||||H|||||l||| | 7‘ ~‘a 9;) r" _) This is to certify that the thesis entitled VAGINAL BLEEDING DURING THE FIRST 20 WEEKS OF PREGNANCY AND THE RISK OF PRETERM DELIVERY presented by VERONIKA SKOROKHOD has been accepted towards fulfillment of the requirements for the MS. degree in EpidemiologL /flw 4/ %%7¢m Major Professor’ s Si ature 6' // /2 o/fl ’ / Date MSU is an Affirmative Action/Equal Opportunity Employer LIBRARY Michigan State University PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. MAY BE RECALLED with earlier due date if requested. DATE DUE DATE DUE DATE DUE 5/08 K:/ProilAcc&Pres/ClRC/DateDue.indd VAGINAL BLEEDING DURING THE FIRST 20 WEEKS OF PREGNANCY AND THE RISK OF PRETERM DELIVERY By Veronika Skorokhod A THESIS Submitted to Michigan State University in partial fulfilhnent of the requirements for the degree of MASTER OF SCIENCE Epidemiology 2010 ABSTRACT VAGINAL BLEEDING DURING THE FIRST 20 WEEKS OF PREGNANCY AND THE RISK OF PRETERM DELIVERY By Veronika Skorokhod This study examined associations between vaginal bleeding in the first 20 weeks of pregnancy and risk of preterm delivery (PTD) in two ethnic/racial groups. Data were from the Pregnancy Outcomes and Community Health (POUCH) Study (1998-2004, 5 Michigan communities) and included only women enrolled/interviewed at 20-27 weeks of pregnancy (78% of the cohort; 1,735 non-Hispanic White and 619 African-American). Maternal reports of bleeding in the first half of pregnancy were grouped by time of bleeding (weeks 1-13 only; weeks 14-20 +/- weeks 1-13), duration (524 hrs; >24 hrs) and amount (spotting/slight; Zusual menstrual period). The prevalence of bleeding in weeks 1-20 was similar in non-Hispanic Whites (24.4%) and Afi'ican-Americans (23.4%). In addition these ethnic/racial groups did not differ with respect to timing, duration and amount of bleeding. The risk of PTD was increased among women who bled in “weeks 14-20 +/- weeks 1-13” (non-Hispanic White odds ratio=2.0), for >24 hrs (non-Hispanic White odds ratio=2.0; African- American odds ratio=1.7), and with amounts “_>_ usual menstrual period” (non-Hispanic White odds ratio=2.7; African-American odds ratio=2.2). There were no significant interactions by ethnicity/race. These results suggest that bleeding is associated with increased risk of PTD but ethnic/racial disparities in PTD risk are more strongly linked to pathways that do not involve bleeding in the first 20 weeks of pregnancy. DEDICATION To my wonderful parents, who always believe in me iii ACKNOWLEDGEMENTS I would like to express my sincere gratitude to my advisor Dr. Claudia Holzman for her guidance, inspiration and valuable suggestions during the development of this thesis; as well as for providing me with valuable research experiences and support as a graduate assistant. But most of all I am very grateful for her endless patience and understanding, support and encouragement throughout the difficult times I have encountered during the last couple of years. I thankfully acknowledge the other members of my advisory committee Dr. Hossein Rahbar and Dr. Rachel Fisher for all the time, advice and knowledge they have given me during the development of this thesis. I am appreciative to the entire POUCH Study team, especially Dr. Bertha Bullen for her never-ending patience and all the assistance she provided me with throughout my research. I also acknowledge the faculty and staff of the department of Epidemiology for creating friendly and supportive learning environment. And finally, but not least, a very special thanks to my family for all their support, patience, confidence, and love. To my parents, thank you for encouraging me to pursue my many interests and helping me to achieve my goals. I could not have done this without you. iv TABLE OF CONTENTS LIST OF TABLES .................................................................................... vi LIST OF FIGURES ................................................................................. vii KEY TO ABBREVIATIONS ..................................................................... viii CHAPTER 1. BACKGROUND .................................................................... 1 1.1 . Introduction .................................................................................... 1 1.2. Preterm Delivery .............................................................................. 1 1.3. Risk Factors for Preterm Delivery ........................................................... 3 1.4. Ethnicity/Race and Preterm Delivery ...................................................... 4 1.5. Antenatal Vaginal Bleeding ................................................................ 6 1.6. Underlying Mechanisms for Antenatal Vaginal Bleeding and Preterm Delivery ........................................................................ 7 1.7. Summary of Literature Review .............................................................. 9 1.8. Study Aims and Strengths .................................................................. 12 CHAPTER 2. VAGINAL BLEEIDNG DURING THE FIRST 20 WEEKS OF PREGNANCY AND THE RISK OF PRETERM DELIVERY ............................... 27 2.1 . Introduction ................................................................................. 27 2.2. Subjects and Methods ...................................................................... 28 2.3. Results ........................................................................................ 32 2.4. Discussion ................................................................................... 42 REFERENCES ...................................................................................... 46 LIST OF TABLES Table 1.1. Rough Guide for Survival and Handicaps among Premature Babies. . . . . . .3 Table 1.2. Studies on Association between Antenatal Vaginal Bleeding and Preterm Delivery ................................................................................. 14 Table 2.1. Selected Sociodemographic and Pregnancy History Characteristics of Study Participants ................................................................................. 36 Table 2.2. History of Vaginal Bleeding in the First 20 Weeks of Pregnancy by Maternal Ethnicity/Race ......................................................................... 38 Table 2.3. Association between Vaginal Bleeding in the First 20 Weeks of Pregnancy and a Risk of Preterm Delivery by Maternal Ethnicity/Race ................ 39 Table 2.4. Association between Vaginal Bleeding in the First 20 Weeks of Pregnancy and a Risk of Preterm Delivery ................................................... 40 Table 2.5. Association between Vaginal Bleeding in the First 20 Weeks of Pregnancy and a Risk of Preterm Delivery by Its Subtypes ................................. 41 vi LIST OF FIGURES Figure 1.1. Preterm Deliveries in the US between 1994 and 2004 ............................. 2 Figure 2.1. Underlying Mechanisms for Antenatal Vaginal Bleeding and Preterm Delivery ................................................................................. 8 vii APHUO AVB A/OR BMI BW CI D/P GA GT GW LMP MI N/ S OR PTD PTL PPROM Ref KEY TO ABBREVIATIONS Antepartum Hemorrhage of Unknown Origin Antenatal Vaginal Bleeding Adjusted Odds-Ratio Adjusted Risk-Ratio Body Mass Index Body Weight Confidence Interval During Pregnancy Gestational Age Genital Tract Gestational Week(s) Last Menstrual Period Medically Induced Delivery Not Specified Odds Ratio Preterm Delivery Preterm Labor Preterm Premature Rupture of Membrane Reference Group Relative Risk Vaginal Bleeding viii CHAPTER 1. BACKGROUND 1.1 Introduction Preterm birth currently remains an important issue in prenatal care, since 70-80% percent of all perinatal deaths and a similar proportion of perinatal illnesses occur in the infants delivered preterm (1,2). The numbers of preterm infants born all over the world remains high and the problem of preterm delivery is by no means resolved. Although a large number of studies have been conducted and many factors that increase the risk of preterm delivery discovered (8,13,19,33) the causes of preterm delivery are not fully understood and, at this time, often little can be done in order to prevent preterm birth. 