Increased risk of pneumonia in residents living near poultry farms: does the upper respiratory tract microbiota play a role?

Host and environmental factors shape upper airway microbiota and respiratory health across the human lifespan

Our understanding of the normal variation in the upper respiratory tract (URT) microbiota across the human lifespan and how these relate to host, environment, and health is limited. We studied the microbiota of 3,104 saliva (<10 year-olds)/oropharynx (≥10 year-olds) and 2,485 nasopharynx samples of 3,160 Dutch individuals 0-87 years of age, participating in a cross-sectional population-wide study (PIENTER-3) using 16S-rRNA sequencing. The microbiota composition was strongly related to age, especially in the nasopharynx, with maturation occurring throughout childhood and adolescence. Clear niche- and age-specific associations were found between the microbiota composition and host/environmental factors and health outcomes. Among others, social interaction, sex, and season were associated with the nasopharyngeal microbial community. By contrast, the oral microbiota was more related to antibiotics, tobacco, and alcohol use. We present an atlas of the URT microbiota across the lifespan in association with environment and health, establishing a baseline for future research.

Zoonotic bacteria in the vicinity of animal farms as a factor disturbing the human microbiome: a review

This review is aimed at summarizing the current state of knowledge about the relationship between environmental exposure to the bioaerosol emitted by intensive livestock farming and changes in the microbiome of people living in livestock farm vicinity. The PubMed, Scopus and Web of Science databases were searched by crossing keywords from the following 3 groups: a) "livestock," "animal farms," "animal breeding"; b) "microbiome," "resistome"; c) "livestock vicinity," "farm vicinity," "neighborhoods and health" in 2010-2022. Literature screening did not reveal any paper related to the full microbiome composition in the population studied. In the study, the authors included 7 papers (5 from the Netherlands, 1 from the USA, and 1 from China). The studies confirmed the carriage of Staphylococcus aureus, including methicillin-resistant S. aureus (MRSA), livestockassociated MRSA (LA-MRSA MC398) and multidrug-resistant S. aureus (MDRSA) in the nasal microbiome of adults and children living within 500-2000 m from a livestock farm. Clostridium difficile, including LA-ribotype RT078 carriage, was detected in the intestinal microbiome of adults living within 500-1000 m. Extended-spectrum β-lactamase (ESBL) producing Enterobacteriaceae were confirmed in the intestinal microbiome of adults living within 500-6200 m. Knowledge on the composition of the microflora of people living in livestock farm vicinity is insufficient to conclude about changes in the microbiome caused by the environmental emission of bioaerosol. The carriage prevalence of the LA-bacteria, including both strains with antimicrobial resistance and antimicrobial resistance genes, confirms the presence of zoonotic bacteria in the human microflora in populations without occupational contact with animals. It cannot be ruled out that zoonotic bacteria, as a component of the microbiome, have a negative impact on people's health. Int J Occup Med Environ Health. 2024;37(2):138-52.

Dietary strategies can increase cloacal endotoxin levels and modulate the resident microbiota in broiler chickens

Endotoxins released from poultry feces have been associated with impaired human health. Because endotoxins are released from gram-negative intestinal bacteria, it was hypothesized that dietary strategies may influence endotoxin excretion via modulation of gut microbiota. We therefore tested dietary strategies that could potentially reduce cloacal endotoxin levels in broiler chickens. One-day-old male Ross 308 (N = 1,344) broilers were housed in 48 pens (N = 8 pens/treatment, 28 chickens per pen) and fed 1 of 6 diets for 35 days (d) in a 3-phase feeding program: a basic diet (CON) that served as the reference diet, or basic diet supplemented with butyrate (BUT), inulin (INU), medium-chain fatty acids (MCFA) or Original XPC™LS (XPC), or a high-fiber-low-protein (HF-LP) diet. A significant (P < 0.05) increase in cloacal endotoxin concentration at d 35 was observed in BUT as compared to CON. Analysis of cloacal microbiota showed a trend (P < 0.07) for a higher gram-negative/gram-positive ratio and for a higher relative abundance of gram-negative bacteria at d 35 (P ≤ 0.08) in BUT and HF-LP as compared to CON. A significant (P < 0.05) increase in average daily gain (ADG) and improved feed conversion ratio (P < 0.05) were observed in MCFA during the grower phase (d 14-28), and a significant (P < 0.05) increase in average daily feed intake (ADFI) was observed in MCFA during d 0 to 28. Broilers fed HF-LP had a significantly (P < 0.05) higher FCR and lower ADG throughout the rearing period. No treatment effects were found on footpad dermatitis, but BUT had worst hock burn scores at d 35 (P < 0.01) and MCFA had worst cleanliness scores at d 21 but not at d 35 (treatment*age P < 0.05), while INU had better cleanliness as compared to CON at d 35 (P < 0.05). In conclusion, especially BUT and HF-LP were able to modulate resident microbiota and BUT also increased cloacal endotoxin levels, which was opposite to our hypothesis. The present study indicates that cloacal endotoxin release can be affected by the diet but further study is needed to find dietary treatments that can reduce cloacal endotoxin release.

