We aimed to examine the association between metabolic syndrome and the risk of kidney stone development in a large-scale community-based cohort. A total of 121,579 participants enrolled in the Taiwan Biobank were analyzed. They were divided into two groups on the basis of presence of metabolic syndrome. The presence of kidney stone disease was defined by self-reported history of kidney stones. The mean age of participants was 50 years old, and self-reported kidney stones were observed in 3446 (10%) and 4292 (5%) participants with metabolic syndrome and without metabolic syndrome, respectively. Higher prevalence of kidney stone disease was found in participants with metabolic syndrome compared to those without metabolic syndrome (odds ratio (OR), 1.32; 95% confidence interval (95% CI), 1.25 to 1.39). In addition, the risk of incident kidney stone development was analyzed in a longitudinal cohort of 25,263 participants without kidney stones at baseline during a mean follow-up of 47 months. Multivariable Cox regression analysis revealed that the risk for incident kidney stone disease was higher in participants with metabolic syndrome than those without metabolic syndrome (hazard ratio, 1.24; 95% CI, 1.04 to 1.49). Our study suggests that metabolic syndrome does increase the risk of kidney stones.

The prevalence and incidence rates of kidney stone disease (KSD) in Taiwan are high; however, the association between lipid profile and KSD has yet to be investigated. The aim of this longitudinal study was to investigate the association between lipid profile with baseline and incident KSD in a large Taiwanese cohort. A total of 27,002 people enrolled in the Taiwan Biobank (TWB) were followed for a median of 4 years and classified into two groups according to whether they had (n = 1813; 6.7%) or did not have (n = 25,189; 93.3%) KSD at baseline. The presence of KSD was defined according to a self-reported history of kidney stones. The participants with baseline KSD (n = 1813) were excluded from the follow-up study, and the remaining participants were classified into two groups consisting of those who had (n = 640; 2.5%) or did not have (n = 24,549; 97.5%) incident KSD. After multivariable analysis, compared to quartile 1 of lipid profile, the participants in quartile 4 of triglycerides, quartiles 3 and 4 of high-density lipoprotein cholesterol (HDL-C), and quartile 4 of total cholesterol (Chol)/HDL-C ratio were significantly associated with baseline KSD. In the follow-up study, the participants in quartiles 2, 3, and 4 of triglycerides; quartile 2 of Chol; quartile 4 of HDL-C; quartile 3 of LDL-C; and quartiles 3 and 4 of Chol/HDL-C ratio were significantly associated with incident KSD. Our results showed that hypertriglyceridemia (67–93 mg/dL) was associated with a 1.463-fold increased risk of incident KSD and that low HDL-C (>63 mg/dL) protected against incident KSD formation. In addition, a Chol/HDL-C ratio larger than 3.64 was associated with a 1.381-fold increased risk of incident KSD. Our findings may imply that the optimal management of dyslipidemia may be associated with a lower risk of developing kidney stones.

This study investigates the correlation between body mass index (BMI) and osteoporosis utilizing data from the Taiwan Biobank. Initially, a comprehensive analysis of 119,009 participants enrolled from 2008 to 2019 was conducted to assess the association between BMI and osteoporosis prevalence. Subsequently, a longitudinal cohort of 24,507 participants, initially free from osteoporosis, underwent regular follow-ups every 2–4 years to analyze the risk of osteoporosis development, which was a subset of the main cohort. Participants were categorized into four BMI groups: underweight (BMI < 18.5 kg/m²), normal weight (18.5 kg/m² ≤ BMI < 24 kg/m²), overweight (24 kg/m² ≤ BMI < 27 kg/m²), and obese groups (BMI ≥ 27 kg/m²). A T-score ≤ − 2.5 standard deviations below that of a young adult was defined as osteoporosis. Overall, 556 (14.1%), 5332 (9.1%), 2600 (8.1%) and 1620 (6.7%) of the participants in the underweight, normal weight, overweight and obese groups, respectively, had osteoporosis. A higher prevalence of osteoporosis was noted in the underweight group compared with the normal weight group (odds ratio [OR], 2.20; 95% confidence interval [95% CI], 1.99 to 2.43; p value < 0.001) in multivariable binary logistic regression analysis. Furthermore, in the longitudinal cohort during a mean follow-up of 47 months, incident osteoporosis was found in 61 (9%), 881 (7.2%), 401 (5.8%) and 213 (4.6%) participants in the underweight, normal weight, overweight and obese groups, respectively. Multivariable Cox proportional hazards analysis revealed that the risk of incident osteoporosis was higher in the underweight group than in the normal weight group (hazard ratio [HR], 1.63; 95% CI 1.26 to 2.12; p value < 0.001). Our results suggest that BMI is associated with both the prevalence and the incidence of osteoporosis. In addition, underweight is an independent risk factor for developing osteoporosis. These findings highlight the importance of maintaining normal weight for optimal bone health.

