CoChat
Sign Up
Cited by 27Air Quality and Health ImpactsBirth, Development, and HealthGestational Diabetes Research and Management

Association of Prenatal and Perinatal Exposures to Particulate Matter With Changes in Hemoglobin A1c Levels in Children Aged 4 to 6 Years

Open access
Moody, Emily C., Cantoral, Alejandra, Tamayo-Ortiz, Marcela, Pizano-Zárate, Ma. Luisa, Schnaas, Lourdes, Kloog, Itai, Oken, Emily, Coull, Brent +4 more·2019·JAMA Network Open
DOI 10.1001/jamanetworkopen.2019.17643PMC PMC6991256
Open this paper in CoChat — free accountOpen PDF

Abstract

Importance: Environmental risk factors for childhood type 2 diabetes, an increasing global problem, are understudied. Air pollution exposure has been reported to be a risk factor for this condition. Objective: To examine the association between prenatal and perinatal exposures to fine particulate matter with a diameter less than 2.5 μm (PM2.5) and changes in hemoglobin A1c (HbA1c), a measure of glycated hemoglobin and marker of glucose dysregulation, in children aged 4 to 7 years. Design, Setting, and Participants: The Programming Research in Obesity, Growth, Environment, and Social Stressors (PROGRESS) study, a birth cohort study conducted in Mexico City, Mexico, recruited pregnant women from July 3, 2007, to February 21, 2011, through public health maternity clinics. The present analysis includes 365 mother-child pairs followed up until the child was approximately 7 years of age. This study included data from only study visits at approximately 4 to 5 years (visit 1) and 6 to 7 years (visit 2) post partum because HbA1c levels were not measured in earlier visits. The data were analyzed from March 11, 2018, to May 3, 2019. Exposures: Daily PM2.5 exposure estimates at participants' home addresses from 4 weeks prior to mothers' date of last menstrual period (LMP), a marker of the beginning of pregnancy, to 12 weeks after the due date. Exposure was estimated from satellite measurements and calibrated against ground PM2.5 measurements, land use, and meteorological variables. Main Outcomes and Measures: Outcomes included HbA1c levels at 4 to 5 years and 6 to 7 years of age, and the change in the level from the former age group to the latter. Results: The sample included 365 children, of whom 184 (50.4%) were girls. The mean (range) age of the children was 4.8 (4.0-6.4) years at visit 1, and 6.7 (6.0-9.7) years at visit 2. At the time of delivery, the mean (range) age of the mothers was 27.7 (18.3-44.4) years, with a mean (range) prepregnancy body mass index of 26.4 (18.5-43.5). The mean (SD) prenatal PM2.5 exposure (22.4 μg/m3 [2.7 μg/m3]) was associated with an annual increase in HbA1c levels of 0.25% (95% CI, 0.004%-0.50%) from age 4 to 5 years to 6 to 7 years compared with exposure at 12 μg/m3, the national regulatory standard in Mexico. Sex-specific effect estimates were statistically significant for girls (β = 0.21%; 95% CI, 0.10% to 0.32%) but not for boys (β = 0.31%; 95% CI, -0.09% to 0.72%). The statistically significant windows of exposure were from week 28 to 50.6 after the mother's LMP for the overall cohort and from week 11 to the end of the study period for girls. Lower HbA1c levels were observed at age 4 to 5 years in girls (β = -0.72%; 95% CI, -1.31% to -0.13%, exposure window from week 16 to 37.3) and boys (β = -0.98%; 95% CI, -1.70% to -0.26%, exposure window from the beginning of the study period to week 32.7), but no significant association was found in the overall cohort (β = -0.13%; 95% CI, -1.27% to 1.01%). There was no significant association between PM2.5 exposure and HbA1c level at age 6 to 7 years in any group. Conclusions and Relevance: The findings of this study suggest that prenatal and perinatal exposures to PM2.5 are associated with changes in HbA1c, which are indicative of glucose dysregulation, in early childhood. Further research is needed because this finding may represent a risk factor for childhood or adolescent diabetes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jamanetworkopen.2019.17643

