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    Analysis of hyperuricemia in physical examination population of a hospital in Haikou

    2022-09-19 03:49:36XiaoBoTangYingZiLinLiuTingLiuChanJuanZhaoChengXianHuangLanHuangWuJianXieJunCaiChenYouXuanYan
    Journal of Hainan Medical College 2022年14期

    Xiao-Bo Tang, Ying-Zi Lin, Liu-Ting Liu, Chan-Juan Zhao, Cheng-Xian Huang, Lan Huang, Wu-Jian Xie, Jun-Cai Chen, You-Xuan Yan

    1. The First Affiliated Hospital of Hainan Medical College, Haikou 570102, China

    2. School of Public Hejalth, Hainan Medical University, Haikou 571199, China

    Keywords:Haikou Baseline survey Hyperuricemia Influencing factors

    ABSTRACT Objective: Explore the influencing factors of Hyperuricemia (HUA) in natural people aged 35-74 in Haikou. Methods: Between June 2017 and December 2020, 8754 different study subjects aged 35-74 years were enrolled for the baseline survey at the physical examination center of a tri partite hospital in Haikou. Results: Overall detection rate of HUA was 18.5%,including 25.6% in male and 10.4% in female. HUA detection rates varied between the 35-45 and 46-55 age groups (P<0.05).The binary logistic results showed that high blood pressure,triglyceride, low density lipoprotein and creatinine were the risk factors of HUA (P<0.05).Conclusions: The baseline survey results show that the detection rate of HUA in a hospital in Haikou is relatively high. Men and groups with high blood pressure, creatinine, triglyceride and low-density lipoprotein should be the key groups for the early prevention and treatment of hyperuricemia(HUA).?Corresponding author: LIN Ying-zi

    1. Introduction

    Uric acid (UA) is a kind of heterocyclic compound containing carbon, nitrogen, oxygen and hydrogen. It is the end product of purine metabolism. Uric acid is formed through the decomposition of nucleic acids, purines and their compounds in food intake by various biological enzymes in the body. Uric acid is very insoluble in water, alcohol and ether, and most of it exists in the form of urate in serum. Uric acid in the body is in a state of dynamic balance.When uric acid increases (and) or excretion decreases, it will lead to the increase of serum uric acid (SUA). This dynamic balance is disturbed, so that uric acid accumulates in the body, resulting in hyperuricemia (HUA)[1]. Clinical studies confirm that HUA is an independent risk factor for cardiovascular disease, and elevated serum uric acid is closely related to lipid abnormalities, diabetes and cardiovascular diseases[2-3]. In recent years, with the development of social economy and the change of people's diet and lifestyle, the incidence rate of abnormal HUA and blood lipid level is increasing year by year. HUA has become an important disease threatening human health. HUA and dyslipidemia are occult and have no obvious symptoms. Therefore, some people can't find it as soon as possible or disagree after finding it, fail to take any prevention and treatment measures, and miss the early diagnosis and treatment,which lays a hidden danger for the occurrence of cardiovascular and cerebrovascular diseases. The middle-aged and elderly people are often the high incidence population of chronic diseases such as HUA and abnormal blood lipid level. This study aims to explore the influencing factors of HUA and provide an effective basis for reducing the occurrence and development of local HUA.

    2. Materials and Methods

    2.1 Research objects

    From June 2017 to December 2020, 8754 subjects aged 35-74 were included in the physical examination center of a third class hospital in Haikou for baseline survey. Inclusion criteria: ① Native place is Hainan and has lived in Hainan Province for more than 5 years; ② Age range: 35-74 years; ③ No serious physical disability or mental illness, able to communicate normally and voluntarily sign the informed consent form; ④ No stroke, coronary heart disease,malignant tumor, chronic obstructive pulmonary disease (COPD),diabetes or hypertension were found before admission. Exclusion criteria: persons with a history of mental illness and long-term use of psychotropic drugs, persons with disabilities, people with acute and critical diseases, pregnant women and local migratory birds.

    2.2 Research methods

    The surveyors were trained according to unified standards and used unified measurement tools. The height and weight of the subjects were measured by China Shuangjia height and weight meter (NO:SK-X80) and the static blood pressure was measured by Japan OMRON electronic sphygmomanometer (NO: HEM-7071). The subjects were collected 5 ml of sitting sterile elbow venous blood at rest. They were required to be fasting for 12 hours before blood collection, and the biochemical indexes such as leukocyte count,total cholesterol and triglyceride were detected.