1.2 Preterm Delivery Preterm delivery (defined as live birth before 37 completed weeks of pregnancy) is a major public health concern (3). In 2004 in the United States 1 in 8 babies (12.5% of live births) were born prematurely with 2% of these born very prematurely (live birth before 34 completed weeks of pregnancy) (4). Preterm delivery rates are especially high among poor, inner city, and minority pregnant mothers. The rate of preterm birth in the United States in 2002-2004 (average) was the highest for African-American infants (17.6%), followed by Native American (13.4%), Hispanic (11.8%), non-Hispanic White (11.3%), and Asian (10.4%) (4). Despite improvement in many health indicators, the rate of preterm delivery in the US showed no improvement from 1994-2004 (Figure 1.1). In fact it continues to increase, reaching 12.7% in 2005 (5) and 12.8% in 2006 (6). Figure 1.1. Preterm Deliveries in the US between 1994 and 2004 Percent Of IIVG births 15- o 11.4 11.6 11.8115 11.9 12.1 12.3 12.5 11.0 11.0 11 104 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Preterm delivery is the second leading cause of infant death in the US. In 2004, 36.5% of all infant deaths in the US were preterm-related (4). Surviving infants are likely to be at a high risk of damage to the central nervous system resulting in serious disorders such as cerebral palsy, chronic respiratory problems and infections, as well as long-term neurological and developmental impairments, mental and cognitive dysfunctions, increased rate of cardiovascular disorders, hypertension, and diabetes. They may end up with lifelong handicaps, varying in degree from slight to severe (Table 1.1). Table 1.1. Rough Guide for Survival and Handicaps among Premature Babies GeStafiontlwteglfs? Delivery Survival (°/o) Handicaps (%) 24 60 6° 26 95 4° 28 96 25 3O 97 15 32-36 98+ <3 1.3 Risk Factors for Preterm Delivery It is impossible to predict which women will deliver prematurely but there are risk factors associated with an increased risk, and some but not all of these factors are modifiable. Risk factors for preterm delivery include demographic characteristics, obstetric history, certain maternal medical conditions, and behavioral factors. Demographic factors for preterm delivery include African-American race (4,8), extremes of maternal age (under 17 or over 35 years old) (9-11), low socioeconomic status (12). Obstetric history includes multiple gestations (14,15), short cervix (less than 2 cm at less than 24 weeks of gestation) (16,17), incompetent cervix, malformation of the uterus (8), certain birth defects in a baby, and previous history of preterm delivery (1 8). Maternal medical conditions include diabetes (28), hypertension (32,33), clotting disorders (64,72- 74). Infections in genitourinary tract also pose a risk (8,19-25). Behavioral factors include smoking during pregnancy (22-24), alcohol consumption in pregnancy (8,13), illegal drug use (especially cocaine) while pregnant (25,26), low pre—pregnancy weight, obesity (28,29), low or excessive weight gain during pregnancy (8). In addition preterm delivery can be associated with stressful life situations and certain occupational factors. Some studies have found an association between high levels of stress caused by anxiety, depression, major life events, such as loss of a job, death of a family member, divorce, and higher rates of delivering preterm (13,27-30). The theory is that severe stress can lead to the release of hormones that can trigger uterine contractions and subsequent preterm delivery. There is evidence that extremely physically demanding jobs or long working hours play a role in preterm delivery. Women who had to stand for long periods of time (over 40 hours per week) or had extremely tiring jobs were more likely to deliver preterm (31,32). Despite the progress in the field of obstetrics and gynecology, the predictive value of currently substantiated risk factors for preterm delivery is rather low and there are no effective treatments to substantially prolong gestation once preterm labor begins. 1.4 Ethnicity/Race and Preterm Delivery The risk of preterm delivery varies among women in different ethnic/racial groups. African-American women are at the highest risk of delivering preterm followed by Native American and Hispanic women. The risk is the lowest for Asian and non- Hispanic White women (4,50). Furthermore women born in the US (except for some Asian and non-Hispanic White) are at a higher risk of delivering preterm compared to foreign-bom women of the same ethnicity/race (50,51). It seems that father’s ethnicity/race may also affect pregnancy outcomes (51,53). Compared to women partnered with men of the same race, non-Hispanic White women partnered with African-American men are at a higher risk of delivering preterm; however African-American women partnered with White men do not appear to be at an elevated risk (51). While black women in general are known to have the highest risk of delivering preterm this risk varies significantly once their ancestry and nativity are taken into account. The risk appears to be the highest in the US-bom black women compared with foreign-bom black women (50-52). The cause for a high risk of preterm delivery among African-American women remains uncertain. Many suspected demographic and socioeconomic risk factors have been compared between African-American and White women but these risk factors seem to account for very little ethnicity/race difference in the rates of preterm delivery (54,55). There is a number of medical conditions that are associated with preterm delivery for which African-American women appear to be at a higher risk. African-American women are significantly more likely to be obese (26-29), to be affected by both chronic and gestational diabetes (28,30), and have higher risk of developing hypertension (31-33) than non-Hispanic White women. All of these conditions are also known to be risk factors for development of preeclamsia, which in turn is one of the causes for preterm delivery (33). In addition compared to women from other ethnic/racial groups African- American women have higher rates of preterm delivery associated with prevalent reproductive tract infections during pregnancy, particularly bacterial vaginosis, T richomonas vaginalis and Chlamydia trachomatis (22-25). Furthermore preterm delivery can be associated with stressful life situations (13,39-42). While African-American women are subjected to more stress (43,44). they may also have more adverse health effects due to stress (45,47). Cardiovascular reactivity is one of the indicators of susceptibility to stress and in at least two studies African-American women had higher levels of cardiovascular reactivity than White women (45,46). It is very important to understand why Afiican-American women are at increased risk of preterm delivery in order to implement effective interventions. One area that has not been commonly investigated is the role of bleeding in preterm delivery among African-American women versus White women. 1.5 Antenatal Vaginal Bleeding Vaginal bleeding is a common complication that may occur at any time during pregnancy. There are many different reasons why a woman may experience antenatal vaginal bleeding. The likely cause of vaginal bleeding changes over the course of pregnancy. Vaginal bleeding in the first trimester of pregnancy is not uncommon, occurring in 20-30% of all pregnancies (56). It can be associated with normal implantation of an embryo into the uterine wall (known as implantational bleeding), cervical changes due to pregnancy or it can be caused by more serious factors, such as miscarriage (15-20% of pregnancies) (57), ectopic pregnancy (1 in 60 pregnancies) (58) or molar pregnancy (1 in 1,000 pregnancies) (59). Vaginal bleeding in the second and third trimesters of pregnancy is less common. Causes for vaginal bleeding later in pregnancy are different from those in early pregnancy. Most common causes of vaginal bleeding during second and/or third trimester are problems with a placenta, such as placental abruption (about 1% of pregnancies) (60) or placenta previa (1 in 200 pregnancies) (61). Other causes include problems with the cervix, uterine rupture, and premature labor. Antenatal vaginal bleeding can also be caused by conditions unrelated to pregnancy, such as vagina] or sexually transmitted infections (8,19-21), abnormalities of cervix or vagina, carcinoma or cervical polyps (52), and various kinds of trauma (63). Different maternal inherited or acquired bleeding disorders can also result in antenatal vaginal bleeding. They include hemophilia (extremely rare cause, occurs in 1 in 10,000 women) (64) or thrombophilia (72-74). Certain gynecological procedures, such as Chorionic Villus Sampling (CVS) and Amniocentesis can cause bleeding as well. However in about 50% of pregnancies the cause of vaginal bleeding is unknown (65,66). Antenatal vaginal bleeding has been associated with adverse pregnancy outcomes, such as preterm delivery, low birth weight, stillbirth, and perinatal death (75). 