The upper respiratory tract microbiota of healthy adults is affected by Streptococcus pneumoniae carriage, smoking habits, and contact with children

BACKGROUND

The microbiota of the upper respiratory tract is increasingly recognized as a gatekeeper of respiratory health. Despite this, the microbiota of healthy adults remains understudied. To address this gap, we investigated the composition of the nasopharyngeal and oropharyngeal microbiota of healthy adults, focusing on the effect of Streptococcus pneumoniae carriage, smoking habits, and contact with children.

RESULTS

Differential abundance analysis indicated that the microbiota of the oropharynx was significantly different from that of the nasopharynx (P < 0.001) and highly discriminated by a balance between the classes Negativicutes and Bacilli (AUC of 0.979). Moreover, the oropharynx was associated with a more homogeneous microbiota across individuals, with just two vs. five clusters identified in the nasopharynx. We observed a shift in the nasopharyngeal microbiota of carriers vs. noncarriers with an increased relative abundance of Streptococcus, which summed up to 30% vs. 10% in noncarriers and was not mirrored in the oropharynx. The oropharyngeal microbiota of smokers had a lower diversity than the microbiota of nonsmokers, while no differences were observed in the nasopharyngeal microbiota. In particular, the microbiota of smokers, compared with nonsmokers, was enriched (on average 16-fold) in potential pathogenic taxa involved in periodontal diseases of the genera Bacillus and Burkholderia previously identified in metagenomic studies of cigarettes. The microbiota of adults with contact with children resembled the microbiota of children. Specifically, the nasopharyngeal microbiota of these adults had, on average, an eightfold increase in relative abundance in Streptococcus sp., Moraxella catarrhalis, and Haemophilus influenzae, pathobionts known to colonize the children's upper respiratory tract, and a fourfold decrease in Staphylococcus aureus and Staphylococcus lugdunensis.

CONCLUSIONS

Our study showed that, in adults, the presence of S. pneumoniae in the nasopharynx is associated with a shift in the microbiota and dominance of the Streptococcus genus. Furthermore, we observed that smoking habits are associated with an increase in bacterial genera commonly linked to periodontal diseases. Interestingly, our research also revealed that adults who have regular contact with children have a microbiota enriched in pathobionts frequently carried by children. These findings collectively contribute to a deeper understanding of how various factors influence the upper respiratory tract microbiota in adults. Video Abstract.

Air pollution-associated shifts in the human airway microbiome and exposure-associated molecular events

Publications addressing air pollution-induced human respiratory microbiome shifts are reviewed in this article. The healthy respiratory microbiota is characterized by a low density of bacteria, fungi and viruses with high diversity, and usually consists of Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria, viruses and fungi. The air's microbiome is highly dependent on air pollution levels and is directly reflected within the human respiratory microbiome. In addition, pollutants indirectly modify the local environment in human respiratory organs by reducing antioxidant capacity, misbalancing proteolysis and modulating inflammation, all of which regulate local microbiomes. Improving air quality leads to more diverse and healthy microbiomes of the local air and, subsequently, residents' airways.

The possible role of particulate matter on the respiratory microbiome: evidence from in vivo to clinical studies

Environmental pollution, which contains ambient particulate matter, has been shown to have a significant impact on human health and longevity over the past 30 years. Recent studies clearly showed that exposure to particulate matter directly caused adverse effects on the respiratory system via various mechanisms including the accumulation of free radical peroxidation, the imbalance of intercellular calcium regulation, and inflammation, resulting in respiratory diseases. Recent evidence showed the importance of the role of the respiratory microbiome on lung immunity and lung development. In addition, previous studies have confirmed that several chronic respiratory diseases were associated with an alteration in the respiratory microbiome. However, there is still a lack of knowledge with regard to the changes in the respiratory microbiome with regard to the role of particulate matter exposure in respiratory diseases. Therefore, this review aims to summarize and discuss all the in vivo to clinical evidence which investigated the effect of particulate matter exposure on the respiratory microbiome and respiratory diseases. Any contradictory findings are incorporated and discussed. A summary of all these pieces of evidence may offer an insight into a therapeutic approach for the respiratory diseases related to particulate matter exposure and respiratory microbiome.

Intensive poultry farming: A review of the impact on the environment and human health

Poultry farming is one of the most efficient animal husbandry methods and it provides nutritional security to a significant number of the world population. Using modern intensive farming techniques, global production has reached 133.4 mil. t in 2020, with a steady growth each year. Such intensive growth methods however lead to a significant environmental footprint. Waste materials such as poultry litter and manure can pose a serious threat to environmental and human health, and need to be managed properly. Poultry production and waste by-products are linked to NH₃, N₂O and CH₄ emissions, and have an impact on global greenhouse gas emissions, as well as animal and human health. Litter and manure can contain pesticide residues, microorganisms, pathogens, pharmaceuticals (antibiotics), hormones, metals, macronutrients (at improper ratios) and other pollutants which can lead to air, soil and water contamination as well as formation of antimicrobial/multidrug resistant strains of pathogens. Dust emitted from intensive poultry production operations contains feather and skin fragments, faeces, feed particles, microorganisms and other pollutants, which can adversely impact poultry health as well as the health of farm workers and nearby inhabitants. Fastidious odours are another problem that can have an adverse impact on health and quality of life of workers and surrounding population. This study discusses the current knowledge on the impact of intensive poultry farming on environmental and human health, as well as taking a look at solutions for a sustainable future.

