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1.  Preventive Care Use among the Belgian Elderly Population: Does Socio-Economic Status Matter? 
Objective: To analyze the association between influenza and pneumococcus vaccination and blood cholesterol and blood sugar measurement by Belgian elderly respondents (≥65 years) and socio-demographic characteristics, risk factors, health status and socio-economic status (SES). Methods: A cross-sectional study based on 4,544 non-institutionalized elderly participants of the Belgian Health Interview Surveys 2004 and 2008. Multivariate logistic regression models were constructed to examine the independent effect of socio-demographic characteristics, risk factors, health status and SES on the four preventive services. Results: After adjustment for age, sex, region, survey year, living situation, risk factors (body mass index, smoking status, physical activity) and health status (self-assessed health and longstanding illness) lower educated elderly were significantly less likely to report a blood cholesterol and blood sugar measurement. For instance, elderly participants with no degree or only primary education were less likely to have had a cholesterol and blood sugar measurement compared with those with higher education. Pneumococcus vaccination was not related to educational level, but lower income groups were more likely to have had a pneumococcus immunization. Influenza vaccination was not significantly related to SES. Conclusion: The results highlight the need to promote cholesterol and blood sugar measurement for lower SE groups, and pneumococcus immunization for the entire elderly population. Influenza immunization seems to be equally spread among different SE groups.
doi:10.3390/ijerph110100355
PMCID: PMC3924448  PMID: 24368427
preventive care; socioeconomic status; elderly population; Belgium
2.  Methodological basics and evolution of the Belgian health interview survey 1997–2008 
Archives of Public Health  2013;71(1):24.
Background
The Belgian Health Interview Survey (BHIS) is organised every 4 to 5 years and collects health information from around 10,000 individuals in a face-to-face setting. This manuscript describes the methodological choices made in the sampling design, the outcomes of the previous surveys in terms of participation rates and achieved targets and the factors to be accounted for in data-analysis.
Methods
The BHIS targets all persons residing in Belgium with no restrictions on age or nationality. Trimestral copies of the National Population Registry are used as the sampling frame. To select the respondents, a multistage sampling design is applied involving a geographical stratification, a selection of clusters, a selection of households within each cluster and a selection of respondents within each household. Using matched substitution of non-participating households assures the realisation of the predefined net-sample.
Results
For each BHIS the required number of participants is achieved, including the years when an oversampling of provinces and of the elderly occurred. The sampling design guarantees that the survey is implemented in large cities as well as in small municipalities. A growing problem is related to the sampling frame: it is increasingly subject of deterioration, especially in the Brussels-Capital Region.
Conclusions
The methodological approach developed for the first BHIS proves to be accurate and was kept nearly unchanged throughout the following surveys. Fieldwork substitution contributes to a considerable extent to the success of the fieldwork but yields in higher percentages of non-participation. The sampling design requires special attention when analysing the data: the unequal selection probability, e.g. due to the non-proportional stratification at the regional level, necessitates the use of weights. The BHIS is progressively embedded in the European Health Survey, a process that doesn’t jeopardise the comparability of the Belgian results throughout time.
doi:10.1186/0778-7367-71-24
PMCID: PMC3844891  PMID: 24047278
Health interview survey; Survey-methodology; Fieldwork substitution
3.  Impact of Genetic Notification on Smoking Cessation: Systematic Review and Pooled-Analysis 
PLoS ONE  2012;7(7):e40230.
Objectives
This study aimed to evaluate the impact of genetic notification of smoking-related disease risk on smoking cessation in the general population. Secondary objectives were to assess the impact of genetic notification on intention-to-quit smoking and on emotional outcomes as well as the understanding and the recall of this notification.
Methods
A systematic review of articles from inception to August 2011 without language restriction was realized using PubMed, Embase, Scopus, Web of Science, PsycINFO and Toxnet. Other publications were identified using hand search. The pooled-analysis included only randomized trials. Comparison groups were (i) high and low genetic risk versus control, and (ii) high versus low genetic risk. For the pooled-analysis random effect models were applied and sensitivity analyses were conducted.
Results
Eight papers from seven different studies met the inclusion criteria of the review. High genetic risk notification was associated with short-term increased depression and anxiety. Four randomized studies were included in the pooled-analysis, which revealed a significant impact of genetic notification on smoking cessation in comparison to controls (clinical risk notification or no intervention) in short term follow-up less than 6 months (RR = 1.55, 95% CI 1.09–2.21).
Conclusions
In short term follow-up, genetic notification increased smoking cessation in comparison to control interventions. However, there is no evidence of long term effect (up to 12 month) on smoking cessation. Further research is needed to assess more in depth how genetic notification of smoking-related disease could contribute to smoking cessation.
doi:10.1371/journal.pone.0040230
PMCID: PMC3394798  PMID: 22808123
4.  Public health in the genomic era: will Public Health Genomics contribute to major changes in the prevention of common diseases? 
The completion of the Human Genome Project triggered a whole new field of genomic research which is likely to lead to new opportunities for the promotion of population health. As a result, the distinction between genetic and environmental diseases has faded. Presently, genomics and knowledge deriving from systems biology, epigenomics, integrative genomics or genome-environmental interactions give a better insight on the pathophysiology of common diseases. However, it is barely used in the prevention and management of diseases. Together with the boost in the amount of genetic association studies, this demands for appropriate public health actions. The field of Public Health Genomics analyses how genome-based knowledge and technologies can responsibly and effectively be integrated into health services and public policy for the benefit of population health. Environmental exposures interact with the genome to produce health information which may help explain inter-individual differences in health, or disease risk. However today, prospects for concrete applications remain distant. In addition, this information has not been translated into health practice yet. Therefore, evidence-based recommendations are few. The lack of population-based research hampers the evaluation of the impact of genomic applications. Public Health Genomics also evaluates the benefits and risks on a larger scale, including normative, legal, economic and social issues. These new developments are likely to affect all domains of public health and require rethinking the role of genomics in every condition of public health interest. This article aims at providing an introduction to the field of and the ideas behind Public Health Genomics.
doi:10.1186/0778-7367-69-8
PMCID: PMC3436652  PMID: 22958637
Epidemiology; Genomics; Epigenomics; Prevention; Public Health; Public Health Genomics; Translational Research; Policymaking; Personalised Healthcare

Results 1-4 (4)