Long COVID exhibits clinically distinct phenotypes at 3-6 months post-SARS-CoV-2 infection: results from the P4O2 consortium.

BACKGROUND: Four months after SARS-CoV-2 infection, 22%-50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient. METHODS: Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3-6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARS-CoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering. RESULTS: Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category. CONCLUSIONS: Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment.

Pulmonary function 3-6 months after acute COVID-19: A systematic review and multicentre cohort study.

Aims: To describe pulmonary function 3-6 months following acute COVID-19, to evaluate potential predictors of decreased pulmonary function and to review literature for the effect of COVID-19 on pulmonary function. Materials and methods: A systematic review and cohort study were conducted. Within the P4O2 COVID-19 cohort, 95 patients aged 40-65 years were recruited from outpatient post-COVID-19 clinics in five Dutch hospitals between May 2021-September 2022. At 3-6 months post COVID-19, medical records data and biological samples were collected and questionnaires were administered. In addition, pulmonary function tests (PFTs), including spirometry and transfer factor, were performed. To identify factors associated with PFTs, linear regression analyses were conducted, adjusted for covariates. Results: In PFTs (n = 90), mean ± SD % of predicted was 89.7 ± 18.2 for forced vital capacity (FVC) and 79.8 ± 20.0 for transfer factor for carbon monoxide (DLCO). FVC was

Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study.

BACKGROUND: In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90-150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort. METHODS: In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40-65 years were included. Data collection at 3-6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9-12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found. RESULTS: According to the FSS, fatigue was reported by 75.9% of the patients at 3-6 months after infection and by 57.1% of the patients 9-12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients. CONCLUSIONS: This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12-18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.

Prenatal exposure to per- and polyfluoroalkyl substances and early childhood adiposity and cardiometabolic health in the Healthy Start study.

BACKGROUND/OBJECTIVES: Observational and experimental studies have suggested that prenatal exposure to per- and polyfluoroalkyl substances (PFAS) can increase childhood adiposity and cardiometabolic disruption. However, most previous studies have used weight-based measures that cannot distinguish between fat mass and lean mass. We evaluated associations of prenatal PFAS exposure with precisely measured body composition and cardiometabolic biomarkers in early childhood. SUBJECTS: 373 eligible mother-infant pairs in the Healthy Start longitudinal cohort. METHODS: We used multiple linear regression and Bayesian kernel machine regression models to estimate associations between five PFAS in maternal mid-pregnancy serum, and early childhood adiposity via air displacement plethysmography. Secondary outcomes included body mass index, waist circumference, and fasting serum lipids, glucose, insulin and adipokines. Models were adjusted for potential confounders and effect modification by child sex was evaluated. RESULTS: The median age of children at assessment was 4.6 years. Prenatal concentration of perfluorooctanoate (PFOA) was positively associated with percent fat mass (0.89% per log2-unit increase, 95% CI: 0.15, 1.64), while perfluorononanoate (PFNA) was positively associated with fat mass index and body mass index. Cardiometabolic markers in blood were generally not associated with prenatal PFAS in this population. Mixture models confirmed the importance of PFNA and PFOA in predicting percent fat mass, while PFNA was most important for fat mass index, body mass index, and waist circumference. There were no significant effects of the five PFAS as a mixture, potentially due to opposing effects of different PFAS. CONCLUSIONS: Our results agree with previous studies showing that prenatal serum concentrations of certain PFAS are positively associated with early childhood adiposity. Notably, associations were stronger for measures incorporating precisely measured fat mass compared to measures of body size or weight. Early life increases in adiposity may precede the development of adverse cardiometabolic health outcomes in children exposed to PFAS during gestation.

The effects of the COVID-19 pandemic on PICU admissions for severe asthma exacerbations: A single-center experience.

