Neighborhood Deprivation is Associated with Increased Risk of Prenatal Smoke Exposure
Tóm tắt
Despite years of advisories against the behavior, smoking among pregnant women remains a persistent public health issue in the USA. Recent estimates suggest that 9.4% of women smoke before pregnancy and 7.1% during pregnancy in the USA. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy, including educational attainment, employment status, housing conditions, poverty, and racial demographics. However, most of these studies have relied upon self-reported measures of smoking, which are subject to reporting bias. To more accurately and objectively assess smoke exposure in mothers during pregnancy, we used Bayesian index models to estimate a neighborhood deprivation index (NDI) for block groups in Durham County, North Carolina, and its association with cotinine, a marker of smoke exposure, in pregnant mothers (n = 887 enrolled 2005–2011). Results showed a significant positive association between NDI and log cotinine (beta = 0.20, 95% credible interval = [0.11, 0.29]) after adjusting for individual covariates (e.g., race/ethnicity and education). The two most important variables in the NDI according to the estimated index weights were percent females without a high school degree and percent Black population. At the individual level, Hispanic and other race/ethnicity were associated with lowered cotinine compared with non-Hispanic Whites. Higher education levels were also associated with lowered cotinine. In summary, our findings provide stronger evidence that the socio-geographic variables of educational attainment and neighborhood racial composition are important factors for smoking and secondhand smoke exposure during pregnancy and can be used to target intervention efforts.
Tài liệu tham khảo
Adams, E. K., Markowitz, S., Kannan, V., Dietz, P. M., Tong, V. T., & Malarcher, A. M. (2012). Reducing prenatal smoking: The role of state policies. American Journal of Preventive Medicine, 43, 34–40.
Averett, S., & Wang, Y. (2013). The effects of earned income tax credit payment expansion on maternal smoking. Health Economics, 22, 1344–1359. https://doi.org/10.1002/hec.2886
Bailey, B. A. (2006). Factors predicting pregnancy smoking in Southern Appalachia. American Journal of Health Behavior, 30, 413–421.
Benowitz, N. L., Bernert, J. T., Caraballo, R. S., Holiday, D. B., & Wang, J. (2009). Optimal serum cotinine levels for distinguishing cigarette smokers and nonsmokers within different racial/ethnic groups in the United States between 1999 and 2004. American Journal of Epidemiology, 169, 236–248. https://doi.org/10.1093/aje/kwn301
Bernert, J. T., Jacob, P., Holiday, D. B., Benowitz, N. L., Sosnoff, C. S., Doig, M. V., Feyerabend, C., Aldous, K. M., Sharifi, M., Kellogg, M. D., & Langman, L. J. (2009). Interlaboratory comparability of serum cotinine measurements at smoker and nonsmoker concentration levels: A round-robin study. Nicotine & Tobacco Research, 11, 1458–1466. https://doi.org/10.1093/ntr/ntp161
Bronfenbrenner, U. (1992). Ecological systems theory. In Six theories of child development: Revised formulations and current issues. (pp. 187–249). Jessica Kingsley Publishers.
BullCity150. (2018). Bull City 150. bullcity150.org
Colman, G. J., & Joyce, T. (2003). Trends in smoking before, during, and after pregnancy in ten states. American Journal of Preventive Medicine, 24, 29–35.
