Literature DB >> 23897644

Exploring the implications of small-area variation in the incidence of multiple sclerosis.

Chris Green, Bo Nancy Yu, Ruth Ann Marrie.   

Abstract

In this study, we describe the geospatial variation in the incidence of multiple sclerosis (MS) in Manitoba, Canada, and the sociodemographic characteristics associated with MS incidence. By using administrative health data, we identified all incident cases of MS in Manitoba from 1990 to 2006 (n = 2,290) and geocoded them to 230 neighborhoods in the City of Winnipeg and 268 municipalities in rural Manitoba. Age-standardized incidence rates for 1990-2006 (combined) were calculated for each region. By using the spatial scan statistic, we identified high-rate clusters in southwestern (incidence rate ratio (IRR) = 1.48) and central Winnipeg (IRR = 1.54) and low-rate clusters in north-central Winnipeg (IRR = 0.52) and northern Manitoba (IRR = 0.48). Multivariable Poisson regression showed a positive association between MS incidence rates and socioeconomic status. Despite our finding that MS incidence varied geographically and by socioeconomic status, the low Gini coefficient of 0.152 for MS incidence identified in this study suggests that the causes of MS are pervasive across all population groups. Searching for local-level causes of the disease may therefore not be as productive as investigating etiological factors operating at the population level. This may require an examination of macro-level differences in environmental exposures between high- and low-incidence regions of the world.

Entities:  

Keywords:  ecological analysis; geographic information system; incidence; multiple sclerosis

Mesh:

Year:  2013        PMID: 23897644     DOI: 10.1093/aje/kwt092

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  7 in total

1.  Multiple sclerosis incidence in Tuscany from administrative data.

Authors:  Daiana Bezzini; L Policardo; F Profili; G Meucci; M Ulivelli; S Bartalini; P Francesconi; M A Battaglia
Journal:  Neurol Sci       Date:  2018-08-08       Impact factor: 3.307

2.  Progressive rural-urban disparity in acute stroke care.

Authors:  Sergio Gonzales; Michael T Mullen; Lesli Skolarus; Dylan P Thibault; Uduak Udoeyo; Allison W Willis
Journal:  Neurology       Date:  2017-01-04       Impact factor: 9.910

3.  Using the Lorenz Curve to Characterize Risk Predictiveness and Etiologic Heterogeneity.

Authors:  Audrey Mauguen; Colin B Begg
Journal:  Epidemiology       Date:  2016-07       Impact factor: 4.822

4.  Geographical inequalities in use of improved drinking water supply and sanitation across Sub-Saharan Africa: mapping and spatial analysis of cross-sectional survey data.

Authors:  Rachel L Pullan; Matthew C Freeman; Peter W Gething; Simon J Brooker
Journal:  PLoS Med       Date:  2014-04-08       Impact factor: 11.069

5.  High incidence and increasing prevalence of multiple sclerosis in British Columbia, Canada: findings from over two decades (1991-2010).

Authors:  Elaine Kingwell; Feng Zhu; Ruth Ann Marrie; John D Fisk; Christina Wolfson; Sharon Warren; Joanne Profetto-McGrath; Lawrence W Svenson; Nathalie Jette; Virender Bhan; B Nancy Yu; Lawrence Elliott; Helen Tremlett
Journal:  J Neurol       Date:  2015-07-24       Impact factor: 4.849

6.  Small-area distribution of multiple sclerosis incidence in western France: in search of environmental triggers.

Authors:  Karima Hammas; Jacqueline Yaouanq; Morgane Lannes; Gilles Edan; Jean-François Viel
Journal:  Int J Health Geogr       Date:  2017-09-21       Impact factor: 3.918

7.  Is Geo-Environmental Exposure a Risk Factor for Multiple Sclerosis? A Population-Based Cross-Sectional Study in South-Western Sardinia.

Authors:  Maria Cristina Monti; Davide Guido; Cristina Montomoli; Claudia Sardu; Alessandro Sanna; Salvatore Pretti; Lorena Lorefice; Maria Giovanna Marrosu; Paolo Valera; Eleonora Cocco
Journal:  PLoS One       Date:  2016-09-26       Impact factor: 3.240

  7 in total

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