Air pollution from livestock farms and the oropharyngeal microbiome of COPD patients and controls

Air pollution from livestock farms is known to affect respiratory health of patients with chronic obstructive pulmonary disease (COPD). The mechanisms behind this relationship, however, remain poorly understood. We hypothesise that air pollutants could influence respiratory health through modulation of the airway microbiome. Therefore, we studied associations between air pollution exposure and the oropharyngeal microbiota (OPM) composition of COPD patients and controls in a livestock-dense area. Oropharyngeal swabs were collected from 99 community-based (mostly mild) COPD cases and 184 controls (baseline), and after 6 and 12 weeks. Participants were non-smokers or former smokers. Annual average livestock-related outdoor air pollution at the home address was predicted using dispersion modelling. OPM composition was analysed using 16S rRNA-based sequencing in all baseline samples and 6-week and 12-week repeated samples of 20 randomly selected subjects (n = 323 samples). A random selection of negative control swabs, taken every sampling day, were also included in the downstream analysis. Both farm-emitted endotoxin and PM₁₀ levels were associated with increased OPM richness in COPD patients (p < 0.05) but not in controls. COPD case-control status was not associated with community structure, while correcting for known confounders (multivariate PERMANOVA p > 0.05). However, members of the genus Streptococcus were more abundant in COPD patients (Benjamini-Hochberg adjusted p < 0.01). Moderate correlation was found between ordinations of 20 subjects analysed at 0, 6, and 12 weeks (Procrustes r = 0.52 to 0.66; p < 0.05; Principal coordinate analysis of Bray-Curtis dissimilarity), indicating that the OPM is relatively stable over a 12 week period and that a single sample sufficiently represents the OPM. Air pollution from livestock farms is associated with OPM richness of COPD patients, suggesting that the OPM of COPD patients is susceptible to alterations induced by exposure to air pollutants.

Mechanistic Insights into the Impact of Air Pollution on Pneumococcal Pathogenesis and Transmission

Streptococcus pneumoniae (the pneumococcus) is the leading cause of pneumonia and bacterial meningitis. A number of recent studies indicate an association between the incidence of pneumococcal disease and exposure to air pollution. Although the epidemiological evidence is substantial, the underlying mechanisms by which the various components of air pollution (particulate matter and gases such as NO2 and SO2) can increase susceptibility to pneumococcal infection are less well understood. In this review, we summarize the various effects air pollution components have on pneumococcal pathogenesis and transmission; exposure to air pollution can enhance host susceptibility to pneumococcal colonization by impairing the mucociliary activity of the airway mucosa, reducing the function and production of key antimicrobial peptides, and upregulating an important pneumococcal adherence factor on respiratory epithelial cells. Air pollutant exposure can also impair the phagocytic killing ability of macrophages, permitting increased replication of S. pneumoniae. In addition, particulate matter has been shown to activate various extra- and intracellular receptors of airway epithelial cells, which may lead to increased proinflammatory cytokine production. This increases recruitment of innate immune cells, including macrophages and neutrophils. The inflammatory response that ensues may result in significant tissue damage, thereby increasing susceptibility to invasive disease, because it allows S. pneumoniae access to the underlying tissues and blood. This review provides an in-depth understanding of the interaction between air pollution and the pneumococcus, which has the potential to aid the development of novel treatments or alternative strategies to prevent disease, especially in areas with high concentrations of air pollution.

Establishing farm dust as a useful viral metagenomic surveillance matrix

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance.

Air path of antimicrobial resistance related genes from layer farms: Emission inventory, atmospheric transport, and human exposure

Animal husbandry is a significant contributor to increased environmental antimicrobial resistance (AMR), but little is known regarding the dissemination of AMR from animal farms via airborne transmission. Here, we connected the air path of AMR related genes tailored to layer poultry farms from source of escape to end of sedimentation. The emission inventories of 8 AMR related genes from all 163-layer poultry farms around Beijing city were quantified. We developed the atmospheric transport model with a gene degradation module to estimate the spatiotemporal distribution of airborne AMR, and also assessed their corresponding regional exposure and sedimentation. Total emissions of 16 S rDNA and AMR related genes from layer houses ranged from 10¹⁵ to 10¹⁶ copies year^-1. Those layer-sourced genes contributed 1-14.6% of antimicrobial resistant genes, 4.9% of Staphylococcus spp. and 2.2% of CintI1 to the corresponding annual genetic burden of Beijing's urban air. The average exposure of the Beijing residents to layer-sourced airborne 16 S rDNA was 1.39 × 10⁴ copies year^-1 person^-1, approximately 87% of them would be deposited in the upper respiratory tract. The findings highlight that air medium represents an important dissemination pathway of animal-sourced genes to AMR burden in humans and environment.

