronic conditions known as cardiovascular-kidney-metabolic multimorbidity. This is not merely the presence of two separate diseases; it is a progressive state where the failure of one system accelerates the decline of the others, a pattern that becomes increasingly common as people age. While it is widely known that moving the body helps the heart and metabolism, scientists have struggled to pinpoint exactly when and how exercise interrupts this specific chain of decline. Does a walk in the park stop the very first sign of trouble, or does it only help those who are already struggling with multiple conditions? Understanding the precise moment when physical activity exerts its greatest power is crucial for designing effective public health strategies that can keep older adults healthy for longer.

To answer this, researchers turned to two massive groups of people: nearly 20,000 middle-aged and older adults in China and more than 36,000 in Europe. These participants were part of long-term studies that track health over many years, allowing scientists to watch how people move from being healthy to developing single health issues, and eventually to accumulating multiple conditions. The researchers categorized the participants based on how active they were, distinguishing between those who were inactive, those who engaged in moderate activity, and those who performed vigorous exercise. They then mapped out the specific journey each person took through their health states, tracking the exact transitions from having no disease, to having a single issue like high blood pressure, to developing a combination of heart, kidney, and metabolic problems, and finally to death.

The study revealed a clear and consistent pattern: the more intense the physical activity, the lower the risk of falling into this dangerous cycle of multiple diseases. People who engaged in vigorous activity were significantly less likely to have multiple chronic conditions at any given time compared to those who were inactive. More importantly, when looking at the future, those who exercised vigorously were less likely to develop these multiple conditions in the first place. The analysis showed that this protective effect was not spread evenly across all stages of the disease process. Instead, the benefits were most concentrated at the very beginning of the journey. Physical activity was most powerful at preventing the initial onset of disease and at stopping the progression from a single metabolic issue, such as diabetes or high blood pressure, to a more complex state involving the heart and metabolism.

The researchers found that once a person developed a single metabolic problem, moving to a state where they also had heart or kidney issues was a critical turning point. Vigorous activity significantly reduced the likelihood of making this dangerous jump. The data suggested that the earlier the intervention, the better the outcome. While exercise helped people who were already sick, its most profound impact was seen in preventing the initial accumulation of disease and in reducing the risk of death for those who had already developed these conditions. The study also noted that the kidney system was less clearly linked to physical activity in their data, likely because self-reported kidney disease is harder to track accurately than heart or metabolic issues, but the overall trend for the heart and metabolism was undeniable.

By examining the specific pathways of disease progression, the study offered a new perspective on how to approach chronic illness in aging populations. It suggests that waiting until a person has multiple conditions to encourage exercise might be too late to prevent the most severe outcomes. Instead, the greatest benefit for the population would come from encouraging vigorous physical activity before metabolic disturbances appear, or very shortly after they are detected. This approach could stop the chain reaction before it gains momentum, keeping people in a state of health for longer and reducing the burden of complex, multi-system disease. The findings reinforce the idea that physical activity is not just a general health tip but a specific, powerful tool that can alter the trajectory of how chronic diseases develop and interact over a lifetime.

Problem Statement

Cardiovascular-kidney-metabolic (CKM) multimorbidity represents a critical public health challenge, characterized by the stepwise accumulation of impairments across the cardiovascular, kidney, and metabolic systems. While physical activity is widely recognized as protective for individual cardiovascular and metabolic health, its specific role in the trajectory of CKM development remains poorly understood. Existing literature often focuses on single disease endpoints or treats multimorbidity merely as the co-occurrence of conditions, failing to identify the specific stages in the disease accumulation process (from disease-free to single-domain, to multi-domain, to death) where physical activity exerts the greatest influence. Furthermore, conventional statistical methods (e.g., logistic regression, standard Cox models) provide static associations or unidirectional risks, lacking the capacity to reconstruct the full dynamic pathway of disease progression.

Methodology

The study utilized a longitudinal design analyzing data from two large, nationally representative cohorts:

China Health and Retirement Longitudinal Study (CHARLS): $n = 19,533$ (data from 2011–2020).
Survey of Health, Ageing and Retirement in Europe (SHARE): $n = 36,756$ (data from 2015–2020).