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 62

  1. [1]Dabelea D, Mayer-Davis EJ, Saydah S,; SEARCH for Diabetes in Youth Study Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014; 311(17):-. doi: 10.1001/jama.2014.3201 24794371 PMC4368900 · DOI · Paper page
  2. [2]Mayer-Davis EJ, Lawrence JM, Dabelea D,; SEARCH for Diabetes in Youth Study Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012. N Engl J Med. 2017; 376(15): 1419- 1429. doi: 10.1056/NEJMoa1610187 28402773 PMC5592722 · DOI · Paper page
  3. [3]Dabelea D, Stafford JM, Mayer-Davis EJ,; SEARCH for Diabetes in Youth Research Group Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood. JAMA. 2017; 317(8): 825- 835. doi: 10.1001/jama.2017.0686 28245334 PMC5483855 · DOI · Paper page
  4. [5]Esposito K, Petrizzo M, Maiorino MI, Bellastella G, Giugliano D Particulate matter pollutants and risk of type 2 diabetes: a time for concern? Endocrine. 2016; 51(1): 32- 37. doi: 10.1007/s12020-015-0638-2 26024974 · DOI
  5. [7]Balti EV, Echouffo-Tcheugui JB, Yako YY, Kengne AP Air pollution and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2014; 106(2): 161- 172. doi: 10.1016/j.diabres.2014.08.010 25262110 · DOI
  6. [8]Eze IC, Hemkens LG, Bucher HC, Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta-analysis. Environ Health Perspect. 2015; 123(5): 381- 389. doi: 10.1289/ehp.1307823 25625876 PMC4421762 · DOI
  7. [9]He D, Wu S, Zhao H, Association between particulate matter 2.5 and diabetes mellitus: a meta-analysis of cohort studies. J Diabetes Investig. 2017; 8(5): 687- 696. doi: 10.1111/jdi.12631 28122165 PMC5583950 · DOI
  8. [10]Mao G, Nachman RM, Sun Q, Individual and joint effects of early-life ambient exposure and maternal prepregnancy obesity on childhood overweight or obesity. Environ Health Perspect. 2017; 125(6): 067005. doi: 10.1289/EHP261 28669938 PMC5743454 · DOI
  9. [11]Rundle A, Hoepner L, Hassoun A, Association of childhood obesity with maternal exposure to ambient air polycyclic aromatic hydrocarbons during pregnancy. Am J Epidemiol. 2012; 175(11): 1163- 1172. doi: 10.1093/aje/kwr455 22505764 PMC3491973 · DOI
  10. [12]Alderete TL, Habre R, Toledo-Corral CM, Longitudinal associations between ambient air pollution with insulin sensitivity, β-cell function, and adiposity in Los Angeles Latino children. Diabetes. 2017; 66(7): 1789- 1796. doi: 10.2337/db16-1416 28137791 PMC5482082 · DOI · Paper page
  11. [14]Chiu YH, Hsu HH, Coull BA, Prenatal particulate air pollution and neurodevelopment in urban children: examining sensitive windows and sex-specific associations. Environ Int. 2016; 87: 56- 65. doi: 10.1016/j.envint.2015.11.010 26641520 PMC4691396 · DOI
  12. [15]Chiu YM, Hsu HL, Wilson A, Prenatal particulate air pollution exposure and body composition in urban preschool children: examining sensitive windows and sex-specific associations. Environ Res. 2017; 158: 798- 805. doi: 10.1016/j.envres.2017.07.026 28759881 PMC5570541 · DOI
  13. [16]Rosa MJ, Just AC, Guerra MS, Identifying sensitive windows for prenatal particulate air pollution exposure and mitochondrial DNA content in cord blood. Environ Int. 2017; 98: 198- 203. doi: 10.1016/j.envint.2016.11.007 27843010 PMC5139686 · DOI · Paper page
