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1.
Int J Prev Med ; 10: 188, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31807258

RESUMO

BACKGROUND: Associations between smoking and health-related quality of life (HRQoL) in the general population remain unclear. The aim of the study was to quantify the independent associations between smoking and HRQoL. METHODS: A cross-sectional population-based study was conducted on a total sample of 2197 participants obtained by multistage sampling to investigate the associations between smoking and HRQoL in the general population of southeast and southwest of Iran, aged 18-100 years in 2012-2013. Data were collected using a self-administrated of the 36-Item Short Form Survey (SF-36) questionnaire. Linear regression analyses were used to evaluate the associations between HRQoL and smoking while adjusting for various socioeconomic variables. In this study, P < 0.05 was considered a significant difference. RESULTS: Out of the total of 2197 participants, current smokers and never smokers accounted for 13% and 87%, respectively. The mean HRQoL indices were for the current smokers 66.66 ± 17.86, and never smokers 71.35 ± 18.47 (P < 0.001). Independent associations between smoking and HRQoL were found, including negative associations (P < 0.001). The multivariate associations between smoking status and HRQoL, male smokers had a lower physical functioning, mental health, and total SF-36 score. CONCLUSIONS: Smoking was independently related to HRQoL, with large differences according to the gender. This study showed that there is a significant difference in the quality of life related to health in male smokers compared to male nonsmokers.

2.
Med J Islam Repub Iran ; 31: 59, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29445688

RESUMO

Background: Studies have shown that people using complementary health insurances have more access to health services than others. In the present study, we aimed at finding the differences between out- of- pocket payments and health service utilizations in complementary health insurances (CHIs) users and nonusers. Methods: Propensity score matching was used to compare the 2 groups. First, confounder variables were identified, and then propensity score matching was used to compare out- of- pocket expenditures with dental, general physician, hospital inpatient, emergency services, nursing, midwifery, laboratory services, specialists and rehabilitation services utilization. Results: Our results revealed no significant differences between the 2 groups in out- of- pocket health expenditures. Also, the specialist visits, inpatient services at the hospital, and dental services were higher in people who used CHIs compared to nonusers. Conclusion: People did not change their budget share for health care services after using CHIs. The payments were equal for people who were not CHIs users due to the increase in the quantity of the services.

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