Subjects
The subjects were Japanese men aged 29–70 years (n = 12,528) who had received periodic health checkup examinations at workplaces in Yamagata Prefecture in Japan. The original database used in this study was a collection of the results of annual health checkup examinations performed from April 2005 to March 2006 for workers in a district of Japan. The database used in this study was supplied by a health checkup institute, by which the questionnaires were prepared. Informed consent was not obtained from each subject, and the protocol of this study including no informed consent from each subject was approved by the Ethics Committee of Yamagata University School of Medicine (No. 112 from April 2005 to March 2006, approved on March 13, 2006) and the Hyogo College of Medicine Ethics Committee (No. 3003 in 2018).
Histories of alcohol consumption, cigarette smoking, regular exercise (almost every day for 30 min or longer per day), illness, and therapy for illness were self-reported by questionnaires. The questionnaires used in this study were prepared by the health checkup institute and include standard questions on individual lifestyles and histories of disease and medication therapy. Names of drugs used for treatment of each disease and information on Japanese traditional medicines used for therapy for diabetes and hyperuricemia were not included in the questionnaire used in this study. Since most people do not have a good understanding of the names of drugs they are taking, history of medication therapy was simply asked in the questionnaire for each of the diseases including hypertension, dyslipidemia, hyperuricemia and diabetes as “Are you receiving medication therapy to lower blood pressure level?”, “Are you receiving medication therapy to lower blood cholesterol level?”, “Are you receiving medication therapy to lower blood urate level?”, and “Are you receiving insulin injection or medication therapy to lower blood sugar level?”, respectively.
Individuals for whom information on any of the variables tested in this study was lacking were excluded from the subjects of this study. Individuals receiving medication therapy for hyperuricemia were also excluded from the subjects of this study. A cross-sectional study was performed using a local population-based database for the above subjects.
Average alcohol consumption of each subject per week was reported on questionnaires. Frequency of habitual alcohol drinking was asked in the questionnaire as “How frequently do you drink alcohol?”. Frequency of weekly alcohol drinking was categorized as “every day” (regular drinkers), “sometimes” (occasional drinkers) and “never” (nondrinkers). Cigarette smokers were defined as subjects who had smoked for 6 months or longer and had smoked for the past month or longer. Then the subjects who were smokers were further asked “What is your average cigarette consumption per day?”. The response categories for this question were “less than 21 cigarettes per day”, “21 or more and less than 41 cigarettes per day” and “41 or more cigarettes per day”.
Measurements
Height and body weight were measured with the subjects wearing light clothes at the health checkup. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was measured at the navel level according to the recommendation of the definition of the Japanese Committee for the Diagnostic Criteria of Metabolic Syndrome [14], and visceral obesity was evaluated by the ratio of waist circumference (cm) to height (cm) (waist-to-height ratio: WHtR). Blood pressure was measured by trained nurses, who were part of the local health-checkup company, with a mercury sphygmomanometer once on the day of the health checkup after each subject had rested quietly in a sitting position. Korotkoff phase V was used to define diastolic pressure. Fasted blood was sampled from each subject in the morning, and serum urate, triglycerides and HDL cholesterol were measured by enzymatic methods using commercial kits, pureauto S UA, pureauto S TG-N and cholestest N-HDL (Sekisui Medical Co., Ltd, Tokyo, Japan), respectively. Hemoglobin A1c was measured by NGSP (the National Glycohemoglobin Standardization Program)-approved technique using the latex cohesion method with a commercial kit (Determiner HbA1c, Kyowa Medex, Tokyo, Japan). Since the standards of hemoglobin A1c used for measurement are different in the NGSP method and JDS (the Japan Diabetes Society) method, hemoglobin A1c values were calibrated by using a formula proposed by JDS [15]: hemoglobin A1c (NGSP) (%) = 1.02 × hemoglobin A1c (JDS) (%) + 0.25%. Coefficients of variation for reproducibility of each measurement were ≤ 3% for urate, ≤ 3% for triglycerides, ≤ 5% for HDL cholesterol and ≤ 5% for hemoglobin A1c.
Criteria of metabolic syndrome
Metabolic syndrome was defined, according to the criteria by IDF (the International Diabetes Federation) [16] with a slight modification, as the presence of 2 or more risk factors in addition to visceral obesity diagnosed as large waist circumstance. Risk factors included in the criteria are visceral obesity, high blood pressure, dyslipidemina (low HDL cholesterol and/or high triglycerides) and hyperglycemia evaluated by hemoglobin A1c. The criterion for each risk factor was defined as follows: visceral obesity, WHtR ≥ 0.5; hypertension, systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg; low HDL cholesterol, HDL cholesterol < 40 mg/dl; high triglycerides, triglycerides ≥ 150 mg/dl; diabetes, hemoglobin A1c ≥ 6.5%. Subjects receiving drug therapy for hypertension, dyslipidemia and diabetes were also included in the above definitions of hypertension, dyslipidemia and diabetes, respectively.
Statistical analysis
The values of urate in participants were arranged in ascending order, and then the participants were divided into four quartile groups, and each variable was compared among the quartile groups for urate by univariate and multivariate analyses as explained below. Serum urate concentrations were measured as a unit of mg/dl with one decimal place, and there was a considerable number of subjects who showed the same value of urate concentration at each quartile border. Thus, it was impossible to divide the subjects into 4 quartile groups consisting of completely equal numbers of subjects. The subjects were therefore divided into 4 quartile groups with the similar numbers of subjects: 3150 subjects in the 1st quartile, 3214 subjects in the 2nd quartile, 2986 subjects in the 3rd quartile and 3178 subjects in the 4th quartile. Categorical variables were compared by means of Pearson’s Chi square test for independence. In univariate analysis, means of each variable were compared among the quartile groups by using analysis of variance (ANOVA) followed by Scheffé’s F-test as a post hoc test. In multivariate analysis, mean levels of each variable were compared by using analysis of covariance (ANCOVA) followed by Student’s t-test after Bonferroni correction. Triglyceride levels are known not to show a normal distribution. In fact, in the present study, triglyceride levels did not show a normal distribution (data not shown). They are therefore presented as a median with 25 and 75 percentile values and were compared among the groups non-parametrically by using Kruskal–Wallis test followed by Steel–Dwass test as a post hoc test in univariate analysis or were used after log-transformation in multivariate analysis. In logistic regression analysis, crude and adjusted odds ratios for metabolic syndrome and each of its components were estimated. Pearson’s correlation coefficients and standardized partial regression coefficients were calculated in univariate and multivariate linear regression analyses, respectively. Age, smoking, alcohol drinking and regular exercise were used as other explanatory variables or covariates in multivariate analyses. BMI was also added to the explanatory variables in analyses of variables other than WHtR and metabolic syndrome. In addition, histories of drug therapy for hypertension, dyslipidemia, and diabetes were adjusted for calculation of means of systolic or diastolic blood pressure, HDL cholesterol or log-transformed triglycerides, and hemoglobin A1c, respectively, in ANCOVA. Covariates were continuously or sequentially adjusted in multivariate analyses. Age and lifestyle-related factors including smoking, alcohol drinking and regular exercise are known to be possible confounders for the above relationships and thus were used as potential covariates in multivariate analyses. In addition, histories of medication therapy for diabetes, hypertension and dyslipidemia were used as covariates in analysis of hemoglobin A1c, blood pressure, and blood lipids, respectively, since each therapy directly influences the levels of these variables. Probability (p) values less than 0.05 were defined as significant. Statistical analyses were performed using a computer software program (SPSS version 16.0 J for Windows, Chicago IL, USA).