Key Methodological Components:

Exposure Definition: Physical activity was self-reported and categorized into three hierarchical levels: Inactive (reference), Moderately active (at least one moderate session/week, no vigorous), and Vigorously active (at least one vigorous session/week).
CKM Domain Definition: Diseases were assigned to three domains based on self-reported physician diagnoses:
- Cardiovascular (C): Heart attack, coronary heart disease, stroke, etc.
- Kidney (K): Kidney disease.
- Metabolic (M): Hypertension, diabetes/hyperglycemia, and high cholesterol/dyslipidemia.
- Multimorbidity: Defined as the presence of $\ge 2$ positive domains.
Statistical Approaches:
1. Cross-Sectional Analysis: Multivariable logistic regression to assess the association between activity levels and prevalent CKM burden.
2. Time-to-Event Analysis: Time-varying Cox proportional hazards models (with a one-wave lag to reduce reverse causation) to estimate the risk of incident CKM multimorbidity.
3. Multistate Modeling: A continuous-time Markov model was employed to map the disease progression. This model defined nine mutually exclusive states (No CKM; single domains C, K, M; two-domain states CK, CM, KM; three-domain state CKM; and Death). It allowed for 20 distinct unidirectional transition pathways (no recovery or domain regression in the primary model) to estimate transition intensities, probabilities, and mean sojourn times.
Covariates: All models were adjusted for age, sex, residence, education, marital status, wealth, smoking, alcohol use, and depressive symptoms.

Key Results

1. Cross-Sectional Associations:
After full adjustment, vigorously active participants demonstrated significantly lower odds of prevalent CKM multimorbidity compared to inactive participants in both cohorts:

CHARLS: OR = 0.64 (95% CI 0.59–0.69).
SHARE: OR = 0.60 (95% CI 0.56–0.63).
The protective association strengthened as the number of affected domains increased.

2. Incident Risk (Time-to-Event):
Vigorous activity was associated with a reduced risk of developing incident CKM multimorbidity:

CHARLS: HR = 0.83 (95% CI 0.75–0.92).
SHARE: HR = 0.79 (95% CI 0.72–0.87).
The association for moderate activity was significant in SHARE but not in CHARLS.

3. Multistate Transition Dynamics:
The multistate analysis revealed that the protective effect of vigorous activity is not uniform across all disease stages but is concentrated in specific transitions:

Onset: Strongest protection observed at the transition from a disease-free state to the onset of a single domain, particularly Cardiovascular onset and the transition from Metabolic to Cardiovascular-Metabolic (M $\to$ CM) disease.
- CHARLS (M $\to$ CM): HR = 0.71 (95% CI 0.62–0.82).
- SHARE (M $\to$ CM): HR = 0.80 (95% CI 0.71–0.89).
Progression: Activity reduced the risk of progressing to higher-order multimorbidity states.
Mortality: Vigorous activity was consistently associated with lower transition intensities to death from all living states.
Sojourn Times: Once individuals reached the CKM multimorbidity state (3 domains), the mean sojourn time was long (e.g., 27.6 years in CHARLS), indicating the difficulty of reversing established multimorbidity.

4. Sensitivity Analyses:
Results remained robust when the metabolic domain was redefined (excluding lipids), when using complete-case analysis, and when applying competing-risk models. A supplementary four-state model allowing for backward recovery confirmed that the CKM multimorbidity state remains highly persistent even when recovery is theoretically possible.

Key Contributions

Granular Trajectory Mapping: Unlike previous studies that treated multimorbidity as a static endpoint, this study utilized a nine-state multistate model to map the specific pathways of CKM accumulation across two distinct populations (China and Europe).
Stage-Specific Insights: The study identified that physical activity's most potent protective effects occur at the early onset of disease and during the transition from metabolic disturbance to combined cardiovascular-metabolic disease, rather than solely at the final stages of severe multimorbidity.
Cross-Population Validation: The consistency of findings across CHARLS and SHARE suggests that the protective mechanisms of physical activity against CKM accumulation are generalizable across different healthcare systems and cultural contexts.
Methodological Rigor: By distinguishing the independent progression of cardiovascular, kidney, and metabolic domains, the study provides a more nuanced understanding of how activity influences specific disease domains (e.g., noting that kidney-related transitions were less consistently significant, likely due to data limitations).

Significance and Claims

The authors claim that these findings reinforce the role of physical activity as a primary prevention strategy for CKM syndrome. The study suggests that the greatest population-level benefit is achieved by intervening before or shortly after the appearance of metabolic disturbance, as this is the stage where activity most effectively halts the cascade toward multi-domain multimorbidity.

The paper modestly concludes that while the observational design cannot rule out all residual confounding, the use of time-varying exposures and lagged analyses mitigates reverse causation. The authors emphasize that because established multimorbidity is difficult to reverse (long sojourn times), early intervention is critical. They do not claim to have proven causality definitively but argue that the results provide strong evidence to support physical activity guidelines specifically targeting the early stages of CKM accumulation to improve population health and reduce mortality.

Problem Statement

Methodology

Key Results

Key Contributions

Significance and Claims

More like this