  14. [17]Braun JM, Wright RJ, Just AC, Relationships between lead biomarkers and diurnal salivary cortisol indices in pregnant women from Mexico City: a cross-sectional study. Environ Health. 2014; 13(1): 50. doi: 10.1186/1476-069X-13-50 24916609 PMC4068833 · DOI
  15. [19]Just AC, Wright RO, Schwartz J, Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City. Environ Sci Technol. 2015; 49(14): 8576- 8584. doi: 10.1021/acs.est.5b00859 26061488 PMC4509833 · DOI
  16. [21]Burris HH, Baccarelli AA, Byun HM, Offspring DNA methylation of the aryl-hydrocarbon receptor repressor gene is associated with maternal BMI, gestational age, and birth weight. Epigenetics. 2015; 10(10): 913- 921. doi: 10.1080/15592294.2015.1078963 26252179 PMC4844209 · DOI
  17. [22]Ananth CV, Schisterman EF Confounding, causality, and confusion: the role of intermediate variables in interpreting observational studies in obstetrics. Am J Obstet Gynecol. 2017; 217(2): 167- 175. doi: 10.1016/j.ajog.2017.04.016 28427805 PMC5545051 · DOI
  18. [23]Capurro H, Konichezky S, Fonseca D, Caldeyro-Barcia R A simplified method for diagnosis of gestational age in the newborn infant. J Pediatr. 1978; 93(1): 120- 122. doi: 10.1016/S0022-3476(78)80621-0 650322 · DOI
  19. [24]Rosa MJ, Just AC, Tamayo y Ortiz M, Prenatal and postnatal stress and wheeze in Mexican children: sex-specific differences. Ann Allergy Asthma Immunol. 2016; 116(4): 306- 312.e1. doi: 10.1016/j.anai.2015.12.025 26822280 PMC4826313 · DOI
  20. [25]Gasparrini A, Scheipl F, Armstrong B, Kenward MG A penalized framework for distributed lag non-linear models. Biometrics. 2017; 73(3): 938- 948. doi: 10.1111/biom.12645 28134978 · DOI
  21. [26]Alderete TL, Chen Z, Toledo-Corral CM, Ambient and traffic-related air pollution exposures as novel risk factors for metabolic dysfunction and type 2 diabetes. Curr Epidemiol Rep. 2018; 5(2): 79- 91. doi: 10.1007/s40471-018-0140-5 30319933 PMC6178230 · DOI
  22. [27]Brook RD, Xu X, Bard RL, Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution. Sci Total Environ. 2013; 448: 66- 71. doi: 10.1016/j.scitotenv.2012.07.034 22901427 PMC4391076 · DOI
  23. [28]Chen Z, Salam MT, Toledo-Corral C, Ambient air pollutants have adverse effects on insulin and glucose homeostasis in Mexican Americans. Diabetes Care. 2016; 39(4): 547- 554. doi: 10.2337/dc15-1795 26868440 PMC4806768 · DOI
  24. [29]Fleisch AF, Gold DR, Rifas-Shiman SL, Air pollution exposure and abnormal glucose tolerance during pregnancy: the project Viva cohort. Environ Health Perspect. 2014; 122(4): 378- 383. doi: 10.1289/ehp.1307065 24508979 PMC3984217 · DOI
  25. [30]Honda T, Pun VC, Manjourides J, Suh H Associations between long-term exposure to air pollution, glycosylated hemoglobin and diabetes. Int J Hyg Environ Health. 2017; 220(7): 1124- 1132. doi: 10.1016/j.ijheh.2017.06.004 28712959 PMC5580354 · DOI
  26. [31]Lucht SA, Hennig F, Matthiessen C, Air pollution and glucose metabolism: an analysis in non-diabetic participants of the Heinz Nixdorf Recall Study. Environ Health Perspect. 2018; 126(4): 047001. doi: 10.1289/EHP2561 29616776 PMC6071794 · DOI
  27. [32]Peng C, Bind MC, Colicino E, Particulate air pollution and fasting blood glucose in nondiabetic individuals: associations and epigenetic mediation in the Normative Aging Study, 2000-2011. Environ Health Perspect. 2016; 124(11): 1715- 1721. doi: 10.1289/EHP183 27219535 PMC5089881 · DOI
  28. [33]Toledo-Corral CM, Alderete TL, Habre R, Effects of air pollution exposure on glucose metabolism in Los Angeles minority children. Pediatr Obes. 2018; 13(1): 54- 62. doi: 10.1111/ijpo.12188 27923100 PMC5722706 · DOI