1.6 Underlying Mechanisms for Antenatal Bleeding and Preterm Delivery The reason for the association between antenatal vaginal bleeding and adverse pregnancy outcomes, including preterm delivery remains unclear. Different underlying mechanisms have been suggested (67) (Figure 1.2). Some cases of preterm delivery may result from thrombin activation (68-71). Thrombin is a coagulation protein that has many effects in the coagulation cascade. Its primary role is to convert fibrinogen (a soluble protein that is produced by the liver and found in blood plasma) to an active form that assembles into fibrin (a protein involved in the clotting of blood), as well as catalyzing many other coagulation-related reactions. In addition to its activity in the coagulation cascades, thrombin promotes platelet activation. Thrombin is also known as a potent uterotonic agonist (69). Due to the difficulties in the direct measurement of thrombin, indirect measures have been used in studies to assess the coagulation cascade and activated thrombin production. Most often studies use the TAT test: thrombin—antithrombin HI (TAT) complex levels measure the amount of activated thrombin bound to antithrombin HI, an endogenous thrombin antagonist (68,69). The bleeding causes the generation of thrombin, which causes an outpouring of enzymes capable of ripening the cervix and damaging fetal membranes, resulting in preterm premature rupture of membrane, and leading to preterm delivery (70). On the other hand thrombin also binds to receptors on uterine muscle cells to trigger contractions, which may promote preterm labor (71). Figure 2.1. Underlying Mechanisms for Antenatal Vaginal Bleeding and Preterm Delivery ANTENATAL VAGINAL BLEEDING URO GENITAL INFECTIONS PRETERM DELIVERY Thrombophilia is an abnormality in the coagulation pathways that predisposes an individual to thrombosis. It can be inherited, acquired or combined. Maternal thrombophilias increase risk of several adverse pregnancy outcomes including early or late spontaneous abortions, pre-eclampsia, placental abruption, and intrauterine growth restriction (72,73). The most common inherited thrombophilias consist of Factor V Leiden and the prothrombin gene mutation G20210A, and more rare ones include deficiencies of protein C, S and antithrombin HI. Recently, deficiency of protein Z has been linked to pregnancy complications, including preterm delivery. It is possible for more than one inherited thrombophilia to be present (73,74). Importantly, in the addition to the direct effects of bleeding and thrombin, bleeding might also result from other underlying problems, such as infection or inflammation, which in turn can lead to preterm delivery (67). In these cases bleeding may be more of a marker than a cause. These distinctions can be difficult to determine. 1.6 Summary of Literature Review Studies on the association between antenatal vaginal bleeding and the risk of preterm delivery date back to the late 1950’s. The focus in this review is on studies conducted starting from early 1980’s, since the availability of an ultrasound in this more recent period made it possible to obtain better estimates of gestational age. The majority of studies were conducted in various parts of the US, however there were also studies conducted in Australia, Brazil, China, Egypt, Finland, Germany, India, Israel, Korea, Pakistan, Saudi Arabia, and United Kingdom. Sample sizes for these studies range from 75 to 16,506 women. Some studies reported gestational age at the enrollment into the study. It ranged from 10 to 29 gestational weeks (76,78,79,84). Bleeding history was mostly collected by maternal questionnaires/interview at the various stages of pregnancy; however some studies used reviews of medical records instead or in addition to the maternal self-report. The majority of studies defined preterm delivery as “live birth at less then 37 completed weeks of gestation”. Studies that assessed timing of bleeding, did it primarily by trimesters but some studies referred to the first or second half of pregnancy (80,91). Most studies reported assessing heaviness of bleeding episodes (78-81,84) but only one study reported taking duration of bleeding episodes into account (79). The potential confounders most frequently taken into consideration were maternal age, ethnicity/race, education, parity, marital status, cigarette smoking, and alcohol consumption during pregnancy. Some studies also considered medical insurance status, and elements of medical and obstetric histories. Most studies reported the prevalence of antenatal vaginal bleeding. It ranged between 4.9% and 35.5% (76,78-80,82-84). The majority of studies have found a moderate to severe increase in the risk of preterm delivery associated with antenatal vaginal bleeding (76-84,86—94), particularly bleeding during first trimester of pregnancy only (78,85), and during the second half of pregnancy (91,92). One study reported significant increase in the risk of vaginal bleeding during the second half of pregnancy for women that had some bleeding during the first half (91). A very limited number of studies have assessed ethnicity/race—specific differences for the risk of preterm delivery in association with antenatal vaginal bleeding. Studies that did found ethnicity/race-specific odds-ratios to be greater in non- Hispanic White than in African-American women (79,80). There were some differences in results of prior studies. One study found 10 a significant association between preterm delivery and vaginal bleeding during the second but not first trimester of pregnancy (83). While most of the studies that accounted for heaviness of bleeding episodes found that the risk of delivering preterm was notably higher among women with heavier bleeding episodes (78-80,84), one study found no association between heaviness of bleeding episodes and preterm delivery (84). A number of factors may potentially account for the differences in the results of prior studies. First, there have been differences in times in pregnancy when bleeding history was assessed. Information on bleeding was typically gathered by asking study participants, and recall bias may have occurred in women queried after delivery or late in pregnancy following other complications. Second, many studies have failed to include characteristics of bleeding in their analysis, particularly duration of bleeding episodes. It is important to take these characteristics into account, since they may influence the association between antenatal vaginal bleeding and the risk of preterm delivery. Third, studies have used different definitions of preterm delivery, and bleeding characteristics, particularly there was great variability in defining heaviness of bleeding episodes. Finally, studies differed with respect to study design, sample size, and confounders selected during data collection and statistical analysis. Among studies on the association between antenatal vaginal bleeding and the risk of preterm delivery very few studies attempted to separate preterm delivery into its clinical subtypes (i.e. preterm labor, premature rupture of membrane, and medically induced delivery) (78,79,93,95). Only one study considered both bleeding characteristics (timing, duration, and heaviness), and clinical subtypes of preterm delivery (79). One more study assessed the relation between heaviness of bleeding and the risk of preterm 11 premature rupture of membrane (78). It has been found that antenatal vaginal bleeding increases the risk of preterm delivery in all subgroups but especially for preterm labor (79,93,95). At present time the desirability of separating preterm delivery into its clinical subtypes remains an open topic. Some researchers maintain that such separation should be made (95,96) while others oppose it (97). Based on the results of some prior studies it has been recommend that the subtypes should be examined first, and then combined back together only if they turn out to be homogenous (95,96). It is firrther recommended that preterm labor and preterm premature rupture of membrane could be combined into spontaneous preterm delivery, however medically induced preterm delivery should be kept separately (95,96). More studies are needed in order to further understand the association between vaginal bleeding during pregnancy and the risk of preterm delivery, the underlying mechanism for this association, and implications for prenatal care. Consideration of preterm delivery’s clinical subtypes might provide additional insights into these associations. 