Socioeconomic inequality in self-rated health and its determinants: an Oaxaca blinder decomposition in Ilam, West of Iran during 2023.

AIM: To determine inequality and decompose it's in Self-Rated Health (SRH). METHOD: This population-based cross-sectional study was undertaken on the entire population of the city of Ilam, Iran, in 2023. Multi-stage stratified cluster random sampling with proportion-to-size approach was used to select the participants. Oaxaca-Blinder decomposition technique was used to show the amount of inequity in SRH and to decompose of the gap of SRH between the poor and the rich group of participants. RESULTS: 1370 persons participated in the study. The 59.38% of participants stated good SRH status and just 8.86% of participants had poor SRH status. The results of the Oaxaca-Blinder decomposition revealed a considerable gap (15.87%) in the poor status of SRH between the rich and the poor. A large proportion (89.66%) of this difference was described by explained portion of the model. The results of decomposition showed that economic status was directly responsible for explaining 27.98% of overall inequality gap between rich and poor people. Moreover, hopelessness to future (32.64%), having an underlying disease (18.34%) and difference in the education level (10.71%) were associated with an increase in inequality disfavoring the poor. CONCLUSION: For people suffering from underlying disease, it is suggested to devise policies to improve access to/and remove healthcare utilization barriers. To address hopelessness to future, it is recommended to carry out further studies to reveal factors which affect it in more details. This can help policy makers to formulate more realistic and evidence-informed policies on order to lessen the current socioeconomic inequity in SRH.

High prevalence of mental disorders: a population-based cross-sectional study in the city of Ilam, Iran.

Aim: To determine the age- and sex-standardized prevalence and risk factors of depression, anxiety, and stress symptoms in the city of Ilam. Method: In this population-based cross-sectional study, 1,350 people were invited using a multi-stage stratified cluster random sampling method. Depression, anxiety, and stress symptoms were measured using the DASS-21 standard questionnaire. For data analysis, multiple ordinal logistic regression was used in Stata version 12 software. A significance level of 5% was considered. Results: The data of 1,431 people were analyzed. The age- and sex-standardized prevalence (95% CI) of severe depression, anxiety, and stress symptoms was 19.90% (17.64 to 22.16), 25.95% (23.48 to 28.43), and 15.75% (13.69 to 17.81), respectively. There was a positive association among depression symptoms with female sex (OR: 1.52; p < 0.003), Kurdish ethnicity (OR: 2.15; p < 0.004), low educational level (OR: 1.37; p < 0.031), job losing history (OR: 1.64; p < 0.001), mental disorders history (OR: 2.17; p < 0.001), hopelessness for the future (OR: 5.38; p < 0.001), and history of other diseases (OR: 1.67; p < 0.001). There was a positive association among anxiety symptoms with female sex (OR: 1.72; p < 0.001), job losing history (OR: 1.53; p < 0.003), mental disorders history (OR: 2.11; p < 0.001), hopelessness to future (OR: 3.33; p < 0.001) and history of other diseases (OR: 1.97; p < 0.001). Hopelessness for the future and a history of other diseases were the most effective variables for anxiety symptoms and stress symptoms. Conclusion: A significant proportion of Ilam's urban population suffers from mental disorders. Increasing people's awareness, establishing counseling centers, and improving infrastructure should be considered by mental health policymakers who work in the province.

Separation and quantification of diazinon in water samples using liquid-phase microextraction-based effervescent tablet-assisted switchable solvent method coupled to gas chromatography-flame ionization detection.

This study used a liquid-phase microextraction-based effervescent tablet-assisted switchable solvent method coupled to gas chromatography-flame ionization detection as an eco-efficient, convenient-to-use, cost-effective, sensitive, rapid, and efficient method for extracting, preconcentrating, and quantifying trace amounts of diazinon in river water samples. As a switchable solvent, triethylamine (TEA) was used. In situ generation of CO2 using effervescent tablet containing Na2 CO3 and citric acid changed the hydrophobic TEA to the hydrophilic protonated triethylamine carbonate (P-TEA-C). CO2 removal from the specimen solution using NaOH caused P-TEA-C to be converted into TEA and led to phase separation, during which diazinon was extracted into the TEA phase. The salting-out process was helpful in enhancing extraction efficiency. In addition, a number of significant parameters that affect extraction recovery were examined. Under optimum conditions, the limit of detection and limit of quantitation were 0.06 and 0.2 ng/ml, respectively. The extraction recovery percentage and pre-concentration factor were obtained at 95 and 190%, respectively, and the precision (inter- and intra-day, relative standard deviation %, n = 5) was <5%.

Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population.

BACKGROUND: The novel coronavirus (COVID-19) has infected nearly 9.5 million people in 216 countries, areas, or territories in the world. The fight against the COVID-19 has become a very serious international challenge. The aim of this study was to determine the predictors of COVID-19-preventive behaviors using the health belief model (HBM). MATERIALS AND METHODS: This cross-sectional study was conducted with the participation of 558 samples from the adult population of Iran. The online convenience sampling was conducted in this research. The online 68-item questionnaire link was published all over Iran through social networks including Telegram and WhatsApp, which are common in Iran. The data were analyzed using SPSS software version 19. Descriptive statistics, bivariate Pearson's correlation test, and multiple linear regression were used to analyze the data. RESULTS: The mean age of the subjects was 33.3 ± 10.01 years. The participants were often female (61.3%), married (57.9%), and resident of the city (81.0%) with university educational level (78.8%). The results showed that the HBM structures predicted 29.3% of the preventive behaviors of COVID-19 in the subjects. The perceived benefits, perceived barriers, and self-efficacy significantly predicted the preventive behaviors, but the perceived susceptibility and perceived severity were not significant in the regression model. The internet and virtual social networks (49.8%), broadcast (33.5%), and healthcare providers (15.8%) were the most important sources of information related with COVID-19. In response to COVID-19-related internal cues to action, 36.6% did not pay attention and 34.7% tried to self-medicate. Only 28.5% of the subjects referred to the hospital, healthcare center, or physician. CONCLUSION: Self-efficacy, perceived barriers, and perceived benefits were the key determinants of COVID-19-preventive behaviors in the subjects. It can be concluded that the HBM is a good tool to predict COVID-19-preventive behaviors in Iranian population.