(1) Background: We aimed to explore the associations between menopause, postmenopausal hormone therapy, and metabolic syndrome in a large community-based group of Asian women. (2) Methods: This is a cross-sectional study in which we enrolled women aged 30 to 70 years with sufficient information about menopausal status from the Taiwan Biobank. The definition for metabolic syndrome used in this study aligns with the Bureau of Health Promotion’s (Taiwan) proposed definition. (3) Results: A total of 17,460 women were recruited. The postmenopausal group had a higher metabolic syndrome prevalence (30% vs. 14%) and 1.17 times higher odds ratio (OR) than the premenopausal group (95% confidence interval [CI] = 1.02 to 1.33). Regarding the types of menopause, surgical menopause was associated with metabolic syndrome (OR = 1.40; 95% CI = 1.20 to 1.63); however, natural menopause was not associated with metabolic syndrome. Interestingly, postmenopausal hormone therapy was associated with a lower risk of metabolic syndrome in the women with natural menopause (OR = 0.79; 95% CI = 0.70 to 0.89), but not in those with surgical menopause. (4) Conclusions: Our results suggest that menopause is associated with an increased prevalence of metabolic syndrome, while postmenopausal hormone therapy is associated with a lower prevalence of metabolic syndrome in women with natural menopause.

Metabolic syndrome (MetS) is prevalent in Taiwan; however, the association between MetS and cognitive function is unclear. The aim of this study was to explore the associations between MetS, its components, and obesity-related indices with cognitive function in a large Taiwanese cohort. We enrolled a total of 28,486 participants who completed the Mini-Mental State Examination (MMSE) questionnaire, which was used to evaluate cognitive function. MetS was defined according to the NCEP-ATP III guidelines and modified criteria for Asians. Ten obesity-related indices were also evaluated: body mass index (BMI), abdominal volume index (AVI), body adiposity index (BAI), waist–hip ratio (WHR), a body shape index (ABSI), lipid accumulation product, waist-to-height ratio (WHtR), conicity index (CI), body roundness index (BRI), and triglyceride glucose index. The prevalence of MetS and its components (except for hypertriglyceridemia) and the number of MetS components increased while the cognitive impairment worsened (from MMSE ≥ 24, 18–23 to 0–17). In addition, increases in all obesity-related index values were associated with a decline in cognitive function (from MMSE ≥ 24, 18–23 to 0–17, ANOVA p < 0.001). Multivariable analysis showed that MetS (p = 0.002), abdominal obesity (p < 0.001), low high-density lipoprotein cholesterol (p = 0.004), and hyperglycemia (p = 0.012) were significantly associated with a low MMSE score. Further, participants with high BMI (p = 0.001), WHR (p < 0.001), WHtR (p < 0.001), BRI (p < 0.001), CI (p < 0.001), BAI (p < 0.001), AVI (p < 0.001), and ABSI (p < 0.001) values were significantly associated with a low MMSE score. Our results show that MetS and its components (except for hypertriglyceridemia and high blood pressure) may lead to cognitive impairment, and that high values of obesity-related indices were associated with poor cognitive function.