Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort
Abstract Background Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driv...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-11-01
|
| Series: | Environmental Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12940-022-00934-z |
| _version_ | 1811309181415718912 |
|---|---|
| author | Sheena E. Martenies Lauren Hoskovec Ander Wilson Brianna F. Moore Anne P. Starling William B. Allshouse John L. Adgate Dana Dabelea Sheryl Magzamen |
| author_facet | Sheena E. Martenies Lauren Hoskovec Ander Wilson Brianna F. Moore Anne P. Starling William B. Allshouse John L. Adgate Dana Dabelea Sheryl Magzamen |
| author_sort | Sheena E. Martenies |
| collection | DOAJ |
| description | Abstract Background Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort. Methods Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking. Results Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed. Conclusions NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects. |
| first_indexed | 2024-04-13T09:37:46Z |
| format | Article |
| id | doaj.art-49377af472a34dd29cb538c89a6ee29d |
| institution | Directory Open Access Journal |
| issn | 1476-069X |
| language | English |
| last_indexed | 2024-04-13T09:37:46Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Environmental Health |
| spelling | doaj.art-49377af472a34dd29cb538c89a6ee29d2022-12-22T02:52:02ZengBMCEnvironmental Health1476-069X2022-11-0121111510.1186/s12940-022-00934-zUsing non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohortSheena E. Martenies0Lauren Hoskovec1Ander Wilson2Brianna F. Moore3Anne P. Starling4William B. Allshouse5John L. Adgate6Dana Dabelea7Sheryl Magzamen8Department of Kinesiology and Community Health, University of Illinois at Urbana-ChampaignDepartment of Statistics, Colorado State UniversityDepartment of Statistics, Colorado State UniversityDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical CampusLifecourse Epidemiology of Adiposity and Diabetes (LEAD Center), University of Colorado Anschutz Medical CampusDepartment of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz CampusDepartment of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz CampusDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical CampusDepartment of Environmental and Radiological Health Sciences, Colorado State UniversityAbstract Background Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort. Methods Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking. Results Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed. Conclusions NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects.https://doi.org/10.1186/s12940-022-00934-zBirth weightAdiposityEnvironmental mixturesSocial stressorsAir displacement plethysmographyNon-parametric Bayes shrinkage |
| spellingShingle | Sheena E. Martenies Lauren Hoskovec Ander Wilson Brianna F. Moore Anne P. Starling William B. Allshouse John L. Adgate Dana Dabelea Sheryl Magzamen Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort Environmental Health Birth weight Adiposity Environmental mixtures Social stressors Air displacement plethysmography Non-parametric Bayes shrinkage |
| title | Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort |
| title_full | Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort |
| title_fullStr | Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort |
| title_full_unstemmed | Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort |
| title_short | Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort |
| title_sort | using non parametric bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the healthy start cohort |
| topic | Birth weight Adiposity Environmental mixtures Social stressors Air displacement plethysmography Non-parametric Bayes shrinkage |
| url | https://doi.org/10.1186/s12940-022-00934-z |
| work_keys_str_mv | AT sheenaemartenies usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT laurenhoskovec usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT anderwilson usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT briannafmoore usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT annepstarling usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT williamballshouse usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT johnladgate usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT danadabelea usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort AT sherylmagzamen usingnonparametricbayesshrinkagetoassessrelationshipsbetweenmultipleenvironmentalandsocialstressorsandneonatalsizeandbodycompositioninthehealthystartcohort |