Association between water and sanitation, air and emission pollution and climate change and neurological disease distribution: A study based on GBD data.

Along with the urbanization and industrialization of countries, the prevalence of chronic diseases has increased. There is ample evidence that ambient pollution can play a major role in these diseases. This study aimed to investigate the association between neurological disorders (NDs) and their subtypes with environmental factors. In this country-level study, we used the age-standardized prevalence and incidence rate (per 100,000 populations) of NDs and its subtypes that have been taken from the Global Burden of Disease (GBD) database in 2019. We used correlation and regression analysis to assess the association between variables. Also, multivariable regression analysis was performed to identify the most important variables in NDs distribution. Age-adjusted NDs incidence rate was significantly higher in developed countries compared to developing countries (11345.25 (95% CI: 11634.88-11055.62) and 9956.37 (95% CI: 10138.66-9774.08)). Association results indicated that the impact of water and sanitation could be more effective than air pollution on NDs. The increase in water and sanitation index levels was positively correlated with NDs incidence rate and prevalence (regression coefficient (b) = 38.011 (SE = 6.50) and b = 118.84 (SE = 20.64), p < 0.001, respectively) after adjusting socio-economic and demographic factors. Furthermore, the incidence of NDs was negatively correlated with the increase in air quality (b = -16.30 (SE = 7.25), p = 0.008). Water and sanitation and their related factors are plausible factors in the distribution of NDs, which may be linked to the potential role of air and water pollution, such as heavy metals and particle matters. These results can be used by politicians and municipal service planners for future planning.

Socioeconomic determinants of global distribution of multiple sclerosis: an ecological investigation based on Global Burden of Disease data.

BACKGROUND: Socioeconomic factors may be involved in risk of multiple sclerosis (MS), either indirectly or as confounding factors. In this study two comprehensive indicators reflecting socioeconomic differences, including the Human Development Index (HDI) and Prosperity Index (PI), were used to assess the impact of these factors on the worldwide distribution of MS. METHODS: The data for this global ecological study were obtained from three comprehensive databases including the Global Burden of Disease (as the source of MS indices), United Nations Development Programme (source for HDI) and the Legatum Institute Database for PI. MS indices (including prevalence, incidence, mortality, and disability-adjusted life years) were all analyzed in the form of age- and sex-standardized. Correlation and regression analyses were used to investigate the relationship between HDI and PI and their subsets with MS indices. RESULTS: All MS indices were correlated with HDI and PI. It was also found that developed countries had significantly higher prevalence and incidence rates of MS than developing countries. Education and governance from the PI, and gross national income and expected years of schooling from the HDI were more associated with MS. Education was significantly related to MS indices (p < 0.01) in both developed and developing countries. CONCLUSION: In general, the difference in income and the socioeconomic development globally have created a landscape for MS that should be studied in more detail in future studies.

Association of the global distribution of multiple sclerosis with ultraviolet radiation and air pollution: an ecological study based on GBD data.

Given the growing global trend of multiple sclerosis (MS), this study was designed to evaluate environmental determinates of the worldwide distribution of MS in the presence of socioeconomic and geographic indices. MS data was obtained from the Institute for Health Metrics and Evaluation website. The air pollution parameters, including particles with aerodynamic diameter less than 2.5 µm (PM2.5), tropospheric ozone, and solid fuel use, were acquired from global burden of disease resources and the World Health Organization. Ultraviolet index (UVI) values were obtained from the Tropospheric Emission Monitoring Internet Service website. Correlation and linear regression analyses were used to investigate the relationship between air pollution and environmental parameters with MS variables. The average prevalence and incidence rates in countries with high UVI were 5.17 and 0.25 per 100,000, respectively, and in countries with low UVI were 101.37 and 0.78, respectively. The results showed negative associations between prevalence, incidence and mortality of MS with ozone concentrations (ß = - 1.04, - 0.04, and - 0.01 respectively; P < 0.01). Also, the fully adjusted model showed significant negative correlation of UVI with the MS variables in the presence of other variables (P < 0.01). Our findings demonstrated that UVI had the strongest significant inverse association with MS distribution. Consequently, vitamin D intake may be a major contributor to MS development. However, this study showed a slight influence of air pollution on the prevalence of MS in the presence of other parameters. Given the inconsistent results of previous studies, further studies may be required.

A new method of "student-centered formative assessment" and improving students' performance: An effort in the health promotion of community.

BACKGROUND: Improving the learning process in education will empower medical students, and also formative assessment helps improve the teaching-learning process by providing ongoing reflective information about learning gaps. OBJECTIVE: The aim of this study was to explore the effect of student-centered formative assessment by weekly reflective self-correction quizzes on medical laboratory students' performance on the final examination of hematology course in 2018. MATERIALS AND METHODS: A semi-experimental study was conducted on fifty students divided randomly into intervention (n = 25) and control groups (n = 25) using convenience sampling in 2018 from Torbat Heydariyeh University of Medical Sciences, Iran. Data analysis was performed using SPSS software version 16, two-sample t-test, Chi-square test, and analysis of covariance. RESULTS: The intervention had positive effects on students' mean test scores in hematology II so that the intervention and control groups managed to obtain 18.45 ± 1.46 and 14.57 ± 2.64, respectively (P < 0.01). CONCLUSIONS: The results suggested that weekly formative assessments along with reflective self-correction activity and active participation of students in the learning process by designing questions could improve student learning.

Do socioeconomic factors affect the prevalence of multiple sclerosis in Iran?

BACKGROUND: A rising trend for incidence of multiple sclerosis (MS) has been observed during the recent years in Iran. Several factors have been investigated as the reason, but socioeconomic determinants have been neglected. The present study aimed to investigate the relationship between Human Development Index (HDI), income and education and MS prevalence in the provinces of Iran. METHODS: The data used in this study were obtained from three sources: (a) National Registry of MS for MS prevalence data from 2006 to 2013, (b) Statistical Centre of Iran for demographic, income, and percentage of educated people data, and (c) some previous studies for HDI data. RESULTS: The findings showed high prevalence of MS in the provinces of Iran. Most patients were residents of provinces with a higher socioeconomic level. Significant relationships were found between the prevalence of MS and HDI, income and educational level (P = .002, P = .006, and P = .001, respectively). CONCLUSION: Socioeconomic determinants in Iran are different from those in many other countries. It seems that Iranian provinces with a higher socioeconomic level have higher prevalence of MS. Further studies in smaller scale are needed to better understand the relationship between socioeconomic determinants and MS prevalence in the provinces of Iran.