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RESEARCH PRODUCT

Air pollution, residential greenness and metabolic dysfunction during early pregnancy in the infancia y medio ambiente (Inma) cohort

Kristina W. WhitworthMikel Subiza-pérezMikel Subiza-pérezAmal RammahMartine VrijheidMartine VrijheidJesús IbarluceaChristopher I. AmosMònica GuxensElaine SymanskiCarmen IñiguezCarmen IñiguezMarisa EstarlichMarisa Estarlich

subject

PM<sub>2.5</sub>GDMHealth Toxicology and MutagenesisAir pollutionEarly pregnancy factor010501 environmental sciencesLogistic regressionmedicine.disease_causeNO201 natural sciences0302 clinical medicinePregnancy030212 general & internal medicineGeneral Environmental ScienceAir PollutantsbiologyRRegression analysis3. Good healthGestational diabetesCohortMedicineFemalegestational diabetesresidential greennesNitrogen DioxidePM2.5High cholesterolArticleOddslipids03 medical and health sciencesSDG 3 - Good Health and Well-beingEnvironmental healthNO<sub>2</sub>Air PollutionmedicineHumans0105 earth and related environmental sciencesPregnancybusiness.industryPublic Health Environmental and Occupational HealthEnvironmental Exposuremedicine.disease13. Climate actionresidential greennessbiology.proteinGeneral Earth and Planetary SciencesParticulate Matterbusiness

description

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM2.5 and NO2 exposures and the metabolic outcomes. Though not statistically significant, high PM2.5 exposure (≥25 µg/m3) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO2 exposure (≥39.8 µg/m3) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy. This work is supported by a National Institute of Environmental Health Sciences (NIEHS) fellowship from the Training in Precision Environmental Health Sciences (TPEHS) Program (NIH Grant No. T32ES027801). E.S., K.W.W., and C.I.A. were partially supported by a NIEHS P30 Environmental Health Sciences Core Center grant (P30ES030285). The INMA study was funded by grants from Instituto de Salud Carlos III (Red INMA G03/176, CB06/02/0041; FIS-FEDER: PI03/1615, PI04/1509, PI04/1112, PI04/1931, PI05/1079, PI05/1052, PI06/0867, PI06/1213, PI07/0314, PI09/02647, PI11/01007, PI11/02591, PI11/02038, PI13/1944, PI13/2032, PI14/00891, PI14/01687, PI16/1288, PI17/00663, FIS-PI18/01142 incl. FEDER funds; Miguel Servet-FEDER CP11/00178, CP15/00025, and CPII16/00051, CPII18/00018), Generalitat de Catalunya-CIRIT 1999SGR 00241, EU Commission (FP7-ENV-2011 cod 282957 and HEALTH.2010.2.4.5-1), Generalitat Valenciana: FISABIO (UGP 15-230, UGP-15-244, and UGP-15-249), and Alicia Koplowitz Foundation 2017, Department of Health of the Basque Government (2005111093), Provincial Government of Gipuzkoa (DFG06/002), and annual agreements with the municipalities of the study area (Zumarraga, Urretxu, Legazpi, Azkoitia y Azpeitia y Beasain). We also acknowledge support from the Spanish Ministry of Science and Innovation and the State Research Agency through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program.

10.3390/ijerph18179354https://doi.org/10.3390/ijerph18179354