1.7 Study Aims and Strengths Study Aims The aim of this study is to consider associations between antenatal vaginal bleeding and the risk of preterm delivery. This aim will be operationalized by considering characteristics of bleeding (timing, duration, and heaviness of bleeding episodes), ethnicity/race-specific effect, influence of potential confounding factors, and clinical 12 subtypes of preterm delivery (preterm labor, premature rupture of membrane, and medically induced delivery). Study Strengths Major strengths of this study are prospective design, the fact that women were not selected based on their bleeding history, and the large sample size. In addition estimates of gestational age based on the last menstrual period were confirmed using estimates by an early ultrasound for 90% of study participants. Furthermore, recall bias was minimized due to the fact that bleeding information was collected early in pregnancy; and differential reporting was impossible, since at the time of the interview the outcome of the pregnancy was unknown. Obtaining information by self-report has its limitations and strengths. Although there is subjectivity in recalling bleeding, self-report is potentially more accurate and complete than information obtained from medical records. 13 .AmomemoflE 5:8 56%ch ESE: 0383652 Amouopfiv .EmeobmfioRE .emeasatofia .coacotog: 3:530 .83ch Eco: A9535 .coaaanm 3502a .BocoomBoHoEBobcom «Econ—q £335 858—3 $33 @5529 oBmEEoE Eodmuz vooQNT magic 885:9 «€534 €833 32:38 32on dB 8: 30 mm v .36 vmv Hm 853:6 beam 5853030 mev .aon d% wEonm .mcoufimow 29:2: o>uooamobom 56:36 6? 3:532 . EEC. ”sous—SQ .89on 88 .wde ”5&3 Jméumo .02 .8383 3&8: % .3 no xomEoUoE ofim min—am =33:qu PH.— oEEh 25,—. 553.5 6932280 «2820 $30: 63.3 Eat—5830 wage—3222.0 =o_m=_o:—\=o_m=_oxm 0:52 “58.: 3:85 3:5 flux—22 unoEmmomm< ~=QE=oEm 55.33:.— ..e 23> £33— 35% oEuonméoS—bfifim Dogma $5.85 an ow< Enema—389 35.2 «95— .CoZ—on 8580...— EE Mum—coo:— _a£w«> 132.35.. 5952. 553983.. .5 «3.5% .~.— 22F 14 .v.mm-n._ ”5 o\cma .vNcHMO ”assess 23%: waEF :2 .29: JR 3 waZ 30 cmém Q va C .30 wmv 8 $2 :3»: {Nine ”5 $3 .Nm. WMO ”SE 3233sz 8 53.8% o: .flfifimo: KENS—63:2 :2 3c 2 v 35, 2: a $23 :23 ”6 $3 .0235 .3 a: 3:8: .wfioem 5:9: 5 5538a <3 5:3, Saga? ”SOME; @2853 3:26:58 .G:N Q .2 53 .30 omv an 8.8 38:05 m.m-m._ ”5 $3 .3 .NHMO aw 33:08 £03338 5:0 EN 5:0 «3 .83» m _N own BEBE: tocoo 3:00:85 ”HE .0885 228:0: 33:5 ”$8885 :5 Mug £23235 :SBwEm dos—33:0 .0? 13.532 QUE. 38m «350 ._ _.N|c_._ ”5&3 ngumo 4:08:85 3 Boom ”Em =So>0 .02 :8595 toga—om $2 .130 538: .338 .Sodva wage—n 2866525. ”Nola; AU .33 .vduMO .88 73985 HO 3:88: ”ZONE $05:on 30 mm v mo has :5 05 “a m> vfluz .25.on 8 0:: 863:? 358: ABOV _.~H~.om.m> Emficdm A5533: .223:me :SoEEm 38m— H<0 :85 m2 mo :2 :5 a 3% mgms .m> $5.3 woom ”DE .02 .mEooo: Eamom 55:35 We :3 EN .3 Ho >28: .5253 .3 2.3. 15 $552388 >05“:on “550 23.th £2.5me .362: «Ego um. $5395 .358“ 3:8? .mcoufimum DEB—:8 «Bov— d. meu £839 382500 a .203 a. oEn—EonuQ 35% 3.50385 €0an map—«9:5: $853 meow. N41; magma 6.NHMO .02 mi 92 .130 SQ 30 mm v .95 a. E 53 A333: EN .csozvv E ”E8855 >3 NEE. IIF Benz .aquB .95 8E .285? 35% 9.233 Sego.§:~_ 3583 $2225 a he 3502 32on .333 8:835 .293 we core—Ema“ "5803 m2 90 mm v .358 maven—n 8522 ES .328:on £8.53me 07538 $293 $ 30.53— m\z (8 2E 23 walefi llaefioxm meow w.m-w.m ”5.33 .C.mnm0 62 m2 $32.5» .3 B :5me €3.53 .3 asap 17 .243 00...? .o. 32 EacEE d2 .295 .88 a 30 02m 0. "Aw 2 .25 3833 30 :V a 5.3 05 $80 £00880 m he.“ .. .350; .505 .3 .A0_q£:8 .295 ”was .EV *mafilfisla .88 a. E 58 .380 cam .380 02 ”803085 3v 3883. 808—380 mo 00—3 N 855 0:93 .3 tomEQBm 0% 308m 00 Ho: D0230 £8000 08:80.8 0: £800» 2V 0mm 18.888 imam 08% 0.5% £89588» 082:8 amém “BO 8%ng oooakofiafiho 25 23 voom .E 00 was.» A9380 .3 03a... 18 .v.m-m._ ”H083 .mNHMOZ £030: 508080.60 w.Tm.o ”5°83 .o._um0\< ”:08 08~\080>0m m.~-o._ ”5°83 dgnmoz ”:08 um _ \080>0m w._-o._ 80$? .m._um0\< ”0800,00 £00— ”8008088800508 odToN ”5°83 6.0352 ”0020: 508080.60 N666 “5°83 KAHMOF. £08 08N\080>0m m.m-o._ ”Saba 64352 ”.20: um _ \080>0m v.N-N._ “5°83 KAN M02 ”08080 30— “08:5 ”m0; .0.m-m.~ ”—0.803 .0835)». £020: 808080.60 0N8; “5&3 .NLHMO)‘ E08 08N\08>0m OWN.— uUfifia 6435).. ”.20: um _ \080>0m ~.N-N._ ”6°83 0435?. ”080.60 000— 88853838 ”PS =80>O $080888 80.880 8 0800 80808 .80080w 80.88 .808w08 8803.“ 8088008 38008 .30 08 080808880 0% £08088 £08880 880888 08>00 8088 .3808 £60883 8808008 .80 008 8:80 _0w0_= .008 88080 $83080 .08008 20800808 .0880 .80 80880—880 £803 3808 80800800 .008 .0w0 380802 $055.58.... .32? ”00> 050 03.... £38. .va 58 008830 30 2v 8 58 2: A0020: 808 8 080.60 $080808 .8 .208 08m 8 080.60 $080888 .8 .208 02 8 080>0m M080>0m v.00: wllJoIIIEEF .0 09.0.0. £808.88 :85 .00808808008 88.80002 £88038 08:88 888—0xm m\Z :.0.wuz wwfl 3980 £80 0.0 080802 w8020x0v 30 8: 08:22 Sow ._0 00 80> 50.808 .NA 030R. 19 mow._nz 3080808 80880 8 30 um v M32 000-83 8.2-86 80°33 0800 830808 88880—0008 .mKHMOZ .00uMO .088080 888:.80 .808880 6:80 08m .380 82 “am 0.8080802 8080088 08m 5805 80888 0200800808 8000088 .EV mg .880 8000088 08m 8 m> N.m-w.o 80.x? .0330 0808000 08080008 08888 0>8080080m .0. W002 .0. T8 -28. .000 083.2 .3. .8880 slang 8080088 00— 88809008 w880 ooom 888; .02 0088088080000 880002 m2 ._0 00 0.80.2. mhuz .36 mm V 80732 .00808508 0000: 08 8080800000 69008 .0=8V .30 VmV 80 033.2 82 08880 $830803 95-0008800m 02 0008300: 08080008 8000380 883. ”8808—08 8.880080% .30 VmV 00 9.8 $2 8 x08 88:? 00800000 0080008 Sam 8 >90 0mv 80 ODE?‘ .02 38008 .8 3030”“ $2 ._0 00 880.— 80.05.00 .8 03.8. 20 3:? ”5x3 in; Q >25 gofizonvmmfi .v.N.._.N Magma .N.Nnmm\< 303v .2? 3 8: :5 363m 088 3 @8833 .EOMHE 68583 2233.5.“ .355 8583 ”£88 Ems—ta .3 s 55.2 52m mogawuaéa .mcouaoszOo 83.8985 .motSmE 0383558 a. .862: .8: $5 32: .92 .293 .E .30 SW .m.m-m.~ ”Ho 33 KAHMOE 63% 3:83 .3995 SE voEzgsmv as 303—033 8: 35w“ «$2.33 ”:2 63.850 vogmfi 30 mm v 0:383 ”9:835 go 313 a0 83 ddnmoz 90 09¢ .335 358 6an 383 .BE3 55 .850 88 62 ”1E .25 .88 .03 Eng“: m2 gm w.m-~.m :0 $3 “QNHMOE M33 ”EOMAE .02 .3383 388m m2 .3 B 536me Ava—39V .NA 03.? 21 30 um v 3ng dean—anon wane—8&8: .328 fig 5:0 “2 .maousmow =8“:ch Sag—am .Eofimm .95 m2 ”888—5.: 2?: wIEE. IFi Incomde—ofi as, 83383 $5552; 82 m> .9885 vcm .02 m2 m2 .3 Ho Stav— cmv. T2 092-32 «:50 .m:oM-w=om £925 28 Emma: EEoEE 5th 30 um v .838 wEvooS 8505— 3.980 .25.on .waflofim .0585 2:28am .mcousmow oat—=8 -ommo guacamobom 6x33 3 23:8 5.58:? am“ 5532 .36 “AA an 3 A56: E ”830 32 ”PE .2 .0838 3338 m2 .3 Ho :20 .2353 .3 035 22 mafifiuz 30 mm v 237:2 .Abco tonoU $2 @988 18608 a no 3038 a. 32385 33 deg ”5&3 .mNuMa .oZ REES: :ofioaéH m2 .3 6 88:23 30 mm v .o.v.m.~ ”583 J.~HMO\< ”baa 8308.5 tam 305.5053 698: .szv w _ fiwuz wwfl ”6.x? fume? 8:8838 5:202 lllmsagsm was 5308.5 E @358? .aoEofi .35. a E 58 3o :8- ma :8 ”wag; @0265 .353 beam“: 5:0 wcm .bno H2 3:335»: .8: 3:33 ”$288.5 3v wIEE.IF 0.8a c6555 van—Em $.34 ”6.x? .m.~umo\< .wfioem Jfiioaeo .30 av a owaESmE ”~93: £33 38m .333 32.88 2:88 Eamon .mcoufimow 23:2: tonou o>cooamo£ m.~-m._ ”5&3 Jfiumoz £23260 .owm ~§a2 353:6 8 53 3“ av ”couioxm an»: «N 30 ”engages: .82 u$£>3fl .oZ REES 5.223: 36 av :5 “BEES cam .130 EEm A5253 .3 2e; 23 wmvnz 3.2-33 3.8559 30 mm v .mcotflmuw 032:6 tocou $2 $2 ”aofiioxm 32 ”We; ”5°33 ._.Nu.mm .oZ $2 30 cm v .3 Ho 5.5m Ems; sense anmuz $5me 32333800 _§w2o8§m 3o 3v 3 ans 25 23253 553,5 3.502858 RSV many—SB .8: .323: .53: (db $me Vto> >52 .