Theo Niyonsenga

Dr Theo Niyonsenga is Associate Professor of Biostatistics, University of Canberra (UC) Faculty of Health, and member of both UC Health Research Institute (HRI) and Centre for Research and Action in Population Health (CeRAPH). Dr Niyonsenga was trained in Mathematics, Physics & Engineering Sciences (Bachelor of Science, National University of Rwanda, 1979-82); in Mathematical Statistics (Master of Science & PhD, University of Montreal, Canada, 1982-91); and completed his postdoctoral research training in Biometry (University of Montreal, Canada, 1991-92). Dr Niyonsenga has more than 20 years of experience working as a biostatistician in research, teaching and statistical consulting. He developed and applied statistical methods to collaborative research projects focusing on, but not limited to, the areas of multivariate data analysis methods such as structural equations modeling, longitudinal and multi-level data analysis, spatial statistics with application to spatial epidemiology.  Dr Niyonsenga commenced his continuing position with the University of Canberra by end of January 2017.  Prior to this relocation, he worked at the University of South Australia from September 2013 till January 2017. Other work experience was acquired as Adjunct Professor at the University of Saskatchewan School of Public Health (Canada); Associate Professor of Biostatistics and Epidemiology at the Florida International University School of Public Health (US); Research Associate at the University of Sherbrooke Clinical Research Centre (Canada); and as Consultant respectively for the Public Health Agency of Canada and Saskatoon Health Region, University of Saskatchewan as well as Quebec National Institutes for Public Health.

The interests in statistical methodology have been in spatial statistics and GIS environment, multivariate statistics as well as hierarchical and regression trees models with applications in cardiovascular disease risk factors, birth defects, pregnancy planning, substance abuse as well as HIV/AIDS risk behaviours and survival. In cardiovascular disease and risk factors, published work looked at: family history variables as risk factors of cardiovascular disease; geographic disparities in the use of and accessibility to health services; use of Hierarchical Bayesian models to deal with longitudinal and spatially correlated count data. In substance use and HIV/AIDS research, research focussed at conceptual models relating constructs such as substance use behaviours, acculturation and socio-cultural assets as well as growth models within the structural equations modelling approach. A secondary data analysis of the Youth Risk Behaviour Survey explored HIV/AIDS and substance use risk behaviours among adolescents. Other work explored the correlates of the inter-generation transmission of substance use (drug and alcohol drinking) between Latina mothers and daughters. Finally, multi-level survival models were also used to evaluate the role of socio-economic status variable in explaining racial disparities in AIDS survival. In these models, socio-economic indices were developed and used to measure rural-urban differences in the incidence of AIDS and to predict HIV/AIDS survival. Other work examined: effects of folic acid food fortification on the prevalence of neural tube defects in Canada; racial/ethnic and geographic variations in infant mortality rates and in childhood lead poisoning in South Florida. In terms of bio-psycho-social determinants of health, research focused on pregnancy planning and bio-psychosocial determinants of pregnancy length and fetal growth, exploring factors such stress and self-esteem.

Key Words: biostatistics; geographic variations; longitudinal study; cancer epidemiology; cancer research; cardiovascular risk factors; substance abuse; human immunodeficiency virus (HIV); acquired immunodeficiency syndrome (AIDS); psychosocial predictors; Spatio-temporal models; Multi-level and SEM Models; Pschosocial and biomedical determinants of health.