Abstract Background Arsenic (As) exposure poses significant health risks to exposed populations, with exposure occurring predominantly via diet for the general population as recently referred by the European Food Safety Authority. This study assesses the environmental burden of disease (EBD) for three cancer types related to arsenic, across Europe. Methods A literature review was conducted to 1) identify the dose-response function (DRF) to assess the cancer risk in European populations, and 2) define EBD approaches applicable to the available data. Country-specific data (Belgium, Denmark, Portugal) for EBD calculation (exposure, socioeconomic status, health outcomes) were gathered. Disability-Adjusted Life Years (DALY) estimations were performed by calculating attributable cases (AC). Results Two main references are used for DRF: the United States Food and Drug Administration DRF for assessing bladder and lung cancer risks, and the United States Environmental Protection Agency DRF for skin cancer. Preliminary results for Belgium indicate that inorganic arsenic dietary exposure ranges from 0.084 [0.080 - 0.088] to 0.102 [0.097 - 0.107] µg/kg body weight per day, varying with education level. Stratified estimates suggest that individuals with higher educational attainment (ISCED levels 5 & 6) have a marginally higher average daily intake of arsenic compared to those with lower educational attainment (ISCED levels 0, 1 & 2). DALY attributable to inorganic arsenic exposure follow the same trend as exposure levels, i.e. individuals with a higher education level bear a higher burden of disease than individuals of the low education stratum. This concerns the three studied cancers. Conclusions This study quantifies DALY related to inorganic arsenic from dietary exposure for different European countries. Our findings will contribute to better target public health policies and interventions for arsenic risk mitigation. Key messages • Exposure to inorganic arsenic is confirmed in European countries. • EBD studies guide action priorities to tackle chemical risk factors.

Abstract Issue Excess weight status is one of the main metabolic risk factors for non-communicable diseases. According to the Belgian health interview survey of 2018, 49.3% of the adult population suffered from overweight. Despite the great national burden, and apart from isolated actions, there is not anymore a comprehensive nutritional and physical activity health plan in Belgium. Consequentially, Belgium requires action-oriented research to support the implementation of evidence-based policies for the prevention of excessive weight gain. Description of the Problem The WaIST project aims to assess the contribution of excess weight status to the societal impact of non-communicable diseases, disability and multi-morbidity, and to model and compare the potential impact of internationally recommended health policies. The project also aims to support knowledge translation and policy transfer through a close interaction with national decision makers and stakeholders. Results The disease burden of diabetes, cardiovascular diseases, cancer and musculoskeletal disorders will be estimated in terms of disability-adjusted life years (DALYs) and healthcare expenses from a societal perspective. For this purpose, survey, registry, health insurance, and hospital discharge data will be used. Subsequently, health interventions tackling overweight will be selected considering scientific evidence and stakeholder priorities. Health impact assessments will then be conducted projecting the future impact of the interventions on health outcomes and costs related to excess weight status. Lessons The use of national data for the computation of the burden of disease provides better estimates for DALYs and costs compared to European or global study results. Moreover, the results of the project will allow to explore the impact of health intervention specific for the Belgian case. Key messages Considering the burden associated with overweight-related diseases, preventing obesity is important from a public health and financial perspective. Integrating these results into evidence-based policies could provide governments and partners with a key tool for effective health interventions.

TPS 701: Spatial determinants of population health, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Background/Aim: Mental health in a broad sense is defined as the ability to cope with problems and fulfill one's role in society. In this area, Belgium has a poor record, featuring a high number of depressions and anxiety disorders. The NAMED project aims at exploring different dimensions of mental health in Belgium in relation to the (non) built environment. Methods: Data from the Health Interview Survey (HIS) 2008 and 2013 was used. Variables describing mental health and annoyance at home (air pollution, noise, smells, …) for 13.905 participants were analyzed using the R statistical language. Based on mixed factor analysis (FAMD) on mental health variables and environmental stressors, relevant indicators were selected and screened on differences between provinces. Results: Five indicators were selected for both mental health and environmental stressors based on their contribution to the first four dimensions. The state of mental health was similar in the majority of the provinces, but differences in the dimensions of mental health problems could be seen. Psychological distress was lowest in West-Flanders, and highest in Brussels. Subjective health however was highest in Brabant Walloon and lowest in West-Flanders. Suicidal ideation and depression was observed more often in Namur and Hainaut and less so in Limburg and Antwerp. Brussels performed poorly on nearly all dimensions of mental health. When looking at residential annoyances, traffic noise and vibrations were mentioned most often, and densely populated provinces were more affected than others. Airplane noise was most prevalent in Brussels and Flemish Brabant. More than 80% of the participants were not at all annoyed by air pollution at home. In Brussels, this drops to 60%. Conclusions: Provinces with more mention of environmental stressors appear to have more mental health problems, although this association is not always straightforward and depends on the dimension of mental health considered.

