Abstract
Objective
This study aimed to investigate the effect of the ratio of cumUHR on MI, based on the hypothesis that higher exposure to the ratio of cumUHR is associated with a higher risk of MI.
Methods
Participants who underwent three examinations between 2006 and 2010 were selected. The cumUHR from baseline to the third check was calculated, multiplying the mean between consecutive checks by the time interval between visits. The association between cumUHR and MI and its progression was evaluated by Cox proportional hazards regression model. The cumulative incidence of endpoint events between cumUHR groups was compared using a log-rank test. Stratification by age, sex, and BMI was further performed.
Results
A total of 53,697 people, with an average age of 53.08 years, 78 % of whom were male, with a median follow-up of 10.51 years and 744 myocardial infarction events, were enrolled. The highest cumUHR quartile, MI, had the highest cumulative incidence (log-rank P < 0.01). Multivariate COX regression analysis showed that in the fully adjusted model, there was a high level of concentration in the highest cumUHR quartile (HR, 1.52; 95 % CI, 1.20-1.92) and participants with longer duration of high UHR exposure (HR, 1.55; 95 % CI, 1.22-1.97).
Conclusions
The risk of MI increases with cumUHR and is influenced by the time course of cumUHR. In particular, in people aged ≥ 60 years, males, and BMI < 28 kg/m 2 , the risk of MI is more affected by the level of UHR, and more attention should be paid to controlling the level of UHR.
Introduction
Myocardial infarction (MI) is the leading cause of cardiovascular disease deaths worldwide, accounting for about half of CVD deaths and a quarter of all global deaths in 2019. Its prevalence has also been on the rise, increasing from 96.89 million in 1990 to 197 million in 2019. , In China, the number of people affected by MI increased from 17.46 million in 1990 to 45.2 million in 2019. The mortality rate of MI has also been increasing, from 32.56 per 100,000 in 2002 to 131.39 per 100,000 in 2020 MI places a heavy burden on the global healthcare system, especially in China, so a better understanding and identification of risk factors to prevent MI is of great importance for public health and clinical practice.
In addition to the traditional risk factors such as hypertension, diabetes, dyslipidemia, and alcohol consumption, elevated serum uric acid (SUA) and decreased high-density lipoprotein cholesterol (HDL-C) are risk factors for morbidity and mortality of MI The ratio of UA to HDL-C (uric acid to high-density lipoprotein cholesterol ratio) is a biomarker representing chronic inflammation and metabolic status, , which can predict not only the risk of type 2 diabetes mellitus, metabolic syndrome, and acute coronary syndrome, but also the risk of MI. However, most of the current studies on the relationship between UHR and MI use a single measurement, which is insufficient to accurately reflect the effect of long-term UHR levels on the development of MI . Therefore, we evaluated the relationship between cumulative UHR (cumUHR) and MI based on a large community prospective cohort of the Kailuan study (study registration number: ChiCTR-TNC-11001489).
Methods
Study population
The participants in this study are from the Kailuan study. The Kailuan Study is a prospective cohort study being conducted in Tangshan, China. From 2006 to 2007 (hereinafter referred to as 2006), Kailuan General Hospital and its 11 affiliated hospitals conducted the first health examination and questionnaire survey on the in-service and retired employees of Kailuan Group, and then conducted a follow-up visit to them every two years, and conducted a health assessment and questionnaire survey on demographic characteristics, lifestyle factors and medication history. This study was approved by the Ethics Committee of Kailuan General Hospital in accordance with the Declaration of Helsinki (Yilun Zi No. 5, 2006).
Inclusion criteria: (1) Those who participated in the 2006, 2008 and 2010 health examinations consecutively; (2) Those who agree to participate in this study and sign the informed consent form. Exclusion criteria: (1) Patients with a history of myocardial infarction and malignant tumors before 2010 were excluded; (2) Excluding patients with missing UA and/or HDL-C physical examination data. In the end, a total of 53,697 participants were included in this study. The inclusion and exclusion process is shown in Fig. 1 .