  29. [34]Wolf K, Popp A, Schneider A,; KORA-Study Group Association between long-term exposure to air pollution and biomarkers related to insulin resistance, subclinical inflammation, and adipokines. Diabetes. 2016; 65(11): 3314- 3326. doi: 10.2337/db15-1567 27605624 · DOI
  30. [35]Rajagopalan S, Brook RD Air pollution and type 2 diabetes: mechanistic insights. Diabetes. 2012; 61(12): 3037- 3045. doi: 10.2337/db12-0190 23172950 PMC3501850 · DOI
  31. [37]Gingras V, Hivert MF, Oken E Early-life exposures and risk of diabetes mellitus and obesity. Curr Diab Rep. 2018; 18(10): 89. doi: 10.1007/s11892-018-1050-0 30159823 · DOI
  32. [38]Fleisch AF, Kloog I, Luttmann-Gibson H, Gold DR, Oken E, Schwartz JD Air pollution exposure and gestational diabetes mellitus among pregnant women in Massachusetts: a cohort study. Environ Health. 2016; 15: 40. doi: 10.1186/s12940-016-0121-4 26911579 PMC4765142 · DOI
  33. [40]Hu H, Ha S, Henderson BH, Association of atmospheric particulate matter and ozone with gestational diabetes mellitus. Environ Health Perspect. 2015; 123(9): 853- 859. doi: 10.1289/ehp.1408456 25794412 PMC4559952 · DOI
  34. [41]Robledo CA, Mendola P, Yeung E, Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus. Environ Res. 2015; 137: 316- 322. doi: 10.1016/j.envres.2014.12.020 25601734 PMC6204222 · DOI
  35. [42]Kish L, Hotte N, Kaplan GG, Environmental particulate matter induces murine intestinal inflammatory responses and alters the gut microbiome. PLoS One. 2013; 8(4): e62220. doi: 10.1371/journal.pone.0062220 23638009 PMC3634745 · DOI
  36. [43]Salim SY, Kaplan GG, Madsen KL Air pollution effects on the gut microbiota: a link between exposure and inflammatory disease. Gut Microbes. 2014; 5(2): 215- 219. doi: 10.4161/gmic.27251 24637593 PMC4063847 · DOI
  37. [44]Alderete TL, Jones RB, Chen Z, Exposure to traffic-related air pollution and the composition of the gut microbiota in overweight and obese adolescents. Environ Res. 2018; 161: 472- 478. doi: 10.1016/j.envres.2017.11.046 29220800 PMC5747978 · DOI · Paper page
  38. [45]Mutlu EA, Comba IY, Cho T, Inhalational exposure to particulate matter air pollution alters the composition of the gut microbiome. Environ Pollut. 2018; 240: 817- 830. doi: 10.1016/j.envpol.2018.04.130 29783199 PMC6400491 · DOI
  39. [46]Howe CG, Eckel SP, Habre R, Association of prenatal exposure to ambient and traffic-related air pollution with newborn thyroid function: findings from the Children’s Health Study. JAMA Netw Open. 2018; 1(5): e182172. doi: 10.1001/jamanetworkopen.2018.2172 30646156 PMC6324507 · DOI
  40. [47]Janssen BG, Saenen ND, Roels HA, Fetal thyroid function, birth weight, and in utero exposure to fine particle air pollution: a birth cohort study. Environ Health Perspect. 2017; 125(4): 699- 705. doi: 10.1289/EHP508 27623605 PMC5382000 · DOI · Paper page
  41. [48]Zhao Y, Cao Z, Li H, Air pollution exposure in association with maternal thyroid function during early pregnancy. J Hazard Mater. 2019; 367: 188- 193. doi: 10.1016/j.jhazmat.2018.12.078 30594719 · DOI
  42. [49]Lee AG, Kaali S, Quinn A, Prenatal household air pollution is associated with impaired infant lung function with sex-specific effects: evidence from GRAPHS, a cluster randomized Cookstove Intervention Trial. Am J Respir Crit Care Med. 2019; 199(6): 738- 746. doi: 10.1164/rccm.201804-0694OC 30256656 PMC6423100 · DOI
  43. [50]Hsu HH, Chiu YH, Coull BA, Prenatal particulate air pollution and asthma onset in urban children: identifying sensitive windows and sex differences. Am J Respir Crit Care Med. 2015; 192(9): 1052- 1059. doi: 10.1164/rccm.201504-0658OC 26176842 PMC4642201 · DOI