Air pollution and endocrine disruptors induce human microbiome imbalances: A systematic review of recent evidence and possible biological mechanisms

A rich body of literature indicates that environmental factors interact with the human microbiome and influence its composition and functions contributing to the pathogenesis of diseases in distal sites of the body. This systematic review examines the scientific evidence on the effect of environmental toxicants, air pollutants and endocrine disruptors (EDCs), on compositional and diversity of human microbiota. Articles from PubMed, Embase, WoS and Google Scholar where included if they focused on human populations or the SHIME® model, and assessed the effects of air pollutants and EDCs on human microbiome. Non-human studies, not written in English and not displaying original research were excluded. The Newcastle-Ottawa Scale was used to assess the quality of individual studies. Results were extracted and presented in tables. 31 studies were selected, including 24 related to air pollutants, 5 related to EDCs, and 2 related to EDC using the SHIME® model. 19 studies focussed on the respiratory system (19), gut (8), skin (2), vaginal (1) and mammary (1) microbiomes. No sufficient number of studies are available to observe a consistent trend for most of the microbiota, except for streptococcus and veillionellales for which 9 out of 10, and 3 out of 4 studies suggest an increase of abundance with exposure to air pollution. A limitation of the evidence reviewed is the scarcity of existing studies assessing microbiomes from individual systems. Growing evidence suggests that exposure to environmental contaminants could change the diversity and abundance of resident microbiota, e.g. in the upper and lower respiratory, gastrointestinal, and female reproductive system. Microbial dysbiosis might lead to colonization of pathogens and outgrowth of pathobionts facilitating infectious diseases. It also might prime metabolic dysfunctions disrupting the production of beneficial metabolites. Further studies should elucidate the role of environmental pollutants in the development of dysbiosis and dysregulation of microbiota-related immunological processes.

Residential proximity to livestock animals and mortality from respiratory diseases in The Netherlands: A prospective census-based cohort study

BACKGROUND

There is increasing evidence of associations between residential proximity to livestock farms and respiratory morbidity, but less is known about potential effects on respiratory mortality among residents.

OBJECTIVES

We aimed to assess potential associations between respiratory mortality and residential proximity to (intensive) livestock farming.

METHODS

In DUELS, a national census-based cohort, we selected all inhabitants from rural and semi-urban areas of the Netherlands, aged ≥30 years and living at the same address for five years up to baseline (2004). We followed these ∼4 million individuals for respiratory mortality (respiratory system diseases, chronic lower respiratory diseases, pneumonia) from 2005 to 2012. We computed the average number of cattle, pigs, chicken, and mink present in 500 m, 1000 m, 1500 m and 2000 m of each individual's residence in the period 1999-2003. Analyses were conducted using Cox proportional hazards regression, adjusting for potential confounders at individual and neighbourhood level.

RESULTS

We found evidence that living up to 2000 m of pig farms was associated with respiratory mortality, namely from chronic lower respiratory diseases, with Hazard Ratios ranging from 1.06 (1.02, 1.10) in people living close to low numbers (<median number of animals) of pigs in 1000 m and 1.18 (1.13, 1.24) in those living near high numbers (≥median) of pigs in 2000 m. We also found indications of higher pneumonia mortality in people living near mink farms.

CONCLUSION

Our results are in line with previous findings of adverse respiratory effects in people living near livestock farms. Little is known about the physical, chemical, and biological exposures leading to respiratory morbidity and mortality warranting further explorations of air contaminants in the vicinity of livestock farms.

The air we breathe: understanding the impact of the environment on pneumonia

An increased risk of community-acquired pneumonia has been shown in residents of rural livestock farming areas in the Netherlands and United States, probably due to air pollution exposure or zoonotic infections. Spatial epidemiological analyses have particularly implicated poultry and goat farms in the increased risk-an observation that warrants further research. Studying the viral or bacterial etiology of community-acquired pneumonia using traditional microbiological methods or metagenomic sequencing could help to fathom to what extent environmental factors and causative pathogens contribute to spatial differences in the incidence of severe acute respiratory infections.

Identified micro-organisms in hospitalized community-acquired pneumonia patients living near goat and poultry farms

BACKGROUND

In the Netherlands, an increased risk of community-acquired pneumonia (CAP) has been reported for adults living near goat and poultry farms. Previous results of respiratory microbiome studies in hospitalized CAP patients near poultry farms suggested a higher relative abundance of Streptococcus pneumoniae. This retrospective study, using routine laboratory data from hospitalized CAP patients, aims to explore possible aetiologic micro-organisms of CAP in relation to livestock exposure.

METHODS

Patient characteristics and PCR and urinary antigen test results were retrieved retrospectively from electronic medical records of CAP patients admitted to the Jeroen Bosch Hospital or Gelre Hospital in the Netherlands during 2016-2017. Distances between the patients' home address and the nearest poultry and goat farm were calculated. Differences in laboratory test results between CAP patients with and without goat or poultry farms within 2 km of their home address were analyzed using Fisher's exact test.

