Cardiovascular disease (CVD) is the most common chronic non-communicable disease, with an increasing prevalence worldwide and is also the leading cause of death globally. The ratio of high-sensitivity C-reactive protein (hs-CRP) to albumin (ALB) , known as the C-reactive protein to albumin ratio (CAR) , is a novel inflammatory marker. Our research team has previously investigated its association with CVD and found that a high CAR is closely related to an increased risk of CVD onset. Existing studies have reported that the risk of CVD associated with high levels of hs-CRP decreases gradually from middle-aged populations (51-64 years) to elderly populations (≥65 years) . However, it remains unclear whether the impact of CAR, as a novel marker for assessing CVD risk, on incident CVD differs among different age groups.

To explore the impact of CAR on incident CVD in different age groups.

A total of 54 951 participants who attended the third health examination in the Kailuan Cohort Study in 2010 were included. Demographic and clinical data, physical examination results, and laboratory test indicators of the participants were collected. The CAR was calculated and log-transformed (lgCAR) . Participants were divided into four quartile groups based on lgCAR: Q1 (lgCAR<-4.34, n=13 744) , Q2 (-4.34≤lgCAR<-3.67, n=13 731) , Q3 (-3.67≤lgCAR<-2.83, n=13 736) , and Q4 (lgCAR≥-2.83, n=13 740) . They were also stratified by age into <40 years (n=9 617) , 40-49 years (n=12 633) , 50-59 years (n=17 740) , and ≥60 years (n=14 691) . Follow-up began from the time of the 2010 health examination and ended at the occurrence of CVD, all-cause death, or the end of follow-up on 2021-12-31. The cumulative incidence of CVD in the total population and each age group was calculated using the Kaplan-Meier method, and comparisons between groups were made using the Log-rank test. Cox proportional hazards regression analysis was used to assess the risk of CVD in the total population at different CAR levels. The multiplicative interaction between age and CAR quartile groups was explored using the Cox regression model, and the analysis was repeated after stratifying by age. To eliminate the impact of medication use on the results, sensitivity analyses were conducted by excluding participants who took antihypertensive, antidiabetic, or lipid-lowering drugs at baseline or during follow-up. To eliminate the impact of reverse causality and short follow-up duration, sensitivity analyses were conducted by excluding participants with a follow-up duration of less than 1 year. Given the high mortality risk of CVD and the potential competition between CVD and patient death, a competing risk model for death was used to analyze the impact of different CAR levels on CVD in participants aged 60 years and older.

A total of 54 951 participants were included in the final analysis, including 41 083 men (74.8%) and 13 868 women (25.2%) , with a mean age of 51.7±12.8 years. The mean lgCAR values in groups Q1 to Q4 were -5.6±1.5, -4.0±0.2, -3.3±0.2, and -2.2±0.6, respectively. There were statistically significant differences among the Q1 to Q4 groups in terms of age, gender, higher education, smoking, alcohol consumption, physical exercise, BMI, hs-CRP, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, total cholesterol, systolic blood pressure, diastolic blood pressure, diabetes, hypertension, antihypertensive medication use, antidiabetic medication use, lipid-lowering medication use, estimated glomerular filtration rate, alanine aminotransferase, ALB, and lgCAR (P<0.05) . The mean follow-up duration was 10.38±1.99 years, during which 3, 444 participants (6.27%) developed CVD. The number of incident CVD cases in groups Q1 to Q4 was 659, 809, 901, and 1 075, respectively, with cumulative incidences of 4.79%, 5.89%, 6.56%, and 7.82%. The Log-rank test showed that the differences in cumulative incidence of CVD among the Q1 to Q4 groups in the total population and different age groups were statistically significant (P<0.05) . The results of The Cox proportional hazards regression model indicated that after adjusting for confounding factors, the risk of incident CVD in group Q4 was 1.20 times that of group Q1 (HR=1.20, 95%CI=1.07-1.35) , and there was an interaction between age and CAR group with CVD (P_interaction=0.021) . In the <40 years, 40-49 years, 50-59 years, and ≥60 years age groups, the risk of incident CVD in group Q4 was 1.13 times (HR=1.13, 95%CI=0.55-2.33) , 1.44 times (HR=1.44, 95%CI=1.06-1.96) , 1.24 times (HR=1.24, 95%CI=1.02-1.50) , and 1.11 times (HR=1.11, 95%CI=0.93-1.33) that of group Q1, respectively. The results of the sensitivity analysis showed that after excluding participants who took lipid-lowering drugs at baseline or during follow-up, there was an interaction between age and CAR group with CVD (P_interaction=0.020) . After excluding participants who took antidiabetic drugs at baseline or during follow-up, there was an interaction between age and CAR group with CVD (P_interaction=0.015) . After excluding participants with a follow-up duration of less than 1 year, there was an interaction between age and CAR group with CVD (P_interaction=0.045) . The Cox proportional hazards regression model analysis found that the association between CAR group and incident CVD was consistent with the main results, and the association between CAR group and incident CVD still existed in the middle-aged population (40-59 years) , with the risk of CVD associated with elevated CAR decreasing with age. After excluding participants who took antihypertensive drugs at baseline or during follow-up, the interaction between age and CAR group with CVD was not significant (P_interaction=0.114) . The Cox proportional hazards regression model analysis found that compared with the main results, in the 50-59 years age group, the statistical association between CAR group and incident CVD was not significant (P>0.05) . The competing risk model for death was used to analyze the impact of different CAR levels on CVD in participants aged 60 years and older, and the results were consistent with the main results, showing no association between CAR and incident cardiovascular events.

