1.What Explains Socioeconomic Inequality in Health-related Quality of Life in Iran? A Blinder-Oaxaca Decomposition.
Satar REZAEI ; Mohammad HAJIZADEH ; Yahya SALIMI ; Ghobad MORADI ; Bijan NOURI
Journal of Preventive Medicine and Public Health 2018;51(5):219-226
OBJECTIVES: This study aimed to explain the health-related quality of life (HRQoL) gap between the poorest and the wealthiest quintiles in the capitals of Kermanshah and Kurdistan Provinces (Kermanshah and Sanandaj), in western Iran. METHODS: This was a cross-sectional study conducted among 1772 adults. Data on socio-demographic characteristics, socioeconomic status (SES), lifestyle factors, body mass index, and HRQoL of participants were collected using a self-administered questionnaire. The slope and relative indices of inequality (SII and RII, respectively) were employed to examine socioeconomic inequality in poor HRQoL. Blinder-Oaxaca (BO) decomposition was used to quantify the contribution of explanatory variables to the gap in the prevalence of poor HRQoL between the wealthiest and the poorest groups. RESULTS: The overall crude and age-adjusted prevalence of poor HRQoL among adults was 32.0 and 41.8%, respectively. The SII and RII indicated that poor HRQoL was mainly concentrated among individuals with lower SES. The absolute difference (%) in the prevalence of poor HRQoL between the highest and lowest SES groups was 28.4. The BO results indicated that 49.9% of the difference was explained by different distributions of age, smoking behavior, physical inactivity, chronic health conditions, and obesity between the highest and lowest SES groups, while the remaining half of the gap was explained by the response effect. CONCLUSIONS: We observed a pro-rich distribution of poor HRQoL among adults in the capitals of Kermanshah and Kurdistan Provinces. Policies and strategies aimed at preventing and reducing smoking, physical inactivity, chronic health conditions, and obesity among the poor may reduce the gap in poor HRQoL between the highest and lowest SES groups in Iran.
Adult
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Body Mass Index
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Cross-Sectional Studies
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Health Status Disparities
;
Humans
;
Iran*
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Life Style
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Obesity
;
Prevalence
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Quality of Life*
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Smoke
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Smoking
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Social Class
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Socioeconomic Factors*
2.Socioeconomic inequalities in metabolic syndrome and its components in a sample of Iranian Kurdish adults
Pardis MOHAMMADZADEH ; Farhad MORADPOUR ; Bijan NOURI ; Farideh MOSTAFAVI ; Farid NAJAFI ; Ghobad MORADI
Epidemiology and Health 2023;45(1):e2023083-
OBJECTIVES:
The worldwide incidence of metabolic syndrome (MetS) has increased in recent decades. In this study, we investigated the socioeconomic inequalities associated with MetS and its components in a sample of the Iranian Kurdish population.
METHODS:
We used data from 3,996 participants, aged 35 years to 70 years, from the baseline phase of the Dehgolan Prospective Cohort Study (February 2018 to March 2019). The concentration index and concentration curve were used to measure inequality and the Blinder-Oaxaca decomposition method was used to examine the contribution of various determinants to the observed socioeconomic inequality in MetS and its components.
RESULTS:
The prevalence of MetS was 34.44% (95% confidence interval [CI], 32.97 to 35.93). The prevalence of MetS was 26.18% for those in the highest socioeconomic status (SES), compared with 40.51% for participants in the lowest SES. There was a significant negative concentration index for MetS (C=-0.13; 95% CI, -0.16 to -0.09), indicating a concentration of MetS among participants with a lower SES. The most prevalent component was abdominal obesity (59.14%) with a significant negative concentration index (C=-0.21; 95% CI, -0.25 to -0.18). According to decomposition analysis, age, gender, and education were the highest contributing factors to inequality in MetS and its components.
CONCLUSIONS
This study showed socioeconomic inequality in MetS. People with a low SES were more likely to have MetS. Therefore, policymakers and health managers need to develop appropriate strategies to reduce these inequalities in MetS across age groups, genders, and education levels, especially among women and the elderly.