The research group delivers interdisciplinary scientific contributions to applied research and method development with the mission to disseminate insights into the public health science context. The research group seeks to strengthen the academic identity of public health scientists with respect to quantitative methodology. It is a main ambition of the research unit to achieve this with integration of core disciplines such as demography, intervention methodology, biostatistics and health economics.
Path 1: Demography, health economics and the determinant of NCDs
The demographic transition clearly indicates the success of the historical decrease in overall mortality and the consequential increase in life expectancies in all societies over time. At the same time, fertility levels have dropped markedly the last 50 years with ageing populations as an emerging consequence with more and more people reaching retirement age and a predicted longer life span after that. With the simultaneous epidemiological transition, a higher proportion of people are acquiring multiple chronic diseases through their life time, most of them health-behaviour related and unequally distributed in the population. The changing age-structure and the challenges associated with ageing populations will increase demands for public health services and strain limited budget resources in low-, middle- and high income countries. Countering this requires effective health planning and systems development based on high quality evidence and research for making fair decisions for action. The identification of specific target groups, e.g. vulnerable group (often suffer a higher risk) is a core pre-requisite for designing and performing adequate health interventions and services.
This path will contribute with applicable models translating epidemiological measures of risk into population health measures by considering life expectancy and healthy life expectancy summary measures, and to explore economic, societal and health impact of demographic changes.
Path 2: Outcome research, methods for evaluation and communication
Public health interventions can not always be evaluated in a randomized design, and there is a strong need for exploring modern analytical strategies to detect and remove the effects of unobserved confounding (instrumental variables, negative control outcomes and exposures, propensity scores, etc). Further, public health interventions are often complex to evaluate as their effects may have several facets and be substantially delayed before observed – and/or require the proper perspective for valid assessment. For example, screening programs will advance time of diagnosis, which in an open cohort perspective may easily be mistaken for over-detection of the disease. On the other hand, analyses based on open cohorts may be the only feasible approach due to constraints on maximal follow-up. How to understand and communicate such complex effects as lead-time (advancement of time of diagnosis) may be supported with quantitative thought experiments implemented in a user-friendly computer program. Modeling of effects may also allow provision of better and more tailored information to future participants in screening and other preventive health programs.
The research group involves the following four scientific senior staff and their respective research groups:
Associate professor Henrik Støvring: firstname.lastname@example.org
Associate professor Mette Vinther Skriver: email@example.com
Associate professor Kim Moesgaard Iburg: firstname.lastname@example.org
Associate professor Ulrika Enemark: email@example.com