BACKGROUND: The incidence of severe asthma exacerbations (SAE) requiring a pediatric intensive care unit (PICU) admission during the coronavirus disease 2019 (COVID-19) pandemic (and its association with public restrictions) is largely unknown. We examined the trend of SAE requiring PICU admission before, during, and after COVID-19 restrictions in Amsterdam, the Netherlands, and its relationship with features such as environmental triggers and changes in COVID-19 restriction measures. METHODS: In this single-center, retrospective cohort study, all PICU admissions of children aged ≥2 years for severe asthma at the Amsterdam UMC between 2018 and 2022 were included. The concentrations of ambient fine particulate matter (PM2.5 ) and pollen were obtained from official monitoring stations. RESULTS: Between January 2018 and December 2022, 228 children were admitted to the PICU of the Amsterdam UMC for SAE. While we observed a decrease in admissions during periods of more stringent restriction, there was an increase in the PICU admission rate for SAE in some periods following the lifting of restrictions. In particular, following the COVID-19 restrictions in 2021, we observed a peak incidence of admissions from August to November, which was higher than any other peak during the indicated years. No association with air pollution or pollen was observed. CONCLUSION: We hypothesize that an increase in clinically diagnosed viral infections after lockdown periods was the reason for the altered incidence of SAE at the PICU in late 2021, rather than air pollution and pollen concentrations.

Precision Medicine for More Oxygen (P4O2)-Study Design and First Results of the Long COVID-19 Extension.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has led to the death of almost 7 million people, however, with a cumulative incidence of 0.76 billion, most people survive COVID-19. Several studies indicate that the acute phase of COVID-19 may be followed by persistent symptoms including fatigue, dyspnea, headache, musculoskeletal symptoms, and pulmonary functional-and radiological abnormalities. However, the impact of COVID-19 on long-term health outcomes remains to be elucidated. Aims: The Precision Medicine for more Oxygen (P4O2) consortium COVID-19 extension aims to identify long COVID patients that are at risk for developing chronic lung disease and furthermore, to identify treatable traits and innovative personalized therapeutic strategies for prevention and treatment. This study aims to describe the study design and first results of the P4O2 COVID-19 cohort. Methods: The P4O2 COVID-19 study is a prospective multicenter cohort study that includes nested personalized counseling intervention trial. Patients, aged 40-65 years, were recruited from outpatient post-COVID clinics from five hospitals in The Netherlands. During study visits at 3-6 and 12-18 months post-COVID-19, data from medical records, pulmonary function tests, chest computed tomography scans and biological samples were collected and questionnaires were administered. Furthermore, exposome data was collected at the patient's home and state-of-the-art imaging techniques as well as multi-omics analyses will be performed on collected data. Results: 95 long COVID patients were enrolled between May 2021 and September 2022. The current study showed persistence of clinical symptoms and signs of pulmonary function test/radiological abnormalities in post-COVID patients at 3-6 months post-COVID. The most commonly reported symptoms included respiratory symptoms (78.9%), neurological symptoms (68.4%) and fatigue (67.4%). Female sex and infection with the Delta, compared with the Beta, SARS-CoV-2 variant were significantly associated with more persisting symptom categories. Conclusions: The P4O2 COVID-19 study contributes to our understanding of the long-term health impacts of COVID-19. Furthermore, P4O2 COVID-19 can lead to the identification of different phenotypes of long COVID patients, for example those that are at risk for developing chronic lung disease. Understanding the mechanisms behind the different phenotypes and identifying these patients at an early stage can help to develop and optimize prevention and treatment strategies.

Identifying risk factors for COPD and adult-onset asthma: an umbrella review.

