Maternal mortality: a cross-sectional study in global health.

BACKGROUND: Although most of maternal deaths are preventable, maternal mortality reduction programs have not been completely successful. As targeting individuals alone does not seem to be an effective strategy to reduce maternal mortality (Millennium Development Goal 5), the present study sought to reveal the role of many distant macrostructural factors affecting maternal mortality at the global level. METHODS: After preparing a global dataset, 439 indicators were selected from nearly 1800 indicators based on their relevance and the application of proper inclusion and exclusion criteria. Then Pearson correlation coefficients were computed to assess the relationship between these indicators and maternal mortality. Only indicators with statistically significant correlation more than 0.2, and missing values less than 20% were maintained. Due to the high multicollinearity among the remaining indicators, after missing values analysis and imputation, factor analysis was performed with principal component analysis as the method of extraction. Ten factors were finally extracted and entered into a multiple regression analysis. RESULTS: The findings of this study not only consolidated the results of earlier studies about maternal mortality, but also added new evidence. Education (std. B = -0.442), private sector and trade (std. B = -0.316), and governance (std. B = -0.280) were found to be the most important macrostructural factors associated with maternal mortality. Employment and labor structure, economic policy and debt, agriculture and food production, private sector infrastructure investment, and health finance were also some other critical factors. These distal factors explained about 65% of the variability in maternal mortality between different countries. CONCLUSION: Decreasing maternal mortality requires dealing with various factors other than individual determinants including political will, reallocation of national resources (especially health resources) in the governmental sector, education, attention to the expansion of the private sector trade and improving spectrums of governance. In other words, sustainable reduction in maternal mortality (as a development indicator) will depend on long-term planning for multi-faceted development. Moreover, trade, debt, political stability, and strength of legal rights can be affected by elements outside the borders of countries and global determinants. These findings are believed to be beneficial for sustainable development in Post-2015 Development Agenda.

Assessing the validity and reliability of the farsi version of inventory drug-taking situations.

OBJECTIVE: Inventory Drug-Taking Situations (IDTS) is a universal instrument used to determine high-risk situations resulting in drug abuse. The aim of this study was to translate this questionnaire to Farsi, and to assess its validity and reliability by applying it to Iranian drug users. METHODS: As a psychometric study, 300 drug users participated in a treatment program in National Center of Addiction Studies filled in a version of Inventory of Drug Taking Situations. We assessed face and content validity, internal consistency, and reliability based on the completed questionnaires, using test-retest method and confirmatory factor analysis. RESULTS: Internal consistency analysis confirmed that all subscales of IDTS were reliable (Cronbach alpha was ranging from 0.7 to 0.81). Analyses indicated that each of the subscales was unifactorial; however, unpleasant emotions had a second eigenvalue that was nearly large enough to be a second factor. Confirmatory factor analysis was used to test the fit of the data to the original version of IDTS. Based on goodness of fit indices, we found that all factors were fitted (χ2/df = 1.43, GFI = 0.98, RMSEA = 0.038). The test-retest reliability was satisfactory(r > 0.6). CONCLUSION: The Farsi version of Inventory of Drug Taking Situations was shown to be a valid and reliable instrument to apply in clinical and research settings in Iran.