AIMS:To analyse whether care trajectories (CT) were associated with increased prevalence of parenteral hypoglycemic treatment (PHT=insulin or GLP-1 analogues), statin therapy or RAAS-inhibition. Introduced in 2009 in Belgium, CTs target patients with type 2 diabetes mellitus (T2DM), in need for or with PHT.METHODS:Retrospective study based on a registry with 97 general practitioners. The evolution in treatment since 2006 was compared between patients with vs. without a CT, using longitudinal logistic regression.RESULTS:Comparing patients with (N=271) vs. without a CT (N=4424), we noted significant differences (p<0.05) in diabetes duration (10.1 vs. 7.3 years), HbA1c (7.5 vs. 6.9%), LDL-C (85 vs. 98mg/dl), microvascular complications (26 vs. 16%). Moreover, in 2006, parenteral treatment (OR 52.1), statins (OR 4.1) and RAAS-inhibition (OR 9.6) were significantly more prevalent (p<0.001). Between 2006 and 2011, the prevalence rose in both groups regarding all three treatments, but rose significantly faster (p<0.05) after 2009 in the CT-group.CONCLUSIONS:Patients enrolled in a CT differ from other patients even before the start of this initiative with more intense hypoglycemic and cardiovascular treatment. Yet, they presented higher HbA1c-levels and more complications. Enrolment in a CT is associated with additional treatment intensification.

BACKGROUND:In 2009, the Belgian National Institute of Health and Disability Insurance established a care trajectory (CT) for a subgroup of type 2 diabetes mellitus patients (T2DM) based on Wagner's chronic care model. The goal of this CT is to optimise the quality of care using an integrated multidisciplinary approach. This study aims to identify patient-related factors associated with inclusion in a CT and to determine the most frequent reasons for non-inclusion.METHODS:In 2010, the Belgian Sentinel Network of General Practices conducted a prevalence study of type 2 diabetes. The surveillance study carried out by this nationwide, representative network collected unique information about eligibility for the CT, inclusion in the CT and reasons for non-inclusion. Based on the official inclusion and exclusion criteria, we first identified a group of eligible patients. Within this group, we then calculated the proportion of patients included in a CT as well as the prevalence of reasons for non-inclusion as reported by GPs. Furthermore, bivariate associations between patient-level parameters and inclusion were analysed. Finally, any patient-level parameters found to be statistically significant were included in a multivariate logistic regression model.RESULTS:The 2010 study recorded 4600 Belgian type 2 diabetes patients. According to the official criteria, 589 patients were eligible for inclusion in a CT T2DM. By the end of August 2011, 95 patients had been included in a CT T2DM. Our findings reveal that the younger the eligible patient was, the more likely he or she was to be included in a CT. Patients living in Flanders were more likely to be included in the CT than were patients living in Wallonia. Motivated patients with specific plans to change their diets were also more likely to be included in a CT. The two most frequently reported reasons for non-inclusion were participation in another diabetes care programme and the timing of this surveillance study (inclusion will take place in the near future).CONCLUSIONS:Eligible diabetes patients who were admitted to a CT T2DM during the early phases of CT implementation were mainly found to be those who are able to make progress in their disease trajectories. In the future, more attention could be paid to also include more high-risk patients.

Starting in 2009, the first ever Belgian nationwide data collection network using routine data extracted from primary care EPR (upload method) has been built from scratch. The network also uses a manual web-based data collection method. This paper compares these two methods by analysing missing and most recent values for certain parameters. We collected data from 4954 practices, pertaining to 29,180 patients. Mean values for the most recent parameters were similar regardless of which data collection method was used. Many missing recent values (>46%) were found for all of the parameters when using the upload method. It seems that, in Belgium, uploading routine data from primary care EPR on a large scale is suitable and allows the collection of chronological retrospective data. However, the method still requires major, carefully controlled improvements.

De laatste tien jaar zijn in Belgie meerdere specifieke onderzoeksnetwerken, permanent of tijdelijk, gelanceerd. In dit onderzoeksrapport wordt een generiek model van gegevensstroom voor een onderzoeksnetwerk beschreven en getoetst aan het nationale privacysysteem

