Cargando…

The Prevalence of Multiple Sclerosis in 3 US Communities

INTRODUCTION: We estimated the prevalence of multiple sclerosis (MS) in 3 large geographic areas in the southern, middle, and northern United States. METHODS: The primary data source was medical records from office visits to private neurologists' practices or to neurology departments in tertiar...

Descripción completa

Detalles Bibliográficos
Autores principales: Williamson, Dhelia M., Noonan, Curtis W., Henry, Judy P., Wagner, Laurie, Indian, Robert, Lynch, Sharon G., Neuberger, John S., Schiffer, Randolph, Trottier, Janine, Marrie, Ruth Ann
Formato: Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811507/
https://www.ncbi.nlm.nih.gov/pubmed/20040227
Descripción
Sumario:INTRODUCTION: We estimated the prevalence of multiple sclerosis (MS) in 3 large geographic areas in the southern, middle, and northern United States. METHODS: The primary data source was medical records from office visits to private neurologists' practices or to neurology departments in tertiary care facilities during a 3-year period. Additional data sources included patient advocacy groups, nursing homes, and general practitioners. RESULTS: Three-year US age-adjusted prevalence estimates for the study areas varied substantially. The prevalence was lowest (47.2 per 100,000 population) in the Texas study area (33°30′ north latitude), intermediate (86.3 per 100,000 population) in the Missouri study area (39°07′ north latitude), and highest (109.5 per 100,000 population) in the Ohio study area (41°24′ north latitude). The geographic differences remained strong after age-adjustment to the world standard population. The inverse association between UV light exposure and MS prevalence estimates was consistent with this observed latitude gradient. In all 3 areas, MS prevalence was highest among women, people aged 40 to 59 years, and non-Hispanics. CONCLUSION: These results provide necessary prevalence estimates for community cluster investigations and establish baseline estimates for future studies to evaluate temporal trends in disease prevalence.