Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA

1 Department of Geology and Geography, Georgia Southern University, Statesboro, Georgia 30460-8149, USA;
2 Department of Geography and Anthropology, Kennesaw State University, Kennesaw, Georgia 30144-5591, USA;
3 Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia 30460-8015, USA

Special Issues: Spatial Aspects of Health: Methods and Applications

This study estimates the neighborhood socioeconomic status (SES) effect on the risk of preterm birth (PTB) using multilevel regression (MLR) models. Birth data retrieved from year 2000 and 2010 Georgia Vital Records were linked to their respective census tracts. Principle component analysis (PCA) was performed on nine selected census variables and the first two principal components (Fac1 and Fac2) were used to represent the neighborhood-level SES in the MLR models. Two-level random intercept MLR models were specified using 122,744 and 112,578 live and singleton births at the individual level and 1613 and 1952 census tracts at the neighborhood level, for 2000 and 2010, respectively. After adjustment for individual level factors, Fac1, which represents disadvantaged SES, respectively generated an Odds Ratio of 1.056 (95% CI: 1.031-1.081) and 1.080 (95% CI: 1.056-1.105) for these two years, showing a modest but statistically significant effect on PTB. After adjusting for individual level factors and the census tract level factors, Intra-class correlation (ICC) was 1.2% and 1.4%, for year 2000 and 2010, respectively. The two IOR-80% intervals, 0.73-1.52 (year 2000) and 0.73-1.59 (year 2010) suggest large unexplained between census tract variation. The Median Odds Ratio (MOR) value of 1.21(year 2000) and 1.23 (year 2010) revealed that the un-modeled neighborhood effect was smaller than two individual-level predictor variables, race, and tobacco use but larger than the fixed effect of census tract-level predicting variable, Fac1 and all the other individual level factors. Overall, better census tract level SES was found to have a modest protective effect for PTB risk and the effects of the two examined years were similar. Large unexplained between census tract heterogeneity warrants more sophisticated MLR models to further investigate the PTB risk factors and their interactions at both individual and neighborhood levels.
  Figure/Table
  Supplementary
  Article Metrics

References

1. Callaghan WM, MacDorman MF, Rasmussen SA, et al. (2006) The contribution of preterm birth to infant mortality rates in the United States. Pediatrics 118:1566-1573.    

2. U.S. Centers for Disease Control and Prevention. (2013) Preterm Birth. Available from: http://www.cdc.gov/reproductivehealth/MaternalInfantHealth/PretermBirth.htm.

3. Berkowitz GS, Papiernik E. (1993) Epidemiology of preterm birth. Epidemiol. Rev.15 :414-443.

4. Institute of Medicine. (1985) Preventing low birthweight. Washington, D.C.: National Academy Press.

5. March of Dimes. (2012) 2012 Premature Birth Report Card. Available from: http://www.marchofdimes.com/peristats/pdflib/998/us.pdf.

6. March of Dimes. (2014) 2014 Premature Birth Report Card. Available from: http://www.marchofdimes.org/materials/premature-birth-report-card-united-states.pdf.

7. Ritz B, Yu F, Chapa G, et al. (2000) Effect of Air Pollution on Preterm Birth among Children Born in Southern California between 1989 and 1993. Epidemiology 11:502-511.    

8. Kyrklund-Blomberg NB, Granath F, Cnattingius S. (2005) Maternal smoking and causes of very preterm birth. Acta Obstet. Gynecol. Scand. 84:572-577.

9. Behrman JR, Rosenzweig MR. (2001) The Returns to Increasing Body Weight. Penn Institute For Economic Research, PIER Working Paper 01-052. Available at SSRN: http://ssrn.com/abstract=297919 or http://dx.doi.org/10.2139/ssrn.297919.

10. Collins JW, David RJ, Simon DM, et al. (2007) Preterm birth among African American and white women with a lifelong residence in high-income Chicago neighborhoods: an exploratory study. Ethnic. Dis. 17: 113-117.

11. Kramer MR, Hogue CR. (2009) What causes racial disparities in very preterm birth? A biosocial perspective. Epidemiol. Rev. 31: 84-98

12. Darrow LA, Strickland MJ, Klein M., et al. (2009) Seasonality of birth and implications for temporal studies of preterm birth. Epidemiology 20:699-706.

13. Miranda ML, Messer LC, Kroeger GL. (2012) Associations between the Quality of the Residential Built Environment and Pregnancy Outcomes among Women in North Carolina. Environ. Health Perspect. 120:471-477.