BACKGROUND: COPD and adult-onset asthma (AOA) are the most common noncommunicable respiratory diseases. To improve early identification and prevention, an overview of risk factors is needed. We therefore aimed to systematically summarise the nongenetic (exposome) risk factors for AOA and COPD. Additionally, we aimed to compare the risk factors for COPD and AOA. METHODS: In this umbrella review, we searched PubMed for articles from inception until 1 February 2023 and screened the references of relevant articles. We included systematic reviews and meta-analyses of observational epidemiological studies in humans that assessed a minimum of one lifestyle or environmental risk factor for AOA or COPD. RESULTS: In total, 75 reviews were included, of which 45 focused on risk factors for COPD, 28 on AOA and two examined both. For asthma, 43 different risk factors were identified while 45 were identified for COPD. For AOA, smoking, a high body mass index (BMI), wood dust exposure and residential chemical exposures, such as formaldehyde exposure or exposure to volatile organic compounds, were amongst the risk factors found. For COPD, smoking, ambient air pollution including nitrogen dioxide, a low BMI, indoor biomass burning, childhood asthma, occupational dust exposure and diet were amongst the risk factors found. CONCLUSIONS: Many different factors for COPD and asthma have been found, highlighting the differences and similarities. The results of this systematic review can be used to target and identify people at high risk for COPD or AOA.

Medication use in uncontrolled pediatric asthma: Results from the SysPharmPediA study.

BACKGROUND: Uncontrolled pediatric asthma has a large impact on patients and their caregivers. More insight into determinants of uncontrolled asthma is needed. We aim to compare treatment regimens, inhaler techniques, medication adherence and other characteristics of children with controlled and uncontrolled asthma in the: Systems Pharmacology approach to uncontrolled Paediatric Asthma (SysPharmPediA) study. MATERIAL AND METHODS: 145 children with moderate to severe doctor-diagnosed asthma (91 uncontrolled and 54 controlled) aged 6-17 years were enrolled in this multicountry, (Germany, Slovenia, Spain, and the Netherlands) observational, case-control study. The definition of uncontrolled asthma was based on asthma symptoms and/or exacerbations in the past year. Patient-reported adherence and clinician-reported medication use were assessed, as well as lung function and inhalation technique. A logistic regression model was fitted to assess determinants of uncontrolled pediatric asthma. RESULTS: Children in higher asthma treatment steps had a higher risk of uncontrolled asthma (OR (95%CI): 3.30 (1.56-7.19)). The risk of uncontrolled asthma was associated with a larger change in FEV1% predicted post and pre-salbutamol (OR (95%CI): 1.08 (1.02-1.15)). Adherence and inhaler techniques were not associated with risk of uncontrolled asthma in this population. CONCLUSION: This study showed that children with uncontrolled moderate-to-severe asthma were treated in higher treatment steps compared to their controlled peers, but still showed a higher reversibility response to salbutamol. Self-reported adherence and inhaler technique scores did not differ between controlled and uncontrolled asthmatic children. Other determinants, such as environmental factors and differences in biological profiles, may influence the risk of uncontrolled asthma in this moderate to severe asthmatic population.

The disease-specific clinical trial network for primary ciliary dyskinesia: PCD-CTN.

Primary ciliary dyskinesia (PCD) is a rare genetic disorder characterised by impaired mucociliary clearance leading to irreversible lung damage. In contrast to other rare lung diseases like cystic fibrosis (CF), there are only few clinical trials and limited evidence-based treatments. Management is mainly based on expert opinions and treatment is challenging due to a wide range of clinical manifestations and disease severity. To improve clinical and translational research and facilitate development of new treatments, the clinical trial network for PCD (PCD-CTN) was founded in 2020 under the framework of the European Reference Network (ERN)-LUNG PCD Core. Applications from European PCD sites interested in participating in the PCD-CTN were requested. Inclusion criteria consisted of patient numbers, membership of ERN-LUNG PCD Core, use of associated standards of care, experience in PCD and/or CF clinical research, resources to run clinical trials, good clinical practice (GCP) certifications and institutional support. So far, applications from 22 trial sites in 18 European countries have been approved, including >1400 adult and >1600 paediatric individuals with PCD. The PCD-CTN is headed by a coordinating centre and consists of a steering and executive committee, a data safety monitoring board and committees for protocol review, training and standardisation. A strong association with patient organisations and industrial companies are further cornerstones. All participating trial sites agreed on a code of conduct. As CTNs from other diseases have demonstrated successfully, this newly formed PCD-CTN operates to establish evidence-based treatments for this orphan disease and to bring new personalised treatment approaches to patients.

