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Adgent MA, Buth E, Noroña-Zhou A, Szpiro AA, Loftus CT, Moore PE, Wright RJ, Barrett ES, LeWinn KZ, Zhao Q, Nguyen R, Karr CJ, Bush NR, Carroll KN. Maternal stressful life events during pregnancy and childhood asthma and wheeze. Ann Allergy Asthma Immunol 2024; 132:594-601.e3. [PMID: 38122928 PMCID: PMC11069451 DOI: 10.1016/j.anai.2023.12.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/28/2023] [Accepted: 12/03/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Studies have linked prenatal maternal psychosocial stress to childhood wheeze/asthma but have rarely investigated factors that may mitigate risks. OBJECTIVE To investigate associations between prenatal stress and childhood wheeze/asthma, evaluating factors that may modify stress effects. METHODS Participants included 2056 mother-child dyads from Environmental influences on Child Health Outcomes (ECHO)-PATHWAYS, a consortium of 3 prospective pregnancy cohorts (the Conditions Affecting Neurocognitive Development and Learning in Early Childhood study, The Infant Development and Environment Study, and a subset of the Global Alliance to Prevent Prematurity and Stillbirth study) from 6 cities. Maternal stressful life events experienced during pregnancy (PSLEs) were reported using the Pregnancy Risk Assessment Monitoring System Stressful Life Events questionnaire. Parents reported child wheeze/asthma outcomes at age 4 to 6 years using standardized questionnaires. We defined outcomes as ever asthma, current wheeze, current asthma, and strict asthma. We used modified Poisson regression with robust standard errors (SEs) to estimate risk ratios (RRs) and 95% CI per 1-unit increase in PSLE, adjusting for confounders. We evaluated effect modification by child sex, maternal history of asthma, maternal childhood traumatic life events, neighborhood-level resources, and breastfeeding. RESULTS Overall, we observed significantly elevated risk for current wheeze with increasing PSLE (RR, 1.09 [95% CI, 1.03-1.14]), but not for other outcomes. We observed significant effect modification by child sex for strict asthma (P interaction = .03), in which risks were elevated in boys (RR, 1.10 [95% CI, 1.02-1.19]) but not in girls. For all other outcomes, risks were significantly elevated in boys and not in girls, although there was no statistically significant evidence of effect modification. We observed no evidence of effect modification by other factors (P interactions > .05). CONCLUSION Risk of adverse childhood respiratory outcomes is higher with increasing maternal PSLEs, particularly in boys.
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Affiliation(s)
| | - Erin Buth
- University of Washington, Seattle WA
| | | | | | | | | | | | - Emily S. Barrett
- Rutgers School of Public Health, Environmental and Occupational Health Sciences Institute; Piscataway NJ
| | - Kaja Z. LeWinn
- University of California San Francisco, San Francisco CA
| | - Qi Zhao
- University of Tennessee Health Sciences Center, Memphis TN
| | | | | | - Nicole R. Bush
- University of California San Francisco, San Francisco CA
| | - Kecia N. Carroll
- Vanderbilt University Medical Center, Nashville TN
- Icahn School of Medicine at Mount Sinai, New York NY
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Farmer N, Maki KA, Barb JJ, Jones KK, Yang L, Baumer Y, Powell-Wiley TM, Wallen GR. Geographic social vulnerability is associated with the alpha diversity of the human microbiome. mSystems 2023; 8:e0130822. [PMID: 37642431 PMCID: PMC10654076 DOI: 10.1128/msystems.01308-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/26/2023] [Indexed: 08/31/2023] Open
Abstract
IMPORTANCE As a risk factor for conditions related to the microbiome, understanding the role of SVI on microbiome diversity may assist in identifying public health implications for microbiome research. Here we found, using a sub-sample of the Human Microbiome Project phase 1 cohort, that SVI was linked to microbiome diversity across body sites and that SVI may influence race/ethnicity-based differences in diversity. Our findings, build on the current knowledge regarding the role of human geography in microbiome research, suggest that measures of geographic social vulnerability be considered as additional contextual factors when exploring microbiome alpha diversity.