  44. [51]Lee A, Leon Hsu HH, Mathilda Chiu YH, Prenatal fine particulate exposure and early childhood asthma: effect of maternal stress and fetal sex. J Allergy Clin Immunol. 2018; 141(5): 1880- 1886. doi: 10.1016/j.jaci.2017.07.017 28801196 PMC5803480 · DOI
  45. [52]Bolton JL, Marinero S, Hassanzadeh T, Gestational exposure to air pollution alters cortical volume, microglial morphology, and microglia-neuron interactions in a sex-specific manner. Front Synaptic Neurosci. 2017; 9: 10. doi: 10.3389/fnsyn.2017.00010 28620294 PMC5449437 · DOI
  46. [53]Cowell WJ, Bellinger DC, Coull BA, Gennings C, Wright RO, Wright RJ Associations between prenatal exposure to black carbon and memory domains in urban children: modification by sex and prenatal stress. PLoS One. 2015; 10(11): e0142492. doi: 10.1371/journal.pone.0142492 26544967 PMC4636293 · DOI
  47. [54]Lakshmanan A, Chiu YH, Coull BA, Associations between prenatal traffic-related air pollution exposure and birth weight: modification by sex and maternal pre-pregnancy body mass index. Environ Res. 2015; 137: 268- 277. doi: 10.1016/j.envres.2014.10.035 25601728 PMC4354711 · DOI
  48. [55]Bolton JL, Auten RL, Bilbo SD Prenatal air pollution exposure induces sexually dimorphic fetal programming of metabolic and neuroinflammatory outcomes in adult offspring. Brain Behav Immun. 2014; 37: 30- 44. doi: 10.1016/j.bbi.2013.10.029 24184474 · DOI
  49. [56]Bolton JL, Smith SH, Huff NC, Prenatal air pollution exposure induces neuroinflammation and predisposes offspring to weight gain in adulthood in a sex-specific manner. FASEB J. 2012; 26(11): 4743- 4754. doi: 10.1096/fj.12-210989 22815382 · DOI
  50. [57]Ghosh R, Rankin J, Pless-Mulloli T, Glinianaia S Does the effect of air pollution on pregnancy outcomes differ by gender? a systematic review. Environ Res. 2007; 105(3): 400- 408. doi: 10.1016/j.envres.2007.03.009 17493608 · DOI
  51. [58]Galjaard S, Ameye L, Lees CC, Sex differences in fetal growth and immediate birth outcomes in a low-risk Caucasian population. Biol Sex Differ. 2019; 10(1): 48. doi: 10.1186/s13293-019-0261-7 31500671 PMC6734449 · DOI
  52. [59]Rosenfeld CS Sex-specific placental responses in fetal development. Endocrinology. 2015; 156(10): 3422- 3434. doi: 10.1210/en.2015-1227 26241064 PMC4588817 · DOI
  53. [60]Shivers KY, Amador N, Abrams L, Hunter D, Jenab S, Quiñones-Jenab V Estrogen alters baseline and inflammatory-induced cytokine levels independent from hypothalamic-pituitary-adrenal axis activity. Cytokine. 2015; 72(2): 121- 129. doi: 10.1016/j.cyto.2015.01.007 25647266 PMC4365931 · DOI
  54. [61]Borai A, Livingstone C, Abdelaal F, Bawazeer A, Keti V, Ferns G The relationship between glycosylated haemoglobin (HbA1c) and measures of insulin resistance across a range of glucose tolerance. Scand J Clin Lab Invest. 2011; 71(2): 168- 172. doi: 10.3109/00365513.2010.547947 21348785 · DOI
  55. [62]Chan CL, Pyle L, Newnes L, Nadeau KJ, Zeitler PS, Kelsey MM Continuous glucose monitoring and its relationship to hemoglobin A1c and oral glucose tolerance testing in obese and prediabetic youth. J Clin Endocrinol Metab. 2015; 100(3): 902- 910. doi: 10.1210/jc.2014-3612 25532041 PMC4333034 · DOI
  56. [63]Jansen H, Wijga AH, Scholtens S, Change in HbA1c levels between the age of 8 years and the age of 12 years in Dutch children without diabetes: the PIAMA birth cohort study. PLoS One. 2015; 10(4): e0119615. doi: 10.1371/journal.pone.0119615 25875773 PMC4395421 · DOI
