Preterm and Repeat Preterm Births: Identification of At-Risk Women Guide Program Development Rodney Wise, MD, FACOG Maternity Program Medical Director Professor Ob/Gyn, LSUHSC-Shreveport Lyn Kieltyka, PhD, MPH MCH Epidemiologist CDC Assignee to Louisiana Louisiana Maternal Child Health Program Office of Public Health New Orleans, LA June 24, 2008

Louisiana Infant Mortality Trend Join point regression p < 0.05p < 0.1

Louisiana PPOR Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Mortality Rate 11.4 per 1, Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Mortality Rate 11.4 per 1,

Louisiana Caucasian Women Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Mortality Rate 8.6 per 1,000 Total Mortality Rate 9.0 per 1,

Louisiana African American Women Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Mortality Rate 15.4 per 1,000 Total Mortality Rate 15.4 per 1,

Louisiana Excess Mortality Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Excess Mortality 5.3 per 1, Birth Weight Fetal Deaths Neo- natal Post- Neonatal g g Total Excess Mortality 5.3 per 1, Internal reference group: LA White women, 20+ years of age, some college

Causes of Infant Mortality ~45-50% related to length of gestation/ fetal growth

Preterm Births in Louisiana Source: National Center for Health Statistics, final natality data. Retrieved June 4, 2008, from

Preterm Birth (<37 completed weeks gestation) Significant problem in Louisiana and the US –2004 Preterm Births (PTB, wks) U.S. 12.5% Louisiana 15.6% –2004 Very Preterm Births (VPTB, 20-31wks) U.S. 2.0% Louisiana 2.8% Rates of PTB are increasing Contributes to Infant Mortality –Leading cause of infant mortality in Louisiana –Second leading cause of infant mortality in US –Leading cause of African American infant mortality in Louisiana and U.S.

Contributor to Morbidity Neonatal –Neurodevelopmental handicaps (CP, mental retardation) –Chronic respiratory problems –Intraventricular hemorrhage –Periventricular Leukomalacia –Infection –Retrolental fibroplasia –Necrotizing enterocolitis –Neurosensory deficits (hearing, visual) Life-long effects of fetal programming –Diabetes –Hypertension –Potential future preterm delivery

Preterm Birth Generates Enormous Health Care Costs Average newborn hospital charges: $4,300 vs. $58,000 for a preterm baby* Total U.S. hospital charges for infant stays due to prematurity/low birth weight: $11.9 Billion* Maternity & related expenses: –Often the largest cost to employers’ health care plans Costs include: –Contribution to infant mortality/morbidity –Financial costs * Source: Agency for Healthcare Research and Quality, 2000 Nationwide Inpatient Sample Prepared by March of Dimes Perinatal Data Center, 2003

Types of Preterm Birth Spontaneous Preterm Labor Spontaneous Premature Rupture of Membranes Medical Intervention Preterm Birth While this suggests distinct pathways, many of the risk factors for all 3 are similar

Probability of Preterm Labor Previous preterm birth30% >2 previous PTB70% Twins50% Triplets and higher 75%-95% Uterine malformations30%

Pathways to Spontaneous Preterm Labor/Delivery Infection 40% –cytokines Stress (maternal/fetal) 25% –CRH Bleeding (decidual, abruption) 25% Stretching (uterine distention) 10%

Research Question 1 What is the relationship between preterm birth and – substance use (smoking and alcohol) before and during pregnancy, –stressful life events –intimate partner violence –pre-pregnancy BMI, weight gain, and –pregnancy spacing (birth interval)?

