Impact of different physical examination frequencies on biochemical indicator variability in community-dwelling older adults: an 8-year retrospective cohort study

Technical Summary: Impact of Different Physical Examination Frequencies on Biochemical Indicator Variability in Community-Dwelling Older Adults

Problem Statement
With the accelerating aging of China's population, cardiovascular disease (CVD) has become the leading cause of mortality, driven significantly by the accumulation of modifiable risk factors. While the World Health Organization designates regular health examinations as a core primary prevention strategy, existing evidence largely relies on cross-sectional data from single examinations. There is a critical gap in longitudinal understanding regarding how the frequency of health examinations—a behaviorally modifiable factor—influences the long-term trajectories of cardiometabolic and hepatic/renal indicators in older adults. This study addresses the need to clarify whether higher examination frequencies can delay or reverse the deterioration of these critical health markers.

Methodology
The research employed an 8-year retrospective cohort study design (2018–2025) utilizing data from the National Basic Public Health Service (NBPH) database at the Tairi Community Health Service Center in Shanghai.

• Cohort: The study included 57,020 valid examination records from community-dwelling permanent residents aged ≥60 years who completed all mandatory national protocol items.
• Exposure Variable: The total number of health check-ups attended by each individual over the 8-year period was treated as a continuous exposure variable.
• Outcomes: Eleven biochemical indicators were analyzed, including Body Mass Index (BMI), serum creatinine (CREA), blood urea nitrogen (BUN), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and fasting glucose (GLU).
• Statistical Analysis: Linear Mixed-Effects Models (LMM) with random intercepts for each subject were used to analyze longitudinal changes. The models adjusted for age, sex, baseline indicator values, and time. Crucially, an interaction term between examination frequency and time was included to determine if the rate of change in indicators differed based on examination frequency.
• Data Handling: Skewed variables (TG, ALT, AST, GLU) underwent natural logarithmic transformation. Multiple comparisons were corrected using the Benjamini-Hochberg procedure to control the false discovery rate (FDR).

Key Results
The longitudinal analysis revealed a complex, indicator-specific association between examination frequency and health trajectories:

1. Favorable Trajectories (Renal, Lipid, and Hepatic): Higher examination frequency was significantly associated with improved long-term trajectories for several key indicators.

   • Renal Function: Serum creatinine (CREA) levels decreased significantly with higher frequency (β = −0.926 µmol/L per additional check-up), with a significant negative interaction over time, suggesting accelerated improvement.
   • Lipid Profile: LDL-C levels decreased (β = −0.029 mmol/L), also showing a significant negative time interaction. Total cholesterol (TC) and triglycerides (log-transformed) showed main effects, though TG showed a positive interaction (see below).
   • Liver Enzymes: ALT levels decreased significantly (log ALT: β = −0.0077).
   • Other Indicators: Total bilirubin (TBIL), fasting glucose (log GLU), and AST showed significant negative main effects, indicating lower levels associated with frequent exams, though without significant time interactions.

2. Adverse or Neutral Trajectories:

   • BMI and Triglycerides: Contrary to the favorable trends in other markers, higher examination frequency was associated with a faster increase in BMI over time (interaction β = 0.011 kg/m²/year) and a slight increase in triglyceride levels.
   • BUN: No significant association was found between examination frequency and blood urea nitrogen levels.
   • HDL-C: Showed a minimal negative main effect but no significant interaction with time.

3. Sex Stratification: While some variations were observed in interaction effects between sexes (e.g., for log TG), three-way interaction tests revealed no statistically significant differences, indicating that sex was not a significant modifier of the overall interaction effects.

Significance and Claims
The paper posits that regular health monitoring is a valuable strategy for chronic disease risk management, but its efficacy is not universal across all biological markers.

• Monitoring-Feedback-Action Cycle: The study suggests that for indicators like CREA, LDL-C, and liver enzymes, frequent examinations may facilitate a "monitoring-feedback-action" cycle. Regular data feedback likely enhances health awareness, prompting lifestyle adjustments or timely medical adherence that improves these specific markers over time.
• Limitations of Monitoring Alone: The adverse trends observed for BMI and triglycerides highlight a critical limitation: biological monitoring alone is insufficient to reverse the natural deterioration of indicators heavily influenced by lifestyle (diet and physical activity). The authors suggest that the observed rise in BMI and TG among frequent examiners may reflect "reverse causation" (individuals with existing metabolic risks seeking more frequent care) or a management dilemma where monitoring is not paired with effective, structured lifestyle interventions.
• Ceiling Effect: For indicators like TBIL, GLU, and TC, the study observes a "ceiling effect" or diminishing returns. Frequent exams help maintain favorable levels and correct initial risks, but they do not necessarily accelerate the rate of decline once a stable control plateau is reached.

Conclusion
The study concludes that while higher examination frequencies are generally associated with more favorable long-term trajectories for cardiometabolic and hepatic/renal function, this benefit is not automatic. To achieve comprehensive health promotion, particularly for weight and lipid management, biological indicator monitoring must be deeply integrated with effective, sustained lifestyle interventions rather than relying on monitoring as a standalone strategy.