The association between menopause, postmenopausal hormone therapy, and kidney stone disease in Taiwanese women

Association between milk consumption and kidney stones in U.S. adults: results from NHANES 2007-2018

Background

Dietary strategies play a crucial role in the prevention of kidney stones. While milk is known for its rich nutritional content, its impact on kidney stone formation remains unclear. This study aimed to examine the relationship between milk consumption and the risk of kidney stones among U.S. adults.

Methods

We included 24,620 participants aged 20 and older from the National Health and Nutrition Examination Survey (2007-2018). Milk consumption was defined based on each participant's response to the questionnaire item on "Past 30 day milk product consumption." Kidney stones history was self-reported by participants. The analysis employed weighted multivariate logistic regression models, followed by subgroup analyses for result validation, and explored the age-related dynamics of milk consumption's effect on kidney stone risk using a restricted cubic spline model.

Results

Adjusted findings revealed that higher milk intake was associated with a decreased risk of kidney stones (odds ratio [OR] = 0.90, 95% confidence interval [CI] 0.85-0.96), notably among women (OR = 0.86, 95% CI 0.80-0.92) but not significantly in men (OR = 0.94, 95% CI 0.86-1.02). Smoothed curves across all ages showed that women consuming milk had a lower incidence of kidney stones than those who did not, particularly with regular consumption.

Conclusion

This study uncovered that across all age groups, higher frequency of milk consumption in women is associated with a reduced risk of kidney stones. However, further prospective cohort studies are needed to confirm this finding.

The association between body mass index and osteoporosis in a Taiwanese population: a cross-sectional and longitudinal study

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.

Secondhand smoke increases the risk of developing chronic obstructive pulmonary disease

Smoking is the most important risk factor for chronic obstructive pulmonary disease (COPD), however evidence from large-scale studies on whether secondhand smoke (SHS) increases the risk of COPD is still lacking. We conducted this large longitudinal study to investigate the association between SHS and the development of COPD. This is a longitudinal study. Data on 6519 subjects who were never-smokers, had no history of COPD, and had complete lung function records were extracted from the Taiwan Biobank. They were divided into two groups according to SHS exposure: no exposure and exposure groups. Data were collected when participants enrolled in the study and during regular follow-up. Cox proportional hazards regression models were used to estimate the relative risk (RR) and 95% confidence interval (CI) for the association between SHS and the risk of developing COPD. At 48 months of follow-up, 260 (4%) participants in the no exposure group and 34 (7%) participants in the exposure group developed COPD. The RR of incident COPD development was significantly higher in the exposure group than that in the no exposure group after adjusting for confounders (RR = 1.49; 95% CI 1.04 to 2.14; P value = 0.031). There is a dose-response relationship between the duration of exposure to SHS and the risk of incident COPD, which demonstrates that an additional hour of exposure to SHS per week was associated with a 1.03-fold increased likelihood of developing COPD after adjusting for confounders (RR = 1.03; 95% CI 1.00 to 1.05; P value = 0.027). SHS exposure contributes to the development of COPD. This finding can help raise awareness of the harms of SHS and provide a reference for formulating anti-smoking policies.

A Genome-Wide Association Study of Metabolic Syndrome in the Taiwanese Population

The purpose of this study was to investigate genetic factors associated with metabolic syndrome (MetS) by conducting a large-scale genome-wide association study (GWAS) in Taiwan, addressing the limited data on Asian populations compared to Western populations. Using data from the Taiwan Biobank, comprehensive clinical and genetic information from 107,230 Taiwanese individuals was analyzed. Genotyping data from the TWB1.0 and TWB2.0 chips, including over 650,000 single nucleotide polymorphisms (SNPs), were utilized. Genotype imputation using the 1000 Genomes Project was performed, resulting in more than 9 million SNPs. MetS was defined based on a modified version of the Adult Treatment Panel III criteria. Among all participants (mean age: 50 years), 23% met the MetS definition. GWAS analysis identified 549 SNPs significantly associated with MetS, collectively mapping to 10 genomic risk loci. Notable risk loci included rs1004558, rs3812316, rs326, rs4486200, rs2954038, rs10830963, rs662799, rs62033400, rs183130, and rs34342646. Gene-set analysis revealed 22 associated genes: CETP, LPL, APOA5, SIK3, ZPR1, APOC1, BUD13, MLXIPL, TOMM40, GCK, YKT6, RPS6KB1, FTO, VMP1, TUBD1, BCL7B, C19orf80 (ANGPTL8), SIDT2, SENP7, PAFAH1B2, DOCK6, and FOXA2. This study identified genomic risk loci for MetS in a large Taiwanese population through a comprehensive GWAS approach. These associations provide novel insights into the genetic basis of MetS and hold promise for the potential discovery of clinical biomarkers.

Association between Menopause, Postmenopausal Hormone Therapy and Metabolic Syndrome

(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.