Bias ; Confounding Factors (Epidemiology) ; Epidemiologic Methods ; Humans

OBJECTIVE: To evaluate whether smoking is a risk factor for female sexual dysfunction (FSD) and to determine the relationship between the cumulative smoking dose and FSD in premenopausal women. METHODS: The study population consisted of sexually active premenopausal women. The frequency of FSD and female sexual function index (FSFI) total score were evaluated according to the smoking status (never/former and current smokers). Evaluation of sexual function was done using FSFI questionnaire, and women with FSFI score of < or =26.55 were considered to have FSD. In current smokers, sexual function was also evaluated according to the cumulative smoking dose and nicotine dependency. RESULTS: A total of 900 women were included, and the frequency of current smokers and the frequency of FSD were 62 (6.9%) and 496 (55.1%), respectively. In current smokers, the frequency of FSD was significantly higher and the median total FSFI score was significantly lower than in never/former smokers, and this difference of FSD remained significant after adjustment for confounding variables. Among current smokers, the cumulative smoking dose (pack-years) and the total FSFI score showed negative correlation, in which increased cumulative smoking dose was associated with lower total FSFI score (r=-0.278, P<0.05). In terms of nicotine dependency, the total FSFI score of moderately to heavily nicotine dependent smokers was significantly lower than that of lightly dependent smokers. CONCLUSION: In premenopausal women, current smoking was an independent risk factor for FSD. And cumulative smoking dose and nicotine dependency were associated with higher risk of FSD.
Confounding Factors (Epidemiology) ; Female ; Humans ; Nicotine ; Risk Factors ; Smoke ; Smoking*

BACKGROUND: Korea set up new diagnosis related group (DRG) as demonstration project in 2009. The new DRG was reformed in 2016. The main purpose of study is to identify the effect of reform on accuracy of payment. METHODS: This study collected inpatient data from a hospital which contains medical information and cost from 2015 to 2016. The dependent variables were accuracy of total, bundled, unbundled payment, and payment for procedures. To analyze the effect of reform, this study conducted a multi-variate regression analysis adjusting for confounding variables. RESULTS: The accuracy of payment increased after policy reform. The accuracy of total, bundled, unbundled payment, and payment for procedures significantly increased 3.90%, 2.92%, 9.03%, and 14.57% after policy reform, respectively. The accuracy of unbundled payment showed the largest increase among dependent variables. CONCLUSION: The results of study imply that policy reform enhanced the accuracy of payment. The government needs to monitor side effects such as increase of non-covered services. Also, leads to a considerable improvement in the value of cost unit accounting as a strategic play a role in development of DRG.
Confounding Factors (Epidemiology) ; Diagnosis ; Diagnosis-Related Groups ; Humans ; Inpatients ; Korea

BACKGROUND: Korea set up new diagnosis related group (DRG) as demonstration project in 2009. The new DRG was reformed in 2016. The main purpose of study is to identify the effect of reform on accuracy of payment. METHODS: This study collected inpatient data from a hospital which contains medical information and cost from 2015 to 2016. The dependent variables were accuracy of total, bundled, unbundled payment, and payment for procedures. To analyze the effect of reform, this study conducted a multi-variate regression analysis adjusting for confounding variables. RESULTS: The accuracy of payment increased after policy reform. The accuracy of total, bundled, unbundled payment, and payment for procedures significantly increased 3.90%, 2.92%, 9.03%, and 14.57% after policy reform, respectively. The accuracy of unbundled payment showed the largest increase among dependent variables. CONCLUSION: The results of study imply that policy reform enhanced the accuracy of payment. The government needs to monitor side effects such as increase of non-covered services. Also, leads to a considerable improvement in the value of cost unit accounting as a strategic play a role in development of DRG.
Confounding Factors (Epidemiology) ; Diagnosis ; Diagnosis-Related Groups ; Humans ; Inpatients ; Korea

Confounding is the distortion of a disease/exposure association brought about by other factors which are not considered in the study design or the data analysis. These factors are called confounding factors. We should be cautious in data analysis of observational study of association of disease/exposure, since confounding often occurred in observational study. This study examines confounding effect according to data pattern (the ratio of controls to cases, the ratio of exposures to non-exposures for each level of confounding factor), criteria for treating a variable as a confounding variable, and some notes for the analysis in case-control study.
Case-Control Studies* ; Confounding Factors (Epidemiology) ; Observational Study ; Statistics as Topic

OBJECTIVETo explore the biases and confoundings in Spatial Epidemiological studies.

METHODSPossible bias and confounding and their impact on study results in Spatial Epidemiology were analyzed in given examples.

RESULTSIn Spatial Epidemiology, biases related to ascertainment/numerator/denominator induced by the choice of the disease induction/latency period and mis-specification of exposure-disease model, exposure inaccuracy, spatial dependency, significance tests etc. were involved, as well as to ecological, socio-economic confoundings factors.

CONCLUSIONThe sources of bias in 'Spatial Epidemiology' were both numerous and complex, that might be overestimated or underestimated on the study results. Hence, careful interpretation of such studies was needed.