    2.3 Diagnostic criteria

    1. Normal value range of blood biochemical test sheet: alanine aminotransferase (7-40) U / L, aspartate aminotransferase (15-35) U/L, direct bilirubin (0-6.8) umol/L, indirect bilirubin (1.7-17) umol/L, urea nitrogen (2.6-7.5) mmol/L, creatinine (41-73) umol/L. 2.HUA diagnostic criteria: UA ≥ 420 μmol/L for male, female UA ≥350 μmol/L[4]. 3.Diabetes diagnosis: FPG > 7.0mmol/L [5]. 4. Blood pressure grading standard: SBP < 120mmHg and DBP < 80mmHg;High blood pressure: SBP ≥ 140mmHg or DBP ≥ 90mmHg[6]. 5.Body mass index (BMI) grading standard: Lean BMI < 18.5kg/m2,normal weight 18.5 ≤ BMI < 24kg/m2, overweight or obese BMI≥ 24kg/m2[7]. 6. Diagnostic criteria of dyslipidemia: cholesterol(TC) ≥ 5.18mmol/L, triglyceride (TG) ≥ 1.70mmol/L; High density lipoprotein cholesterol (HDL-C) < 1.04 mmol/L; And (or)low density lipoprotein cholesterol (LDL-C) ≥ 3.37mmol/L is high LDL-C; If one or more indicators meet the above diagnostic criteria,it is diagnosed as (total) dyslipidemia [8].

    2.4 Statistical analysis

    Data analysis by SPSS20. The counting data are expressed in(%), and the single factor analysis adopts test. The variables with statistical significance were analyzed by binary logistic regression,and the influencing factors were analyzed with α= 0.050 as the test level.

    3. Results

    3.1Basic information of research objects

    The median age and lower and upper quartiles of 8754 subjects were 46 (40~51), 4649 males (53.1%) and 4105 females (46.9%);The subjects were divided into four age groups: 4203 (48.0%) aged 35-45, 3548 (40.5%) aged 46-55, 936 (10.7%) aged 56-65 and 67(0.8%) aged 66-74.

    3.2 Detection of Hua in the research objects

    Among the 8754 subjects, the detection rate of HUA was 18.5%(1620 / 8754), of which the detection rate of men was 25.6% (1192/ 4649) and that of women was 10.4% (428/4105). There was significant difference in the detection rate of HUA between men and women in 35-45 years old group and 46-55 years old group (χ2= 334.577, P<0.001), and the detection rate of men was higher than that of women,. The prevalence of HUA is mainly concentrated in middle-aged and middle-aged people, and the detection rate of men is higher than that of women. Table 1shows the details of HUA detection among subjects of different sexes.

    Table 1 Comparison of HUA detection among subjects of different sexes n/N (%)

    3.3 Univariate analysis

    HUA detection rates between BMI, blood pressure, alanine and aspartate aminotransferase, urea nitrogen, creatinine, total cholesterol, triglycerides, high-density lipoprotein and low-density lipoprotein levels (P <0.05).

    3.4 Binary logistic analysis

    Taking the detection of HUA as the dependent variable (Y), age(X1), gender (X2), BMI (X3), blood pressure (X4), triglyceride(X5), total cholesterol (X6), high-density lipoprotein (X7), lowdensity lipoprotein (X8) and creatinine (X9) were included in the binary logistic regression model and selected into the variable standard α=0.05, meaningless variables are excluded from the model. The input method binary logistic regression analysis was used to construct the model, the -2-fold log likelihood ratio was 5329.395, and the Hosmer fit test(P=0.062>0.05). The prediction accuracy of the model is 81.6% > 60%, which further shows that the data fitting is good and can accurately reflect the influence of independent variables on dependent variables.

    The results showed that gender, blood pressure, triglyceride, low density lipoprotein and creatinine were the influencing factors of hyperuricemia. The risk of detecting HUA in men was 1.30 times higher than that in women (OR = 1.303,95% CI: 1.076-1.578;P=0.007<0.05), the risk of detecting HUA in high blood pressure was 1.80 times higher than that in normal (OR=1.802,95% CI:1.566-2.075; P<0.001), and the risk of detecting HUA in high triglyceride was 2.38 times higher than that in normal (OR =2.384,95% CI:2.064-2.754;P<0.001) The risk of detecting HUA with high LDL was 1.28 times higher than that of normal (OR= 1.281,95% CI:1.083-1.515; P=0.004 <0.05), and the risk of detecting Hua with high creatinine was 1.98 times higher than that of normal (OR=1.982,95% CI: 1.663-2.362; P < 0.001), as shown in Table 3.