Ambient air pollution during pregnancy and cardiometabolic biomarkers in cord blood.

Prenatal air pollution exposure has been associated with adverse childhood cardiometabolic outcomes. It is unknown whether evidence of metabolic disruption associated with air pollution is identifiable at birth. We examined exposure to prenatal ambient air pollution and cord blood cardiometabolic biomarkers among 812 mother-infant pairs in the Healthy Start study. Methods: Using inverse-distance-weighted interpolation of ambient concentrations obtained from stationary monitors, we estimated daily particulate matter ≤2.5 micrometers (PM2.5) and ozone (O3) concentrations at participant residences. Daily estimates were averaged by trimester, full-pregnancy, and the 7 and 30 days prior to delivery. Associations of air pollution with the following cord blood biomarkers were estimated via multivariable linear regression: glucose, insulin, glucose/insulin ratio (GIR), leptin, high-density lipoprotein (HDL) cholesterol, non-HDL cholesterol, free fatty acids, and triglycerides. Results: In this Denver-based cohort, PM2.5 concentrations were lower than in many US urban areas, but O3 concentrations regularly exceeded federal air quality standards. Higher O3 concentrations during pregnancy were consistently associated with higher insulin and lower GIR in cord blood. For example, an interquartile range increase in full pregnancy O3 (6.3 parts per billion [ppb]) was associated with 0.13 log-µIU/ml (95% confidence interval [CI] = 0.04, 0.22) higher cord blood insulin, after adjusting for PM2.5 and other confounders. We found positive, but generally nonsignificant, associations between PM2.5 and leptin and isolated associations between pollutants during certain exposure periods and lipids. Conclusions: In this cohort with moderately high O3 exposure, prenatal concentrations of O3 were positively associated with cord blood insulin. Future studies should examine the implications for offspring long-term health.

Green space, air pollution, traffic noise and mental wellbeing throughout adolescence: Findings from the PIAMA study.

BACKGROUND: Green space, air pollution and traffic noise exposure may be associated with mental health in adolescents. We assessed the associations of long-term exposure to residential green space, ambient air pollution and traffic noise with mental wellbeing from age 11 to 20 years. METHODS: We included 3059 participants of the Dutch PIAMA birth cohort who completed the five-item Mental Health Inventory (MHI-5) at ages 11, 14, 17 and/or 20 years. We estimated exposure to green space (the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m, 1000 m and 3000 m), ambient air pollution (particulate matter (PM10 and PM2.5), nitrogen dioxide, PM2.5 absorbance and the oxidative potential of PM2.5) and road traffic and railway noise (Lden) at the adolescents' home addresses at the times of completing the MHI-5. Associations with poor mental wellbeing (MHI-5 score ≤ 60) were assessed by generalized linear mixed models with a logit link, adjusting for covariates. RESULTS: The odds of poor mental wellbeing at age 11 to 20 years decreased with increasing exposure to green space in a 3000 m buffer (adjusted odds ratio (OR) 0.78 [95% CI 0.68-0.88] per IQR increase in the average NDVI; adjusted OR 0.77 [95% CI 0.67-0.88] per IQR increase in the total percentage of green space). These associations persisted after adjustment for air pollution and road traffic noise. Relationships between mental wellbeing and green space in buffers of 300 m and 1000 m were less consistent. Higher air pollution exposure was associated with higher odds of poor mental wellbeing, but these associations were strongly attenuated after adjustment for green space in a buffer of 3000 m, traffic noise and degree of urbanization. Traffic noise was not related to mental wellbeing throughout adolescence. CONCLUSIONS: Residential exposure to green space may be associated with a better mental wellbeing in adolescents.

Prenatal exposure to ambient air pollution and traffic and indicators of adiposity in early childhood: the Healthy Start study.

