Study Design and Procedure
This was a community-based cohort study, which was conducted among older adults aged 60 years or older lived in Weitang town of Suzhou located in the east part of China. Details of the baseline study have been described elsewhere [15-17]. In the baseline examinations, 6,030 families who had older adult aged 60 years or older based on local official records received an invitation letter, which explain the nature of the study and invite the older adults to participate. Exclusion criteria applied to those whom had been living there shorter than six months, had migrated from the residing address, or deceased. Of the 5,613 eligible older adults, 4,611 attended the baseline clinical examinations from August 2014 to February 2015. The final sample at baseline consisted of 4,579 older adults who had complete data of anthropometric examinations, questionnaires and blood sample analyses. Five years later, these participants were invited to attend the anthropometric examination and collected of blood sample. Home visits or revisits were conducted to encourage older adults who did not participant in the follow-up examinations to attend with the aim of improving the follow-up rate of study. Older adults at baseline were excluded when he or she declined to participant, moved away and could not be contacted or deceased before the follow-up examination. Older adults with HUA at baseline or without data about SUA at follow-up examination were excluded. Official death registration forms were used to identify the death of individuals at baseline.
Both baseline and follow-up studies were conducted abide by the tenets of the Helsinki Declaration and were approved by the Institutional Review Board of Soochow University.
Clinical and biochemical measurements
Blood samples of participants were collected and frozen at -80℃ before transferring to laboratory technicians for achieving related data including SUA, fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C) and blood triglycerides.
Blood pressure (BP) was measured using automatic blood pressure monitor (Dinamap model Pro Series DP110X-RW, 100V2; GE Medical Systems Information Technologies, Inc., Milwaukee, Wisconsin, United States) when older adults had a rest of 5 minutes or longer. The recorded BP was average value of the last two readings. Body height and weight of older adults without shoes and with light clothing were measured using a wall-mounted measurement tape and digital scale, separately. Body mass index (BMI, kg/m2) was calculated as the weight in kilograms divided by the square of the height in meters.
These clinical and biochemical indicators were examined with similar procedures for both baseline and follow-up studies participants.
Definitions of HUA and MetS
HUA was defined as 7 mg/dl or above for men and 6 mg/dl or greater for women [18].
MetS of participants were assessed based on the National Cholesterol Education Program-Adult Treatment Panel Ⅲ [19]. MetS was diagnosed when participants met three or more of following components: (1) BMI of 25 kg/m2 or above; (2) high BP (BP of 130/85 mmHg or greater or on antihypertensive drug treatment); (3) elevated blood triglycerides (1.7 mmol/L or higher); (4) diabetes mellitus defines as FPG of 7.0 mmol/L or above or with diabetes; (5) low HDL-C (lower than 1.0 mmol/L in men and 1.3 mmol/L in women).
Assessment of main covariates
Information on participants’ socio-demographic characteristics including age, gender, marriage status (living with spouse/living without spouse), educational level (primary and below education/ secondary education or above) and monthly income (≤1000/1001-3000/>3000 Chinese Yuan) as well as lifestyle habits was collected using a pre-designed questionnaire. Data regarding lifestyle habits such as smoking, alcohol intake, tea consumption and physical activity were also collected during the questionnaire interview.
Statistics analysis
Chi-square test and student’s t-test were separately used to compare categories and continuous variables of participants according to HUA status at follow-up, and percentage as well as mean ± standard deviation were calculated to express the comparison, as appropriate. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using two logistic regression models to estimate the effects of baseline MetS and its components on 5-year incident HUA. The first model adjusted for age and gender only, and the second one additionally adjusted for marriage status, educational level, monthly income, lifestyle habits including alcohol intake, smoking status, tea consumption, physical activity and baseline SUA. In addition, in logistic regressions of assessing linear trends, quartiles of MetS components at baseline were treated as continuous variables by assigning each quartile with a median. Logistic regression model was also used to investigate the influences of different combinations of baseline MetS components on incident HUA and those without any MetS components were treated as “reference group”. A stratified-analysis was performed to evaluate the associations of baseline MetS components with incident HUA in different statuses of diabetes mellitus component.
Data were analyzed using SPSS version 21.0 (SPSS Inc., Chicago, IL, USA) and statistical significance was considered if a p-value was less than 0.05.