Concerns about public health risks of intensive animal production in the Netherlands continue to rise, in particular related to outbreaks of infectious diseases. The aim was to investigate associations between the presence of farm animals around the home address and Q fever and pneumonia.Electronic medical record data for the year 2009 of all patients of 27 general practitioners (GPs) in a region with a high density of animal farms were used. Density of farm animals around the home address was calculated using a Geographic Information System. During the study period, a large Q fever outbreak occurred in this region. Associations between farm exposure variables and pneumonia or ‘other infectious disease’, the diagnosis code used by GPs for registration of Q fever, were analyzed in 22,406 children (0–17 y) and 70,142 adults (18–70 y), and adjusted for age and sex. In adults, clear exposure-response relationships between the number of goats within 5 km of the home address and pneumonia and ‘other infectious disease’ were observed. The association with ‘other infectious disease’ was particularly strong, with an OR [95%CI] of 12.03 [8.79–16.46] for the fourth quartile (>17,190 goats) compared with the first quartile (<2,251 goats). The presence of poultry within 1 km was associated with an increased incidence of pneumonia among adults (OR [95%CI] 1.25 [1.06–1.47]).A high density of goats in a densely populated region was associated with human Q fever. The use of GP records combined with individual exposure estimates using a Geographic Information System is a powerful approach to assess environmental health risks.

In conclusion, indicators of air pollution from livestock farms were inversely associated with respiratory morbidity among neighbouring residents.

The association of body mass index (BMI) with mortality in hemodialysis patients has been found to be reversed in comparison with the general population. This study examined the association of BMI with mortality in the hemodialysis population and the general population when age and time of follow-up were made strictly comparable. Hemodialysis patients who were aged 50 to 75 yr at the start of follow-up were selected from the Netherlands Cooperative Study on the Adequacy of Dialysis-2 (NECOSAD), a prospective cohort study in incident dialysis patients in the Netherlands (n ‫؍‬ 722; age 66 ؎ 7 yr; BMI 25.3 ؎ 4.5 kg/m 2 ), and compared with adults who were aged 50 to 75 yr and included in the Hoorn Study, a population-based prospective cohort study in the same country (n ‫؍‬ 2436; age 62 ؎ 7 yr; BMI 26.5 ؎ 3.6 kg/m 2 ). In both populations, 2-and 7-yr standardized mortality rates were calculated for categories of BMI. Adjusted hazard ratios (HR) of BMI categories were calculated with a BMI of 22.5 to 25 kg/m 2 as the reference category within each population. In 7 yr of follow-up, standardized mortality rates were approximately 10 times higher in the hemodialysis population than those in the general population. Compared with the reference category, the HR of BMI <18.5 kg/m 2 was 2.0 (95% confidence interval [CI]1.2 to 3.4) in the hemodialysis population and 2.3 (95% CI 0.7 to 7.5) in the general population. Obesity (BMI >30 kg/m 2 ) was associated with a HR of 1.2 (95% CI 0.8 to 1.7) in the hemodialysis population and 1.3 (95% CI 0.9 to 2.0) in the general population. In conclusion, a hemodialysis population and a general population with comparable age and equal duration of follow-up showed similar mortality risk patterns associated with BMI. This suggests that there is no reverse epidemiology of BMI and mortality in hemodialysis patients. The clinical implication of this study is that to improve survival in the hemodialysis population, more attention should be paid to patients who are underweight instead of overweight.

No abstract

Type III hyperlipoproteinemia (HLP) is mainly found in homozygous apolipoprotein (APO) E2 (R158C) carriers. Genetic factors contributing to the expression of type III HLP were investigated in 113 hyper-and 52 normolipidemic E2/2 subjects, by testing for polymorphisms in APOC3, APOA5, HL (hepatic lipase) and LPL (lipoprotein lipase) genes. In addition, 188 normolipidemic Dutch control panels (NDCP) and 141 hypertriglyceridemic (HTG) patients were genotyped as well. No associations were found for four HL gene polymorphisms and two LPL gene polymorphisms and type III HLP. The frequency of the rare allele of APOC3 3238 G4C and APOA5 À1131 T4C (in linkage disequilibrium) was significantly higher in type III HLP patients when compared with normolipidemic E2/2 subjects, 15.6 vs 6.9% and 15.1 vs 5.8%, respectively, (Po0.05). Furthermore, the frequencies of the APOA5 c.56 G4C polymorphism and LPL c.27 G4A mutation were higher in type III HLP patients, though not significant. Some 58% of the type III HLP patients carried either the APOA5 À1131 T4C, c.56 G4C and/or LPL c.27 G4A mutation as compared to 27% of the normolipidemic APOE2/2 subjects (odds ratio 3.7, 95% confidence interval ¼ 1.8 -7.5, Po0.0001). The HTG patients showed similar allele frequencies of the APOA5, APOC3 and LPL polymorphisms, whereas the NDCP showed similar allele frequencies as the normolipidemic APOE2/2. Patients with the APOC3 3238 G4C/APOA5 À1131 T4C polymorphism showed a more severe hyperlipidemia than patients without this polymorphism. Polymorphisms in lipolysis genes associate with the expression and severity of type III HLP in APOE2/2.