Data collection
Anthropometric data: including height, weight, and blood pressure, measured by trained investigators following the standard procedures previously described. The measurement will be carried out from 7:00 to 9:00 on the day of the physical examination, and the examinee will take off his hat, wear light clothes and barefoot, and stand in a “standing upright” posture. The height measurement is accurate to 0.1cm, and the weight measurement is accurate to 0.1 kg Body mass index (BMI) is calculated by dividing your weight (kg) by the square of your height (m 2 ). Do not smoke, drink, drink tea, coffee, etc. within 30 min before the blood pressure measurement, and sit quietly with your back for 15 min. The right brachial artery blood pressure was measured by a calibrated benchtop mercury column sphygmomanometer, and the first tone of the Korotkoff sound was used for systolic blood pressure (SBP) reading, and the fifth tone of the Korotkoff sound was used for diastolic blood pressure (DBP) reading. Measure 3 times continuously, with an interval of 1∼2 min each time and take the average value.
Biochemical index measurements: including HDL-C, UA, Low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), serum creatinine (Cr), and high-sensitivity C-reactive protein, hs-CRP). After fasting for 8 to 12 h, fasting blood samples are collected in the morning and infused into a vacuum tube containing EDTA, centrifuged at room temperature and the supernatant is taken for measurement over 4 h. Determine the concentration of UA using a commercial kit (Kehua Bioengineering, Shanghai, China) according to the manufacturer’s instructions. HDL-C and LDL-C are measured using enzymatic colorimetry. FBG was analyzed by hexokinase/glucose-6-phosphate dehydrogenase method. Cr and hs-CRP are measured using the sarcosine oxidase assay. All plasma samples were analyzed at the central laboratory of Kailuan General Hospital with an automated analyzer (Hitachi 7600, Tokyo, Japan). The estimated glomerular filtration rate (eGFR) was calculated using the Cr-based Cooperative Equation for Epidemiology of Chronic Kidney Disease (CKD-EPI).
Questionnaires: Epidemiological data were collected through face-to-face surveys using standard structured questionnaires, including sociodemographic characteristics (age, gender, income, education), lifestyle (dietary habits, smoking, alcohol consumption, physical activity), personal medical history (past medical history), and medication records (antihypertensives, antidiabetics, and lipid-lowering drugs). Smoking is defined as smoking at least 1 cigarette per day on average in the past 1 year. Alcohol consumption is defined as drinking an average of 100ml of liquor (alcohol content ≥50 %) per day for >1 year. Active physical activity is defined as exercising ≥ 3 times per week, with each exercise lasting at least 30 min. The level of education is divided into below high school and above high school. Total salt intake is divided into ≤10 g/day (non-high salt intake) and >10 g/day (high salt intake).
Calculation of cumUHR, duration of high UHR exposure, and grouping
(1) UHR is defined as the ratio of UA to HDL-C: UHR = UA/HDL-C.
(2) cumUHR is defined as the sum of the mean of the UHR of two adjacent physical examinations and the product of the years of continuous follow-up. The calculation is as follows: cumUHR=(UHR2006 + UHR2008)/2 × time2006-2008+(UHR2008+UHR2010)/2 × time 2008-2010 Here, the UHR2006, UHR2008, and UHR2010 are calculated in 2006, 2008, and 2010, respectively, and the UHR, time2006-2008, and time 2008-2010 are the intervals between the two adjacent physical examinations.
The cumUHR quartiles were divided into four groups, i.e., the first quartile (Q1): cumUHR <602.79, the second quartile (Q1): 602.79≤cumUHR <755.55, and the third quartile (Q1): 755.55 ≤ cumUHR < 981.27, Q1: 981.27 ≤ cumUHR.
(3) High UHR is defined as the highest quartile value of UHR for each physical examination. High UHR duration of exposure is defined as the number of times high UHR is achieved in 3 physical examinations, quantified as 0 years (never had a high UHR), 2 years (with one high UHR), 4 years (with two high UHRs), and 6 years (with high UHR in all 3 physical exams). They were divided into 4 groups according to the duration of high UHR continuous exposure.
Follow-up time and determination of endpoint events
In this study, the time of completion of the 2010 annual health examination was taken as the starting point of follow-up, the first occurrence of MI was used as the follow-up endpoint, and when two or more events occurred, the time and event of the first endpoint event were used as the outcome, and the follow-up deadline was December 31, 2021. If a participant dies midway through the outcome, the time of death is at the end of follow-up. According to the World Health Organization’s Multi-Country Surveillance of Trends and Determinants of Cardiovascular Disease, MI is determined based on clinical symptoms and dynamic changes in cardiac enzyme and/or biomarker concentrations, as well as ECG findings; The annual health data of MI, tumors, deaths, etc. are obtained by the Kailuan Social Security Information System, using the 10th revised International Classification of Diseases, and the myocardial infarction code is I21, which is confirmed by professional physicians based on inpatient medical records.