Cowan, B., & Tefft, N. (2012). Education, maternal smoking, and the earned income tax credit. The B.E. Journal of Economic Analysis & Policy, 12(1). https://doi.org/10.1515/1935-1682.3305
Crume, T. (2019). Tobacco use during pregnancy. Clinical Obstetrics and Gynecology, 62, 128–141. https://doi.org/10.1097/GRF.0000000000000413
Dempsey, D. A., Meyers, M. J., Oh, S. S., Nguyen, E. A., Fuentes-Afflick, E., Wu, A. H. B., Jacob III, P., & Benowitz, N. L. (2012). Determination of tobacco smoke exposure by plasma cotinine levels in infants and children attending urban public hospital clinics. Archives of Pediatrics & Adolescent Medicine, 166(9). https://doi.org/10.1001/archpediatrics.2012.170
Dietz, P. M., Homa, D., England, L. J., Burley, K., Tong, V. T., Dube, S. R., & Bernert, J. T. (2011). Estimates of nondisclosure of cigarette smoking among pregnant and nonpregnant women of reproductive age in the United States. American Journal of Epidemiology, 173, 355–359. https://doi.org/10.1093/aje/kwq381
Do, E. K., Green, T. L., Prom-Wormley, E. C., & Fuemmeler, B. F. (2018). Social determinants of smoke exposure during pregnancy: Findings from waves 1 & 2 of the Population Assessment of Tobacco and Health (PATH) Study. Preventive Medicine Reports, 12, 312–320. https://doi.org/10.1016/j.pmedr.2018.10.020
Florescu, A., Ferrence, R., Einarson, T., Selby, P., Soldin, O., & Koren, G. (2009). Methods for quantification of exposure to cigarette smoking and environmental tobacco smoke: Focus on developmental toxicology. Therapeutic Drug Monitoring, 31, 14–30. https://doi.org/10.1097/FTD.0b013e3181957a3b
Fuemmeler, B. F., Dozmorov, M. G., Do, E. K., Zhang, J., Grenier, C., Huang, Z., Maguire, R. L., Kollins, S. H., Hoyo, C., & Murphy, S. K. (2020). DNA methylation in babies born to non-smoking mothers exposed to secondhand smoke during pregnancy: An epigenome-wide association study.
Galiatsatos, P., Brigham, E., Krasnoff, R., Rice, J., Van Wyck, L., Sherry, M., Rand, C. S., Hansel, N. N., & McCormack, M. C. (2020). Association between neighborhood socioeconomic status, tobacco store density and smoking status in pregnant women in an urban area. Preventive Medicine, 136, 106107.
Geweke, J. F. (1991). Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments.
Grant, L. P., Gennings, C., Wickham, E. P., Chapman, D., Sun, S., & Wheeler, D. C. (2018). Modeling pediatric body mass index and neighborhood environment at different spatial scales. In International Journal of Environmental Research and Public Health (Vol. 15, Issue 3). https://doi.org/10.3390/ijerph15030473
Higgins, S. T., Bernstein, I. M., Washio, Y., Heil, S. H., Badger, G. J., Skelly, J. M., Higgins, T. M., & Solomon, L. J. (2010). Effects of smoking cessation with voucher-based contingency management on birth outcomes. Addiction (abingdon, England), 105, 2023–2030. https://doi.org/10.1111/j.1360-0443.2010.03073.x
Houston-Ludlam, A. N., Waldron, M., Lian, M., Cahill, A. G., McCutcheon, V. V, Madden, P. A. F., Bucholz, K. K., & Heath, A. C. (2020). Marital status, partner acknowledgment of paternity, and neighborhood influences on smoking during first pregnancy: Findings across race/ethnicity in linked administrative and census data. Drug and Alcohol Dependence, 217, 108273.
