Residential mobility during pregnancy

1. Residential mobility during pregnancy Assia Miller 12th MCH Conference, Atlanta, Georgia December 7, 2006 National Center on Birth Defects and Developmental Disabilities DISCLAIMER: "The findings and conclusions in this presentation have not been formally disseminated by the Centers for Disease Control and Prevention and should not be construed to represent any agency determination or policy."

2. Background • Perinatal outcome surveillance systems usually record the mother’s residence at the time of delivery • This information is used in studies of birth defects for imputing potential environmental exposures during the first trimester • The use of birth addresses assumes that residential mobility did not occur during pregnancy • Is this assumption true?

3. Terminology: Migration vs. Mobility • MOBILITY refers to any change of permanent address • MIGRATION refers to moves that cross a county or state line

4. Previous studies on residential mobility during pregnancy – I.

5. Previous studies on residential mobility during pregnancy – II. 1997-2001 1984 1981-1983 1999-2001 Overall mobility • <30 years • <2+ children (controls only) • <21 years • <High school graduates • Whites/Hispanics? • Younger maternal age • White race • Prepreg BMI • Family income • <25 years

6. Mobility impact on risk measure • Mobility might lead to misclassification with respect to exposure to a risk factor for disease • Residential address change could result in • Exposure misclassification • Differential (degree of misclassification differs between cases and controls) • Effect estimates may be biased towards or away from the null value • Non-differential (misclassification similar among cases and controls) • Effect estimates might be underestimated

7. Based on Flegal et al.(Am J Epi, 1986)

8. Issues • Do mothers who move during pregnancy differ from mothers who do not move? • If yes, are there correlates of mobility during pregnancy that might need to be taken into account in studies of birth defects and residence at birth? • Is the probability of maternal residential mobility during pregnancy likely to be influenced by the case-control status of the infant?

9. Objectives • To determine the proportion of mothers of infants with and without birth defects (i.e., cases and controls) that changed their residences during pregnancy in Atlanta • To describe residential mobility patterns (number of moves, location change) of mothers and whether these differ by case-control status of the infant • To evaluate possible socio-demographic predictors of residential mobility • Maternal age • Race/ethnicity • Socio-economic status

10. Methods – Dataset • Case-control study dataset: Atlanta Birth Defects Risk Factor Surveillance Study (BDRFSS) dataset • Time period: January 1993 - August 1997 • Place: metro Atlanta (5 counties; at the time of delivery) • Cases: infants/stillbirths with selected major isolated and multiple (2+) defects • Exclusions: syndromes, chromosomal anomalies • Controls: a random sample of births from 18 birth hospitals in metro Atlanta

11. Methods – Interview data • Atlanta Birth Defects Risk Factor Surveillance Study (BDRFSS) dataset • Telephone interview (English or Spanish) on • maternal health • medication use • pregnancy history and fertility • demographics • family history • nutrition • occupational and environmental exposures • tobacco, alcohol use, and substance abuse

12. Pregnancy periods an mobility Date of Birth (DOB) Date of Conception (DOC) 3 months prior to conception 3 months 6 months 2nd trimester 3rd trimester 1st trimester

13. Socio-Economic Status (SES) • Census tract-level aggregated data is relatively useful for generating proxy measures of individual SES (Public Health Disparities Geocoding Project) • SES measured by the percent of people in a census tract living below the federally defined poverty line • A SES category was assigned to eachcase and control mother based on theircensus tract location at the time of conception and delivery • Census tract location was determined by geocoded residential address using GIS SES categories (% of people in poverty per census tract) High – <5.0% Mid-high – 5.0-9.9% Mid-low – 10.0-19.9% Low –   >=20.0%

14. Location change • Movements and actual distances between addresses at the time of conception and birth (~83% all records geocoded at address level for both) were calculated and categorized

15. 1 1 2 3 1 1 1 Location change – moves 1 - Moved into metro Atlanta (intra-state, inter-state) 2 - Inter-county move (within metro Atlanta) 3 - Intra-county move

16. Location change – distance • Actual distancebetween locations(addresses) • < 3 miles • 3-15 miles • 15-70 miles • > 70 miles DOC DOC DOB DOB DOC DOB

17. Statistical analysis • Comparison: mothers who moved and did not move • Socio-demographic factors and other variables included • Maternal race • Maternal age • Parity • SES • Maternal occupation • Maternal education • BMI • Logistic regression (univariate, multivariate) • Non-stratified and stratified analysis (case mothers, control mothers) • Maternal alcohol consumption • Maternal smoking • Intention to become pregnant • Paternal age • Paternal education • Time of first diagnosis • Type of defect (multiple vs. isolated)

