• E-mail :[email]
  • Phone : 0145595152
  • Location : Villejuif, France

Scientific topics

Keywords

ITMO

Last update 2017-11-24 17:43:25.83

Séverine Sabia PhD epidemiology and public health

Course and current status

EMPLOYMENT

2015-           : Researcher, CR1, Inserm – Team Epidemiology of ageing & age-related diseases, Inserm U1018, Villejuif, France.

2010 –         : Research associate, UCL Department of Epidemiology and Public Health, University College London, London, United Kingdom.

2009 – 2010: Post-doctoral position, Inserm – U687, Villejuif.

2006-2009:    PhD in Public Health, option Epidemiology, University of Paris XI, France. 

2004 – 2006: Statistician Inserm – Equipe ERI 20, Villejuif, France. 

 

EDUCATION 

2006-2009:    PhD in Public Health, option Epidemiology, University of Paris XI, France. 

2001-2004:    Master in general engineering (option statistics), Centrale Marseille, France.

 

FUNDING

Aviesan – Inserm 2016: « Physical activity measurement using accelerometers: from “big data” to epidemiological measures », 50000€ 

 

PUBLICATIONS: over 70 publications (19 as first author, h-index=26) http://www.researcherid.com/rid/G-2966-2017

Scientific summary

RESEARCH INTERESTS

  • Health behaviours as determinant of health
  • Ageing
  • Statistical methods 

 

The core of my work is on the impact of health behaviors on aging outcomes. I have shown the importance of the combined effect of health behaviors, and the importance of duration of unhealthy behaviors on both cognitive and motor function. Over the past five years, I have also led a project on the measure of physical activity by accelerometer in the Whitehall II Study. This involves management of the data collection and analyses of the data (Sabia et al, J Am Med Dir Assoc, 2015). My longstanding interests are in methodological issues of statistical analysis in order to study aging outcomes: cubic splines, bootstrap method, longitudinal analyses with repeated data, missing data, etc. This has led to better modeling of longitudinal data, for both the exposure and the outcome. For example, in order to explore changes over time in exposure variables before an event onset, I used mixed models with a backward timescale to test for differences in trajectories of an exposure between those who will develop dementia and the others (Sabia et al, BMJ, 2017). Attrition over the course of a study is common in longitudinal data and I have shown that the impact of smoking on cognitive decline might have been underestimated previously due to higher risk of drop-out among current smokers (Sabia et al, Arch Gen Psychiatry, 2012). 

 

5 KEY PUBLICATIONS:

  1. Sabia S, Dugravot A, Dartigues JF, Abell J, Elbaz A, Kivimaki M, Singh-Manoux A. Physical activity, cognitive decline, and risk of dementia: 28 year follow-up of Whitehall II cohort study. BMJ. 2017;357:j2709.
  2. Singh-Manoux A, Dugravot A, Fournier A, Abell J, Ebmeier K, Kivimaki M, Sabia S. Trajectories of depressive symptoms before diagnosis of dementia: A 28-year follow-up study. JAMA Psychiatry. 2017 Jul 1;74(7):712-718.
  3. Bell JA, Hamer M, van Hees VT, Singh-Manoux A, Kivimaki M, Sabia S. Healthy obesity and objective physical activity. Am J Clin Nutr. 2015;102(2):268-75.
  4. Sabia S, Cogranne P, van Hees VT, Bell JA, Elbaz A, Kivimaki M, Singh-Manoux A. Physical activity and adiposity markers at older ages: accelerometer vs questionnaire data. J Am Med Dir Assoc. 2015;16(5):438.e7-13.
  5. Sabia S, Elbaz A, Dugravot A, Head J, Shipley M, Hagger-Johnson G, Kivimaki M, Singh-Manoux A. Impact of smoking on cognitive decline in early old age: the Whitehall II cohort study. Arch Gen Psychiatry. 2012;69(6):627-35.
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