PURPOSE: The healthy worker effect is an important issue in occupational epidemiology. This study was conducted to propose a new method to test the relation between exposure and mortality in the presence of the healthy worker effect. METHODS: In this study, the healthy worker hire effect was assumed to operate as a confounding variable of health status at the beginning of employment and healthy worker survival effect as a confounding and intermediate variable of employment status. In addition, the proposed method reflects the length bias sampling caused by changing of an employment status. Simulation studies were also carried out to compare the proposed method with Cox's time dependent covariates models . RESULTS: The theoretical development of the healthy worker survival effect is based on the result that an observation with change of an employment status requires that the survival time without intermediate event exceeds the waiting time for the intermediate event. According to our simulation studies, both the proposed method and Cox's time dependent covariates model which includes the change of employment status as time dependent covariates seem to be satisfactory at 5% significance level. However, Cox's time dependent covariates models without or with the change of employment status as time fixed covariate are unsatisfactory. The proposed test is superior in power to tests based on Cox's model. CONCLUSIONS: The healthy worker effect may not be controlled by classical Cox's proportional hazards models. The proposed method performed well in the presence of healthy worker effect in terms of level and power
Bias (Epidemiology) ; Confounding Factors (Epidemiology) ; Employment ; Epidemiology ; Healthy Worker Effect* ; Mortality ; Proportional Hazards Models

BACKGROUND: Previous studies have revealed that sleep duration is linked to both obesity and hypertension. Here, we evaluated the association between sleep duration and hypertension in obese and non-obese premenopausal women using representative national survey data from the Korean population. METHODS: A total of 4,748 subjects over 20 years of age from the Korean National Health and Nutrition Examination Survey from 2010 to 2012 were included. To control for risk factors, multivariable logistic regression was used to calculate the adjusted odds ratios and 95% confidence intervals of hypertension across the following sleep duration categories: <6, 6-8, and >8 h/d. RESULTS: Among the participants, 367 subjects (7.7%) had hypertension. Their mean sleep duration was 7 hours. In the non-obese subjects, after controlling for potential confounding variables, the odds ratio for hypertension was 1.86 fold greater in those with a sleep duration of <6 hours (odds ratio, 1.79; 95% confidence interval, 1.05 to 3.03) as compared to those who slept for 6.8 hours. However, there was no association between sleep duration and the risk of hypertension in obese subjects. Long sleep duration (over 8 h/d) was not associated with hypertension in either the non-obese or the obese subjects in this study. CONCLUSION: Short sleep duration (less than 6 h/d) may be a significant risk factor for hypertension in non-obese premenopausal women. However, there is no association between sleep duration and the risk of hypertension in obese women.
Confounding Factors (Epidemiology) ; Female ; Humans ; Hypertension* ; Korea* ; Logistic Models ; Nutrition Surveys ; Obesity ; Odds Ratio ; Risk Factors

BACKGROUND: South Korea is one of the countries with the longest working hours in the OECD countries. The aim of this study was to evaluate the effect of working hours on depressive symptoms and the role of job stress factors between the two variables among employees in South Korea. METHODS: This study used data from the Korea Working Conditions Survey in 2014. Study subjects included 23,197 employees aged 19 years or older who work more than 35 h per week. Working hours were categorized into 35–39, 40, 41–52, 53–68, and more than 68 h per week. Depressive symptoms were assessed using the WHO’s Well-Being Index with a cut-off score of 13. We calculated prevalence ratios of depressive symptoms according to working hours using log-binomial regression. Through the percentage change in prevalence ratios, we identified the extent of the role of job stress factors that explain depressive symptoms. RESULTS: The risks of depressive symptoms were significantly higher in people who worked 35–39 h per week (PR: 1.09, CI: 1.01–1.18), 53–68 h/week (PR: 1.21, CI: 1.16–1.25), and more than 68 h/week (PR: 1.14, CI: 1.07–1.21) than 40 h/week, after adjusting for confounding variables. Job stress explained the effects of long working hours on depressive symptoms in about 20–40% of the groups working more than 40 h/week. Among the factors of job stress, social support was 10–30%, which showed the highest explanatory power in all working hours. Reward explained 15–30% in the more than 52 h working group, and reward was the most important factor in the working group that exceeded 68 h. CONCLUSIONS: We showed the working hours could be an independent risk factor for depressive symptoms in employees. To improve workers’ mental health, it is important to strengthen social support in the workplace, to provide adequate rewards as they work, and ultimately to regulate the appropriate amount of working hours.
Confounding Factors (Epidemiology) ; Depression ; Korea ; Mental Health ; Organisation for Economic Co-Operation and Development ; Prevalence ; Reward ; Risk Factors

Based on the 10 domestic theses which conducted a case-control study of elderly gravida over 35, meta analysis was made of the general and clinical characteristics of cases of elderly gravida over 35 and controls of gravida under 35 with the following result. The percentage of elderly primipara was 0.5 to 2.0 according to a researcher, and that of elderly gravida 3.3 to 4.5. The percentage of elderly primipara and elderly gravida tended to be in reverse proportion to school career. Elderly gravida was found to have twice as many experiences of spontaneous abortion and the same was true of induced abortion. The ratio of cases of controls in antepartum risk factors are as follows: Finally, it should be admitted that there are some problems in this study such as biased selection, the lack of clear operational definition, the lack of precise P-value, omitted standard deviation and uncontrolled confounding variables.
Abortion, Induced ; Abortion, Spontaneous ; Aged* ; Bias (Epidemiology) ; Case-Control Studies ; Confounding Factors (Epidemiology) ; Female ; Humans ; Pregnancy ; Risk Factors