14. Shi X, Ayotte JD, Onda A, et al. (2015) Geospatial association between adverse birth outcomes and arsenic in groundwater in New Hampshire, USA. Environ. Geochem. Health 37 :333-351.

15. Pickett KE, Pearl M (2001) Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J. Epidemiol. Commun. H.55:111-122.

16. Herrick H. (1996) The association of poverty and residence in predominantly Black neighborhoods with the occurrence of preterm births among Black women: a case-control study of three North Carolina metropolitan areas. Vol. 99, Special Report by the State Center for Health and Environmental Statistics. Raleigh, NC: North Carolina Department of Environment, Health, and Natural Resources.

17. Roberts, EM. (1997) Neighborhood social environments and the distribution of low birthweight in Chicago. Am. J. Public Health 87:597-603.

18. Kaufman JS, Dole N, Savitz DA, et al. (2003) Modeling community-level effects on preterm birth. Ann. Epidemiol.13:377-384.

19. DeFranco EA, Lian M, Muglia LA, et al. (2008) Area-level poverty and preterm birth risk: a population-based multilevel analysis. BMC Public Health 8:316-316.    

20. O'Campo P, Xue X, Wang MC, et al. (1997) Neighborhood risk factors for low birthweight in Baltimore: a multilevel analysis. Am. J. Public Health 87 :1113-8.

21. Duncan C, Jones K, Moon G. (1998) Context, composition and heterogeneity: Using multilevel models in health research. Soc. Sci. Med. 46:97-117.    

22. Merlo J. (2003) Multilevel Analytical Approaches in Social Epidemiology: Measures of Health Variation Compared with Traditional Measures of Association. J. Epidemiol. Commun. H. 57:550-552.

23. Behrman, RE, Butler AS. (2007) Preterm birth: causes, consequences, and prevention., Institute of Medicine of the National Academies: Washington, D.C. : National Academies Press.

24. Bahl R, Martines J, Bhandari N, et al. (2012) Setting research priorities to reduce global mortality from preterm birth and low birth weight by 2015. J. Glob. Health 2 :10403-10403.

25. ShionoPH, Klebanoff MA. (1993) A review of risk scoring for preterm birth. Clin. Perinatol. 20:107-125.

26. Public Health Foundation. (1995). Measuring state expenditures for core public health functions. Am. J. Prev. Med. 11: 58-73.

27. Ren, X. (2013). Investigating the association of preterm birth and residential stability in Georgia. Emory University Master's Thesis. Available from: https://etd.library.emory.edu/view/record/pid/emory:dwfsq

28. Messina LC. (2012). Investigating the association between small-area violent crime and preterm birth in Atlanta, GA: 1998-2006.Emory University Master's Thesis. Available from: https://etd.library.emory.edu/view/record/pid/emory:bqjsm.

29. Tu W, Tu J, Tedders S. (2014). Estimating Neighborhood-level Socio-Economic Effect on Preterm Births Using a Multilevel Approach: A Case Study of Georgia, USA. Ann. GIS 20:181-191.    

30. English PB, Kharrazi M, Davies S, et al. (2003) Changes in the spatial pattern of low birth weight in a southern California county: the role of individual and neighborhood level factors. Soc. Sci. Med. 56: 2073-2088.    

31. Messer LC, Laraia BA, Kaufman JS, et al. (2006) The development of a standardized neighborhood deprivation index. J. Urban Health 83:1041-1062.    

32. Sanagou M, Wolfe R, Forbes A, et al. (2012) Hospital-level associations with 30-day patient mortality after cardiac surgery: a tutorial on the application and interpretation of marginal and multilevel logistic regression. BMC Med. Res. Methodol. 12:28-28.

33. Larsen K, Merlo J. (2005) Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression. American Journal Of Epidemiology 161:81-88.Rauh VA, Andrews HF, Garfinkel RS. (2001) The Contribution of Maternal Age to Racial Disparities in Birthweight: A Multilevel Perspective. Am. J. Public Health 91: 1815-1824.

34. Collins J, Rankin K, David R. (2011) Low Birth Weight Across Generations: The Effect of Economic Environment. Matern. Child Healt. J. 15: 438-445.    

35. Kearns R, Moon R.(2002) From medical to health geography: novelty, place and theory after a decade of change. Pro. Hum. Geog. 26: 605-625.

36. Gelman A, Hill J. (2007) Data analysis using regression and multilevel/hierarchical models. Analytical methods for social research. Cambridge ; New York: Cambridge University Press.

