ABSTRACT
BACKGROUND: Tobacco smoke exposure increases the risk and severity of lower respiratory tract infections in children, yet the mechanisms remain unclear. We hypothesized that tobacco smoke exposure would modify the lower airway microbiome. METHODS: Secondary analysis of a multicenter cohort of 362 children between ages 31 days and 18 years mechanically ventilated for >72 h. Tracheal aspirates from 298 patients, collected within 24 h of intubation, were evaluated via 16 S ribosomal RNA sequencing. Smoke exposure was determined by creatinine corrected urine cotinine levels ≥30 µg/g. RESULTS: Patients had a median age of 16 (IQR 568) months. The most common admission diagnosis was lower respiratory tract infection (53%). Seventy-four (20%) patients were smoke exposed and exhibited decreased richness and Shannon diversity. Smoke exposed children had higher relative abundances of Serratia spp., Moraxella spp., Haemophilus spp., and Staphylococcus aureus. Differences were most notable in patients with bacterial and viral respiratory infections. There were no differences in development of acute respiratory distress syndrome, days of mechanical ventilation, ventilator free days at 28 days, length of stay, or mortality. CONCLUSION: Among critically ill children requiring prolonged mechanical ventilation, tobacco smoke exposure is associated with decreased richness and Shannon diversity and change in microbial communities. IMPACT: Tobacco smoke exposure is associated with changes in the lower airways microbiome but is not associated with clinical outcomes among critically ill pediatric patients requiring prolonged mechanical ventilation. This study is among the first to evaluate the impact of tobacco smoke exposure on the lower airway microbiome in children. This research helps elucidate the relationship between tobacco smoke exposure and the lower airway microbiome and may provide a possible mechanism by which tobacco smoke exposure increases the risk for poor outcomes in children.
Subject(s)
Microbiota , Respiratory Tract Infections , Tobacco Smoke Pollution , Humans , Child , Tobacco Smoke Pollution/adverse effects , Critical Illness , Respiration, Artificial/adverse effects , Smoke/adverse effects , Nicotiana , CotinineABSTRACT
Environmental research often relies on urinary biomarkers which require dilution correction to accurately measure exposures. Specific gravity (SG) and creatinine (UCr) are commonly measured urinary dilution factors. Epidemiologic studies may assess only one of these measures, making it difficult to pool studies that may otherwise be able to be combined. Participants from the National Health and Nutrition Examination Survey 2007-2008 cycle were used to perform k-fold validation of a nonlinear model estimating SG from UCr. The final estimated model was applied to participants from the School Inner-City Asthma Intervention Study, who submitted urinary samples to the Children's Health Exposure Analysis Resource. Model performance was evaluated using calibration metrics to determine how closely the average estimated SG was to the measured SG. Additional models, with interaction terms for age, sex, body mass index, race/ethnicity, relative time of day when sample was collected, log transformed 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and asthma status were estimated and assessed for improvement. The association between monobenzyl phthalate (MBZP) and asthma symptom days, controlling for measured UCr, measured SG, and each estimated SG were compared to assess validity of the estimated SG. The model estimating SG from UCr alone, resulted in a beta estimate of 1.10 (95% CI: 1.01, 1.19), indicating agreement between model-predicted SG and measured SG. Inclusion of age and sex in the model improved estimation (ß = 1.06, 95% CI: 0.98, 1.15). The full model accounting for all interaction terms with UCr resulted in the best agreement (ß = 1.01, 95% CI: 0.93,1.09). Associations between MBZP and asthma symptoms days, controlling for each estimated SG, were within the range of effect estimates when controlling for measured SG and measured UCr (Rate ratios = 1.28-1.34). Our nonlinear modeling provides opportunities to estimate SG in studies that measure UCr or vice versa, enabling data pooling despite differences in urine dilution factors.
Subject(s)
Nonlinear Dynamics , Humans , Child , Specific Gravity , Nutrition Surveys , Creatinine , Body Mass IndexABSTRACT
BACKGROUND: COVID-19 disproportionately affects families of low socioeconomic status and may worsen health disparities that existed prior to the pandemic. Asthma is a common chronic disease in children exacerbated by environmental exposures. METHODS: A cross-sectional survey was conducted to understand the impact of the initial stage of the pandemic on environmental and social conditions, along with access to care for children with asthma in New York City (NYC). Participants were recruited from a community-based organization in East Harlem and a nearby academic Pediatric Pulmonary clinic and categorized as having either public or private insurance (n = 51). RESULTS: Factors significantly associated with public compared to private insurance respectively were: increased reports of indoor asthma triggers (cockroach 76% vs 23%; mold 40% vs 12%), reduced income (72% vs 27%), and housing insecurity (32% vs 0%). Participants with public insurance were more likely to experience conditions less conducive to social distancing compared to respondents with private insurance, such as remaining in NYC (92% vs 38%) and using public transportation (44% vs 4%); families with private insurance also had greater access to remote work (81% vs 8%). Families with public insurance were significantly more likely to test positive for SARS-CoV-2 (48% vs 15%) but less likely to have gotten tested (76% vs 100%). Families with public insurance also reported greater challenges accessing office medical care and less access to telehealth, although not statistically significant (44% vs 19%; 68% vs 85%, respectively). CONCLUSIONS: Findings highlight disproportionate burdens of the pandemic, and how these disparities affect children with asthma in urban environments.