Methods: All Preterm Louisiana linked PRAMS-birth data Data limited to singletons, 24+ weeks gestation, White / Black race only Gestational age from birth certificate –24-31 weeks (very preterm birth, VPTB) –32-36 weeks (moderate preterm birth, MPTB) Univariate and bivariate statistics used to assess distributions and relationships with preterm birth Variables with a significant bivariate relationship (p<0.05) considered in multinomial model –SAS-callable SUDAAN

Sample Characteristics Louisiana PRAMS, Singleton births 24+ weeks, % White 16% <20 years of age; 26% 30+ years 22% < 12 th grade education; 35% HS 53% Married 85% first trimester prenatal care 45% adequate plus prenatal care 7% previous preterm delivery

Factors of Interest: All Preterm Race** Maternal age* Maternal education* Marital status** Previous PTB/Parity** 1st trimester prenatal care entry* Prenatal Care Adequacy** Health insurance type* Hypertension** Smoking before/during pregnancy* Drinking before/during pregnancy* Intimate partner violence* Stressful life events*** Pre-pregnancy body mass index Maternal weight gain (adjusted for gestation)* Pregnancy spacing** (current date of birth – most recent previous date of birth) Pregnancy Intention* *p<0.05; **p<0.0001; ***2 of 4 stress variables p<0.05

Multinomial Results: All Preterm Modifiable Factors VPTBMPTB Variable Reference OR95% CIOR95% CI Hypertension (Yes) No 1.5(1.2, 1.9)1.8(1.5, 2.2) Partner abuse –bef/dur (Yes) No 1.2(0.9, 1.6)1.6(1.1, 2.1) Low weight gain Norm/over 2.0(1.6, 2.7)1.2(0.96, 1.5) APNCU (Kottelchuck Index) Inadequate Inter/Adeq 2.6(1.7, 4.0)4.5(3.1, 6.6) Adequate plus Inter/Adeq 5.4(3.7, 7.8)6.7(5.1, 8.8) Pregnancy Spacing <12 mos 24-<48 m 3.6(2.1, 6.0)2.7(1.4, 5.0) 12-<24 mos 24-<48 m 0.9(0.6, 1.3)1.3(0.9, 1.8) 48+ mos 24-<48 m 1.8(1.2, 2.8)1.0(0.7, 1.3) Never 24-<48 m 0.9(0.2, 3.1)0.8(0.3, 2.4)

VPTBMPTB Variable Reference OR95% CIOR95% CI Black Maternal Race White 2.9(2.2, 3.8)1.4(1.2, 1.7) Previous Preterm birth by parity No previous pregnancy Prev–term 2.9(0.8, 10.3)1.8(0.6, 5.2) Previous –preterm Prev–term 4.3(3.0, 6.4)3.5(2.6, 4.6) Prior fetal or infant loss (Yes) No 2.1(1.6, 2.8)1.3(1.0, 1.6) Multinomial Results : All Preterm non-Modifiable Factors

Multinomial Model Findings NO relationship –substance use (alcohol or tobacco) –stressful life events (ungrouped or grouped) –pre-pregnancy BMI WEAK relationship –partner violence MODERATE relationship –Weight gain for gestation (VPTB only) –Pregnancy spacing < 12 month interval associated with VPTB and MPTB > 4 year interval associated with VPTB only STRONG relationship –Prenatal care adequacy

Research Question 2 What factors are associated with the second birth event being preterm in Louisiana ? –Identification of risk may help target development of intervention programs –Identification or risk factors may target patient specific monitoring –Identification of risk may target individuals for medical intervention

Methods : Repeat Preterm Louisiana Vital Records linked with Medicaid program data First time, singleton Louisiana resident births occurring in identified Linked with subsequent births occurring within next 4 years to same mother Analysis limited to women with 2 nd live birth Outcomes were all preterm birth (PTB, wks) and very preterm birth (VPTB, weeks) Chi-square and logistic regression using SAS

Sample Characteristics Louisiana Vital Records, All first births, % White 33% <20 years of age; 14% 30+ years 24% < 12 th grade education; 34% HS 86% first trimester prenatal care entry 54% Medicaid N=79,690

Factors of Interest: Repeat Preterm Race Maternal age Maternal Education Prenatal care entry Gestational duration of second pregnancy Hypertension Smoking in pregnancy Pregnancy weight gain Pregnancy spacing Maternal diabetes Medicaid status Risk factors identified from Birth Certificate-Medicaid linked data

Repeat Preterm Birth: Relationship Between First and Second Birth Event Birth EGA – VPTB onlyNumberPercent Initial Birth – VPTB Subsequent VPTB, given 1 st VPTB and having 2 nd pregnancy Birth EGA – All PTBNumberPercent Initial Birth – PTB Subsequent PTB, given 1 st PTB and having 2 nd pregnancy