37. Demidenko EZ. (2004) Mixed models : theory and applications, Wiley series in probability and statistics: Hoboken, N.J. : Wiley.

38. Snijders TAB, Bosker RJ. (2012) Multilevel analysis : an introduction to basic and advanced multilevel modeling: Los Angeles; London: SAGE, 2nd ed.

39. R Core Team. 2013. "R: A Language and Environment for Statistical Computing." http://www.r-project.org/.

40. Goldstein H, Browne W, Rasbash J. (2002) Partitioning Variation in Multilevel Models. Understanding Statistics 1: 223-232.    

41. Merlo, J., Chaix B, Ohlsson H, et al. (2006) A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J. Epidemiol. Commun. 60:290-297.

42. Merlo, J., Yang M, Chaix B, et al. (2005) A brief conceptual tutorial on multilevel analysis in social epidemiology: investigating contextual phenomena in different groups of people J. Epidemiol. Commun. 59: 729-736.    

43. Akaike H. (1974) A new look at the statistical model identification. IEEE Trans. Autom. Control 19:716-723.    

44. Geronimus AT, Bound J, Neidert LJ. (1996) On the validity of using census geocode characteristics to proxy individual socioeconomic characteristics. J Am Stat Ass 91: 529-537.    

45. Kwan MP. (2012) The Uncertain Geographic Context Problem. J. Am. Stat. Assoc. 102: 958-968.

46. Wang FH, Guo DS, McLafferty S. (2012) Constructing geographic areas for cancer data analysis: A case study on late-stage breast cancer risk in Illinois. Appl. Geogr. 35:1-11.    

47. Shi W. (2010) Principles of modeling uncertainties in spatial data and analyses." Boca Raton FL: CRC Press/Taylor & Francis.

48. Subramanian S, Chen JT, Rehkopf DH, et al. (2006) Comparing individual- and area-based socioeconomic measures for the surveillance of health disparities: a multilevel analysis of Massachusetts births, 1989–1991. Am. J. Epidemiol. 164:823-834.

49. Cubbin C, Marchi K, Lin M, et al. (2008) Is neighborhood deprivation independently associated with maternal and infant health? Evidence from Florida and Washington. Matern. Child Healt. J. 12:61-74.

50. Behrman BE, Butler AS. (2007) Preterm Birth: Causes, Consequences, and Prevention. Washington, D.C.: National Academy Press.

51. Quesada O, Gotman N, Howell HB, et al. (2012) Prenatal hazardous substance use and adverse birth outcomes. J. Matern. Fetal Neonatal Med. 25: 1222-1227.    

52. Llop S1, Ballester F, Estarlich M, et al. (2010). Preterm birth and exposure to air pollutants during pregnancy. Environ. Res. 110: 778-85.    

53. Partridge S, Balayla J, Holcroft CA, et al. (2012) Inadequate prenatal care utilization and risks of infant mortality and poor birth outcome: a retrospective analysis of 28,729,765 U.S. deliveries over 8 years. Am. J. Perinat. 29:787-793.

54. Ma X. (2013) Food Environment and Birth Outcomes In University of South Carolina. (Doctoral dissertation). Retrieved from http://scholarcommons.sc.edu/etd/2330

55. Daniel M, Moore S, Kestens Y. (2008) Framing the biosocial pathways underlying associations between place and cardiometabolic disease. Health & Place 14:117–132.

56. Meng G, Thompson ME, Hall GB. (2013) Pathways of neighborhood-level socio-economic determinants of adverse birth outcomes. Int. J. Health Geogr. 12: 32. doi: 10.1186/1476-072X-12-32    

57. Townsend P, Davidson N, Whitehead M. (1992) Inequalities in Health: the Black Report and the Health Divide. New York: Penguin.

58. Richmond ME. (1917) Social diagnosis. New York: Russell Sage Foundation.

59. Moellering H, Tobler W. (1972) Geographical Variances. Geogr. Anal. 4:34-50.

60. Jones K. (1991). Specifying and Estimating Multi-Level Models for Geographical Research. Trans. Inst. Br. Geogr. 2:148-159.

61. Robinson WS. (1950). Ecological correlations and the behavior of individuals. Am. Sociol. Rev. 15:351-357.    

62. Macintyre S,Ellaway A, Cummins S. (2002). Place effects on health: how can we conceptualise, operationalise and measure them? Soc. Sci. Med. 55:125-139.    

Copyright Info: © 2015, Wei Tu, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline
Copyright © AIMS Press All Rights Reserved