Résumé
OBJECTIVES: The lowest-low fertility status of Korea has continued for the past 17 years despite governmental efforts to encourage childbirth. As the number of working women has increased, their residence patterns have changed; however, the impact of this factor has yet to be explored. Therefore, this study was conducted to investigate the effects of residence patterns relative to the workplace on the total fertility rate of working women.METHODS: Information on eligibility and healthcare utilization was obtained from the National Health Information Database between 2011 and 2015. The study participants were working women aged 15-49 years. We classified their residence relative to their workplace into 3 patterns: same municipality, same province, and different province. The total fertility rate was calculated and logistic regression was performed of childbirth according to residence pattern, adjusting for age, insurance contribution quartile, size of the workplace, year of birth, and province of residence.RESULTS: The total fertility rates of working women from 2011 to 2015 were 1.091, 1.139, 1.048, 1.073, and 1.103, respectively. The total fertility rate by residence pattern was highest in women residing in the same municipality as their workplace. After adjustment, the odds of childbirth in women from the same municipality and the same province were 21.6% and 16.0% higher than those of women residing in a different province, respectively.CONCLUSIONS: The total fertility rate was higher among women living near their workplace. Therefore, effective policy measures should be taken to promote the proximity of working women's workplace and residence.
Sujets)
Femelle , Humains , Taux de natalité , Prestations des soins de santé , Fécondité , Assurance , Corée , Modèles logistiques , Parturition , Politique publique , Femmes qui travaillentRésumé
OBJECTIVES@#To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status.@*METHODS@#This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status.@*RESULTS@#Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight.@*CONCLUSIONS@#These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.
Résumé
OBJECTIVES@#The lowest-low fertility status of Korea has continued for the past 17 years despite governmental efforts to encourage childbirth. As the number of working women has increased, their residence patterns have changed; however, the impact of this factor has yet to be explored. Therefore, this study was conducted to investigate the effects of residence patterns relative to the workplace on the total fertility rate of working women.@*METHODS@#Information on eligibility and healthcare utilization was obtained from the National Health Information Database between 2011 and 2015. The study participants were working women aged 15-49 years. We classified their residence relative to their workplace into 3 patterns: same municipality, same province, and different province. The total fertility rate was calculated and logistic regression was performed of childbirth according to residence pattern, adjusting for age, insurance contribution quartile, size of the workplace, year of birth, and province of residence.@*RESULTS@#The total fertility rates of working women from 2011 to 2015 were 1.091, 1.139, 1.048, 1.073, and 1.103, respectively. The total fertility rate by residence pattern was highest in women residing in the same municipality as their workplace. After adjustment, the odds of childbirth in women from the same municipality and the same province were 21.6% and 16.0% higher than those of women residing in a different province, respectively.@*CONCLUSIONS@#The total fertility rate was higher among women living near their workplace. Therefore, effective policy measures should be taken to promote the proximity of working women's workplace and residence.
Résumé
OBJECTIVES: To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status. METHODS: This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status. RESULTS: Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight. CONCLUSIONS: These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.
Sujets)
Consommation d'alcool , Ensemble de données , Diabète , Consommation de boisson , Emploi , Assurance , Corée , Mode de vie , Ischémie myocardique , Surpoids , Fumée , Arrêter de fumer , Fumer , Accident vasculaire cérébral , Prise de poidsRésumé
OBJECTIVES: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. METHODS: Data from self-reported questionnaires that assessed an individual's history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. RESULTS: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of self-reported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. CONCLUSIONS: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.