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

被引:28
作者
Moghaddam, Vahid Kazemi [1 ]
Dickerson, Aisha S. [2 ]
Bazrafshan, Edris [3 ,4 ]
Seyedhasani, Seyedeh Nahid [4 ,5 ]
Najafi, Fereshteh [6 ]
Hadei, Mostafa [7 ]
Momeni, Jalil [8 ]
Moradi, Ghasem [8 ]
Sarmadi, Mohammad [3 ,4 ,9 ]
机构
[1] Neyshabur Univ Med Sci, Dept Environm Hlth Engn, Neyshabur, Iran
[2] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
[3] Torbat Heydariyeh Univ Med Sci, Sch Hlth, Dept Environm Hlth Engn, Torbat Heydariyeh, Iran
[4] Torbat Heydariyeh Univ Med Sci, Hlth Sci Res Ctr, Torbat Heydariyeh, Iran
[5] Torbat Heydariyeh Univ Med Sci, Sch Paramed Sci, Dept Hlth Informat Technol, Torbat Heydariyeh, Iran
[6] Univ Tehran Med Sci, Sch Publ Hlth, Dept Epidemiol & Biostat, Tehran, Iran
[7] Univ Tehran Med Sci, Sch Publ Hlth, Dept Environm Hlth Engn, Tehran, Iran
[8] Torbat Heydariyeh Univ Med Sci, Student Res Comm, Torbat Heydariyeh, Iran
[9] Torbat Heydariyeh Univ Med Sci, Neurosci Res Ctr, Torbat Heydariyeh, Iran
关键词
Multiple sclerosis; Human development index; Prosperity index; Socioeconomic factors; Ecology study; ENVIRONMENTAL RISK-FACTORS; RISING PREVALENCE; EPIDEMIOLOGY; CANCER; CHILDHOOD; POSITION; MS;
D O I
10.1186/s12883-021-02170-3
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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.
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页数:11
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