This study was conducted in compliance with the ethical principles mentioned in the Declaration of Helsinki and was consistent with Good Clinical Practice guidelines and local regulatory requirements. The participants were invited to join this study on the day of health screening. Trained nurses evaluated the mental status of all participants during the screening, and then proceeded with informed consent procedures. Written informed consent was obtained from all participants before entering the study. This study was approved by the Institutional Review Board of Chang Gung Memorial Hospital (Approval No. 201800277B0C601).

From January 2013 to December 2018, this longitudinal, community-based cohort study was conducted in four districts of northeastern Taiwan, namely Wanli, Anle, Ruifang, and Gongliao. The participants were recruited from a community outreach health screening program, which included a physical examination, blood and urine laboratory tests, along with a questionnaire survey. The standardized questionnaire was conducted by a trained team of interviewers, and asked about drinking, smoking, and betel nut chewing habits, exercise, medication history (oral hypoglycemic agents, insulin injections, statins, herbs and hormones), family history, and physical and mental health status (short form health survey, sleep quality survey, depression survey, and health knowledge). All of the participants signed informed consent forms.

Blood and urine samples were collected from each participant, and basic physical measurements including blood pressure (mmHg), body weight (kg) and body height (cm) were performed. The laboratory data included biochemistry markers, inflammatory markers, and metabolic syndrome-associated markers. Albuminuria and proteinuria were assessed using the urine samples according to urine albumin creatinine ratio (UACR) and urine protein creatinine ratio (UPCR). Participants with systemic disorders, such as hypertension, hyperlipidemia, and CKD, were recorded. The exclusion criteria were: participants aged ≤ 30 years, participants who were lost to follow-up, participants or their next of kin who declined to be enrolled in the study, and those who had undergone organ transplantation or renal replacement therapy before entering this study. Follow-up examinations were conducted annually, during which the physical measurements, blood and urine laboratory test data, and answers to the survey, were recorded again.

During the recruitment period, 6,734 individuals completed the baseline survey and were invited to attend yearly follow-up visits. Of those invited, 752 attended and 5,982 declined. At the end of the study, 731 patients had successfully completed 5 years of annual follow-up, 14 had died, and 7 had been lost to follow-up.

According to the National Kidney Foundation K/DOQI classification for CKD, CKD was defined as persistent proteinuria or a decreased eGFR of <60 mL/min/1.73 m², determined using the abbreviated Modification of Diet in Renal Disease equation (19).

According to the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) Guidelines, metabolic syndrome is defined as the presence of three out of five of the following criteria:

The HOMA-IR was used to quantify insulin resistance and was calculated as: fasting insulin (μIU/ mL) × fasting glucose (mg/dL)/405. An increased HOMA-IR score denotes decreased insulin sensitivity (20, 21).

BMI was calculated as the body weight divided by the square of the height (kg/m²).

The participants were divided into four groups according to the metabolic body composition status (Supplementary Table 1):

Different from the WHO recommendations, we used the cut-off standard recommended by the Ministry of Health and Welfare in Taiwan, and defined BMI ≥ 24 kg/m² as overweight (22, 23).

Serum level of 25(OH)D was measured using an electro-chemiluminescence immunoassay (Cobas^® Vitamin D3 assay, Roche Diagnostics GmbH, Mannheim, Germany) with an interassay coefficient of variation of 2.2–13.6% (19).

Assays for Biomarkers An enzyme-linked immunosorbent assay (ELISA) was used to quantify the concentration of serum biomarkers. The serum concentrations of leptin and adiponectin were assayed using commercial ELISA kits from Boster (Pleasanton, CA, United States) (24).

The HS-CRP level was assayed using a commercial ELISA kit from Roche (Basel, Switzerland), according to the manufacturers' instructions (24).

A quantitative sandwich enzyme immunoassay technique was used for the TNF-α assay according to the manufacturer's instructions (Immunite 1000 LKNF1, Siemens Medical Solutions Diagnostics, Llanberis, UK) (25).

Beginning from the index date, all eligible participants were followed up for 5 years. The primary outcome of this study was RKFD. In the literature, RKFD was defined as a decline ≥ 30% within 10 years or an absolute annual loss ≥ 3 mL/min/1.73 m² (26). In this 5-year longitudinal follow-up study, RKFD was defined as a 15% decline in estimated glomerular filtration rate (eGFR) within the first 4 years, and a reduction in eGFR which did not improve in the 5th year.

Continuous variables were summarized using means and standard deviations (SDs). All variables were tested for normal distribution using the Kolmogorov-Smirnov test. The Student's t-test was used to compare the means of continuous variables and normally distributed data; otherwise, the Mann-Whitney U-test was used. The study participants were divided into four groups by their MBCS. ANOVA was also employed to compare the means of continuous variables and normally distributed data; otherwise, the Kruskal-Wallis test was used. Categorical data were tested using the chi-square test. Risk factors were assessed with univariable Cox regression analysis. In addition, variables with statistical significance (p < 0.05) in the univariable analysis were included in multivariable analysis by applying multiple logistic regression based on forward elimination of data. Cumulative survival curves as a function of time were produced using the Kaplan-Meier method, and compared using the log rank test. All statistical tests were two-tailed, and a value of p < 0.05 was considered to be statistically significant. Data were analyzed using SPSS version 22.0 for Windows 10 (SPSS, Inc., Chicago, IL, USA).