~.N-v.o ”5.x? ddnmoz Econ—a .wcfloEm .3325 g r93: E338 mBSm Evian 838:0 fiasco QTad ”5&3 .mAHMOE £23260 .03 32.632 58? m2 ”Em: $2 ”magnum .02 .8325: “SEE—om 85085 cam ._a go ofinobm .6325 .3 03:. 24 oNNan >90 mm v 33%;— 638 HgocEwmmv 3% ASNBBEQ 285:»... Eco >90 omv “a m> 3550.030 m2 . 38.33503 33.4%. Eco $508 3062: $3 .2: an.“ King .02 03.8%on m2 .3 a guess 3an wSTRE 30 nmv “a FEB “55 30 years of age), education (<12, =12, and >12 completed years of schooling), parity (no previous live birth, previous live birth/preterm, and previous live birth/term), Medicaid status (yes/no), 31 marital status (married/living with husband, married/not living with husband, not married/living with partner, and not married/not living with partner), cigarette smoking during pregnancy (no smoking during pregnancy, quit smoking before enrollment, smoking up to 1/2 pack per day at enrollment, and smoking over ‘/2 pack per day at enrolment), and alcohol use during pregnancy (yes/no). Polytomous regression was used to assess the relations between bleeding and delivery outcome, i.e. three preterm delivery subtypes (preterm labor, preterm rupture of membrane, medically induced), and term (referent category). Separate models were constructed for each of the tree bleeding variables (timing, duration and heaviness). Bleeding variables were categorized into three levels with “no bleeding” as a referent category. All statistical analysis were performed using Statistical Analysis System Software (Release 9.1.2, SAS Institute, Inc., and Cary, NC). 2.3 Results The distributions of selected maternal socio-demographic and pregnancy history characteristics of study participants are presented in Table 2.1. Among study women 84.1% were enrolled into the study in their 20th-24th week of pregnancy, 46.7% were insured by Medicaid, and 10.4% delivered preterm. The history of any vaginal bleeding in the first 20 weeks of pregnancy was very similar in non-Hispanic White (24.4%) and African-American (23.4%) (Table 2.2). Distribution of timing, duration, and heaviness of bleeding were also similar in both groups. Percentages in Afiican-American women versus non-Hispanic White were not statistically different. In the ethnicity/race-specific analysis, risk of preterm delivery was 32 increased in all bleeding groups; however it was especially high in women with bleeding “in weeks 14-20 +/- weeks 1-13” (14.3% among non-Hispanic White and 13.7% among African- American women), women with bleeding that lasted for over 24 hours (14.4% among non-Hispanic White and 21.6% among Afiican-American), and women with the amount of bleeding described as “same or greater then usual menstrual period” (18.1% among non-Hispanic White and 26.1% among African-American) (Table 2.3). Within the bleeding groups there was no significant ethnic/racial difference in the risk of preterm delivery. Ethnicity/race—specific odds ratios (OR) for preterm delivery in association with bleeding appeared greater in non-Hispanic White (OR range 1.6-2.7) than in Afiican- American women (OR range 1.0-2.2) (Table 2.3); however this was due to the fact that the “no bleeding” group in African-American women had a higher risk of preterm delivery (13.9%) compared to that in non-Hispanic White (7.6%): OR=2.0, 95% CI: 1.4- 2.7. Adjustment for potential confounders, including maternal age, education, parity, marital status, Medicaid status, cigarette smoking, and alcohol consumption during pregnancy did not change odds-ratio estimates by more than 10%. Since there was no significant interactions between ethnicity/race and any of the bleeding characteristics (p=0.34 for timing, p=0.50 for duration, and p=0.51 for heaviness) African-American and non-Hispanic White women were combined for further analysis. Table 2.4 shows the association between vaginal bleeding in the first 20 weeks of pregnancy and the risk of preterm delivery in the model that combined racial/ethnic groups. The risk appeared to be increased in all bleeding groups but especially high in women with amount of bleeding described as “same or greater then usual menstrual period” (OR=2..4, 95% CI: 1.5-4.0), and women with bleeding that lasted for over 24 33 hours (OR=1.8, 95% CI: 1.3-2.7). As for the timing of bleeding, the risk of preterm delivery appeared to be the same in both groups: bleeding “in weeks l-13 only” and “in weeks 14-20 +/- weeks 1-13” (OR=1.6, 95% CIs: 1.1-2.2 and 1.0-2.5 respectively). The results of analysis for the association between vaginal bleeding in the first 20 weeks of pregnancy and preterm delivery subtypes, i.e. preterm labor (PTL), preterm premature rupture of membrane (PPROM), medically induced (MI), are presented in Table 2.5. Of all preterm deliveries 41.2% were preceded by PTL, 26.1% were preceded by PROM, and the remaining 32.7% were delivered with medical intervention. Women with bleeding “in weeks 14-20 +/- weeks 1-13” were at high risk of both PROM (OR=1.9, 95% CI: 0.9-4.1) and medically induced delivery (OR=1.8, 95% CI: 0.9-3.7). However risk of PTL was higher in women with bleeding “in weeks l-l3 only” (OR=1.9, 95% CI: 1.2- 3.0). Women with bleeding that lasted for over 24 hours were at high risk of medically induced delivery (OR=2.1, 95% CI: 1.2- 3.8) and PROM (OR=1.9, 95% C1: 1037). The risk of PTL was lower, and very similar in both groups: women with bleeding that lasted for up to 24 hours, and women with bleeding that lasted for over 24 hours (OR=1.7, 95% CI: 1.0-2.9 and OR=1.6, 95% CI: 0.9-2.9 respectively). Women with the amount of bleeding described as “same or greater then usual menstrual period” were at very high risk of PTL (OR=3.4, 95% CI: 1.8-6.5). Risk of PROM in this group was lower but still very high (OR=2.5, 95% CI: 1.1-6.1). However the risk of medically induced delivery was higher in women with the amount of bleeding described as “spotting/slight” (OR=1.7, 95% CI: l.0-2.8). Overall the strongest association was found between heavy bleeding (described as “same or greater than usual menstrual period”) and both spontaneous subtypes of preterm delivery (for PTL: OR=3.4, 95% CI: 1.8-6.5 and 34 for PROM: OR=2.5, 95% CI: 1.1- 6.1). Medically induced delivery was most strongly related to bleeding that lasted for over 24 hours (OR=2.1, 95% CI: 1.2-3.8). 35 Table 2.1. Selected Sociodemographic and Pregnancy History Characteristics of Study Participants Maternal Characteristics N (%) AGE 15-19 355 (15.1) 20-29 1,325 (56.3) 230 674 (28.6) RACE White Non-Hispanic 1,735 (73.7) African-American 619 (26.3) PARITY No Previous Live Birth 1,024 (43.5) Previous Live Birth/Preterm 105 (4.5) Previous Live Birth/Term 1,225 (52.0) EDUCATION (years) T < 12 409 (17.4) = 12 698 (29.7) > 12 1,244 (52.9) MEDICAID T Have Medicaid 1,100 (46.7) Do not have Medicaid 1,251 (53.1) GESTATIONAL AGE AT ENROLLMENT (wks) I 20-22 1,180 (50.1) 23-24 800 (34.0) 25-27 374 (15.9) GESTATIONAL AGE AT DELIVERY (wks) < 35 79 (3.4) 35-36 166 (7.0) 2 37 2,109 (89.6) 36 Table 2.1. (cont’d) Maternal Characteristics N (%) MARITAL STATUS T Married, living w/husband 1,182 (50.2) Married, not living w/husband 14 (0.6) Not married, living w/partner 533 (22.6) Not married, not living w/partner 618 (26.3) CIGARETTE SMOKING IN PREGNANCY T No smoking during pregnancy 1,689 (71.8) Quit smoking before the enrollment 242 (10.3) Smoking (5 ‘/2 pack p/day) during pregnancy 282 (12.0) Smoking (>'/2 pack p/day) during pregnancy 137 (5.8) ALCOHOL CONSUMPTION IN PREGNANCY T Yes 443 (18.8) No 1,896 (80.5) * Women other than non-Hispanic White and African-American are not included. T Missing values: education-3, Medicaid-3, marital status-7, smoking-4, alcohol-15. 1 Women enrolled into study during 15-19 weeks of pregnancy are not included. 