BACKGROUND: Prenatal exposure to ambient air pollution and traffic have been related to a lower birth weight and may be associated with greater adiposity in childhood. We aimed to examine associations of maternal exposure to ambient air pollution and traffic during pregnancy with indicators of adiposity in early childhood. METHODS: We included 738 participants of the Colorado-based Healthy Start study whose height, weight, waist circumference and/or fat mass were measured at age 4-6 years. We estimated residential exposure to ambient concentrations of fine particulate matter (PM2.5) and ozone (O3) averaged by trimester and throughout pregnancy via inverse distance-weighted interpolation of central site monitoring data. We assessed the distance to the nearest major roadway and traffic density in multiple buffers surrounding the participants' homes. Associations of prenatal exposure to air pollution and traffic with overweight, waist circumference, percent fat mass and fat mass index (FMI) were assessed by logistic and linear regression. RESULTS: Associations of exposure to PM2.5 and O3 at the residential address during pregnancy with percent fat mass and FMI at age 4-6 years were inconsistent across trimesters. For example, second trimester PM2.5 was associated with a higher percent fat mass (adjusted difference 0.70% [95% CI 0.05, 1.35%] per interquartile range (IQR; 1.3 µg/m3) increase), while third trimester PM2.5 was associated with a lower percent fat mass (adjusted difference -1.17% [95% CI -1.84, -0.50%] per IQR (1.3 µg/m3) increase). Residential proximity to a highway during pregnancy was associated with higher odds of being overweight at age 4-6 years. We observed no associations of prenatal exposure to PM2.5 and O3 with overweight and waist circumference. CONCLUSIONS: We found limited evidence of associations of prenatal exposure to ambient PM2.5 and O3 with indicators of adiposity at age 4-6 years. Suggestive relationships between residential proximity to a highway during pregnancy and greater adiposity merit further investigation.

Effects of exposure to surrounding green, air pollution and traffic noise with non-accidental and cause-specific mortality in the Dutch national cohort.

BACKGROUND: Everyday people are exposed to multiple environmental factors, such as surrounding green, air pollution and traffic noise. These exposures are generally spatially correlated. Hence, when estimating associations of surrounding green, air pollution or traffic noise with health outcomes, the other exposures should be taken into account. The aim of this study was to evaluate associations of long-term residential exposure to surrounding green, air pollution and traffic noise with mortality. METHODS: We followed approximately 10.5 million adults (aged ≥ 30 years) living in the Netherlands from 1 January 2013 until 31 December 2018. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 and 1000 m), annual average ambient air pollutant concentrations [including particulate matter (PM2.5), nitrogen dioxide (NO2)] and traffic noise with non-accidental and cause-specific mortality, adjusting for potential confounders. RESULTS: In single-exposure models, surrounding green was negatively associated with all mortality outcomes, while air pollution was positively associated with all outcomes. In two-exposure models, associations of surrounding green and air pollution attenuated but remained. For respiratory mortality, in a two-exposure model with NO2 and NDVI 300 m, the HR of NO2 was 1.040 (95%CI: 1.022, 1.059) per IQR increase (8.3 µg/m3) and the HR of NDVI 300 m was 0.964 (95%CI: 0.952, 0.976) per IQR increase (0.14). Road-traffic noise was positively associated with lung cancer mortality only, also after adjustment for air pollution or surrounding green. CONCLUSIONS: Lower surrounding green and higher air pollution were associated with a higher risk of non-accidental and cause-specific mortality. Studies including only one of these correlated exposures may overestimate the associations with mortality of that exposure.

Green space, air pollution, traffic noise and saliva cortisol in children: The PIAMA study.

