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Pregnancy-associated Crashes and Birth Outcomes: Linking
birth/fetal death records to motor vehicle crash data
Lisa Hyde, Larry Cook
Lenora Olson, Hank Weiss,
J. Michael Dean
Prior Fetal Injury Research
Research on the effects of motor vehicle crashes on fetal outcomes is limited
– Lack of pregnancy information on crash records
– Lack of motor vehicle crash history on birth certificates
Study Objective
Assess the effect of involvement in a motor vehicle crash on the likelihood of adverse events for the fetus
Use probabilistic linkage to combine motor vehicle crash and birth/fetal death records
Probabilistic Linkage Basics
Probabilistic Linkage Theory
Crash Record
Ambulance Record
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Probabilistic record linkage is a method of using statistical properties of variables common to a pair of records to calculate the probability that the records apply to the same person and event...
Probabilistic record linkage is a method of using statistical properties of variables common to a pair of records to calculate the probability that the records apply to the same person and event...
Probabilistic Linkage Theory
Briefly, two statistical properties of each common variable -- reliability and discriminating power -- determine the odds ratio for a true match. The odds ratio is the uniformly most powerful test statistic for discriminating between matched and unmatched record pairs.
Briefly, two statistical properties of each common variable -- reliability and discriminating power -- determine the odds ratio for a true match. The odds ratio is the uniformly most powerful test statistic for discriminating between matched and unmatched record pairs.
Probabilistic Linkage Theory
Probability that a common variable agrees on a matched pair. Approximately 1 - error rate.
Probability that a common variable agrees on an unmatched pair. Approximately 1 / number of values.
Reliability (m)
Discriminating Power (u)
Record Linkage with Imperfect Data
Let us choose a pair of imperfect records and try to decide if they are a match. That is, do they refer to the same individual and event?
CrashRecords
CrashRecords
HealthRecords
HealthRecords
Probabilistic Record Linkage
If each ambulance record matches to one crash record in a file of 100,000 crashes then the odds for a match at random are
1:99,999
CrashRecords
CrashRecords
AmbulanceRecords
AmbulanceRecords
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Crash Record
Ambulance Record
First name agrees...
m = 0.90 u = 0.01 ratio = 90:1
Agreement on first name improves the odds for a match:
1:99,999 x 90:1 = 1:1,111
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Crash Record
Ambulance Record
Last or middle name agrees with last or middle...
m = 0.90 u = 0.04 ratio = 22:1
Agreement on last name improves the odds for a match:
1:1,111 x 22:1 = 1:51
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Sex agrees...
m = 0.99 u = 0.50 ratio = 2:1
Crash Record
Ambulance Record
Agreement on sex improves the odds for a match:
1:51 x 2:1 = 1:25
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Crash Record
Ambulance Record
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Date of BirthMonth agrees...m = 0.99 u = 0.08 ratio = 12:1Day agrees...m = 0.99 u = 0.03 ratio = 30:1Year disagreesm = 0.99 u = 0.01 ratio = 1:99
Agreement on birth date improves the odds for a match:
1:25 x 4:1 = 1:6
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Crash Record
Ambulance Record
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Date of CrashMonth agrees...m = 0.99 u = 0.08 ratio = 12:1Day agrees...m = 0.99 u = 0.03 ratio = 30:1Year agreesm = 1.00 u = 1.00 ratio = 1:1
Agreement on crash date improves the odds for a match:
1:6 x 360:1 = 60:1
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Crash Record
Ambulance Record
Agreement on crash time improves the odds for a match:
60:1 x 12:1 = 1,699:1
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Time of CrashHour agrees...m = 0.90 u = 0.04 ratio = 23:1Minute disagrees...m = 0.50 u = 0.02 ratio = 1:2
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Crash Record
Ambulance Record
Agreement on crash location improves the odds for a match:
1,699:1 x 10:1 = 16,990:1
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Place of crash agrees...
m = 0.99 u = 0.10 ratio = 10:1
Probabilistic Record Linkage
Mary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=NMary Smith F 05/05/45 07/15/96 11:47 Albany US5 Seat=1 Belt=N
Mary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem HospMary Smith Sanchez F 05/05/44 07/15/96 11:55 Albany Fracture Mem Hosp
Crash Record
Ambulance Record
This pair of records has both agreements and disagreements. Our calculations say that the odds are 16,990:1 that the records refer to the same individual and crash event.