RESULTS

In total, 2230 CAP episodes with diagnostic results were included. In only 25% of the CAP episodes, a micro-organism was detected. A positive urinary antigen test for S. pneumoniae was found more often in patients living within two kilometers of goat (15.2% vs. 11.3%) and poultry farms (14.4% vs. 11.3%), however these differences were not statistically significant (p = 0.1047 and p = 0.1376).

CONCLUSION

Our retrospective analysis did not show statistically significant differences in the identified micro-organisms in hospitalized CAP patients related to livestock farming. The study was hampered by limited statistical power and limited laboratory results. Therefore, the potential increased CAP risk around goat and poultry farms will be further explored in a prospective study among CAP patients in primary care.

Use of Antibiotics among Residents Living Close to Poultry or Goat Farms: A Nationwide Analysis in The Netherlands

Prior regional studies found a high risk of pneumonia for people living close to poultry and goat farms. This epidemiological study in the Netherlands used nationwide antibiotic prescription data as a proxy for pneumonia incidence to investigate whether residents of areas with poultry and goat farms use relatively more antibiotics compared to areas without such farms. We used prescription data on antibiotics most commonly prescribed to treat pneumonia in adults and livestock farming data, both with nationwide coverage. Antibiotic use was expressed as defined daily doses per (4-digit Postal Code (PC4) area)-(age group)-(gender)-(month) combination for the year 2015. We assessed the associations between antibiotic use and farm exposure using negative binomial regression. The amoxicillin, doxycycline, and co-amoxiclav use was significantly higher (5-10% difference in use) in PC4 areas with poultry farms present compared to areas without, even after adjusting for age, gender, smoking, socio-economic status, and goat farm presence. The adjusted models showed no associations between antibiotic use and goat farm presence. The variables included in this study could only partly explain the observed regional differences in antibiotic use. This was an ecological study that precludes inference about causal relations. Further research using individual-level data is recommended.

Systematic review of approaches to use of neighborhood-level risk factors with clinical data to predict clinical risk and recommend interventions

BACKGROUND

Despite a large body of literature investigating how the environment influences health outcomes, most published work to date includes only a limited subset of the rich clinical and environmental data that is available and does not address how these data might best be used to predict clinical risk or expected impact of clinical interventions.

OBJECTIVE

Identify existing approaches to inclusion of a broad set of neighborhood-level risk factors with clinical data to predict clinical risk and recommend interventions.

METHODS

A systematic review of scientific literature published and indexed in PubMed, Web of Science, Association of Computing Machinery (ACM) and SCOPUS from 2010 through October 2020 was performed. To be included, articles had to include search terms related to Electronic Health Record (EHR) data Neighborhood-Level Risk Factors (NLRFs), and Machine Learning (ML) Methods. Citations of relevant articles were also reviewed for additional articles for inclusion. Articles were reviewed and coded by two independent reviewers to capture key information including data sources, linkage of EHR to NRLFs, methods, and results. Articles were assessed for quality using a modified Quality Assessment Tool for Systematic Reviews of Observational Studies (QATSO).

RESULTS

A total of 334 articles were identified for abstract review. 36 articles were identified for full review with 19 articles included in the final analysis. All but two of the articles included socio-demographic data derived from the U.S. Census and we found great variability in sources of NLRFs beyond the Census. The majority or the articles (14 of 19) included broader clinical (e.g. medications, labs and co-morbidities) and demographic information about the individual from the EHR in addition to the clinical outcome variable. Half of the articles (10) had a stated goal to predict the outcome(s) of interest. While results of the studies reinforced the correlative association of NLRFs to clinical outcomes, only one article found that adding NLRFs into a model with other data added predictive power with the remainder concluding either that NLRFs were of mixed value depending on the model and outcome or that NLRFs added no predictive power over other data in the model. Only one article scored high on the quality assessment with 13 scoring moderate and 4 scoring low.

CONCLUSIONS

In spite of growing interest in combining NLRFs with EHR data for clinical prediction, we found limited evidence that NLRFs improve predictive power in clinical risk models. We found these data and methods are being used in four ways. First, early approaches to include broad NLRFs to predict clinical risk primarily focused on dimension reduction for feature selection or as a data preparation step to input into regression analysis. Second, more recent work incorporates NLRFs into more advanced predictive models, such as Neural Networks, Random Forest, and Penalized Lasso to predict clinical outcomes or predict value of interventions. Third, studies that test how inclusion of NLRFs predict clinical risk have shown mixed results regarding the value of these data over EHR or claims data alone and this review surfaced evidence of potential quality challenges and biases inherent to this approach. Finally, NLRFs were used with unsupervised learning to identify underlying patterns in patient populations to recommend targeted interventions. Further access to computable, high quality data is needed along with careful study design, including sub-group analysis, to better determine how these data and methods can be used to support decision making in a clinical setting.

