[Show abstract][Hide abstract] ABSTRACT: To date, there are few studies dealing with the impact of metabolic syndrome (MS) on female sexual function, and the association between MS and female sexual dysfunction (FSD) in middle- to old-aged women remains unclear.
To evaluate the impact of MS on sexual function in middle- to old-aged women.
From May 2009 to January 2010, we performed a cross-sectional study of sexually active women (≥ 40 years old) who visited a health-screening clinic. Comprehensive history taking, anthropometric measurement, laboratory testing, and questionnaire administration were performed for each of the total 773 women enrolled.
The Female Sexual Function Index (FSFI) was used to assess the key dimensions of female sexual function.
The median age of enrolled subjects was 48 (40-65) years, and the rates of MS and FSD were 12.2% (94/773) and 54.7% (423/773), respectively. We found that the demographics of women with and without MS (P < 0.05) differed significantly from one another in terms of age, menopausal status, body mass index, educational status, household income, and urinary incontinence (UI) symptoms, although their frequency of FSD was similar (52.1% vs. 55.1%). After adjusting clinical confounders, we found that only the pain domain score was significantly different between women with MS and without MS, while the total FSFI score and other constituent domain scores showed little difference between the two groups. However, in the multivariate logistic regression model, MS and most of its components were not associated with FSD; only age, menopausal status, smoking, depression, and symptomatic UI proved to be independent risk factors for FSD (P < 0.05).
Our study suggests that MS may have little impact on sexual function in middle- to old-aged women. Further studies with population-based and longitudinal design should be conducted to confirm this finding.
Journal of Sexual Medicine 04/2011; 8(4):1123-30. · 3.15 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The objective of this study was to calculate sample size and power in an ongoing cohort, Korea radiation effect and epidemiology cohort (KREEC).
Sample size calculation was performed using PASS 2002 based on Cox regression and Poisson regression models. Person-year was calculated by using data from '1993-1997 Total cancer incidence by sex and age, Seoul' and Korean statistical informative service.
With the assumption of relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, sample size calculation was 405 events based on a Cox regression model. When the relative risk was assumed to be 1.5 then number of events was 170. Based on a Poisson regression model, relative risk=1.3, exposure:non-exposure=1:2 and power=0.8 rendered 385 events. Relative risk of 1.5 resulted in a total of 157 events. We calculated person-years (PY) with event numbers and cancer incidence rate in the non-exposure group. Based on a Cox regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, 136 245PY was needed to secure the power. In a Poisson regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, person-year needed was 129517PY. A total of 1939 cases were identified in KREEC until December 2007.
A retrospective power calculation in an ongoing study might be biased by the data. Prospective power calculation should be carried out based on various assumptions prior to the study.
Journal of Preventive Medicine and Public Health 11/2010; 43(6):543-8.
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to evaluate the association between cigarette smoking and total mortality, cancer mortality and other disease mortalities in Korean adults.
A total of 14,161 subjects of the Korean Multi-center Cancer Cohort who were over 40 years of age and who were cancer-free at baseline enrollment reported their lifestyle factors, including the smoking status. The median follow-up time was 6.6 years. During the follow-up period from 1993 to 2005, we identified 1159 cases of mortality, including 260 cancer mortality cases with a total of 91,987 person-years, by the national death certificate. Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of cigarette smoking for total mortality, cancer mortality and disease-specific mortality, as adjusted for age, gender, the geographic area and year of enrollment, the alcohol consumption status, the education level and the body mass index (BMI).
Cigarette smoking was significantly associated with an increased risk of total mortality, all-cancer mortality and lung cancer mortality (p-trend, <0.01, <0.01, <0.01, respectively). Compared to non-smoking, current smokers were at a higher risk for mortality [HR (95% CI)=1.3 (1.1-1.5) for total mortality; HR (95% CI)=1.6 (1.1-2.2) for all-cancer mortality; HR (95% CI)=3.9 (1.9-7.7) for lung cancer mortality].
This study's results suggest that cigarette smoking might be associated with total mortality, all-cancer mortality and especially lung cancer mortality among Korean adults.
Journal of Preventive Medicine and Public Health 03/2010; 43(2):151-8.