Statistical methods
Normally distributed continuous data were expressed as mean ± standard deviation (x ̅±s), and analysis of variance was used for comparison between groups. The skewed distribution of continuous data was expressed as median (P25-P75), and non-parametric tests were used for comparison between groups. Count data were expressed as frequency and percentage, and chi-square tests were used for comparison between groups. The Kaplan-Meier method was used to calculate the incidence of MI in the cumUHR quartile group and different groups of cumulative exposure time of UHR elevation during continuous follow-up time, and the log-rank test was used to compare the cumulative incidence of the incidence between the groups.
The COX proportional hazards model was used to analyze the association between different quartile levels of cumUHR and MI. In addition, we further analyzed the association of cumUHR with MI by grouping groups based on high UHR duration of exposure. Model 1: Adjust for gender, age. Model 2: Adjust for smoking, alcohol consumption, education, physical activity, salt status, body mass index, fasting blood glucose, systolic blood pressure, low-density lipoprotein cholesterol, eGFR, hs-CRP on the basis of model 1. Model 3: Further adjustment of antihypertensive drugs, hypoglycemic drugs, and lipid-lowering drugs on the basis of model 2. The Kaplan-Meier method was used to calculate the cumulative incidence of MI in each group, and the log-rank test was used for comparison. Restricted cubic splines (RCS) in 3 sections (5th, 50th, 95th percentile) were used to assess whether there was a nonlinear relationship between cumUHR and MI risk.
According to baseline age (< 60 years vs. ≥ 60 years), gender (female vs. male), BMI (< 24 kg/m 2 vs. ≥ 24 kg/m 2 ), hypertension, hyperlipidemia, diabetes mellitus, antihypertensive drugs, antidiabetic drugs, and lipid-lowering drugs were analyzed. The likelihood ratio test was used to test whether there was a multiplicative interaction between the above variables and cumUHR.
According to baseline age (< 60 years vs. ≥ 60 years), gender (female vs. male), and BMI (< 28 kg/m 2 vs. ≥ 28 kg/m 2 ). A likelihood ratio test was used to test whether there was an interaction between the above variables and cumUHR.
In order to test the stability of the results, the population with an eGFR of <60 ml/(min·1.73 m 2 ) was excluded from sensitivity analysis. Subjects with outcome events with a follow-up of <2 years were excluded and the above COX analysis was repeated.
All data were analyzed using SAS 9.4 (SAS Institute, Cary, North Carolina) statistical software. P < 0.05 (bilateral) was statistically significant.
Results
General information
A total of 53,697 subjects were included in this study, including 41,920 males (78.07 %) and 11,777 females (21.93 %), with an average age of (53.08 ± 11.94) years and an average cumUHR of (826.13 ± 454.34). In the cumUHR quartile, the general condition, anthropometric index, biochemical indexes and medication records of the subjects in each group are shown in Table 1 , and the subjects in the highest cumUHR quartile have higher education level, active physical activity, the highest proportion of non-high salt intake, the most smoking and drinking, the highest UA level, the lowest HDL-C level, and a higher proportion of antihypertensive drugs, hypoglycemic drugs and lipid-lowering drugs compared with the first quartile. There were significant differences in age, sex, BMI, SBP, DBP, FBG, UA, TG, HDL-C, LDL-C, hs-CRP and eGFR (P < 0.01). Similar baseline characteristics were observed in the duration grouping of high UHR exposure, as shown in Table S1.
