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Livestock farm emissions may not only affect respiratory health of farmers but also of neighboring residents. To explore associations between spatial and temporal variation in pollutant emissions from livestock farms and lung function in a general, nonfarming, rural population in the Netherlands. We conducted a cross-sectional study in 2,308 adults (age, 20-72 yr). A pulmonary function test was performed measuring prebronchodilator and post-bronchodilator FEV , FVC, FEV /FVC, and maximum mid-expiratory flow (MMEF). Spatial exposure was assessed as (1) number of farms within 500 m and 1,000 m of the home, (2) distance to the nearest farm, and (3) modeled annual average fine dust emissions from farms within 500 m and 1,000 m of the home address. Temporal exposure was assessed as week-average ambient particulate matter <10 μm in diameter and ammonia (NH ) concentrations before lung function measurements. Data were analyzed with generalized additive models (smoothing). A negative association was found between the number of livestock farms within a 1,000-m buffer from the home address and MMEF, which was more pronounced in participants without atopy. No associations were found with other spatial exposure variables. Week-average particulate matter <10 μm in diameter and NH levels were negatively associated with FEV , FEV /FVC, and MMEF. In a two-pollutant model, only NH remained associated. A 25-μg/m increase in NH was associated with a 2.22% lower FEV (95% confidence interval, -3.69 to -0.74), FEV /FVC of -1.12% (-1.96 to -0.28), and MMEF of -5.67% (-8.80 to -2.55). Spatial and temporal variation in livestock air pollution emissions are associated with lung function deficits in nonfarming residents.

One of the largest Q fever outbreaks ever occurred in the Netherlands from 2007-2010, with 25 fatalities among 4,026 notified cases. Airborne dispersion of Coxiella burnetii was suspected but not studied extensively at the time. We investigated temporal and spatial variation of Coxiella burnetii in ambient air at residential locations in the most affected area in the Netherlands (the South-East), in the year immediately following the outbreak. One-week average ambient particulate matter < 10 μm samples were collected at eight locations from March till September 2011. Presence of Coxiella burnetii DNA was determined by quantitative polymerase chain reaction. Associations with various spatial and temporal characteristics were analyzed by mixed logistic regression. Coxiella burnetii DNA was detected in 56 out of 202 samples (28%). Airborne Coxiella burnetii presence showed a clear seasonal pattern coinciding with goat kidding. The spatial variation was significantly associated with number of goats on the nearest goat farm weighted by the distance to the farm (OR per IQR: 1.89, CI: 1.31-2.76). We conclude that in the year after a large Q fever outbreak, temporal variation of airborne Coxiella burnetii is suggestive to be associated with goat kidding, and spatial variation with distance to and size of goat farms. Aerosol measurements show to have potential for source identification and attribution of an airborne pathogen, which may also be applicable in early stages of an outbreak.

Previous research conducted in 2009 found a significant positive association between pneumonia in humans and living close to goat and poultry farms. However, as this result might have been affected by a large goat-related Q fever epidemic, the aim of the current study was to re-evaluate this association, now that the Q-fever epidemic had ended. In 2014/15, 2,494 adults (aged 20-72 years) living in a livestock-dense area in the Netherlands participated in a medical examination and completed a questionnaire on respiratory health, lifestyle and other items. We retrieved additional information for 2,426/2,494 (97%) participants from electronic medical records (EMR) from general practitioners. The outcome was self-reported, physician-diagnosed pneumonia or pneumonia recorded in the EMR in the previous three years. Livestock license data was used to determine exposure to livestock. We quantified associations between livestock exposures and pneumonia using odds ratios adjusted for participant characteristics and comorbidities (aOR). The three-year cumulative frequency of pneumonia was 186/2,426 (7.7%). Residents within 2,000m of a farm with at least 50 goats had an increased risk of pneumonia, which increased the closer they lived to the farm (2,000m aOR 1.9, 95% CI 1.4-2.6; 500m aOR 4.4, 95% CI 2.0-9.8). We found no significant associations between exposure to other farm animals and pneumonia. However, when conducting sensitivity analyses using pneumonia outcome based on EMR only, we found a weak but statistically significant association with presence of a poultry farm within 1,000m (aOR: 1.7, 95% CI 1.1-2.7). Living close to goat and poultry farms still constitute risk factors for pneumonia. Individuals with pneumonia were not more often seropositive for Coxiella burnetii, indicating that results are not explained by Q fever. We strongly recommend identification of pneumonia causes by the use of molecular diagnostics and investigating the role of non-infectious agents such as particulate matter or endotoxins.