37 Table 2.2. History of Vaginal Bleeding in the First 20 Weeks of Pregnancy by Maternal Ethnicity/Race Nonfiizanic African-American (N=1,735) (N=619) N (%) N (%) TIMING No Bleeding in weeks 1-20 1,311 (75.6) 474 (76.6) Bleeding in weeks 1-13 only 298 (17.2) 94 (15.2) Bleeding in weeks 14-20 +/- weeks 1-13 126 (7.2) 51 (8.2) DURATION * No Bleeding 1,311 (75.6) 474 (76.7) Short: 5 24 hours 223 (12.8) 93 (15.1) Long: > 24 hours 201 (11.6) 51 (8.2) HEAVINESS T No Bleeding 1,311 (75.6) 474 (76.7) Light: Spotting/Slight 340 (19.6) 121 (19.6) Heavy: Z Menstrual Period 83 (4.8) 23(3.7) * 1 African-American has missing data. T 1 African-American and l non-Hispanic White have missing data. 38 .bowofio 858%: a E Each ”mEbZ .38 wfimmg 26: 833 Beaumiéo: _ can :wotoE<-§o.E< _ C. .83 95me was smotoE<é85< _ ... A; we 3 sea 0 8.3 2 5. .m. 3 Z 2.”: 2 8.5V we cocoa §b§2 m as .98 S 8.4: E 2.2: m2 9% .2V 3 a: z 9. A38 8». szm \ macaw use 8.3 8 2 .08 we. .3 6.: 2: $3 :S @683 02 a. mmmz§ 24 hours 212 (84.1) 40 (15.9) 1.8 (1.3, 2.7) HEAVINESS T No bleeding 1,619 (90.7) 166 (9.3) Ref Spotting / Slight 403 (87.4) 58 (12.6) 1.4 (1.0, 1.9) 2 Menstrual Period 85 (80.2) 21 (19.8) 2.4 (1.5, 4.0) * 1 missing value in Term. T 2 missing values in Term. NOTE: Term is a reference category. 40 .bowoaao 8:222 a 2 85,—. $902 .EBH E 82:, 9528 N m. .55... E 2;? @525 _ _.. 8.8 .2: 2 8.: m :8 ._.: 3 8.: 8 8.8 .w. : v.8 8. _ : 2 8.8: mm 8.5.. Ease: m 88 8.: S 8.: 8 8.~ .2: S 8.: 2 88 .2: 2 8.: mm 8.:: 8:. 3:8 \ 288m :0: 8.: 8 88m 8.: a. :0: 8.: S 8.8: 22 8583 oz .2 mam—25$: 8.8 .N: S 8.: 2 88 8.: 2 8.: : 88 .2: 3 8.: E 8.3: N: £5: E A 8.~ .2: S 8.: : 88 .2: 3 8.: m 88 .8. : S 8.: cm 8.:: RN 2.2 2 w .3 8.: 8 80m 8.: 2 :3: 8.: S 8.8: a 8.. 858.33 oz .. zofiéaa 8.8 .2: 2 c .: a 2+ .2: 2 8.: w 88 .2: 2 8.: w 8.8: «2 2-718-: 283 a 2:85 8.~ .2: 2 8.: : 8.~ .2: S 8.: : 88 .N: 2 8.: 2 8.:: 2m .48 ME 9.83 a 8:885 :3: 8.: 8 .3 8.: 2 .3: 8.: S 8.8: as; 82 £83 a 2883 oz 052:. :0 $2 : mo 3.: z :0 :2 : mo 8: 2 Co $2 : mo 8: z 3: z 826.: 2.3802 :9: EL as... 89325 a: .3 fez—o: 3.53.5 no :83 2: 25 .35:on me 2.3.3 on :25 2: 5 ”2:3:— 35”.; .5952. :e:a_oemm< .m.~ 035. 41 2.4 Discussion A number of previous studies have reported increased risk of preterm delivery associated with antenatal vaginal bleeding (76-95), particularly during the first trimester of pregnancy (78,85,93), and during the second half of pregnancy (91,92). It has also been reported that vaginal bleeding during the first half of pregnancy significantly increases the risk of vaginal bleeding during the second half of pregnancy (91). A very limited number of studies have assessed ethnic/race—specific differences in the relations between preterm delivery and antenatal vaginal bleeding. Those studies reported that odds-ratios were greater in White than in African-American women (79,80). Similarly in our study we found that ethnic/race-specific odds-ratios for preterm delivery in association with vaginal bleeding during the first 20 weeks of pregnancy were greater in non-Hispanic White than in African-American women; however this was primarily due to the higher risk of preterm delivery in “non-bleeders” (reference group) among Afi'ican-American women compared to non-Hispanic White and there were no statistically significant interactions by race/ethnicity. Thus our study suggests that ethnic/racial disparities in the risk of preterm delivery are not mediated by pathways associated with vaginal bleeding in the first 20 weeks of pregnancy. It is important to take bleeding characteristics (i.e. timing of bleeding, duration and heaviness of bleeding episodes) into account, since they may influence association between antenatal vaginal bleeding and the risk of preterm delivery. Many studies on antenatal vaginal bleeding and the risk of preterm delivery assessed timing of bleeding episodes (76,77,79-83,85,86,90-93) and some assessed heaviness (78-81,84,86); however only one study considered duration of bleeding episodes (79). While most of the 42 studies that considered heaviness of bleeding episodes found that the risk of preterm delivery was notably higher in women with heavier bleeding episodes (78-80,84) some studies found no association between heaviness of bleeding episodes and the risk of preterm delivery (81-86). Our detailed analyses using bleeding characteristics were consistent with previous findings, and suggested a dose effect with higher risk of preterm delivery as severity of bleeding increased. It was noted in our study that associations between the risk of preterm delivery and less severe bleeding were evident but weaker, an important nuance for prenatal care. There are a number of factors that may potentially account for some of the differences in results of prior studies. First, many studies failed to include characteristics of bleeding in their data analysis. Second, studies used different definitions of bleeding characteristics, especially for heaviness of bleeding episodes. Finally, different study designs, various sample sizes, and degrees of control for potential confounders in both data collection and statistical analysis were used by different authors. Among the many studies on vaginal bleeding during pregnancy and risk of preterm delivery very few have attempted to separate preterm delivery into its clinical subtypes, (i.e. PTL, PROM, and MI) (78,79,93,95). It has been reported that antenatal vaginal bleeding increases the risk of PTD in all subgroups but especially for PTL (79, 93,95). Only one study looked at the association between vaginal bleeding and risk of preterm delivery using both bleeding characteristics (timing, duration, and heaviness), and clinical subtypes of preterm delivery (79). One more study assessed the relation between heaviness of bleeding and the risk of PPROM (78). 43 In our study we found that both heavy bleeding (described as “same or greater than usual menstrual period”), and bleeding that lasted for over 24 hours were strongly associated with the risk of both spontaneous subtypes of preterm delivery (PTL and PROM). We also found increased risk of PROM in a group with bleeding described as “spotting/slight”. All these findings were consistent with findings fiom other studies (78, 79). We also found strong associations between bleeding that lasted for over 24 hours and the risk of medically induced delivery and between bleeding “in weeks 1-13 only” and the risk of PTL. These findings contradicted the findings reported by Yang et a1 (79). There has been much debate in the literature as to whether preterm delivery should be separated into its clinical subtypes. While some researchers insist on separation (95 ,96) others stand against it, arguing that these subtypes may not be etiologically different, may be confounded by differences in access to medical care, and may be subject to misclassification (97). Some investigators recommend that the subtypes be examined first, and if they appear to be homogenous, combine them back together (95, 96). In at least two studies, results showed that the overall set of risk factors associated with preterm labor and premature rupture of membrane was the same but different from those for medically induced preterm delivery. Given these findings the authors recommended that preterm labor and preterm premature rupture of membranes be combined into spontaneous preterm delivery and that medically induced preterm delivery be considered separately (95,96). Our study has its strengths and limitations. Major strengths of this study are the large sample size, prospective design, the fact that women were not selected into the study based on their bleeding history, and confirmation of gestational age estimates based 44 on the last menstrual period using early ultrasound estimates for 90% of study women. Furthermore, the interval fi'om period of bleeding during the first 20 weeks of pregnancy to time of maternal interview was short, thus minimizing recall bias; women were able to report up to seven bleeding episodes, and prospective collection eliminated the possibility of differential reporting based on women’s knowledge of pregnancy outcome. Reliance on maternal self-report for information about vaginal bleeding episodes has its limitations and strengths. While there is subjectivity in recalling bleeding, self-report is potentially more accurate and complete than information obtained from medical records. It is possible that women might mistake an early vaginal bleedings as a menstrual period or vise versa but confirmation of gestational dates by ultrasound helps to reduce bias introduced by these types of mistakes. However potential reporting bias could be introduced by the possibility that women known to be at higher risk of delivering preterm, such as those with prior preterm deliveries, might over-report their vaginal bleeding because of increased anxiety during the current pregnancy. It is important to note that our study did not include women who miscarried prior to 20 weeks of pregnancy, and women who suffered fetal loss sometime between 20th and 27th weeks of pregnancy. More studies are needed in order to further understand the association between vaginal bleeding during pregnancy and preterm delivery and the underlying mechanism for this association in order to be able to make recommendations for prenatal care. This study points to the importance of carefully considering bleeding characteristics, ethnic/racial differences, and clinical subtypes of preterm birth in pathways to preterm delivery. 