OBJECTIVES:To picture the 10-year evolution of renal function in patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) and to describe the risk factors for severe decline.SETTING:Primary registration network with 97 general practitioners working in 55 practices sending routinely collected patient data.PARTICIPANTS:From the database, we selected all patients aged 40 years or older with T2DM and at least two creatinine measurements in two different years with an interval of at least 3 months. Based on the last available value of estimated glomerular filtration rate calculated by the modification of diet in renal disease (MDRD) equation, patients were divided into grades of CKD. Severe decline (decline of >4 mL/min/year) and 'certain drop' (CD, year-to-year decline >10 mL/min) were determined in patients with CKD. Determinants of severe decline and CD were investigated with logistic regression and longitudinal logistic regression analysis, respectively.PRIMARY OUTCOME MEASURE:Kidney function (MDRD).RESULTS:4041 patients, 1980 women, were included. The mean age was 71 years, mean diabetes duration was 7.7 years; 1514 (38%) suffered from CKD, 231 (15%) presented with severe decline and 18% of the patients with CKD presented with two or more CDs. Younger age, male gender, mean glycated haemoglobin and a higher number of CDs were significantly associated with the presence of severe decline (p<0.05); statins and higher diastolic blood pressure were significantly associated with the absence of severe decline (p<0.001). ACE inhibitors, other antihypertensive drugs and antidiabetic drugs including insulin therapy were specific determinants of CD.CONCLUSIONS:CKD is highly prevalent in patients with T2DM; a minority of patients evolve into severe decline that is associated with younger age, male gender, 'CD' and manageable factors such as blood pressure, blood glucose, associated drugs prescriptions and statin therapy. Further prospective observational and experimental research is needed to clarify the nature of those associations.

Electronic Patient Records can be interfaced with medical decision support systems and quality of care assessment tools. An easy way of measuring the quality of EPR data is therefore essential. This study identified a number of global quality indicators (tracers) that could be easily calculated and validated them by correlating them with the Sensitivity and Positive Predictive Value (PPV) of data extracted from the EPR. Sensitivity and PPV of automatically extracted data were calculated using a gold standard constructed using answers to questions GPs were asked at the end of each contact with a patient. These properties were measured for extracted diagnoses, drug prescriptions, and certain parameters. Tracers were defined as drug-disease pairs (e.g. insulin-diabetes) with the assumption that if the patient is taking the drug, then the patient is suffering from the disease. Four tracers were identified that could be used for the ResoPrim primary care research database, which includes data from 43 practices, 10,307 patients, and 13,372 contacts. Moderately positive correlations were found between the 4 tracers and between the tracers and the sensitivity of automatically extracted diagnoses. For some purposes, these results may support the potential use of tracers for monitoring the quality of information systems such as EPRs.

The numerous existing primary care-based research networks currently use various data collection methods. In this paper, we compared routine data extracted from general practitioners' (GPs') electronic patient records (EPRs) and GPs' answers to an electronic questionnaire. We investigated for 10,307 Belgian patients 10 healthcare conditions using clinical and biological parameters (cholesterol, blood pressure, and body mass index), diagnoses (hypertension, diabetes, and personal past cardiovascular event(s)), and drug prescriptions (antidiabetic drugs, aspirin, statins, and antihypertensive drugs). We found a relatively fair agreement (Kappa≥0.40) between the two data collection methods for 7 healthcare conditions, but no agreement for the biological parameters. When EPR data was used and compared with the questioning method, the prevalence of diagnoses and drug prescriptions was relatively lower and the prevalence of clinical and biological parameters was relatively higher (all missing data excluded) in the EPR data than in the data collected using the questioning method. Using EPR data, we calculated an acceptable proxy for the prevalence as observed using the questioning method. The comparison of the two data collection methods was a worthwhile approach, in that it could highlight potential ways to improve both care quality and information systems.

There are many secondary benefits to collecting routine primary care data, but we first need to understand some of the properties of this data. In this paper we describe the method used to assess the PPV and sensitivity of data extracted from Belgian GPs' EPR (diagnoses, drug prescriptions, referrals, and certain parameters), using data collected through an electronic questionnaire as a gold standard. We describe the results of the ResoPrim phase 2 project, which involved 4 software systems and 43 practices (10,307 patients). This method of assessment could also be applied to other research networks.

There are many secondary benefits to collecting routine primary care data, but we first need to understand some of the properties of this data. In this paper we describe the method used to assess the PPV and sensitivity of data extracted from Belgian GPs' EPR (diagnoses, drug prescriptions, referrals, and certain parameters), using data collected through an electronic questionnaire as a gold standard. We describe the results of the ResoPrim phase 2 project, which involved 4 software systems and 43 practices (10,307 patients). This method of assessment could also be applied to other research networks.

Efficiency and privacy protection are essential when setting up nationwide research networks. This paper investigates the extent to which basic services developed to support the provision of care can be re-used, whilst preserving an acceptable privacy protection level, within a large Belgian primary care research network. The generic sustainable confidentiality management model used to assess the privacy protection level of the selected network architecture is described. A short analysis of the current architecture is provided. Our generic model could also be used in other countries.