COPD-diagnosis is confirmed by post-bronchodilator (BD) spirometry. However, epidemiological studies often rely on pre-BD spirometry, self-reports, or medical records. This population-based study aims to determine COPD-prevalence based on four different operational definitions and their level of agreement, and to compare associations between COPD-definitions and risk factors. COPD-prevalence in 1,793 adults from the general Dutch population (aged 18-70 years) was assessed based on self-reported data, Electronic Medical Records (EMR), and post-BD spirometry: using the FEV1/FVC below the lower limit of normal (LLN) and GOLD fixed cut-off (FEV1/FVC <0.70). Using spirometry as a reference, sensitivity was calculated for self-reported and EMR-based COPD. Associations between COPD and known risk factors were assessed with logistic regression. Data were collected as part of the cross-sectional VGO study (Livestock Farming and Neighboring Residents' Health Study). The highest prevalence was found based on spirometry (GOLD: 10.9%, LLN: 5.9%), followed by self-report (4.6%) and EMR (2.9%). Self-reported or EMR-based COPD identified less than 30% of all COPD-cases based on spirometry. The direction of association between known risk factors and COPD was similar across the four definitions, however, magnitude and significance varied. Especially indicators of allergy were more strongly associated with self-reported COPD compared to the other definitions. COPD-prevalence varied depending on the used definition. A substantial number of subjects with spirometry-based COPD cannot be identified with questionnaires or medical records which can cause underestimation of COPD-prevalence. The influence of the different COPD-definitions on associations with known risk factors was limited.

Background The home address is a common spatial proxy for exposure assessment in epidemiological studies but mobility may introduce exposure misclassification. Mobility can be assessed using self-reports or objectively measured using GPS logging but self-reports may not assess the same information as measured mobility. We aimed to assess mobility patterns of a rural population in the Netherlands using GPS measurements and self-reports and to compare GPS measured to self-reported data, and to evaluate correlates of differences in mobility patterns. Method In total 870 participants filled in a questionnaire regarding their transport modes and carried a GPS-logger for 7 consecutive days. Transport modes were assigned to GPS-tracks based on speed patterns. Correlates of measured mobility data were evaluated using multiple linear regression. We calculated walking, biking and motorised transport durations based on GPS and self-reported data and compared outcomes. We used Cohen’s kappa analyses to compare categorised self-reported and GPS measured data for time spent outdoors. Results Self-reported time spent walking and biking was strongly overestimated when compared to GPS measurements. Participants estimated their time spent in motorised transport accurately. Several variables were associated with differences in mobility patterns, we found for instance that obese people (BMI > 30 kg/m 2 ) spent less time in non-motorised transport (GMR 0.69–0.74) and people with COPD tended to travel longer distances from home in motorised transport (GMR 1.42–1.51). Conclusions If time spent walking outdoors and biking is relevant for the exposure to environmental factors, then relying on the home address as a proxy for exposure location may introduce misclassification. In addition, this misclassification is potentially differential, and specific groups of people will show stronger misclassification of exposure than others. Performing GPS measurements and identifying explanatory factors of mobility patterns may assist in regression calibration of self-reports in other studies.

Background Prior to the 2007–2010 Q fever epidemic in the Netherlands, the seroprevalence of antibodies against Coxiella burnetii in the general population was 1.5%, which is low compared to other countries. We aimed to determine the seroprevalence after the Q fever epidemic among people living in the affected area, compare the seroprevalence with the incidence of Q fever notifications during the 2007–2010 Q fever epidemic, and to identify farm exposures associated with having antibodies against C. burnetii . Methods During the period March 2014–February 2015, residents aged 18–70 years from two provinces were invited by general practitioners to complete a questionnaire on their symptoms and personal characteristics and to submit a blood sample. We used the mandatory provincial database of livestock licences to calculate distance to farms/farm animals for each participant. To compare ELISA-positive participants for C. burnetii antibodies with those who were negative, we calculated prevalence ratios (PR) using binominal regression. We compared the C. burnetii seroprevalence in the period March 2014–February 2015 with the incidence of Q fever notifications during the 2007–2010 Q fever epidemic at municipal level by calculating the Spearman correlation coefficient. Results Of the 2296 participants (response rate: 34%), 6.1% ( n  = 139, 95% CI 5.1–7.1%) had C. burnetii antibodies (range in municipalities: 1.7–14.1%). C. burnetii seroprevalence was higher in individuals living within 1000 m of goat farms (PR 3.0; 95% CI 1.4–6.4) or within 1000 m of > 50 goats (PR 1.9; 95% CI 1.2–3.0). Seroprevalence increased with decreasing distance to the closest goat farm that was infected during the epidemic years (< 500 m, PR 9.5, 95% CI 2.8–32; 500–1000 m, PR 4.5, 95% CI 2.6–7.7; 1000–1500 m, PR 2.2, 95% CI 1.1–4.3, 1500–2000 m, PR 1.2, 95% CI 0.6–2.5; > 2000 reference group). There was no significant correlation between C. burnetii seroprevalence and Q fever incidence during the 2007–2010 epidemic ( r s  = 0.42, p  = 0.156). Conclusions Results showed a remarkable spatial variation in C. burnetii seroprevalence in a relatively small livestock dense area. It confirms previous evidence that the Q fever epidemic was primarily the result of airborne C. burnetii transmission from Q fever affected goat farms.

