Abstract Details

Title Retrospective Mortality Analysis of Hereditary Ataxia in the United States (2000–2020) and Forecast to 2050 Using ARIMA

Topic Movement Disorders

Presentation(s) P4 - Poster Session 4 (8:00 AM-9:00 AM)

Poster/Presentation
Number 16-015

Objective To quantify United States mortality trends in hereditary ataxias, compare rates by sex, race, census region, and urbanization, and forecast burden to 2050.

Background Population level mortality patterns for hereditary ataxias in the United States remain poorly characterized, which limits planning for care and research.

Design/Methods We analyzed United States Multiple Cause of Death data from CDC WONDER, years 2000 to 2020. Deaths were identified with ICD 10 code G11, hereditary ataxias. Age adjusted mortality rates, per 100,000, used the 2000 United States standard population with 95 percent confidence intervals. Temporal trends were evaluated with joinpoint regression to estimate annual percent change. Forecasts to 2050 used autoregressive integrated moving average, with sensitivity analysis using linear regression. Analyses were stratified by sex, race, census region, and National Center for Health Statistics urbanization categories.

Results National age adjusted mortality increased across 2000 to 2020, with a significant positive annual percent change. Rates rose in both sexes and were consistently higher in males. Relative increases were largest among Black or African American individuals and in the West region. Directionally similar increases were observed across urbanization categories. Forecasting projected continued growth in mortality through 2050. Sensitivity analyses produced qualitatively similar trends, with wider uncertainty in smaller strata.

Conclusions Mortality associated with hereditary ataxias rose in the United States during 2000 to 2020, and forecasts indicate continued increases. Findings point out to growing clinical and public health needs. Better phenotyping and coding, earlier diagnosis, and registry linked surveillance could refine estimates and inform service planning.

Authors/Disclosures
Maria Nawaz, PhD PRESENTER	Miss Nawaz has nothing to disclose.
Muhammad Junaid Iqbal, PhD	Dr. Iqbal has nothing to disclose.
Fiza Wali, MBBS	Miss Wali has nothing to disclose.
Laraib Israr, Masters	Ms. Israr has nothing to disclose.
Faizan I. Khan, MBBS	Dr. Khan has nothing to disclose.
Hanzala A. Farooqi, MBBS	Mr. Farooqi has nothing to disclose.
Ahmed Kunwer Naveed, MD	Dr. Naveed has nothing to disclose.
Areeba Kabir, MD	Dr. Kabir has nothing to disclose.
Gianluca Morganti	Mr. Morganti has nothing to disclose.
Anastasia Ricci	Dr. Ricci has nothing to disclose.
Michele Menotta, PhD	Prof. Menotta has nothing to disclose.

��ɫ��

��ɫ��