Vitamin D and Urinary Incontinence among Korean Women: a Propensity Score-matched Analysis from the 2008-2009 Korean National Health and Nutrition Examination Survey.
Hyo Serk LeeJun Ho LeePublished in: Journal of Korean medical science (2017)
A recent study investigated the role of vitamin D in urinary incontinence (UI). However, very few data are available on this topic. Therefore, we evaluated these relationships using nationally representative data from Korea. We included 6,451 women over the age of 20 years who had participated in the Korea National Health and Nutrition Examination Survey IV. We conducted a propensity-matched study by identifying women with UI. Women without UI, matched for menopause, number of pregnancies, hypertension, diabetes, body mass index, age, stroke, asthma, and chronic obstructive pulmonary disease, were selected as a control group at a 2:1 ratio. The χ² test, t-test and logistic regression analyses were used. Following propensity score matching, 558 UI cases and 1,116 normal controls were included, and confounders (menopause, hypertension, diabetes mellitus, asthma, age, obesity, and number of pregnancies) were evenly dispersed and did not differ significantly between the groups. There was no significant difference between the mean vitamin D levels of the UI and normal groups (vitamin D: 18.4 ± 6.6 vs. 18.5 ± 7.0 ng/mL; P = 0.752). Additionally, there was no significant difference in the distribution of vitamin D levels (< 20 ng/mL, 20-30 ng/mL, > 30 ng/mL: 63.8%, 30.5%, and 5.7% in normal controls, 64.0%, 27.8%, and 8.2% in UI cases; P = 0.107). In conclusion, low serum vitamin D is not significantly and independently related to female UI after propensity score matching in representative Korean data.
Keyphrases
- urinary incontinence
- chronic obstructive pulmonary disease
- polycystic ovary syndrome
- body mass index
- pregnancy outcomes
- blood pressure
- type diabetes
- electronic health record
- lung function
- big data
- cardiovascular disease
- insulin resistance
- metabolic syndrome
- weight gain
- postmenopausal women
- physical activity
- machine learning
- weight loss
- preterm birth
- pregnant women
- artificial intelligence
- adipose tissue
- deep learning
- air pollution
- data analysis
- gestational age
- allergic rhinitis
- drug induced
- cerebral ischemia