18. RESULTS

19. BDRFS Study sample size

20. Residential mobility among case and control mothersby pregnancy period ~24% moved twice or more DOC=Date of Conception DOB=Date of Birth

21. Location change among case and control mothers between DOC and DOB

22. Location change among case and control mothers between DOC and DOB N/A=Not Available

23. Residential mobility among case mothers by defect groups between DOC and DOB *1 case with Respiratory System Defect was excluded from analysis

24. Socio-demographic characteristics associated with maternal mobilityMULTIVARIATEanalysis, NON-STRATIFIED ** Adjusted for maternal race, maternal age, SES, parity, maternal smoking, and planned pregnancy * Subjects with unknown status were deleted

25. Socio-demographic characteristics associated with maternal mobilityMULTIVARIATEanalysis, NON-STRATIFIED ** Adjusted for maternal race, maternal age, SES, parity, maternal smoking, and planned pregnancy

26. Socio-demographic characteristics associated with maternal mobilityMULTIVARIATEanalysis, NON-STRATIFIED ** Adjusted for maternal race, maternal age, SES, parity, maternal smoking, and planned pregnancy

27. Socio-demographic characteristics associated with maternal mobilityMULTIVARIATEanalysis, NON-STRATIFIED ** Adjusted for maternal race, maternal age, SES, parity, maternal smoking, and planned pregnancy * Subjects with unknown status were deleted

28. Summary of results – I. • About 22% of pregnant women moved during pregnancy in metro Atlanta • Proportion: ~8% in 1st trimester, twice as many during the 2nd trimester • Distance: • < 3 miles: 4.5% • 3-15 miles: 8.0% • >15 miles: 5.5% • Mainly intra-county move • No significant differences in movement patterns between case mothers and control mothers

29. Summary of results – II. • Pregnant women were more likely to move if they • were younger • had higher SES • did not plan their pregnancies • smoked • No significant differences in socio-demographic predictors between case and control mothers (data not shown) • No significant difference in movement by defect group among case mothers

30. Limitations • Number of controls small • Only English/Spanish speaking mothers included • Chromosomal defects (Down syndrome) excluded – pregnancy management might affect movement (i.e., better care) • Gestational age based on survey • Moving out from metro Atlanta not captured

31. Strengths • Population-based • Case-control setting • Relatively large sample size • Recent time period • Adjusted for several risk factors • Multiple residential addresses per mother geocoded

32. Public Health Implications • Residential mobility during pregnancy is an issue • Overall results similar to previous U.S. studies • Certain socioeconomic factors play important role • Extrapolating potential exposure data during earlier pregnancy periods based on addresses at birth • Could introduce exposure misclassification, primarily non-differential • Might lead to underestimation of true impact of environmental teratogen

33. Public Health Implications • This information (extent and type of mobility) could be important • In environmental studies (depending on the study question) • In geographical (spatial) cluster analysis • For environmental tracking programs • For studies of pregnancy outcomes and potential environmental exposures based on residence at the time of delivery, residential mobility during pregnancy needs to be taken into account as it could be an important source of bias

34. THANKS! • C. J. Alverson • Mike Atkinson • Alissa Berzen • Don Gambrell • Bennett Gardner • Peggy Honein • MACDP Abstractors • …and others • Csaba Siffel • Adolfo Correa E-mail: AMiller@cdc.gov

35. Percentage of population aged 1 and older that moved in the past year, 1948-2002 20% 15% Wolf and Longino, The Gerontologist, 45:5-11, 2005

36. Based on Flegal et al.(Am J Epi, 1986)

37. Socio-demographic characteristics associated with maternal mobilityMULTIVARIATEanalysis, NON-STRATIFIED ** Adjusted for maternal race, maternal age, SES, parity, maternal smoking, and planned pregnancy Univariate analysis – significant Multivariate - not significant

38. True RR = 10 Mobility rate: 20% Impact on risk measure – II. • What extent? (Quantification) Continuous risk measure (i.e., distance to a fixed point) Dichotomous risk measure • Probability of movement • Direction of movement • Distance moved

39. QUIZ Percentage of population aged 1 and older that moved in the past year increased between 1948 and 2002 TRUE FALSE

40. SPACE (LOCATION) TIME HEALTH OUTCOME

41. Background – Exposure • Environmental exposures (i.e., air pollution, disinfection byproducts, living near point source exposure) might be associated with adverse pregnancy outcomes

42. Background – Time • First trimester of pregnancy:critical/sensitive exposure period for most major congenital malformations Moore and Persaud, The Developing Human, 5th Ed.

43. Percentage of population making any move in the past year, by age group, 1948-2002 20-29 30-34 45-64 64+ Wolf and Longino, The Gerontologist, 45:5-11, 2005