    4. Discussion

    4.1 The detection rate of hyperuricemia in a hospital in Haikou is relatively high

    In recent years, a study shows that the overall prevalence of Hua in Chinese population is 13.0%, of which 18.5% are men and 8.0%are women [9], and the prevalence of Hua in all parts of the country is on the rise [10]. According to Jin Hong [11] and others, among5123 middle-aged and elderly residents in a health service center in Chengdu in 2012, 15.94% were detected in men and 8.97% in women. The total physical examination rate of HUA of 8754 subjects in this study was 18.5% (1620/8754), 25.6% (1192/4649) for men and 10.4% (428/4105) for women, which were higher than this conclusion. It is suggested that the prevalence of HUA varies greatly in different regions, and the dietary pattern in different regions may be one of the factors affecting the level of blood uric acid [12].

    Table 2 Comparison of HUA detection rates among study subjects with different indicators.

    Table 3 Binary logistic regression analysis of HUA detected in different characteristic populations.

    4.2 The detection rate of hyperuricemia in middle-aged and elderly men is higher than that in women. Middle-aged men and middle-aged and elderly women are high-risk groups

    The results of this study showed that the prevalence of HUA in men at different ages was higher than that in women, and women were less likely to suffer from HUA than men (OR =1.303,95%CI:1.076-1.578; P=0.007<0.05). Except for the 56-65-year-old group and 66-74-year-old group, the detection rate of men in other groups was significantly higher than that of women (P < 0.05), which was the same as the previous research results [13]. The high detection rate of male HUA is mainly concentrated in young adults; The high detection rate of women is mainly concentrated in the middleaged and elderly population, which is consistent with the research results of Tuoya et al. [14]. The reasons may be: ① men have more social activities (such as social intercourse and making friends)than women, and have more bad living habits (such as staying up late, loving soft drinks, excessive intake of sugar [15], less exercise,etc.), which aggravates the burden of renal function. ② Men are more likely to smoke and drink alcohol than women, and nicotine and alcohol are risk factors for HUA in healthy people [16-17]. ③Androgen can promote the reabsorption of uric acid, inhibit the excretion of uric acid, and affect the metabolism of purine in the liver. On the contrary, estrogen has a significant excretion of uric acid[16]. Therefore, postmenopausal women[18] and young and middleaged men should be the key prevention and treatment objects. The staff of the local centers for Disease Control and prevention should strengthen the monitoring of blood uric acid and blood lipids of key prevention and control objects, so as to effectively prevent and control the exposure of cardiovascular disease risk factors.

    4.3 HUA is closely related to multiple influencing factors,and it is combined with cardiovascular disease prevention and control

    The results of this study showed that high blood pressure,triglyceride, low density lipoprotein and creatinine were the risk factors of HUA in local middle-aged and elderly residents (P<0.05).A large number of studies have proved that hypertension is an independent risk factor for HUA, and there is a causal and mutually reinforcing relationship between them [19]. Abnormal creatinine index is more likely to detect HUA (OR =1.982,95% CI: 1.663-2.362; P< 0.001), which is consistent with the existing research conclusions [20]. In addition, when the level of triglyceride in serum exceeds the threshold, some free fatty acids generated by its decomposition will undergo esterification reaction or enter the body,which requires more ATP decomposition and energy supply, so as to increase the generation of uric acid [21]. This study also confirmed that abnormal triglyceride is a risk factor for hyperuricemia (OR=2.384,95% CI: 2.064-2.754; P<0.001). Liver and kidney are the main organs of uric acid excretion, and the level of blood uric acid is closely related to the excretion of uric acid in kidney [22]. After the increase of blood lipid, the ketone body in the body also increases,resulting in the decrease of renal acid excretion function and the increase of blood uric acid [23]. In addition, HUA may play a key role in the development and process of chronic kidney disease [24].

    4.4 Research advantages and disadvantages

    In this study, multi-stage cluster random sampling method was used to investigate the epidemiology of HUA in local residents aged 35-74. Before the survey, first master the demographic data and characteristics of each survey unit, and then carry out the survey.Before that, a large number of relevant population studies were not carried out locally, thus filling the gap in this field.

    The limitations of COVID-19 study for:(1) Due to the new outbreak of pneumonia, the delayed site investigation resulted in the lack of physical examination and questionnaire survey of the HUA population in the survey. (2) This study only uses cross-sectional survey data, which has some limitations in reflecting causality.Follow up data will be further completed in the future.

    Author's contribution

    Tang Xiao-bo: Thesis Writing and revision; Lin Liu-ting:conception and modification of the paper; Zhao Chan-juan: data analysis guidance and put forward modification opinions; Huang Cheng-xian, Huang Lan and Xie Wu: data extraction and sorting;Chen Jun-cai, Yan You-xuan: data collection; Lin ying-zi: guide the writing of the thesis and put forward suggestions for revision.

    Author statement

    There is no actual or potential conflict of interest in this article.

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