Factors Associated with Repeat Preterm Birth: Among women with second birth event, N=34,741 Variable All PTB Odds Ratio (95% CI) VPTB Odds Ratio (95% CI) Race (ref: white) African American1.5 (1.4, 1.6)2.3 (1.9, 2.7) Other0.9 ( 0.7, 1.2)0.9 (0.4, 1.8) Age (ref: 30-34) <201.4 (1.2, 1.6)ns (1.1, 1.5)ns (0.9, 1.3)ns >351.0 (0.8, 1.4)ns Education (ref: >12) <121.4 (1.2, 1.5)1.5 (1.2, 1.9) (1.0, 1.2)1.1 (0.9, 1.3)

Factors Associated with Repeat Preterm Birth: Among women with second birth event, N=34,741 Variable All PTB Odds Ratio (95% CI) VPTB Odds Ratio (95% CI) Medicaid (ref: not Medicaid)ns1.3 (1.0, 1.5) Prenatal Care Entry (ref: 1st) 2 nd Trimesterns1.3 (1.1, 1.6) 3 rd Trimesterns0.9 (0.5, 1.5) No Prenatal Carens1.5 (0.8, 2.8) Pregnancy Spacing (ref: 24+mo) <12 months3.4 (3.0, 3.9)4.5 (3.5, 5.8) months1.7 (1.5, 1.9)1.8 (1.4, 2.4) months1.4 (1.3, 1.6)1.6 (1.3, 2.1) months1.2 (1.1, 1.4)1.3 (1.0, 1.7) months1.2 (1.1, 1.4)1.1 (0.8, 1.5)

Factors Associated with Repeat Preterm Birth: Among women with second birth event, N=34,741 Variable All PTB Odds Ratio (95% CI) VPTB Odds Ratio (95% CI) Weight gain < 10 pounds 1.3 (1.2, 1.5) 2.2 (1.1, 1.4) Maternal diabetes and/or hypertension 2.4 (2.1, 2.7)1.8 (1.3, 2.4) Initial PTB (ref: no PTB)3.7 (3.4, 4.0)-- Initial VPTB (ref: no VPTB) (4.9, 8.0) Smoking not significant in this analysis.

Conclusions: Significant Factors for Repeat Preterm Births Women in repeat All PTB group: –African American (OR 1.5) –< High school education (OR 1.4) –Age < 20 years (OR 1.4), years (OR 1.3) –Poor weight gain (OR 1.5) –Have co-existing hypertension / diabetes (OR 2.4) –Frequent conceptions (OR 3.4, <12 mos) Women in the repeat VPTB group: –African American (OR 2.3) –< High school education (OR 1.5) –Poor weight gain (OR 2.2) –Have co-existing hypertension / diabetes (OR 1.8) –Frequent conceptions (OR 4.5, <12 mos)

Limitations Preterm birth analysis –Self-report (PRAMS) –Small sample size in some groups Repeat Preterm birth –Limited to women who had a repeat birth –Small sample size for the repeat VPTB group –Some characteristics likely under-reported on birth certificate (i.e. smoking) –Subsequent birth may not be identified due to incorrect or missing identifiers –Deterministic linkage only (SSN)

Program Implications for Louisiana Utilize data to guide program development Limited program resources allocated to best opportunity for improvement based on program knowledge and data results Ongoing cycle integrated with program evaluation

Current and Planned Efforts Birth Weight Fetal DeathsNeo-natalPost-Neonatal g Nurse Family Partnership Family Planning Waiver Substance Use / Depression / IPV screening Folic Acid (Pre- / Inter-conception Care) g Access to care - Medicaid Hospital Levels of Care Child Health Injury Prevention / SIDS education Program Louisiana Perinatal Commission, Louisiana FIMR Network, and Child Death Review benefit all cells

Challenges Working across agencies / partnerships Political will to set priorities / adopt change Funding and sustainability Timeliness / availability of data Need for evidence based programs –Ongoing program monitoring / evaluation