Ambient air pollution and respiratory bacterial infections, a troubling association: epidemiology, underlying mechanisms, and future challenges

The World Health Organization attributed more than four million premature deaths to ambient air pollution in 2016. Numerous epidemiologic studies demonstrate that acute respiratory tract infections and exacerbations of pre-existing chronic airway diseases can result from exposure to ambient (outdoor) air pollution. In this context, the atmosphere contains both chemical and microbial pollutants (bioaerosols), whose impact on human health remains unclear. Therefore, this review: summarises the findings from recent studies on the association between exposure to air pollutants-especially particulate matter and ozone-and onset or exacerbation of respiratory infections (e.g. pneumonia, cystic fibrosis lung infection, and tuberculosis); discusses the mechanisms underlying the relationship between air pollution and respiratory bacterial infections, which is necessary to define prevention and treatment strategies; demonstrates the relevance of air pollution modelling in investigating and preventing the impact of exposure to air pollutants on human health; and outlines future actions required to improve air quality and reduce morbidity and mortality related to air pollution.

Morbidity Rates in an Area with High Livestock Density: A Registry-Based Study Including Different Groups of Patients with Respiratory Health Problems

There is continuing debate and public health concern regarding the previously confirmed association between high livestock density and human health. The primary aim of the current study is to assess the prevalence of respiratory and other health problems in a livestock dense area in the Netherlands, based on recent longitudinal health data and a large sample. Analyses are expanded with the investigation of different subgroups of patients with respiratory health problems and the inclusion of various chronic and acute health outcomes, as well as prescribed medication. Prevalence of health symptoms and chronic conditions was assessed for the period 2014-2016, based on electronic health records registered in 26 general practices located in areas with intensive livestock farming in the Netherlands ("livestock dense area", n = 117,459 unique residents in total). These were compared with corresponding health data from general practices (n = 22) in different rural regions with a low density of livestock farms or other major environmental exposures ("control area", n = 85,796 unique residents in total). Multilevel regression models showed a significantly higher prevalence of pneumonia in the total sample in the livestock dense area, which was also observed among susceptible subgroups of children, the elderly, and patients with chronic obstructive pulmonary disease (COPD). Lower respiratory tract infections, respiratory symptoms, vertigo, and depression were also more common in the livestock dense area compared to the control area. In general, there were no significant differences in chronic conditions such as asthma, COPD, or lung cancer. Prescription rates for broad-spectrum antibiotics were more common among patients with pneumonia in the livestock dense area. Acute respiratory infections and symptoms, but not chronic conditions, were considerably more common in areas with a high livestock density. Identification of causal pathogens on the basis of serological analyses could further elucidate the underlying mechanisms behind the observed health effects.

Risk of pneumonia among residents living near goat and poultry farms during 2014-2016

In the Netherlands, an association was found between the prevalence of pneumonia and living near goat and poultry farms in 2007-2013. This association then led to regulatory decisions to restrict the building of new goat farms and to reduce emissions of poultry farms. Confirmation of these results, however, is required because the period of previous analyses overlapped a Q-fever epidemic in 2007-2010. To confirm the association, we performed a population-based study during 2014-2016 based on general practitioner (GP) data. Electronic medical records of 90,183 persons were used to analyze the association between pneumonia and the population living in the proximity (within 500-2000 m distance) of goat and poultry farms. Data were analyzed with three types of logistic regression (with and without GP practice as a random intercept and with stratified analyses per GP practice) and a kernel model to discern the influence of different statistical methods on the outcomes. In all regression analyses involving adults, a statistically significant association between pneumonia and residence within 500 meters of goat farms was found (odds ratio [OR] range over all analyses types: 1.33-1.60), with a decreasing OR for increasing distances. In kernel analyses (including all ages), a population-attributable risk between 6.0 and 7.8% was found for a distance of 2000 meters in 2014-2016. The associations were consistent across all years and robust for mutual adjustment for proximity to other animals and for several other sensitivity analyses. However, associations with proximity to poultry farms are not supported by the present study. As the causes of the elevated pneumonia incidence in persons living close to goat farms remain unknown, further research into potential mechanisms is required for adequate prevention.

Insights into Livestock-Related Microbial Concentrations in Air at Residential Level in a Livestock Dense Area

Microbial air pollution from livestock farms has raised concerns regarding public health. Little is known about airborne livestock-related microbial levels in residential areas. We aimed to increase insights into this issue. Air measurements were performed in 2014 and 2015 at 61 residential sites in The Netherlands. Quantitative-PCR was used to assess DNA concentrations of selected bacteria (commensals: Escherichia coli and Staphylococcus spp.; a zoonotic pathogen: Campylobacter jejuni) and antimicrobial resistance (AMR) genes ( tetW, mecA) in airborne dust. Mixed models were used to explore spatial associations (temporal adjusted) with livestock-related characteristics of the surroundings. DNA from commensals and AMR genes was detectable even at sites furthest away from farms (1200 m), albeit at lower levels. Concentrations, distinctly different between sites, were strongly associated with the density of farms in the surroundings especially with poultry and pigs. C. jejuni DNA was less prevalent (42% of samples positive). Presence of C. jejuni was solely associated with poultry (OR: 4.7 (95% CI: 1.7-14), high versus low poultry density). Residential exposure to livestock-related bacteria and AMR genes was demonstrated. Identified associations suggest contribution of livestock farms to microbial air pollution in general and attribution differences between farm types. This supports the plausibility of recent studies showing health effects in relation to residential proximity to farms.