A high CAR level is an independent risk factor for incident CVD. The association between CAR and the risk of CVD onset is age-dependent in the middle-aged population, and the risk of CVD associated with elevated CAR decreases with increasing age.

心血管疾病（CVD）是最常见的慢性非传染性疾病，其患病率在全球范围内呈上升趋势，也是世界上人口死亡的主要原因。超敏C反应蛋白（hs-CRP）与白蛋白（ALB）比值（CAR）是一种新型的炎症指标，既往本研究团队对其与CVD的关联进行了研究，发现高CAR与CVD发病风险增加密切相关。且目前已有研究报道了从中年人群（51~64岁）到老年人群（≥65岁），高水平的hs-CRP所致的CVD发病风险逐渐降低。然而，CAR作为评估CVD风险的新型指标，其对新发CVD的影响在不同年龄段人群中是否存在差异尚不明确。

探讨不同年龄段CAR对新发CVD的影响。

纳入参加开滦队列研究2010年度第3次体检的54 951例参与者为研究对象，收集参与者人口学与临床数据、体检资料与实验室检查指标。计算CAR并进行对数转化（lgCAR），依据lgCAR四分位数将研究对象分为Q1组（lgCAR<-4.34，n=13 744）、Q2组（-4.34≤lgCAR<-3.67，n=13 731）、Q3组（-3.67≤lgCAR<-2.83，n=13 736）、Q4组（lgCAR≥-2.83，n=13 740），并按年龄进行分层，即<40岁（n=9 617）、40~49岁（n=12 633）、50~59岁（n=17 740）和≥60岁（n=14 691）。以完成2010年度体检的时间为随访起点，以发生CVD、全因死亡和到达随访结束日期为随访终点对患者进行随访，随访截至2021-12-31。采用Kaplan-Meier方法计算总人群和各年龄段人群CVD累积发病率，并采用Log-rank检验进行组间比较。采用Cox比例风险回归分析不同CAR水平总人群发生CVD的风险。通过Cox比例风险回归模型探究年龄与CAR各分位数组间的乘法交互作用，并按年龄进行分层重复上述分析。为了消除服用药物对结果产生的影响，排除基线和随访时服用降压、降糖、降脂药物的研究对象后进行敏感性分析；为了消除反向因果关系和随访时间过短对结果造成的影响，排除随访时间<1年的研究对象后进行敏感性分析；由于CVD的死亡风险较高，CVD和患者死亡之间可能存在相互竞争，因此对60岁以上的参与者采用死亡竞争风险模型分析不同CAR水平对CVD的影响。

最终纳入54 951例研究对象，其中男41 083例（74.8%），女13 868例（25.2%），研究对象平均年龄（51.7±12.8）岁，Q1~Q4组平均lgCAR分别为-5.6±1.5、-4.0±0.2、-3.3±0.2、-2.2±0.6。Q1~Q4组年龄、性别、接受高等教育、吸烟、饮酒、体育锻炼、BMI、hs-CRP、低密度脂蛋白胆固醇、高密度脂蛋白胆固醇、总胆固醇、收缩压、舒张压、糖尿病、高血压、服用降压药、服用降糖药、服用降脂药、估算肾小球滤过率、丙氨酸氨基转移酶、ALB、lgCAR比较，差异有统计学意义（P<0.05）。平均随访（10.38±1.99）年，随访期间共3 444例（6.27%）研究对象发生了CVD，Q1~Q4组新发CVD病例分别为659、809、901、1 075例；累积发病率分别为4.79%、5.89%、6.56%、7.82%，Log-rank结果表明，总人群与不同年龄段Q1~Q4组研究对象CVD的累积发病率差异有统计学意义（P<0.05）。Cox比例风险回归模型分析结果表明，在校正混杂因素后，Q4组人群新发CVD的风险是Q1组的1.20倍（HR=1.20，95%CI=1.07~1.35），年龄和CAR组与CVD存在交互作用（P_交互=0.021）。在<40岁、40~49岁、50~59岁和≥60岁人群中Q4组新发CVD的风险分别为Q1组的1.13倍（HR=1.13，95%CI=0.55~2.33）、1.44倍（HR=1.44，95%CI=1.06~1.96）、1.24倍（HR=1.24，95%CI=1.02~1.50）和1.11倍（HR=1.11，95%CI=0.93~1.33）。敏感性分析结果显示，在排除基线和随访期间服用降脂药的人群中，年龄和CAR组与CVD存在交互作用（P_交互=0.020），在排除基线和随访期间服用降糖药的人群中，年龄和CAR组与CVD存在交互作用（P_交互=0.015），在排除随访时间<1年的人群中，年龄和CAR组与CVD存在交互作用（P_交互=0.045）；Cox比例风险回归模型分析结果与主结果保持一致，CAR分组与新发CVD的关联在中年人群（40~59岁）中依然存在，并且随着年龄的增长，CAR升高所导致的CVD发病风险降低。排除在基线和随访期间服用降压药的人群后，年龄和CAR组与CVD之间的交互作用不显著（P_交互=0.114）；Cox比例风险回归模型分析发现，与主结果相比，在50~59岁人群中，CAR分组与新发CVD的统计学关联无意义（P>0.05）。对≥60岁研究对象采用死亡竞争风险模型分析不同CAR水平对CVD的影响，结果与主结果保持一致，CAR与新发心血管事件无关联。

高CAR水平是新发CVD的独立危险因素，CAR与CVD发病风险的关联在中年人群呈年龄依赖性，而随着年龄增加，高CAR所致的CVD发病风险呈下降趋势。