Hoyo, C., Murtha, A. P., Schildkraut, J. M., Jirtle, R. L., Demark-Wahnefried, W., Forman, M. R., Iversen, E. S., Kurtzberg, J., Overcash, F., Huang, Z., & Murphy, S. K. (2011). Methylation variation at IGF2 differentially methylated regions and maternal folic acid use before and during pregnancy. Epigenetics, 6, 928–936. https://doi.org/10.4161/epi.6.7.16263
Ingall, G., & Cropley, M. (2010). Exploring the barriers of quitting smoking during pregnancy: A systematic review of qualitative studies. Women and Birth, 23(2), 45–52. https://doi.org/10.1016/j.wombi.2009.09.004
Jacob, P., Yu, L., Duan, M., Ramos, L., Yturralde, O., & Benowitz, N. L. (2011). Determination of the nicotine metabolites cotinine and trans-3′-hydroxycotinine in biologic fluids of smokers and non-smokers using liquid chromatography–tandem mass spectrometry: Biomarkers for tobacco smoke exposure and for phenotyping cytochrome P450 2. Journal of Chromatography B, 879(3), 267–276. https://doi.org/10.1016/j.jchromb.2010.12.012
Jedrychowski, W., Perera, F., Mroz, E., Edwards, S., Flak, E., Bernert, J. T., Mrozek-Budzyn, D., Sowa, A., & Musiał, A. (2009). Fetal exposure to secondhand tobacco smoke assessed by maternal self-reports and cord blood cotinine: Prospective cohort study in Krakow. Maternal and Child Health Journal, 13, 415–423. https://doi.org/10.1007/s10995-008-0350-4
Joubert, B. R., Felix, J. F., Yousefi, P., Bakulski, K. M., Just, A. C., Breton, C., Reese, S. E., Markunas, C. A., Richmond, R. C., Xu, C.-J., Küpers, L. K., Oh, S. S., Hoyo, C., Gruzieva, O., Söderhäll, C., Salas, L. A., Baïz, N., Zhang, H., Lepeule, J., … London, S. J. (2016). DNA methylation in newborns and maternal smoking in pregnancy: Genome-wide consortium meta-analysis. The American Journal of Human Genetics, 98(4), 680–696. https://doi.org/10.1016/j.ajhg.2016.02.019
Kaneita, Y., Tomofumi, S., Takemura, S., Suzuki, K., Yokoyama, E., Miyake, T., Harano, S., Ibuka, E., Kaneko, A., Tsutsui, T., et al. (2007). Prevalence of smoking and associated factors among pregnant women in Japan. Preventive Medicine, 45, 15–20.
Kondracki, A. J. (2019). Prevalence and patterns of cigarette smoking before and during early and late pregnancy according to maternal characteristics: The first national data based on the 2003 birth certificate revision, United States, 2016. Reproductive Health, 16, 142. https://doi.org/10.1186/s12978-019-0807-5
Kyrklund-Blomberg, N. B., Granath, F., & Cnattingius, S. (2005). Maternal smoking and causes of very preterm birth. Acta Obstetricia Et Gynecologica Scandinavica, 84, 572–577. https://doi.org/10.1080/j.0001-6349.2005.00848.x
LeClere, F. B., & Wilson, J. B. (1997). Smoking behavior of recent mothers, 18–44 years of age, before and after pregnancy: United States, 1990.
Lian, M., Madden, P. A., Lynskey, M. T., Colditz, G. A., Lessov-Schlaggar, C. N., Schootman, M., & Heath, A. C. (2016). Geographic variation in maternal smoking during pregnancy in the Missouri Adolescent Female Twin Study (MOAFTS). PloS One, 11, e0153930. https://doi.org/10.1371/journal.pone.0153930
Liu, Y., Murphy, S. K., Murtha, A. P., Fuemmeler, B. F., Schildkraut, J., Huang, Z., Overcash, F., Kurtzberg, J., Jirtle, R., Iversen, E. S., Forman, M. R., & Hoyo, C. (2012). Depression in pregnancy, infant birth weight and DNA methylation of imprint regulatory elements. Epigenetics, 7, 735–746. https://doi.org/10.4161/epi.20734
Lunn, D. J., Thomas, A., Best, N., & Spiegelhalter, D. (2000). WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility. Statistics and Computing, 10, 325–337. https://doi.org/10.1023/A:1008929526011