Causal relationship between agricultural production and carbon dioxide emissions in selected emerging economies

Continuous threat posed by climate change caused by carbon dioxide emission has reignited global advocacy to confront its negative ramification with the greatest possible firmness. Global food security and agriculture face major challenges under climate change as a result of the potential negative effect of production and implementation of sectoral action to limit global warming. Overall, agricultural greenhouse emissions continue to rise and the analysis of superior data on emissions from farming, livestock, and fisheries can help countries identify opportunities to contemporaneously reduce emissions and address their food security. This study seeks to contribute to the recent literature by examining the causal relationship between agriculture production and carbon dioxide emissions in selected emerging economies for the period 1971 to 2013. The study, therefore, disaggregated agriculture production into crop production index and livestock production index to explicate the distinct and to find individual variable contribution to carbon dioxide emissions. By using FMOLS and DOLS, empirical results indicate that 1% increase in economic growth, crop production index, and livestock production index will cause a proportional increase in carbon dioxide emission by 17%, 28%, and 28% correspondingly, while 1% increase in energy consumption and population improves the environment of emerging economies. The direction of causality among the variables was, accordingly, examined using PMG estimator. Potentially, for emerging countries to achieve Sustainable Development Goal of ensuring zero hunger for their citizenry requires the need to alter their farming production techniques and also adopt agricultural technology method, which is more environmentally friendly.

Associations between pneumonia and residential distance to livestock farms over a five-year period in a large population-based study

In a recent study of electronic health records (EHR) of general practitioners in a livestock-dense area in The Netherlands in 2009, associations were found between residential distance to poultry farms and the occurrence of community-acquired pneumonia (CAP). In addition, in a recent cross-sectional study in 2494 adults in 2014/2015 an association between CAP and proximity to goat farms was observed. Here, we extended the 2009 EHR analyses across a wider period of time (2009–2013), a wider set of health effects, and a wider set of farm types as potential risk sources. A spatial (transmission) kernel model was used to investigate associations between proximity to farms and CAP diagnosis for the period from 2009 to 2013, obtained from EHR of in total 140,059 GP patients. Also, associations between proximity to farms and upper respiratory infections, inflammatory bowel disease, and (as a control disease) lower back pain were analysed. Farm types included as potential risk sources in these analyses were cattle, (dairy) goats, mink, poultry, sheep, and swine. The previously found association between CAP occurrence and proximity to poultry farms was confirmed across the full 5-year study period. In addition, we found an association between increased risk for pneumonia and proximity to (dairy) goat farms, again consistently across all years from 2009 to 2013. No consistent associations were found for any of the other farm types (cattle, mink, sheep and swine), nor for the other health effects considered. On average, the proximity to poultry farms corresponds to approximately 119 extra patients with CAP each year per 100,000 people in the research area, which accounts for approximately 7.2% extra cases. The population attributable risk percentage of CAP cases in the research area attributable to proximity to goat farms is approximately 5.4% over the years 2009–2013. The most probable explanation for the association of CAP with proximity to poultry farms is thought to be that particulate matter and its components are making people more susceptible to respiratory infections. The causes of the association with proximity to goat farms is still unclear. Although the 2007–2010 Q-fever epidemic in the area probably contributed Q-fever related pneumonia cases to the observed additional cases in 2009 and 2010, it cannot explain the association found in later years 2011–2013.

Pneumonia risk of people living close to goat and poultry farms - Taking GPS derived mobility patterns into account

We previously observed an increased incidence of pneumonia in persons living near goat and poultry farms, using animal presence around the home to define exposure. However, it is unclear to what extent individual mobility and time spent outdoors close to home contributes to this increased risk. Therefore, the aim of the current study was to investigate the role of mobility patterns and time spent outdoors in the vicinity of goat or poultry farms in relation to pneumonia risk. In a rural Dutch cohort, 941 members logged their mobility using GPS trackers for 7 days. Pneumonia was diagnosed in 83 subjects (participants reported that pneumonia had been diagnosed by a medical doctor, or recorded in EMR from general practitioners, 2011-2014). We used logistic regression to evaluate pneumonia-risk by presence of goat farms within 500 and 1000 m around the home and around GPS-tracks (only non-motorised mobility), also we evaluated whether more time spent outdoors increased pneumonia-risks. We observed a clearly increased risk of pneumonia among people living in close proximity to goat farms, ORs increased with closer distances of homes to farms (500 m: 6.2 (95% CI 2.2-16.5) 1000 m: 2.5 (1.4-4.3)) The risk increased for individuals who spent more time outdoors close to home, but only if homes were close to goat farms (within 500 m and often outdoors: 12.7 (3.6-45.4) less often: 2.0 (0.3-9.2), no goat farms and often outdoors: 1.0 (0.6-1.6)). For poultry we found no increased risks. Pneumonia-risks increased when people lived near goat farms, especially when they spent more time outdoors, mobility does not seem to add to these risks.