ObjectivesExposure to farm environments during childhood and adult life seems to reduce the risk of atopic sensitisation. Most studies have been conducted among farmers, but people living in rural areas may have similar protective effects for atopy. This study aims to investigate the association between residential proximity to livestock farms and atopy among non-farming adults living in a rural area in the Netherlands.MethodsWe conducted a cross-sectional study among 2443 adults (20–72 years). Atopy was defined as specific IgE to common allergens and/or total IgE ≥100 IU/mL. Residential proximity to livestock farms was assessed as 1) distance to the nearest pig, poultry, cattle or any farm, 2) number of farms within 500 m and 1000 m, and 3) modelled annual average fine dust emissions from farms within 500 m and 1000 m. Data were analysed with multiple logistic regression and generalised additive models.ResultsThe prevalence of atopy was 29.8%. Subjects living at short distances from farms (<327 m, first tertile) had a lower odds for atopy compared with subjects living further away (>527 m, third tertile) (OR 0.79, 95% CI 0.63 to 0.98). Significant associations in the same direction were found with distance to the nearest pig or cattle farm. The associations between atopy and livestock farm exposure were somewhat stronger in subjects who grew up on a farm.ConclusionsLiving in close proximity to livestock farms seems to protect against atopy. This study provides evidence that protective effects of early-life and adult farm exposures may extend beyond farming populations.

Background Recent serological studies indicate that hepatitis E virus (HEV) is endemic in industrialised countries. The increasing trend in the number of autochthonous cases of HEV genotype 3 in Western European countries, stresses the importance to get insight in the exact routes of exposure. Pigs are the main animal reservoir, and zoonotic food-borne transmission of HEV is proven. However, infected pigs can excrete large amounts of virus via their faeces enabling environmental transmission of HEV to humans. This might pose a risk for of neighbouring residents of livestock farming. Methods Within a large study on the health of people living in the vicinity of livestock farming we performed a cross-sectional population-based serological survey among 2,494 non-farming adults from the general population in a livestock-dense area in the south of the Netherlands. Participants completed risk factor questionnaires and blood samples of 2,422 subjects (median age 58 years, range 20–72) were tested for anti-HEV IgG using an enzyme immune assay (Wantai). The aim of this study was to determine the HEV seroprevalence and to assess whether seropositivity in adults was associated with living in the vicinity of pig farms. Results The average seroprevalence of HEV was 28.7% (95% CI: 26.9–30.5). Determinants associated with an increased risk for HEV seropositivity were male gender and low level of education. There was a clear trend of increasing prevalence with increasing age (Chi-square test for linear trend, X 2  = 83.1; p  < 0.001). A high number of pigs within 1,000 m of the residential address was not a risk factor for seropositivity. Conclusions This study confirmed the high HEV seroprevalence (29%) in the general population of the Netherlands, but presence of antibodies was not associated with residential proximity to pig farms. The prevalence increased with age from 10% in adolescents to 33% among those aged 50 and above, supporting the assumption of a cumulative lifetime exposure to HEV in the Netherlands as well as a higher infection pressure in the past. Our findings cannot refute the assumption that transmission is primarily food-borne.

[...]patients with COPD reported more symptoms in areas with high farm density (20, 22). [...]only a limited number of studies measured pulmonary function in neighboring residents, and most studies focused on spatial variation (e.g., distance to the nearest farm). Because of low concentrations of H2S and strong correlation with other pollutants, Guidry and coworkers (8) argued that health effects can probably not be attributed to H2S alone, but to a mixture of which H2S is part of. Because individuals were subjected to pulmonary function tests on one occasion, but over a study period of a year (between March 2014 and February 2015), we adjusted for week-average air pollution concentrations before each individual's lung function test (39). Because NH3 is mostly locally generated (40, 41), this suggests that the temporal associations with lung function were mostly driven by locally generated pollutants, represented by NH3. [...]air pollutant emissions from livestock farms are associated with a reduced lung function level in nonfarming residents of a rural area in the Netherlands.

One of the largest Q fever outbreaks ever occurred in the Netherlands from 2007-2010, with 25 fatalities among 4,026 notified cases. Airborne dispersion of Coxiella burnetii was suspected but not studied extensively at the time. We investigated temporal and spatial variation of Coxiella burnetii in ambient air at residential locations in the most affected area in the Netherlands (the South-East), in the year immediately following the outbreak. One-week average ambient particulate matter < 10 Mm samples were collected at eight locations from March till September 2011. Presence of Coxiella burnetii DNA was determined by quantitative polymerase chain reaction. Associations with various spatial and temporal characteristics were analyzed by mixed logistic regression. Coxiella burnetii DNA was detected in 56 out of 202 samples (28%). Airborne Coxiella burnetii presence showed a clear seasonal pattern coinciding with goat kidding. The spatial variation was significantly associated with number of goats on the nearest goat farm weighted by the distance to the farm (OR per IQR: 1.89, CI: 1.31-2.76). We conclude that in the year after a large Q fever outbreak, temporal variation of airborne Coxiella burnetii is suggestive to be associated with goat kidding, and spatial variation with distance to and size of goat farms. Aerosol measurements show to have potential for source identification and attribution of an airborne pathogen, which may also be applicable in early stages of an outbreak.