Green space, air pollution, and traffic noise exposure may be associated with stress levels in children. A flattened diurnal cortisol slope (the decline in cortisol concentrations from awakening to evening) is an indicator of chronic stress. We examined associations of green space, ambient air pollution, and traffic noise with the diurnal cortisol slope in children 12 years of age. METHODS: At age 12 years, 1,027 participants of the Dutch PIAMA birth cohort collected three saliva samples during 1 day. We estimated residential exposure to green space (i.e., the average Normalized Difference Vegetation Index [NDVI] and percentages of green space in circular buffers of 300 m and 3,000 m), air pollution, and traffic noise. Associations of these exposures with the diurnal cortisol slope (in nmol/L per hour) were assessed by multiple linear regression, adjusting for potential confounders. RESULTS: Higher average NDVI and total percentage of green space in a 3,000 m buffer were associated with a larger diurnal decrease in cortisol levels (adjusted difference [95% confidence interval] = -0.11 nmol/L/hr [-0.21, 0.00 nmol/L/hr] per interquartile range increase in the average NDVI; -0.13 nmol/L/hr [-0.26, 0.00 nmol/L/hr] per interquartile range increase in the total percentage of green space). These associations were largely driven by associations with the percentage of agricultural green space and by associations in children living in nonurban areas. We observed no relationships between air pollution or traffic noise and the diurnal cortisol slope. CONCLUSIONS: Residential exposure to green space in a buffer of 3,000 m may be associated with lower stress levels in children 12 years of age.

Fat Mass Accretion from Birth to 5 Years and Metabolic Homeostasis in Childhood: the Healthy Start Study.

CONTEXT: It is unclear how fat mass accretion in early life is related to glucose-insulin homeostasis. OBJECTIVE: Examine associations of fat and fat-free mass accretion from birth to early childhood with glucose-insulin homeostasis in early childhood in a multi-ethnic cohort. METHODS: Observational Healthy Start study with data collection from 2010 to 2020. Air displacement plethysmography at birth and 4.8 (SD 0.7) years estimated fat mass percent (FMP, %), fat mass index (FMI, kg/m2), and fat-free mass index (FFMI, kg/m2). General population recruited from academic obstetrics clinics in Denver, Colorado, consisting of 419 mother/offspring dyads. The main outcome measures were fasting glucose, insulin, homeostasis model assessment-2 insulin resistance (HOMA2-IR), and beta-cell function (HOMA2-B) at 4.8 years. RESULTS: Greater fat mass accretion from birth to early childhood was associated with higher fasting glucose (ΔFMP ß = 0.20 [95% CI 0.06-0.34], ΔFMI ß = 0.90 [0.30-1.50]) in participants of Hispanic, Black, and Other races/ethnicities, while greater fat-free mass accretion was associated with higher fasting glucose in non-Hispanic White participants (ΔFFMI ß = 0.76 [0.21-1.32]). Overall, greater fat, but not fat-free, mass accretion was also associated with higher insulin (ΔFMP ß = 0.14 [0.09-0.18], ΔFMI 0.71 [0.51-0.92]), HOMA2-IR (FMP ß = 0.02 [0.01-0.02], ΔFMI ß = 0.09 [0.06-0.12]), and HOMA2-B (ΔFMP ß = 0.92 [0.18-1.36], ΔFMI ß = 4.76 [2.79-6.73]). CONCLUSION: Greater fat mass accretion in infancy and childhood is associated with shifts in fasting glucose in children of Hispanic, Black, and Other races/ethnicities at 5 years of age. Body composition beginning in early life is relevant for metabolic health, and precise assessments of adiposity in pediatric research are needed.

Surrounding green, air pollution, traffic noise exposure and non-accidental and cause-specific mortality.

BACKGROUND: Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures. OBJECTIVES: The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality. METHODS: We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), nitrogen dioxide (NO2)) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality. RESULTS: We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO2, a HR of 0.98 (0.97, 1.00) per IQR increase in PM2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings. CONCLUSION: We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period.

Acute respiratory effects of livestock-related air pollution in a panel of COPD patients.