A total of 731 participants were included in this study (mean age 57.2 years; 29.1% male). The baseline characteristics of the participants with and without RKFD are shown in Table 1. The incidence of RKFD was 17.1% (125/731), the prevalence of CKD was 2.1%, and diabetes mellitus was present in 9.1% of the study population. There were no significant differences in age and the prevalence of CKD between those with and without RKFD. The RKFD group had a higher percentage of females and higher prevalence rates of diabetes mellitus and cerebrovascular accident (CVA). With regards to the use of medications, the RKFD group was more likely to regularly use oral hypoglycemic agents (OHAs) and painkillers. The RKFD group also had significantly higher levels of eGFR and UACR. With regards to the factors associated with metabolic syndrome, there were no significant differences in BMI, blood pressure, fasting glucose, triglycerides, HDL cholesterol, leptin, adiponectin, tumor necrosis factor alpha (TNF-α) and vitamin D between the participants with and without RKFD. The RKFD group had significantly higher glycated hemoglobin (HbA1C), insulin, and HOMA-IR, and higher percentages of MUNW and MUOW; while the non-RKFD group had significantly higher total cholesterol and low-density lipoprotein (LDL) cholesterol, and higher percentage of MHNW. We also compared the social psychology variables of the study population (Supplementary Table 2). The RKFD group tended to have a lower level of education and less alcohol consumption, and higher percentages of vegetarians and depressive mood.

The baseline characteristics and social psychology variables of the study population according to their MBCS are presented in Tables 2, 3, respectively. The MHOW group had the highest percentage of males. The participants in the MUNW group were the oldest, but the MUOW group had the highest prevalence rates of diabetes mellitus, hypertension, cardiovascular disease and gout. There was no significant difference in the prevalence of CKD between the different MBCS groups. The MUOW group had worse metabolic profile, including the highest blood pressure, BMI, waist circumstance, triglycerides, uric acid, glutamic pyruvic transaminase (GPT), UACR, fasting glucose, HbA1C, insulin, leptin and HOMA-IR, and the lowest HDL cholesterol and adiponectin. In addition, the MUOW also had the highest inflammatory markers, including TNF-α and HS-CRP, as well as the highest use of OHAs and anti-hypertensives (Table 2). The MUNW group had the highest blood urea nitrogen level. With respect to social psychology, the MUNW and MUOW groups had significantly lower levels of education, while the MUNW group had a higher prevalence of smoking than the other groups (Table 3).

The RKFD rate and UACR according to MBCS are depicted in Figures 1A,B, respectively. The MUOW group had the highest UACR, while the MUNW group had the highest RKFD rate.

The univariable Cox proportional hazards analysis identified that 16 (Table 4) of the 44 variables (Tables 1, 3) were good prognostic indicators. In the Cox regression multivariable analysis, age, CVA, eGFR, UACR, use of painkillers, depressive mood, MUNW and MUOW were significant independent prognosticators for RKFD. CVA had the highest hazard ratio (HR) for RKFD [HR: 3.48, 95% confidence interval (CI): 1.08–11.17], following by MUNW (HR: 2.24, 95% CI: 1.26–3.99), depression (HR: 1.95, 95% CI: 1.23–3.09), use of painkillers (HR: 1.72, 95% CI: 1.04–2.85), and MUOW (HR: 1.61, 95% CI: 1.06–2.45). UACR, eGFR and age were also reliable prognostic indicators.

Table 5 presents the associations of MBCS with RKFD in unadjusted and adjusted models. The effects of adjusting for age, sex, eGFR and total cholesterol were investigated. Compared with the MHNW group, the adjusted HRs of the MUNW and MUOW groups for RKFD were 2.19 (95% CI: 1.22–3.95, p = 0.009) and 1.86 (95% CI: 1.21–2.87, p = 0.005), respectively. In subgroup analysis according to age, similar results were observed in the adjusted model in those ≥ 65 years of age (MHNW: reference; HR: 3.15, 95% CI: 1.26–7.88 for MUNW; HR: 2.45, 95% CI: 1.05–5.74 for MUOW), while this trend was not statistically significant in those <65 years. When the population was stratified by sex, the adjusted HR of the MUOW group for RKFD was 3.03 (95% CI: 1.05–8.75, p = 0.041) in the males. The adjusted HRs of the MUNW and MUOW groups for RKFD were 1.96 (95% CI: 1.02–3.75, p = 0.043) and 1.64 (95% CI: 1.01–2.66, p = 0.044) in the females, respectively. Moreover, the HR in the MHOW group was statistically non-significant in both overall analysis and subgroup analysis of sex and gender. Additional analysis adjusting for education level, alcohol consumption, dietary habits, and depressive mood resulted in similar findings on the effect of MBCS on RKFD (Supplementary Table 3). Figure 2 illustrate the cumulative incidence of RKFD in the study population according to MBCS. As shown in Figure 1, the individuals with MUNW and MUOW had significantly higher incidence rates of RKFD than the individuals with MHNW in the overall cohort. This trend was also statistically significant in individuals ≥ 65 years old, and in females during the study period.