Pichini, S., Basagaña, X. B., Pacifici, R., Garcia, O., Puig, C., Vall, O., Harris, J., Zuccaro, P., Segura, J., & Sunyer, J. (2000). Cord serum cotinine as a biomarker of fetal exposure to cigarette smoke at the end of pregnancy. Environmental Health Perspectives, 108, 1079–1083. https://doi.org/10.1289/ehp.001081079
Räisänen, S., Kramer, M. R., Gissler, M., Saari, J., Hakulinen-Viitanen, T., & Heinonen, S. (2014). Smoking during pregnancy was up to 70% more common in the most deprived municipalities — A multilevel analysis of all singleton births during 2005–2010 in Finland. Preventive Medicine, 67, 6–11. https://doi.org/10.1016/j.ypmed.2014.06.026
Schechter, J., Do, E. K., Zhang, J., Hoyo, C., Murphy, S. K., Kollins, S. H., & Fuemmeler, B. (2020). Effect of prenatal smoke exposure on birth weight: The moderating role of maternal depressive symptoms. Nicotine & Tobacco Research, 22(40):47. https://doi.org/10.1093/ntr/nty267
Shoff, C., & Yang, T. -C. (2013). Understanding maternal smoking during pregnancy: Does residential context matter? Social Science & Medicine, 78, 50–60. https://doi.org/10.1016/j.socscimed.2012.11.027
Tong, V. T., Farr, S. L., Bombard, J., DʼAngelo, D., Ko, J. Y., & England, L. J. (2016). Smoking before and during pregnancy among women reporting depression or anxiety. Obstetrics and Gynecology, 128, 562–570. https://doi.org/10.1097/AOG.0000000000001595
Wagenaar, A. C., Livingston, M. D., Markowitz, S., & Komro, K. A. (2019). Effects of changes in earned income tax credit: Time-series analyses of Washington DC. SSM - Population Health, 7, 100356. https://doi.org/10.1016/j.ssmph.2019.100356
Wen, X., Eiden, R. D., Justicia-Linde, F. E., Wang, Y., Higgins, S. T., Thor, N., Haghdel, A., Peters, A. R., & Epstein, L. H. (2019). A multicomponent behavioral intervention for smoking cessation during pregnancy: A nonconcurrent multiple-baseline design. Translational Behavioral Medicine, 9, 308–318. https://doi.org/10.1093/tbm/iby027
Wheeler, D. C., Boyle, J., Raman, S., & Nelson, E. J. (2021). Modeling elevated blood lead level risk across the United States. Science of the Total Environment, 769, 145237. https://doi.org/10.1016/j.scitotenv.2021.145237
Wheeler, D. C., Czarnota, J., & Jones, R. M. (2017). Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence. PloS One, 12, e0179272. https://doi.org/10.1371/journal.pone.0179272
Wheeler, D. C., Do, E. K., Hayes, R. B., Fugate-Laus, K., Fallavollita, W. L., Hughes, C., & Fuemmeler, B. F. (2020). Neighborhood disadvantage and tobacco retail outlet and vape shop outlet rates. International Journal of Environmental Research and Public Health, 17(8). https://doi.org/10.3390/ijerph17082864
Wheeler, D. C., Jones, R. M., Schootman, M., & Nelson, E. J. (2019a). Explaining variation in elevated blood lead levels among children in Minnesota using neighborhood socioeconomic variables. Science of the Total Environment, 650, 970–977. https://doi.org/10.1016/j.scitotenv.2018.09.088
Wheeler, D. C., Raman, S., Jones, R. M., Schootman, M., & Nelson, E. J. (2019b). Bayesian deprivation index models for explaining variation in elevated blood lead levels among children in Maryland. Spatial and Spatio-Temporal Epidemiology, 30, 100286. https://doi.org/10.1016/j.sste.2019.100286
Xu, J. Q., Murphy, S. L., Kochanek, K. D., & Arias, E. (2020). Mortality in the United States, 2018.
Yang, T. -C., Shoff, C., Noah, A. J., Black, N., & Sparks, C. S. (2014). Racial segregation and maternal smoking during pregnancy: A multilevel analysis using the racial segregation interaction index. Social Science & Medicine, 107, 26–36. https://doi.org/10.1016/j.socscimed.2014.01.030
Zawadzka, M., Buczyński, A., Stelmach, W., Kowalska, A., & Henrykowska, G. (2018). Smoking-related behaviours of pregnant women depending on their place of residence. Central European Journal of Public Health, 26(1), 34–38. https://doi.org/10.21101/cejph.a4564