  57. [64]Saaddine JB, Fagot-Campagna A, Rolka D, Distribution of HbA(1c) levels for children and young adults in the U.S.: Third National Health and Nutrition Examination Survey. Diabetes Care. 2002; 25(8): 1326- 1330. doi: 10.2337/diacare.25.8.1326 12145229 · DOI · Paper page
  58. [66]Zhao K, Ju H, Wang H Metabolic characteristics of obese children with fatty liver: a STROBE-compliant article. Medicine (Baltimore). 2019; 98(16): e14939. doi: 10.1097/MD.0000000000014939 31008924 PMC6494399 · DOI
  59. [67]Beraki Å, Magnuson A, Särnblad S, Åman J, Samuelsson U Increase in physical activity is associated with lower HbA1c levels in children and adolescents with type 1 diabetes: results from a cross-sectional study based on the Swedish pediatric diabetes quality registry (SWEDIABKIDS). Diabetes Res Clin Pract. 2014; 105(1): 119- 125. doi: 10.1016/j.diabres.2014.01.029 24846445 · DOI
  60. [68]Onal ZE, Atasayan V, Gürbüz T, Hepkaya E, Nuhoğlu C Association of glycosylated hemoglobin (HbA1c) levels with insulin resistance in obese children. Afr Health Sci. 2014; 14(3): 533- 538. doi: 10.4314/ahs.v14i3.6 25352869 PMC4209635 · DOI
  61. [69]Vijayakumar P, Nelson RG, Hanson RL, Knowler WC, Sinha M HbA1c and the prediction of type 2 diabetes in children and adults. Diabetes Care. 2017; 40(1): 16- 21. doi: 10.2337/dc16-1358 27810987 PMC5180461 · DOI · Paper page
  62. [71]Weisskopf MG, Webster TF Trade-offs of personal versus more proxy exposure measures in environmental epidemiology. Epidemiology. 2017; 28(5): 635- 643. doi: 10.1097/EDE.0000000000000686 28520644 PMC5543716 · DOI

Cited by

Sorted by citations

Authors
Moody, E. C., Cantoral, A., Tamayo-Ortiz, M., Pizano-Zárate, M. L., Schnaas, L., Kloog, I., Oken, E., Coull, B., Baccarelli, A., Téllez-Rojo, M. M., Wright, R. O., & Just, A. C.
Affiliations
  • Icahn School of Medicine at Mount Sinai (US)
  • Instituto Nacional de Salud Pública (MX)
  • Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Mexico
  • Instituto Nacional de Perinatología (MX)
  • Ben-Gurion University of the Negev (IL)
  • Harvard University (US)
  • Columbia University (US)
Corresponding author
Moody, Emily C.
ORCID
Venue
JAMA Network Open
Publisher
American Medical Association (AMA)
Published
2019-12-18
Volume
2
Issue
12
Pages
e1917643
ISSN
2574-3805 (ISSN-L)
DOI
10.1001/jamanetworkopen.2019.17643
PMC
PMC6991256
OpenAlex
W2995391420
Cited by
27
References
7
Citations by year
2026: 2 · 2025: 3 · 2024: 4 · 2023: 1 · 2022: 7 · 2021: 7 · 2020: 3
FWCI
1.84
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Network Open (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UNM’s Digital Repository (University of New Mexico) (submittedVersion)
Funders
  • National Institutes of Health (UL1TR001433)
  • National Institute of Environmental Health Sciences (and P30ES000002, R00ES023450, P30ES000002, R24ES028522, R01ES021357, R01ES013744)
  • National Center for Advancing Translational Sciences
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32HD049311)
Topics
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Birth, Development, and Health
  • Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
Keywords
PM2.5, air pollution exposure, prenatal exposure, perinatal exposure, HbA1c, glucose dysregulation, birth cohort, PROGRESS study, Mexico City, maternal alcohol consumption, maternal obesity
MeSH terms
Air Pollutants, Air Pollution, Child, Child, Preschool, Diabetes Mellitus, Type 2, Environmental Exposure, Female, Glycated Hemoglobin, Humans, Male, Mexico, Pregnancy, Prenatal Exposure Delayed Effects, Prospective Studies, Risk Factors, Biomarkers, Particulate Matter

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review