ABSTRACT
Objectives@#Our aim was to answer the following questions: (1) Can mental health variance be partitioned to individual and higher levels (e.g., neighborhood and district); (2) How much (as a percentage) do individual-level determinants explain the variability of mental health at the individual-level; and (3) How much do determinants at the neighborhood- or district-level explain the variability of mental health at the neighborhood- or district-level? @*Methods@#We used raw data from the second round of the Urban Health Equity Assessment and Response Tool in Tehran (in 2012-2013, n=34 700 samples nested in 368 neighborhoods nested in 22 districts) and the results of the official report of Tehran’s Center of Studies and Planning (in 2012-2013, n=22 districts). Multilevel linear regression models were used to answer the study questions. @*Results@#Approximately 40% of Tehran residents provided responses suggestive of having mental health disorders (30-52%). According to estimates of residual variance, 7% of mental health variance was determined to be at the neighborhood-level and 93% at the individual-level. Approximately 21% of mental health variance at the individual-level and 49% of the remaining mental health variance at the neighborhood-level were determined by determinants at the individual-level and neighborhood-level, respectively. @*Conclusions@#If we want to make the most effective decisions about the determinants of mental health, in addition to considering the therapeutic perspective, we should have a systemic or contextual view of the determinants of mental health.
ABSTRACT
Objective: To determine the prevalence and socio-economic disparity among victims with disabilities caused by RTAs in Iran as country with a high rate of accidents
Method: The source of data was the Iranian Multiple Indicator Demographic and Health Survey, a nationwide cross-sectional study. The sampling framework was based on the population and housing census for Iran in 2006. Provincial samples ranged from 400 to 6,400 households. The target sample was 3,096 clusters consisting of 2,187 urban and 909 rural clusters. In the present study, all but a few indicators are reported at provincial levels. Mortality indicators, accident and disability rates, low birth weight rate and young age at marriage rates are presented at the national level only. Logistic regression was performed to investigate the individual and family factors influencing RTAs that lead to disability in Iran
Results: The period prevalence [12 months] of road traffic accident disabilities [RTADs] in the total population of 111415 was 30.52 [95% CI: 21.13.41.64] per 100,000 individuals. Among those who had been injured during the year leading up to the study, the proportion of disabilities caused by RTAs was 31.67 [95% CI; 8.51.54.97] per 1000 pedestrians, 20.99 [95% CI: 13.37.30.75] per 1000 motorcyclists, 18.64 [95% CI: 7.71.29.57] per 1000 vehicle drivers. Multivariate logistic regression analysis showed that the risk of RTADs differed significantly in relation to age [AOR 50-59 vs. 0-9=10. 78, p-value:0.05]; activity status [AOR unemployed vs. employed=4.72, p-value:0.001] and family income [AOR q2 vs. q1=0.37, p-value:0.048] of the victim
Conclusion: In addition to the risks associated with socio-economic groups, particularly vulnerable groups, RTADs have consequences which can lead to further marginalization of individuals, can affect their quality of life and damage the community as a whole
ABSTRACT
Objectives: Low birth weight [LEW] is one of the major health problems worldwide. It is important to identify the factors that play a role in the incidence of this adverse pregnancy outcome. This study aimed to develop a tool to measure mothers' lifestyles during pregnancy with a view to the effects of social determinants on health and develop a correlation model of mothers' lifestyles with LBW
Methods: This study was conducted using methodological and case-control designs in four stages by selecting 750 mothers with infants weighing less than 4000 g using multistage sampling
The questionnaire contained 160 items. Face, content, criterion, and construct validity were used to study the psychometrics of the instrument
Results: After psychometrics, 132 items were approved in six domains. Test results indicated the utility and the high fitness of the model and reasonable relationships adjusted for variables based on conceptual models. Based on the correlation model of lifestyle, occupation [-0.263] and social relationships [0.248] had the greatest overall effect on birth weight
Conclusions: The review of lifestyle dimensions showed that all of the dimensions directly, indirectly, or both affected birth weight. Thus, given the importance and the role of lifestyle as a determinant affecting birth weight, attention, and training interventions are important to promote healthy lifestyles