Gender Differences with Dose⁻Response Relationship between Serum Selenium Levels and Metabolic Syndrome-A Case-Control Study.
Chia-Wen LuHao-Hsiang ChangKuen-Cheh YangChien-Hsieh ChiangChien-An YaoKuo-Chin HuangPublished in: Nutrients (2019)
Few studies have investigated the association between selenium and metabolic syndrome. This study aimed to explore the associations between the serum selenium level and metabolic syndrome as well as examining each metabolic factor. In this case-control study, the participants were 1165 adults aged ≥40 (65.8 ± 10.0) years. Serum selenium was measured by inductively coupled plasma-mass spectrometry. The associations between serum selenium and metabolic syndrome were examined by multivariate logistic regression analyses. The least square means were computed by general linear models to compare the serum selenium levels in relation to the number of metabolic factors. The mean serum selenium concentration was 96.34 ± 25.90 μg/L, and it was positively correlated with waist circumference, systolic blood pressure, triglycerides, fasting glucose, and homeostatic model assessment insulin resistance (HOMA-IR) in women, but it was only correlated with fasting glucose and HOMA-IR in men. After adjustment, the odds ratios (ORs) of having metabolic syndrome increased with the selenium quartile groups (p for trend: <0.05), especially in women. The study demonstrated that the serum selenium levels were positively associated with metabolic syndrome following a non-linear dose⁻response trend. Selenium concentration was positively associated with insulin resistance in men and women, but it was associated with adiposity and lipid metabolism in women. The mechanism behind this warrants further confirmation.
Keyphrases
- metabolic syndrome
- insulin resistance
- polycystic ovary syndrome
- blood pressure
- uric acid
- mass spectrometry
- heart failure
- blood glucose
- body mass index
- adipose tissue
- skeletal muscle
- cardiovascular risk factors
- high fat diet
- physical activity
- cardiovascular disease
- hypertensive patients
- pregnancy outcomes
- high speed
- diffusion weighted imaging
- atomic force microscopy
- ms ms
- data analysis
- contrast enhanced