Living close to livestock farms has been associated with increased symptoms in patients with chronic obstructive pulmonary disease (COPD). The causes of these effects are still poorly understood. This panel study attempts to assess the acute effects of livestock-related air pollution in patients with COPD living in an area with intensive livestock farming in the Netherlands. Between February 2015 and July 2016, 82 participants took spirometry measurements twice daily (morning and evening) during a 3-month period, resulting in 12,672 FEV1 and PEF records. Participants also kept a diary on respiratory symptoms as well as livestock-related odor annoyance. Daily average ammonia (NH3) (a proxy for livestock-related air pollution) and fine particulate matter (PM10) levels were collected from monitoring stations in the area. Lung function was analyzed as decrements of >10% and >20% from their median as well as absolute values. Self-reported odor annoyance was analyzed as a dichotomous variable. All analyses were done using generalized estimated equations. We adjusted for humidity, temperature, linear trend, and took multiple testing into account. We found an odds ratio of 1.14 95%CI [1.05; 1.25] for decrements >20% in morning FEV1 per interquartile range (12 µg/m3) increase in NH3 concentration (lag 2). Odor annoyance was negatively associated with evening PEF (-4.46 l/min 95%CI [-7.59; -1.33]). Sensitivity analyses showed a stronger effect in participants with worse baseline lung function. No associations with symptoms were found. Our results show acute effects of livestock-related air pollution on lung function in COPD patients living in close proximity to livestock farms.

Residential surrounding green, air pollution, traffic noise and self-perceived general health.

Self-perceived general health (SGH) is one of the most inclusive and widely used measures of health status and a powerful predictor of mortality. However, only a limited number of studies evaluated associations of combined environmental exposures on SGH. Our aim was to evaluate associations of combined residential exposure to surrounding green, air pollution and traffic noise with poor SGH in the Netherlands. We linked data on long-term residential exposure to surrounding green based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and road- and rail-traffic noise with a Dutch national health survey, resulting in a study population of 354,827 adults. We analyzed associations of single and combined exposures with poor SGH. In single-exposure models, NDVI within 300 m was inversely associated with poor SGH [odds ratio (OR) = 0.91, 95% CI: 0.89, 0.94 per IQR increase], while NO2 was positively associated with poor SGH (OR = 1.07, 95% CI: 1.04, 1.11 per IQR increase). In multi-exposure models, associations with surrounding green and air pollution generally remained, but attenuated. Joint odds ratios (JOR) of combined exposure to air pollution, rail-traffic noise and decreased surrounding green were higher than the odds ratios of single-exposure models. Studies including only one of these correlated exposures may overestimate the risk of poor SGH attributed to the studied exposure, while underestimating the risk of combined exposures.

Associations of Combined Exposures to Surrounding Green, Air Pollution, and Road Traffic Noise with Cardiometabolic Diseases.

BACKGROUND: Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures. OBJECTIVES: We aimed to evaluate associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases. METHODS: In this cross-sectional study, we studied associations between self-reported physician-diagnosed diabetes, hypertension, heart attack, and stroke from a Dutch national health survey of 387,195 adults and residential surrounding green, annual average air pollutant concentrations [including particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text]), PM with aerodynamic diameter [Formula: see text] ([Formula: see text]), nitrogen dioxide ([Formula: see text]), and oxidative potential (OP) with the dithiothreitol (DTT) assay ([Formula: see text])] and road traffic noise. Logistic regression models were used to analyze confounding and interaction of surrounding green, air pollution, and noise exposure. RESULTS: In single-exposure models, surrounding green was inversely associated with diabetes, while air pollutants ([Formula: see text], [Formula: see text]) and road traffic noise were positively associated with diabetes. In two-exposure analyses, associations with green and air pollution were attenuated but remained. The association between road traffic noise and diabetes was reduced to unity when adjusted for surrounding green or air pollution. Air pollution and surrounding green, but not road traffic noise, were associated with hypertension in single-exposure models. The weak inverse association of surrounding green with hypertension attenuated and lost significance when adjusted for air pollution. Only [Formula: see text] was associated with stroke and heart attack. CONCLUSIONS: Studies including only one of the correlated exposures surrounding green, air pollution, and road traffic noise may overestimate the association of diabetes and hypertension attributed to the studied exposure. https://doi.org/10.1289/EHP3857.