Subject(s)
Asthma , COVID-19 , Child , Humans , New York City , Cross-Sectional Studies , SARS-CoV-2 , Patient Acceptance of Health CareABSTRACT
BACKGROUND: Environmental phenols and parabens are endocrine disrupting chemicals (EDCs) with the potential to affect child neurodevelopment including autism spectrum disorders (ASD). Our aim was to assess whether exposure to environmental phenols and parabens during pregnancy was associated with an increased risk of clinical ASD or other nontypical development (non-TD). METHODS: This study included mother-child pairs (Nâ¯=â¯207) from the Markers of Autism Risks in Babies - Learning Early Signs (MARBLES) Cohort Study with urinary phenol and paraben metabolites analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) from repeated pregnancy urine samples. Because family recurrence risks in siblings are about 20%, MARBLES enrolls pregnant women who already had a child with ASD. Children were clinically assessed at 3 years of age and classified into 3 outcome categories: ASD, non-TD, or typically developing (TD). Single analyte analyses were conducted with trinomial logistic regression and weighted quantile sum (WQS) regression was used to test for mixture effects. RESULTS: Regression models were adjusted for pre-pregnancy body mass index, prenatal vitamin use (yes/no), homeowner status (yes/no), birth year, and child's sex. In single chemical analyses phenol exposures were not significantly associated with child's diagnosis. Mixture analyses using trinomial WQS regression showed a significantly increased risk of non-TD compared to TD (ORâ¯=â¯1.58, 95% CI: 1.04, 2.04) with overall greater prenatal phenol and paraben metabolites mixture. Results for ASD also showed an increased risk, but it was not significant. DISCUSSION: This is the first study to provide evidence that pregnancy environmental phenol exposures may increase the risk for non-TD in a high-risk population.
Subject(s)
Autism Spectrum Disorder/epidemiology , Environmental Exposure/statistics & numerical data , Parabens/metabolism , Phenol/metabolism , Autistic Disorder/epidemiology , Biomarkers , Calcium Carbonate , Child , Child, Preschool , Chromatography, Liquid , Cohort Studies , Female , Gas Chromatography-Mass Spectrometry , Humans , Male , Phenols , Pregnancy , Tandem Mass Spectrometry , VitaminsABSTRACT
Background: Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood. Objectives: This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old. Methods: Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders. Results: Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6(SE=2.1) ug/L and 34.9(SE=2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tß=-0.17,95%CI=[-0.46,0.11]; 3Tß=-0.17,95%CI=[-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure. Discussion: Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.
ABSTRACT
Background: Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood. Objectives: This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old. Methods: Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders. Results: Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6 (SE = 2.1) ug/L and 34.9 (SE = 2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tß = -0.17, 95%CI = [-0.46,0.11]; 3Tß = -0.17, 95%CI = [-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure. Discussion: Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.
ABSTRACT
Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQSRSRH), a mixture method successfully applied to 'omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQSRSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQSRSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQSRSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQSRSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQSRSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQSRSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings.
