Correlation between Rate-Pressure Product or Pressure-Rate Quotient and Urinary Albumin-Creatinine Ratio in the Chinese Older Population: The REACTION Study
Chronic kidney disease (CKD) is a significant health threat globally, and an elevated urinary albumin-creatinine ratio (UACR) is a critical marker of impaired renal function and a key risk factor for cardiovascular disease. The rate-pressure product (RPP) and pressure-rate quotient (PRQ) are widely used in clinical practice to quantify cardiac load and hemodynamic response to exercise. Understanding the relationships between RPP or PRQ and UACR is essential for better predicting CKD, particularly in the older population.
This study, conducted as part of the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) Study, aimed to explore the correlation between RPP or PRQ and UACR in the Chinese older population. The REACTION Study initially investigated the association between type 2 diabetes mellitus (T2DM) and/or prediabetes and cancer risk in the general Chinese population. For this analysis, a total of 47,808 participants from seven regional centers in China (Dalian, Lanzhou, Guangzhou, Luzhou, Shanghai, Zhengzhou, and Wuhan) were enrolled. After excluding individuals with primary renal diseases, cardiovascular diseases, neoplastic diseases, and those with missing data or outliers, 34,333 participants were included in the final analysis.
The study collected data on various indicators, including sex, age, smoking status, drinking status, height, weight, waist circumference (WC), hip circumference (HC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), triglycerides (TGs), alanine transferase (ALT), aspartate transferase (AST), gamma-glutamyl transferase (GGT), creatinine (Cr), fasting plasma glucose (FPG), postprandial plasma glucose (PPG), glycosylated hemoglobin (HbA1c), fasting insulin, and UACR. Participants were divided into two groups based on UACR: the normal group (UACR <30 mg/g) and the albuminuria group (UACR ≥30 mg/g). RPP was defined as the product of systolic blood pressure (SBP) and heart rate (HR), while PRQ was calculated by dividing the mean arterial pressure (MAP) by the HR. Participants were further stratified into four groups based on RPP/PRQ percentiles (<25%, 25%–50%, 50%–75%, and ≥75%).
The study also classified participants based on blood glucose levels and body mass index (BMI). According to World Health Organization (WHO) Guidelines, normal glucose tolerance (NGT) was defined as FPG <6.1 mmol/L and PPG <7.8 mmol/L; impaired glucose regulation (IGR) was defined as 6.1 mmol/L ≤ FPG <7.0 mmol/L and/or 7.8 mmol/L ≤ PPG <11.1 mmol/L; and diabetes mellitus was defined as FPG ≥7.0 mmol/L and/or PPG ≥11.1 mmol/L. BMI subgroups were categorized as <18.5 kg/m², 18.5–25.0 kg/m², and ≥25.0 kg/m².
Statistical analysis was performed using SPSS 25.0 software. Continuous variables were expressed as mean ± standard deviation, and categorical variables were expressed as frequencies and percentages. Analysis of variance was used for quantitative data, while the chi-squared test was used for qualitative data. Binary logistic regression analysis was conducted to determine the relationships between RPP or PRQ and UACR, with three models established for this purpose. A restricted cubic spline model with three knots at the 25th, 50th, and 75th percentiles of RPP and PRQ was used to account for potential nonlinear trends.
Among the 34,333 participants (10,577 males and 23,756 females), the average age was 58.3±9.2 years. Baseline characteristics showed that participants in the albuminuria group were older and had higher obesity indices (BMI, WC, and HC), SBP, diastolic blood pressure (DBP), HR, blood glucose indices (FPG, PPG, HbA1c, and fasting insulin), TG, liver function indices (ALT, AST, and GGT), and Cr compared to the normal group. Conversely, the albuminuria group had lower HDL, LDL, TC, and estimated glomerular filtration rate (eGFR).
Binary logistic regression analysis revealed that RPP and higher PRQ were significantly correlated with UACR across all models. The correlation between RPP and UACR was stronger than that between PRQ and UACR. In male participants, RPP and PRQ were significantly correlated with UACR, with odds ratios (ORs) increasing with higher RPP and PRQ percentiles. For example, the OR for RPP at the 75th percentile was 2.66 (95% CI: 2.18–3.25, P <0.001). In female participants, RPP was significantly correlated with UACR, but the correlation with PRQ was only significant at the 50th and 75th percentiles. The OR for RPP at the 75th percentile in females was 1.64 (95% CI: 1.46–1.84, P <0.001).
The study also stratified participants based on blood glucose levels and BMI. RPP was positively associated with UACR in individuals with different blood glucose levels, with the strongest correlation observed in those with normal glucose tolerance and diabetes mellitus. Similarly, RPP was positively associated with UACR in individuals with a BMI ≥18.5 kg/m², with the strongest correlation in overweight individuals (BMI ≥25.0 kg/m²). Higher PRQ was also significantly correlated with UACR across different blood glucose and BMI subgroups.
The study highlighted that albuminuria was present in 13.9% of the older Chinese population. Increased proteinuria is a major determinant of renal function decline in various conditions, including CKD, hypertension, and T2DM. Blood pressure and heart rate are critical hemodynamic parameters for evaluating health, and the combination of these variables, as in RPP and PRQ, may provide better indicators of myocardial oxygen consumption (MVO2). RPP, which reflects the product of SBP and HR, is associated with stroke volume (SV), vascular resistance (VR), and HR. PRQ, calculated as MAP divided by HR, reflects SV and VR. Both RPP and PRQ are influenced by sympathetic and parasympathetic nervous system activity.
The study found that RPP is more capable of predicting kidney disease compared to BP and PRQ, likely due to its enhanced sympathetic nervous system activation, which plays a significant role in renal insufficiency. Elevated heart rate can lead to endothelial cell damage, increasing endothelial cell permeability and microalbuminuria. The predictive ability of RPP and PRQ for CKD was stronger in males than in females, which may be related to sex hormones and renal hemodynamics. Females generally have higher renal vascular resistance and lower absolute resistance, glomerular filtration rate (GFR), and renal plasma flow. Estrogens increase angiotensinogen synthesis but decrease renin and angiotensin-converting enzyme (ACE) synthesis, while testosterone is associated with increased renin release.
The study benefited from a large, community-based sample with wide geographical distribution across China, making the findings generally representative. However, as a cross-sectional study, it could only establish associations and not causality, limiting its predictive value for outcomes. Further prospective follow-up studies are needed to fully determine the mechanisms underlying the association between RPP or PRQ and UACR.
In conclusion, this study demonstrated a significant correlation between RPP or PRQ and UACR in the Chinese older population. The correlation between RPP and UACR was stronger than that between PRQ or BP and UACR, suggesting that RPP may be a better predictor of CKD. These findings underscore the importance of considering hemodynamic parameters in assessing renal health and highlight the need for further research to explore these relationships in greater depth.
doi.org/10.1097/CM9.0000000000002941
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