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Affiliation(s)
- Nicole Farmer
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA
| | - Katherine A. Maki
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA
| | - Jennifer J. Barb
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA
| | - Kelly K. Jones
- Intramural Research Program, National Institute on Minority Health and Health Disparities, Bethesda, Maryland, USA
| | - Li Yang
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | - Tiffany M. Powell-Wiley
- Intramural Research Program, National Institute on Minority Health and Health Disparities, Bethesda, Maryland, USA
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | - Gwenyth R. Wallen
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, Maryland, USA
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Kannoth S, Chung SE, Tamakloe KD, Albrecht SS, Azan A, Chambers EC, Sheffield PE, Thompson A, Woo Baidal JA, Lovinsky-Desir S, Stingone JA. Neighborhood environmental vulnerability and pediatric asthma morbidity in US metropolitan areas. J Allergy Clin Immunol 2023; 152:378-385.e2. [PMID: 36990323 PMCID: PMC10524145 DOI: 10.1016/j.jaci.2023.03.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND Research suggests demographic, economic, residential, and health-related factors influence vulnerability to environmental exposures. Greater environmental vulnerability may exacerbate environmentally related health outcomes. We developed a neighborhood environmental vulnerability index (NEVI) to operationalize environmental vulnerability on a neighborhood level. OBJECTIVE We explored the relationship between NEVI and pediatric asthma emergency department (ED) visits (2014-19) in 3 US metropolitan areas: Los Angeles County, Calif; Fulton County, Ga; and New York City, NY. METHODS We performed separate linear regression analyses examining the association between overall NEVI score and domain-specific NEVI scores (demographic, economic, residential, health status) with pediatric asthma ED visits (per 10,000) across each area. RESULTS Linear regression analyses suggest that higher overall and domain-specific NEVI scores were associated with higher annual pediatric asthma ED visits. Adjusted R2 values suggest that overall NEVI scores explained at least 40% of the variance in pediatric asthma ED visits. Overall NEVI scores explained more of the variance in pediatric asthma ED visits in Fulton County. NEVI scores for the demographic, economic, and health status domains explained more of the variance in pediatric asthma ED visits in each area compared to the NEVI score for the residential domain. CONCLUSION Greater neighborhood environmental vulnerability was associated with greater pediatric asthma ED visits in each area. The relationship differed in effect size and variance explained across the areas. Future studies can use NEVI to identify populations in need of greater resources to mitigate the severity of environmentally related outcomes, such as pediatric asthma.
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Affiliation(s)
- Sneha Kannoth
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY.
| | - Sarah E Chung
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY
| | - Kelvin D Tamakloe
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY
| | - Sandra S Albrecht
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY
| | - Alexander Azan
- Department of Population Health, New York University Langone Health, New York City, NY
| | - Earle C Chambers
- Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, NY
| | - Perry E Sheffield
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, NY
| | - Azure Thompson
- Department of Community Health Sciences, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Jennifer A Woo Baidal
- Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY
| | - Stephanie Lovinsky-Desir
- Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY
| | - Jeanette A Stingone
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY
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Shahunja KM, Sly PD, Huda MM, Mamun A. Trajectories of neighborhood environmental factors and their associations with asthma symptom trajectories among children in Australia: evidence from a national birth cohort study. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2022; 20:835-847. [PMID: 36406622 PMCID: PMC9672149 DOI: 10.1007/s40201-022-00824-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/04/2022] [Accepted: 08/09/2022] [Indexed: 06/16/2023]
Abstract
PURPOSE This study aims to investigate the prospective associations of neighborhood environmental exposure trajectories with asthma symptom trajectories during childhood developmental stages. METHODS We considered asthma symptom, neighborhood environmental factors, and socio-demographic data from the "Longitudinal Study of Australian Children (LSAC)". Group-based trajectory modeling was applied to identify the trajectories of asthma symptom, neighborhood traffic conditions, and neighborhood livability scales (considered for safety and facilities). We used multivariable logistic regression models to assess associations between various neighborhood environmental factors and asthma symptom trajectories. RESULTS We included 4,174 children from the LSAC cohort in our study. Three distinct trajectories for asthma symptom were the outcome variables of this study. Among the neighborhood environmental factors, we identified two distinct trajectories for the prevalence of heavy traffic on street, and two trajectories of neighborhood liveability scale. Compared to the 'Low/no' asthma symptoms trajectory group, children exposed to a 'persistently high' prevalence of heavy traffic on street was also significantly associated with both 'transient high' [relative risk ratio (RRR):1.40, 95% CI:1.25,1.58) and 'persistent high' (RRR: 1.33, 95% CI:1.17,1.50)] asthma symptom trajectory groups. Trajectory of moderate and static neighborhood liveability score was at increased risk of being classified as 'transient high' (RRR:1.16, 95% CI:1.07,1.25) and 'persistent high' (RRR:1.38, 95% CI:1.27,1.50) trajectories of asthma symptom. CONCLUSION Exposure to heavy traffic and poor neighborhood liveability increased the risk of having an unfavourable asthma symptom trajectory in childhood. Reducing neighborhood traffic load and improving neighborhood safety and amenities may facilitate a favorable asthma symptom trajectory among these children. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40201-022-00824-z.