Subject(s)
Gastrointestinal Microbiome , Microbiota , Humans , Feces , Obesity , Body Mass IndexABSTRACT
Diet is widely recognized as a key contributor to human gut microbiome composition and function. However, overall nutrition can be difficult to compare across a population with varying diets. Moreover, the role of food security in the relationship with overall nutrition and the gut microbiome is unclear. This study aims to investigate the association between personalized nutrition scores, variation in the adult gut microbiome, and modification by food insecurity. The data originate from the Survey of the Health of Wisconsin and the Wisconsin Microbiome Study. Individual nutrition scores were assessed using My Nutrition Index (MNI), calculated using data from food frequency questionnaires, and additional health history and demographic surveys. Food security and covariate data were measured through self-reported questionnaires. The gut microbiome was assessed using 16S amplicon sequencing of DNA extracted from stool samples. Associations, adjusted for confounding and interaction by food security, were estimated using Weighted Quantile Sum (WQS) regression models with Random Subset and Repeated Holdout extensions (WQSRSRH), with bacterial taxa used as components in the weighted index. Of 643 participants, the average MNI was 66.5 (SD = 31.9), and 22.8% of participants were food insecure. Increased MNI was significantly associated with altered gut microbial composition (ß = 2.56, 95% CI = 0.52−4.61), with Ruminococcus, Oscillospira, and Blautia among the most heavily weighted of the 21 genera associated with the MNI score. In the stratified interaction WQSRSRH models, the bacterial taxa most heavily weighted in the association with MNI differed by food security, but the level of association between MNI and the gut microbiome was not significantly different. More bacterial genera are important in the association with higher nutrition scores for people with food insecurity versus food security, including Streptococcus, Parabacteroides Faecalibacterium, and Desulfovibrio. Individual nutrition scores are associated with differences in adult gut microbiome composition. The bacterial taxa most associated with nutrition vary by level of food security. While further investigation is needed, results showed a higher nutrition score was associated with a wider range of bacterial taxa for food insecure vs. secure, suggesting nutritional quality in food insecure individuals is important in maintaining health and reducing disparities.
Subject(s)
Gastrointestinal Microbiome , Adult , Cross-Sectional Studies , Diet , Food Insecurity , Food Supply , Humans , Nutrition SurveysABSTRACT
Reward motivation is a complex umbrella term encompassing the cognitions, emotions, and behaviors involved in the activation, execution, and persistence of goal-directed behavior. Altered reward motivation in children is characteristic of many neurodevelopmental and psychiatric disorders. Previously difficult to operationalize, the Progressive Ratio (PR) task has been widely used to assess reward motivation in animal and human studies, including children. Because the neural circuitry supporting reward motivation starts developing during pregnancy, and is sensitive to disruption by environmental toxicants, including metals, the goal of this study was to examine the association between prenatal concentrations of a mixture of neurotoxic metals and reward motivation in children. We measured reward motivation by administering a PR test to 373 children ages 6-8 years enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) Study in Mexico City. Children were asked to press a response lever for a token reward; one press on the response lever was required to earn the first token and each subsequent token required an additional 10 lever presses. Maternal blood concentrations of lead, manganese, zinc, arsenic, cadmium, and selenium were measured using inductively-coupled plasma mass spectrometry during the 2nd and 3rd trimesters of pregnancy. We performed generalized Weighted Quantile Sum (gWQS) regression analyses to examine associations between the prenatal metal mixture and reward motivation; adjusting for child sex, birthweight and age; and maternal IQ, education, and socioeconomic status. The prenatal metal mixture was significantly associated with higher motivation as indicated by more lever presses (ß = 0.02, p < 0.001) and a shorter time between receiving the reinforcer and the first press (ß = 0.23, p = 0.01), and between subsequent presses (ß = 0.07, p = 0.005). Contributions of different metals to this association differed by trimester and child sex. These findings suggest that children with increased exposure to metal during the 2nd and 3rd trimesters of gestation demonstrate increased reward motivation, which may reflect a tendency to perseverate or hypersensitivity to positive reinforcement.
Subject(s)
Metals, Heavy/blood , Motivation/drug effects , Prenatal Exposure Delayed Effects/chemically induced , Reward , Arsenic/blood , Birth Weight/drug effects , Cadmium/blood , Child , Female , Humans , Lead/blood , Male , Manganese/blood , Mental Status and Dementia Tests , Metals, Heavy/adverse effects , Pregnancy/blood , Selenium/blood , Zinc/bloodABSTRACT
OBJECTIVE: The purpose of this study was to assess the cross-sectional association between residential exposure to traffic-related air pollution and obesity in Mexican American adults. METHODS: A total of 7,826 self-reported Mexican Americans aged 20 to 60 years old were selected from the baseline survey of the MD Anderson Mano-a-Mano Mexican American Cohort. Concentrations of traffic-related particulate matter with aerodynamic diameter < 2.5 µm were modeled at geocoded residential addresses using a dispersion models. The residential proximity to the nearest major road was calculated using a Geographic Information System. Linear and logistic regression models were used to estimate the adjusted associations between exposure and obesity, defined as BMI ≥ 30. RESULTS: More than half (53.6%) of the study participants had BMI ≥ 30, with a higher prevalence in women (55.0%) than in men (48.8%). Overall higher traffic-related air pollution exposures were associated with lower BMI in men but higher BMI in women. By stratifying for those who lived in a 0- to 1,500-m road buffer, the one-interquartile-range (685.1 m) increase of distance to a major road had a significant association with a 0.58-kg/m2 lower BMI (95% CI: -0.92 to -0.24) in women. CONCLUSIONS: Exposure to intensive traffic is associated with increased risk of obesity in Mexican American women.