Bacterial-Host Interactions: Physiology and Pathophysiology of Respiratory Infection

It has long been thought that respiratory infections are the direct result of acquisition of pathogenic viruses or bacteria, followed by their overgrowth, dissemination, and in some instances tissue invasion. In the last decades, it has become apparent that in contrast to this classical view, the majority of microorganisms associated with respiratory infections and inflammation are actually common members of the respiratory ecosystem and only in rare circumstances do they cause disease. This suggests that a complex interplay between host, environment, and properties of colonizing microorganisms together determines disease development and its severity. To understand the pathophysiological processes that underlie respiratory infectious diseases, it is therefore necessary to understand the host-bacterial interactions occurring at mucosal surfaces, along with the microbes inhabiting them, during symbiosis. Current knowledge regarding host-bacterial interactions during asymptomatic colonization will be discussed, including a plausible role for the human microbiome in maintaining a healthy state. With this as a starting point, we will discuss possible disruptive factors contributing to dysbiosis, which is likely to be a key trigger for pathobionts in the development and pathophysiology of respiratory diseases. Finally, from this renewed perspective, we will reflect on current and potential new approaches for treatment in the future.

Spatial Variation of Endotoxin Concentrations Measured in Ambient PM10 in a Livestock-Dense Area: Implementation of a Land-Use Regression Approach

BACKGROUND

Results from studies on residential health effects of livestock farming are inconsistent, potentially due to simple exposure proxies used (e.g., livestock density). Accuracy of these proxies compared with measured exposure concentrations is unknown.

OBJECTIVES

We aimed to assess spatial variation of endotoxin in PM₁₀ (particulate matter ≤10μm) at residential level in a livestock-dense area, compare simple livestock exposure proxies to measured endotoxin concentrations, and evaluate whether land-use regression (LUR) can be used to explain spatial variation of endotoxin.

METHODS

The study area (3,000km²) was located in Netherlands. Ambient PM₁₀ was collected at 61 residential sites representing a variety of surrounding livestock-related characteristics. Three to four 2-wk averaged samples were collected at each site. A local reference site was used for temporal variation adjustment. Samples were analyzed for PM₁₀ mass by weighing and for endotoxin by using the limulus amebocyte lysate assay. Three LUR models were developed, first a model based on general livestock-related GIS predictors only, followed by models that also considered species-specific predictors and farm type-specific predictors.

RESULTS

Variation in concentrations measured between sites was substantial for endotoxin and more limited for PM₁₀ (coefficient of variation: 43%, 8%, respectively); spatial patterns differed considerably. Simple exposure proxies were associated with endotoxin concentrations although spatial variation explained was modest (R²<26%). LUR models using a combination of animal-specific livestock-related characteristics performed markedly better, with up to 64% explained spatial variation.

CONCLUSION

The considerable spatial variation of ambient endotoxin concentrations measured in a livestock-dense area can largely be explained by LUR modeling based on livestock-related characteristics. Application of endotoxin LUR models seems promising for residential exposure estimation within health studies. https://doi.org/10.1289/EHP2252.

Impacts of Intensive Livestock Production on Human Health in Densely Populated Regions

In several regions worldwide, the presence of livestock in close proximity to residential areas raises questions about public health implications. The rapid expansion of large-scale livestock farms, increasingly interwoven with urbanized areas, and its potential impact on neighboring residents' health has hardly been accompanied by any research. The current situation in densely populated livestock farming areas could be regarded as a "natural experiment." Most scientific and public health initiatives have focused on emerging zoonoses and antimicrobial resistance as potential health threats. In this commentary, we emphasize the importance of respiratory health effects of noninfectious air pollutant emissions from livestock farms.

Space-time analysis of pneumonia hospitalisations in the Netherlands

Community acquired pneumonia is a major global public health problem. In the Netherlands there are 40,000-50,000 hospital admissions for pneumonia per year. In the large majority of these hospital admissions the etiologic agent is not determined and a real-time surveillance system is lacking. Localised and temporal increases in hospital admissions for pneumonia are therefore only detected retrospectively and the etiologic agents remain unknown. Here, we perform spatio-temporal analyses of pneumonia hospital admission data in the Netherlands. To this end, we scanned for spatial clusters on yearly and seasonal basis, and applied wavelet cluster analysis on the time series of five main regions. The pneumonia hospital admissions show strong clustering in space and time superimposed on a regular yearly cycle with high incidence in winter and low incidence in summer. Cluster analysis reveals a heterogeneous pattern, with most significant clusters occurring in the western, highly urbanised, and in the eastern, intensively farmed, part of the Netherlands. Quantitatively, the relative risk (RR) of the significant clusters for the age-standardised incidence varies from a minimum of 1.2 to a maximum of 2.2. We discuss possible underlying causes for the patterns observed, such as variations in air pollution.

Livestock-associated risk factors for pneumonia in an area of intensive animal farming in the Netherlands

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.