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Affiliation(s)
- K M Shahunja
- UQ Poche Centre for Indigenous Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- ARC Centre of Excellence for Children and Families over the Life Course, The University of Queensland, Brisbane, Australia
- The Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Australia
| | - Peter D Sly
- Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - M Mamun Huda
- UQ Poche Centre for Indigenous Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- ARC Centre of Excellence for Children and Families over the Life Course, The University of Queensland, Brisbane, Australia
| | - Abdullah Mamun
- UQ Poche Centre for Indigenous Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia
- ARC Centre of Excellence for Children and Families over the Life Course, The University of Queensland, Brisbane, Australia
- The Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Australia
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Stas M, Aerts R, Hendrickx M, Delcloo A, Dendoncker N, Dujardin S, Linard C, Nawrot T, Van Nieuwenhuyse A, Aerts JM, Van Orshoven J, Somers B. Exposure to green space and pollen allergy symptom severity: A case-crossover study in Belgium. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 781:146682. [PMID: 33812114 DOI: 10.1016/j.scitotenv.2021.146682] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 03/04/2021] [Accepted: 03/18/2021] [Indexed: 05/17/2023]
Abstract
BACKGROUND The prevalence of pollen allergy has increased due to urbanization, climate change and air pollution. The effects of green space and air pollution on respiratory health of pollen allergy patients are complex and best studied in spatio-temporal detail. METHODS We tracked 144 adults sensitized to Betulaceae pollen during the tree pollen season (January-May) of 2017 and 2018 and assessed their spatio-temporal exposure to green space, allergenic trees, air pollutants and birch pollen. Participants reported daily symptom severity scores. We extracted 404 case days with high symptom severity scores and matched these to 404 control days. The data were analyzed using conditional logistic regression with a 1:1 case-crossover design. RESULTS Case days were associated with exposure to birch pollen concentration (100 grains/m3) [adjusted odds ratio 1.045 and 95% confidence interval (1.014-1.078)], O3 concentration (10 μg/m3) [1.504 (1.281-1.766)] and PM10 concentration (10 μg/m3) [1.255 (1.007-1.565)] on the day of the severe allergy event and with the cumulative exposure of one and two days before. Exposure to grass cover (10% area fraction) [0.655 (0.446-0.960)], forest cover (10% area fraction) [0.543 (0.303-0.973)] and density of Alnus (10%) [0.622 (0.411-0.942)] were protective for severe allergy, but only on the day of the severe allergy event. Increased densities of Betula trees (10%) were a risk factor [unadjusted OR: 2.014 (1.162-3.490)]. CONCLUSION Exposure to green space may mitigate tree pollen allergy symptom severity but only when the density of allergenic trees is low. Air pollutants contribute to more severe allergy symptoms. Spatio-temporal tracking allows for a more realistic exposure assessment.
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Affiliation(s)
- Michiel Stas
- Division Forest, Nature and Landscape, Department Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium; Measure, Model & Manage Bioresponses (M3-BIORES), Division Animal and Human Health Engineering, Department of Biosystems (BIOSYST), KU Leuven, Kasteelpark Arenberg 30-2472, B-3001 Leuven, Belgium.
| | - Raf Aerts
- Division Forest, Nature and Landscape, Department Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium; Risk and Health Impact Assessment, Sciensano (Belgian Institute of Health), J. Wytsmanstraat 14, B-1050 Brussels, Belgium; Division Ecology, Evolution and Biodiversity Conservation, KU Leuven, Kasteelpark Arenberg 31-3245, BE-3001 Leuven, Belgium; Center for Environmental Sciences, Hasselt University, Campus Diepenbeek, Agoralaan Gebouw D, B-3590 Hasselt, Belgium; Mycology and Aerobiology, Sciensano (Belgian Institute of Health), J. Wytsmanstraat 14, B-1050 Brussels, Belgium.
| | - Marijke Hendrickx
- Mycology and Aerobiology, Sciensano (Belgian Institute of Health), J. Wytsmanstraat 14, B-1050 Brussels, Belgium.
| | - Andy Delcloo
- Royal Meteorological Institute of Belgium, Ringlaan 3 Avenue Circulaire, B-1180 Brussels, Belgium; Department of Physics and Astronomy, Ghent University, Proeftuinstraat 86, B-9000 Ghent, Belgium.
| | - Nicolas Dendoncker
- Department of Geography, University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium; Institute for Life, Earth and Environment (ILEE), University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium.
| | - Sebastien Dujardin
- Department of Geography, University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium; Institute for Life, Earth and Environment (ILEE), University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium.
| | - Catherine Linard
- Department of Geography, University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium; Institute for Life, Earth and Environment (ILEE), University of Namur, Rue de Bruxelles 61, B-5000 Namur, Belgium.
| | - Tim Nawrot
- Center for Environmental Sciences, Hasselt University, Campus Diepenbeek, Agoralaan Gebouw D, B-3590 Hasselt, Belgium; Centre Environment and Health, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 35 blok d box 7001, B-3000 Leuven, Belgium.
| | - An Van Nieuwenhuyse
- Centre Environment and Health, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 35 blok d box 7001, B-3000 Leuven, Belgium; Department of Health Protection, Laboratoire national de santé (LNS), 1, Rue Louis Rech, L-3555 Dudelange, Luxembourg.
| | - Jean-Marie Aerts
- Measure, Model & Manage Bioresponses (M3-BIORES), Division Animal and Human Health Engineering, Department of Biosystems (BIOSYST), KU Leuven, Kasteelpark Arenberg 30-2472, B-3001 Leuven, Belgium.
| | - Jos Van Orshoven
- Division Forest, Nature and Landscape, Department Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium.
| | - Ben Somers
- Division Forest, Nature and Landscape, Department Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium.
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