Linkage of Motor Vehicle Crash Records with Birth and Fetal
Death Certificates
Study Databases (1992-1999) Utah Motor Vehicle Crash Data
– All reported motor vehicle crashes– Collected by police officers at the crash scene– Only drivers
Utah Birth Certificate Data– All single live births in Utah
Utah Fetal Death Certificate Data– All reported fetal deaths after 20 weeks gestation– Excludes elective abortions
Linkage Variables
Mother’s first and last name Mother’s date of birth Date of infant birth or fetal death Date of crash
– Compared gestational age / date of last menses with date of crash to ensure the crash occurred during pregnancy
Statistical Analysis Descriptive statistics and logistic regression were
used to assess the impact of having an MVC during pregnancy and wearing a seatbelt on adverse outcomes
Adverse outcomes included:– Low birth weight (<2500 grams)– Excessive maternal bleeding– Fetal distress – Placental abruption
Covariates in Logistic Model Age of the mother Race Weight gain Education level Smoking Alcohol Month of first prenatal visit Number of previous births Medical risk factors Seatbelt use Crash severity (KABCO) Trimester of crash
Birth certificate
Crash database
Birth Certificate Results
Crash Records to Birth Certificates
(1992-1999)
Number of Motor Vehicle CrashesDuring Pregnancy
n = 322,704
8,938 births with a crash (2.8%)
• 322,704 single live births in Utah, 1992 – 1997
• 8,938 (< 3%) were involved in an MVC during pregnancy
Crash
n = 8,938
No Crash
n = 313,766
Age 25.6 years 26.3 years*
Smoking 11.5% 9.3%*
Alcohol 1.7% 1.5%
Number of Previous Births
1.2 1.3*
Completed High School
85.9% 85.6%
Received Care 1st Trimester
84.6% 83.5%** Significant at 0.05 level
Trimester of Crash
0%
20%
40%
1st Trimester 2nd Trimester 3rd Trimester
Trimester of Crash
Per
cent
of
Cra
shes
n = 8,938
Logistic Regression Results for Crash vs. No Crash
Odds Ratio 95% CI
Low birth weight 1.0 (0.9, 1.1)
Excessive bleeding 1.0 (0.7, 1.3)
Fetal distress 1.1 (1.0, 1.2)
Placental abruption 1.0 (0.8, 1.2)
n = 322,704
Seatbelt
n = 7,143
No Seatbelt
n = 1,099
Age 25.8 years 23.9 years*
Smoking 9.8% 21.2%*
Alcohol 1.6% 2.6%*
Number of Previous Births
1.2 1.3
Completed High School
88.1% 73.2%*
Received Care 1st Trimester
85.5% 78.2%** Significant at 0.05 level
Logistic Regression Results forNo Seatbelt vs. No Crash
Odds Ratio 95% CI
Low birth weight 1.3 (1.0, 1.6)*
Excessive bleeding 1.6 (0.9, 2.9)
Fetal distress 1.0 (0.8, 1.4)
Placental abruption 1.0 (0.6, 1.8)
* Significant at 0.05 leveln = 322,704
Logistic Regression Results forNo Seatbelt vs. Seatbelt
Effect Odds Ratio 95% CI
Low birth weight 1.2 (0.9, 1.6)
Excessive bleeding 2.1 (1.0, 4.2)*
Fetal distress 1.1 (0.8, 1.5)
Placental abruption 0.9 (0.4, 1.8)
* Significant at 0.05 leveln = 8,938
Fetal DeathCertificate Results
Crash Records to Fetal
Death Certificates
(1992-1999)
Fetal Death Results
2,645 fetal deaths recorded during study period
45 (1.7%) linked to a motor vehicle crash record
No CrashCrash
45 fetal deaths involved in a crash (1.7%)
n = 2,645
Pregnancies Resulting in Fetal Death
Belted crash
Unbelted crash
Unknown
belt use
Total pregnancies
7,143 1,099 696
Fetal deaths
(Percent)
28
(0.4%)
12
(1.2%)
5
(0.7%)
Unbelted pregnant women were 2.8 (95% CI 1.4, 5.6) times more likely to experience a fetal death than belted pregnant women
Conclusions
Probabilistic linkage is a feasible method to combine crash and birth records
– Comparison group of women not in crashes– No recall bias / loss to follow-up
Failure to to wear a seatbelt may increase the likelihood of adverse fetal events
Questions?
Larry Cook
615 Arapeen Dr., Suite 202
Salt Lake City, UT 84108
801.585.9760