45 10. REFERENCES Slattery M, Morrison JJ. Preterm delivery. Lancet 2002; 360: 1489-97. Demissie K, Rhoads G, Ananth C, Alexander G, Kramer MS, Kogan M, Joseph K. Trends in preterm birth and neonatal mortality among blacks and whites in the United States from 1989 to 1997. Am J Epidemiol. 2001; 154: 307-315. Berkowitz GS, Papiemik E. Epidemiology of preterm birth. Epidemic] Rev. 1993; 15: 414—43. Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Menacker F, Kirmeyer S. Births: F inal data for 2004. National Vital Statistics Reports; (2005) Vol.55(1), Hyattsville, MD: National Center for Health Statistics. Martin JA, Hamilton BE, Sutton PD, Ventura S, Menacker F, Kirmeyer S, Munson M. Births: Final data for 2005. National Vital Statistics Reports; (2007) Vol.56(7), Hyattsville, MD: National Center for Health Statistics. Hamilton BE, Martin JA, Ventura SJ. Births: Preliminary data for 2006. National Vital Statistics Reports; (2006) Vol.56(6), Hyattsville, MD: National Center for Health Statistics. PeriStats, March of Dimes Perinatal Data Center. Adams MM, Sarno AP, Harlass FE, Rawlings J S, Read J A. Risk factors for preterm delivery in a healthy cohort. Epidemiol. 1995 Sep; 6(5): 525-32. Fraser AM, Brockert J E, Ward RH. Association of young maternal age with adverse reproductive outcomes. N Engl J Med. 1995; 332: 1113-17. Smith GC, Pell JP. Teenage pregnancy and risk of adverse perinatal outcomes associated with first and second births: population based retrospective cohort study. BMJ 2001; 323: 476-80. 46 11. 12. 13. 14. 15. 16. 17. 18. 19. Hoffman MC, J effers S, Carter J, Duthely L, Cotter A, Gonzalez-Quintero VH. Pregnancy at or beyond age 40 years is associated with an increased risk of fetal death and death and other adverse outcomes. Am J Obstet Gynecol.2007 May;196(5):e11—3. Kramer MS, Seguin L, Lydon J, Goulet L. Socio-economic disparities in preterm birth: causal pathways and mechanisms. Paediatr Perinatal Epidemiol. 2001; 15: 104-23. Peacock J L, Bland JM, Anderson HR. Preterm delivery: effects of socioeconomic factors, psychological stress, smoking, alcohol, and caffeine. BMJ 1995; 311: 531-535 Gardner MO, Goldenberg RL, Cliver SP, Tucker JM, Nelson KG, Copper RL. The origin and outcome of preterm twin pregnancies. Obstet Gynecol. 1995 Apr; 85(4): 553-7. Kurdi AM, Mesleh RA, Al-Hakeem MM, Khashoggi TY, Khalifa HM. Multiple pregnancy and preterm labor. Saudi Med J. 2004 May; 25(5): 632-7. Iarns JD, Goldenberg RC, Meis PJ, Mercer BM Moawad A, Das A. The length of the cervix and the risk of spontaneous preterm delivery. N Engl J Med. 1996; 334: 567-572. Hassan SS, Romero R, Bersy SM, Dang K, Blackwell SC, Treadwell MC, Wolfe HM. Patients with ultrasonic cervical length equal to 15 mm have nearly 50% risk of early spontaneous preterm delivery. Am J Obstet Gynecol. 2000; 182: 1458-1467. McManemy J, Cooke E, Amon E, Leet T. Recurrence risk for preterm delivery. Am J Obstet Gynecol. 2007 Jun; 196(6): 576.e1-6. Leitich H, Bodner-Adler B, Brunbauer M, Kaider A, Egarter C, Husslein P. Bacterial vaginosis as a risk factor for preterm delivery: A meta-analysis. Am J Obstet Gynecol, Vol. 189(1): 139-147. 47 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. Goldenberg RL, Hauth J C, Andrews WW. Intrauterine infection and preterm delivery. N Engl J Med. 2000; 342: 1500-07. Romero R, Gomez R, Chaiworapongsa T, Conoscenti G, Kim J C, Kim YM. The role of infection in preterm labour and delivery. Paediatr Perinat Epidemiol. 2001; 15 (suppl 2): 41-56. French J I, McGregor J A, Parker R. Readily treatable reproductive tract infections and preterm birth among black women. Am J Obstet Gynecol. 2006 Jun;194(6):1717-26;. Hitti J, Nugent R, Boutain D, Gardella C, Hillier SL, Eschenbach DA.Racial disparity in risk of preterm birth associated with lower genital tract infection. Paediatr Perinat Epidemiol. 2007 Jul;21(4):330-7. F iscella K. Racial disparities in preterm birth. The role of urogenital infections. Public Health Rep 1996;111:104-1 13 Gravett MG, Nelson HP, DeRpuen T, Critchlow C, Eschenbach DA, Holmes KK. Independent associations of bacterial vaginosis and Chlamydia trachomatis infection with adverse pregnancy outcomes. J AMA. 1986;256:1899—1903. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA. 2002 Oct 9;288(14):1723-7. Ehrenberg HM, Dierker L, Milluzzi C, Mercer BM. Prevalence of maternal obesity in an urban center. Am J Obstet Gynecol. 2002 Nov;187(5):1189-93. Rosenberg TJ, Garbers S, Lipkind H, Chiasson MA. Maternal obesity and diabetes as risk factors for adverse pregnancy outcomes: differences among 4 racial/ethnic groups. Am J Public Health. 2005 Sep;95(9):1545-51. Steinfeld JD, Valentine S, Lerer T, Ingardia CJ, Wax JR, Curry SL. Obesity- related complications of pregnancy vary by race. J Matem Fetal Med. 2000 J ul- Aug;9(4):238-41. 48 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. Boyle JP, Honeycutt AA, Venkat Narayan KM, et al. Projection of diabetes burden through 2050 impact of changing demography and disease prevalence in the US. Diabetes Care. 2001;24:1936-1040. Eisner GM. Hypertension: racial differences. Am J Kidney Dis. 1990 Oct;16 (4 Suppl l):35-40. Tanaka M, J aamaa G, Kaiser M, Hills E, Soim A, Zhu M, Shcherbatykh IY, Samelson R, Bell E, Zdeb M, McNutt LA. Racial disparity in hypertensive disorders of pregnancy in New York State: a 10-year longitudinal population- based study. Am J Public Health. 2007 Jan;97(1):163-70. Epub 2006 Nov 30. Eskenazi B, Fenster L, Sidney S. A multivariate analysis of risk factors for preeclarnpsia. JAMA. 1991 Jul 10;266(2):237-41. Nordentoft M, Lou HC, Hansen D, Nim J, Pryds O, Rubin P, Hemmingsen R. Intrauterine growth retardation and premature delivery: the influence of maternal smoking and psychosocial factors. Am J Public Health. 1996; 86: 347—54. Shah NR, Bracken MB. A systematic review and meta-analysis of prospective studies on the association between maternal cigarette smoking and preterm delivery. Am J Obstet Gynecol. 2000; 182: 465-72. Harnmoud AO, Bujold E, Sorokin Y, Schild C, Krapp M, Baurnann P. Smoking in pregnancy revisited: findings from a large population-based study. Am J Obstet Gynecol. 2005 Jun; 192(6): 1856-62. Handler A, Kistin N, Davis F, F erre C. Cocaine use during pregnancy: perinatal outcomes. Am J Epidemiol. 1991; 133: 818-21. Miller JM, Boudreaux MC. A study of antenatal cocaine use: chaos in action. Am J Obstet Gynecol. 1999; 180: 1427-31. Homer CJ, James SA, Siegel E. Work related psychosocial stress and risk of preterm low birth weight delivery. Am J Public Health. 1990; 80: 173-177. 49 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. Perkin MR, Bland J M, Peacock J L, Anderson HR. The effect of anxiety and depression during pregnancy on obstetric complications. Br J Obstet Gynaecol. 1993 Jul; 100(7): 629-34. Wisborg K, Henriksen TB, Hedegaard M, Secher NJ. Do stressful life events affect duration of gestation and risk of preterm delivery? Epidemiol. 1996; 7: 339—45. Lockwood CJ. Stress Associated PTD. J Obstet Gynecol January 1999;180: 264-6. Hoffinan S, Hatch MC. Stress, social support and pregnancy outcome: a reassessment based on recent research. Paediatr Perinat Epidemiol. 1996 Oct; 10(4):380-405. Hogue CJ, Hoffman S, Hatch MC. Stress and preterm delivery: a conceptual framework. Paediatr Perinat Epidemiol. 2001 Jul;15 Suppl 2:30-40. Federenko IS, Wadhwa PD. Women's mental health during pregnancy influences fetal and infant developmental and health outcomes. CNS Spectr. 