| Characteristics | Total | Q1 | Q2 | Q3 | Q4 | P for value |
|---|---|---|---|---|---|---|
| N | 53697 | 13424 | 13424 | 13425 | 13424 | |
| Age, years | 53.08 ± 11.94 | 50.60 ± 10.66 | 52.22 ± 11.64 | 54.19 ± 11.97 | 55.32 ± 12.83 | <0.001 |
| Male, n (%) | 41920(78.07) | 8534(63.57) | 10170(75.76) | 11028(82.15) | 12188(90.79) | <0.001 |
| Female, n (%) | 11777(21.93) | 4890(36.43) | 3254(24.24) | 2397(17.85) | 1236(9.21) | <0.001 |
| Education level, n (%) | <0.001 | |||||
| ≤junior high school | 39308(73.20) | 9733(72.50) | 9907(73.80) | 10015(74.60) | 9653(71.91) | |
| >junior high school | 14389(26.80) | 3691(27.50) | 3517(26.20) | 3410(25.40) | 3771(28.09) | |
| Current smoker, n (%) | 18111(33.73) | 3940(29.35) | 4352(32.42) | 4792(35.69) | 5027(37.45) | <0.001 |
| Current alcohol, n (%) | 18618(34.67) | 3869(28.82) | 4346(32.37) | 5009(37.31) | 5394(40.18) | <0.001 |
| Salt level, g/day | 0.485 | |||||
| ≤10 | 48237(89.83) | 11997(89.37) | 12122(90.30) | 12029(89.60) | 12089(90.06) | |
| >10 | 5460(10.17) | 1427(10.63) | 1302(9.70) | 1396(10.40) | 1335(9.94) | |
| Active physical activity, n (%) | 7619(14.19) | 1602(11.93) | 1687(12.57) | 2081(15.50) | 2249(16.75) | <0.001 |
| Anti-hypertensive drugs, n (%) | 11940(22.24) | 1936(14.42) | 2321(17.29) | 3256(24.25) | 4427(32.98) | <0.001 |
| Hypoglycemic drugs, n (%) | 5079(9.46) | 1228(9.15) | 1233(9.19) | 1314(9.79) | 1304(9.71) | 0.1443 |
| Lipid-lowering drugs, n (%) | 1182(2.20) | 166(1.24) | 229(1.71) | 312(2.32) | 475(3.54) | <0.001 |
| Body mass index, kg/m 2 | 25.11 ± 3.32 | 24.07 ± 3.22 | 24.77 ± 3.24 | 25.37 ± 3.26 | 26.22 ± 3.20 | <0.001 |
| Uric acid, µmol/L | 293.05 ± 88.64 | 224.46 ± 55.85 | 265.17 ± 62.72 | 312.56 ± 70.88 | 370.00 ± 86.99 | <0.001 |
| SBP, mmHg | 130.85 ± 19.09 | 127.31 ± 18.29 | 129.90 ± 18.52 | 131.90 ± 19.07 | 134.29 ± 19.77 | <0.001 |
| DBP, mmHg | 84.32 ± 10.72 | 82.51 ± 10.51 | 84.06 ± 10.53 | 84.75 ± 10.66 | 85.99 ± 10.88 | <0.001 |
| FBG, mmol/L | 5.63 ± 1.45 | 5.57 ± 1.51 | 5.59 ± 1.43 | 5.67 ± 1.47 | 5.69 ± 1.37 | <0.001 |
| Triglyceride, mmol/L | 1.29(0.91-1.91) | 1.10(0.79-1.53) | 1.20(0.89-1.68) | 1.32(0.93-1.95) | 1.63(1.12-2.47) | <0.001 |
| LDL-C, mmol/L | 2.59 ± 0.79 | 2.60 ± 0.78 | 2.60 ± 0.75 | 2.60 ± 0.82 | 2.56 ± 0.81 | <0.001 |
| HDL-C, mmol/L | 1.56 ± 0.49 | 1.80 ± 0.54 | 1.60 ± 0.50 | 1.50 ± 0.41 | 1.33 ± 0.37 | <0.001 |
| hs-CRP, mg/L | 1.02(0.50-2.50) | 0.81(0.35-2.00) | 0.90(0.30-2.10) | 1.20(0.60-2.77) | 1.38(0.70-3.00) | <0.001 |
| eGFR, mL/min/1.73 m 2 | 90.47 ± 18.95 | 93.26 ± 18.92 | 89.15 ± 19.55 | 90.74 ± 18.28 | 88.72 ± 18.69 | <0.001 |
| UHR 2006 | 199.14 ± 179.86 | 135.43 ± 42.12 | 169.74 ± 48.47 | 207.74 ± 58.73 | 283.66 ± 331.21 | <0.001 |
| UHR 2010 | 207.39 ± 233.87 | 131.26 ± 41.14 | 174.80 ± 51.37 | 219.95 ± 68.02 | 303.56 ± 439.97 | <0.001 |
| cumUHR index | 826.13 ± 454.34 | 501.50 ± 75.74 | 675.14 ± 43.57 | 859.46 ± 64.37 | 1268.40 ± 699.34 | <0.001 |
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