2004 Mar;9(3):198-206. Girdler SS, Hinderliter AL, Light KC. Peripheral adrenergic receptor contributions to cardiovascular reactivity: influence of race and gender. J Psychosom Res. 1993;37(2): 177-93. Hatch M, Berkowitz G, J anevic T, Sloan R, Lapinski R, James T, Barth WH Jr. Race, cardiovascular reactivity, and preterm delivery among active-duty military women. Epidemiology. 2006 Mar; 1 7(2): 1 78-82. Mamelle N, Laumon B, Lazar P. Prematurity and occupational activity during pregnancy. Am. J Epidemiol. 1984; 119: 309-322. Ahlborg G Jr, Bodin L, Hogstedt C. Heavy lifting during pregnancy. A hazard to the fetus? Int J Epidemiol. 1990; 19: 90-97. 50 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. Singh GK, Yu SM. Adverse pregnancy outcomes: differences between US-and foreign-bom women in major US racial and ethnic groups. Am J Public Health. 1996 Jun;86(6):837-43. Howard DL, Marshall SS, Kaufinan J S, Savitz DA.Variations in Low Birth Weight and Preterm Delivery Among Blacks in Relation to Ancestry and Nativity: NYC, 1998—2002. Pediatrics 118: e1399-e1405. Aveyard P, Cheng KK, Manaseki S, Gardosi J. The risk of preterm delivery in women from different ethnic groups. J Obstet Gynaecol 2002;109:894—99. Migone A, Emanuel I, Mueller B, Daling J, Little RE. Gestational duration and birthweight in white, black and mixed-race babies. Paediatr Perinat Epidemiol 1991;4z378—91. Buekens P, Klebanoff M. Preterm birth research: from disillusion to the search for new mechanisms. Paediatr Perinat Epidemiol. 2001 Jul; 1 5 Suppl 2: 159-61. Adams MM, Read JA, Rawlings J S, Harlass FB, Sarno AP, Rhodes PH. Preterm delivery among black and white enlisted women in the United States Army. Obstet Gynecol. 1993 Jan;81(1):65-71. MacMullen NJ, Dulski LA, Meagher B. Red alert: perinatal hemorrhage. MCN Am J Matem Child Nurs. 2005 J an-Feb; 30(1): 46-51. Johns J, J auniaux E. Threatened miscarriage as a predictor of obstetric outcome. Obstet Gynecol. 2006 Vol.107(4): 845-50. Lozeau AM, Poter B. Diagnosis and management of ectopic pregnancy. Am Farn Physician. 2005 Nov 1; 72(9): 1719-20 Pigott DC. Images in emergency medicine. Molar pregnancy. Ann Emerg Med. 2007 Jan; 49(1): 14-22. Sakombut E, Leeman L, Fontaine P. Late pregnancy bleeding. Am F am Physician. 2007 Apr 15; 75(8): 1199-206. 51 61. 62. 63. 64. 65. 66. 67. 68. 69. 70. 71. Oyelese Y, Smulian J C. Placenta previa, placenta accreta, and vasa previa. Obstet Gynecol. 2006 Apr; 107(4): 927-41. Brenner PF. Differential diagnosis of abnormal uterine bleeding. Am J Obstet Gynecol. 1996 Sep; 175(3 Pt 2): 766-9. Connolly AM, Katz VL, Bash KL, McMahon MJ, Hansen WF. Trauma and pregnancy. Am J Perinatol. 1997 Jul; 14(6): 331-6. Kadir RA, Economides DL, Braithwaite J, Goldman E, Lee CA. The obstetric experience of carriers of hemophilia. Br J Obstet Gynaecol. 1997 Jul; 104(7): 803-10. Yang J, Savitz DA, Dole N, Hartrnann KE, Herring AH, Olshan AF, Thorp JM Jr. Predictors of vaginal bleeding during the first two trimesters of pregnancy. Paediatr Perinat Epidemiol. 2005 Jul; 19(4): 276-83. Chan CC, To WW. Antepartum hemorrhage of unknown origin-what is its clinical significance? Acta Obstet Gynecol Scand. 1999; 78: 186-90. Lockwood CJ, Kuczynski E. Risk stratification and pathological mechanisms in preterm delivery. Paediatr Perinat Epidemiol. 2001; 15: 78-89; Chaiworapongsa T, Espinoza J, Yoshimatsu J, Kim YM, Bujold B, Edwin S, Yoon BH, Romero R. Activation of coagulation system in preterm labor and preterm premature rupture of membranes. J Matem Fetal Neonatal Med. 2002 Jun; 11(6): 368-73. Elovitz MA, Baron J, Phillippe M. The role of thrombin in preterm parturition. Am J Obstet Gynecol. 185 (2001): 1059—1063. Lockwood CJ. Testing for risk of preterm delivery. Clin Lab Med 2003;23:345- 60. Lockwood CJ, Kuczynski E. Markers of risk for preterm delivery. J Perinat Med. 1999; 27: 5-20. 52 72. 73. 74. 75. 76. 77. 78. 79. 80. Stella CL, Sibai BM. Thrombophilia and adverse matemal-perinatal outcome. Clin Obstet Gynecol. 2006 Dec; 49(4): 850-60. De Santis M, Cavaliere AF, Straface G, Di Gianantonio E, Caruso A. Inherited and acquired thrombophilia: pregnancy outcome and treatment. Reprod Toxicol. 2006 Aug; 22(2): 227-33. Franchini M, Veneri D, Salvagno GL, Manzato F, Lippi G. Inherited thrombophilia. Crit Rev Clin Lab Sci. 2006; 43(3): 249-90. Ananth CV, Savitz DA. Vaginal bleeding and adverse reproductive outcomes: a meta-analysis. Paedatrc and Prenatal Epidemiol. 1994. 8: 62-78. Boggess K, Moss K, Murtha A, Offenbacher S, Beck J. Antepartum vaginal bleeding, fetal exposure to oral pathogens, and risk for preterm birth at <35 weeks of gestation. Am J Obstet Gynecol. (2006) 194; 954-960. Magann EF, Cummings J E, Niederhauser A, Rodriguez-Thompson D, McCormack R, Chauhan SP. Antepartum bleeding of unknown origin in the second half of pregnancy: a review. Obstet Gynecol Surv. 2005 Nov; 60(11): 741-5 Weiss JL, Malone FD, Vidaver J, Ball RH, Nyberg DA, Comstock CH, Hankins GD, Berkowitz RL, Gross SJ, Dugoff L, Timor-Tritsch IE, D’Alton ME. Threatened abortion: A risk factor for poor pregnancy outcome, 3 population based screening study. Am J Obstet Gynecol. (2004) 190: 745-50. Yang J, Hartmann KE, Savitz DA, Herring AH, Dole N, Olshan AF, Thorp JM Jr. Vaginal Bleeding during Pregnancy and Preterm Birth. Am J Epdemiol. 2004. 160(2): 118-125. Yang J, Savitz DA. The effect of vaginal bleeding during pregnancy on preterm and small-for-gestational-age births: US National Maternal and Infant Health Survey, 1988. Paediatr Perinat Epidemiol. 2001; 15: 34—39. 53 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. Leung TY, Chan LW, Tam WH, Leung TN, Lau TK. Risk and Prediction of Preterm Delivery n Pregnancies Complicated by Atepartum Hemorrhage of Unknown Origin before 24 weeks. Gynecol Obstet Invest. 2001; 52: 227-231. Arafa M, Abdel-Fataah M, Abou Zeid H El-Khouly A. Outcomes of pregnancies complicated by early vaginal bleeding. Eastern Mediterranean Health Journal. 2000. 6(2/3): 457-464. Karim SA, Bakhtawar I, Butta AT, J alil M. Effects of first and second trimester vaginal bleeding on pregnancy outcome. J Pak Med Assoc.1998 Feb; 48(2):40-2. Sipla P, Hartikainen-Sorri AL, Oja H, Von Wendt L. Prenatal outcomes of pregnancies complicated by vaginal bleeding. Br J Obstet Gynaecol. Dec.1992, 99: 959-963. Williams MA, Mittendorf R, Lieberman E, Monsoon R. Adverse infant outcomes associated with first trimester vaginal bleeding. Obstet Gynecol. 1991; 78: 14-18. Strobino B, Pantel-Slverman J. Gestational Vaginal Bleeding and Pregnancy Outcome. Am J Epidemiol. 1989. 129(4): 806—815. Hertz J B, Heisteberg L. The outcome of pregnancy after threatened abortion. Obstet Gynecol Scand. 1985; 64: 151-156. Berkowitz GS. Clinical and Obstetrical Risk factors for PTD. The Mount Sinai Journal of Medicine 1985; 52: 239-247. Batzofin JH, Fielding WL, Friedman EA. Effect of vaginal bleeding in early pregnancy on outcome. Obstet Gynecol 1984 (63): 515-518. Berkowitz GS, Harlap S, Beck GL, Freeman DH, Baras M. Early gestational bleeding and pregnancy outcome: A multivariate analysis. International J ouma’l of Epidemiology, 1983; 12: 165-173 54 91. 92. 93. 94. 95. 96. 97. McCormack RA, Doherty DA, Magann EF, Hutchinson M, Newnham JP. Antepartum bleeding of unknown origin in the second half of pregnancy and pregnancy outcomes. BJOG, 2008 Oct;115(11):1451-7. Harlev A, Levy A, Zaulan Y, Koifrnan A, Mazor M, Wiznitzer A, F aizayev E, Sheiner E. Idiopathic bleeding during the second half of pregnancy as a risk factor for adverse perinatal outcome. J Matem Fetal Neonatal Med. 2008 May;21(5):331-5. Hossain R, Harris T, Lohsoonthom V, Williams MA. Risk of preterm delivery in relation to vaginal bleeding in early pregnancy. Eur J Obstet Gynecol Reprod Biol 2007;135:158-63. Kim YJ, Lee BE, Park HS, Kang JG, Kim JO, Ha EH. Risk factors for preterm birth in Korea: a multicenter prospective study. Gynecol Obstet Invest 2005;60 (4):206—12. Berkowitz GS, Blackmore-Prince C, Lapinski RH, Savitz DA. Risk factors for preterm birth subtypes. Epidemiology. 1998 May;9(3):279-85 Pickett KE, Abrams B, Selvin S. Defining preterm delivery--the epidemiology of clinical presentation. Paediatr Perinat Epidemiol. 2000 Oct; 14(4):305-8. Klebanoff MA, Shiono PH. Top down, bottom up and inside out: reflections on preterm birth. Paediatr Perinat Epidemiol. 1995 Apr;9(2):125-9. 55 S li'llljijljlll“ "'llll'lllllljllll!lilllllll 1 93 03163 ..........