你在这里

产科并发症后产后期健康相关生活质量的决定因素

European Journal of Obstetrics & Gynecology and Reproductive Biology, pages 88 - 95

Abstract

Objective

To determine the influence of socio-demographic, clinical parameters and obstetric complications on postpartum health-related quality of life (HRQoL).

Study design

We used data of three randomized controlled trials to investigate HRQoL determinants in women after an obstetric complication. The DIGITAT and HYPITAT trials compared induction of labor and expectant management in women with intra-uterine growth restriction (IUGR) and hypertensive disorders. The WOMB trial randomized anemic women after postpartum hemorrhage to red blood cell transfusion or expectant management. The HRQoL-measure Short-Form36 was completed at six weeks postpartum. Multivariable analyses were used to identify which parameters affected the Short-Form36 physical component score (PCS) and mental component score (MCS).

Results

HRQoL analyses included 1391 women (60%) of the 2310 trial participants. HYPITAT and DIGITAT participants had significantly lower MCS than WOMB participants. In multivariable analysis, PCS after elective and emergency cesarean section was 5–6 points lower than after vaginal delivery. Gestational hypertension, neonatal admission and delivery in an academic hospital had a small negative effect on PCS. No effect was found for randomization status, maternal age, BMI, country of birth, education, parity, induction of labor, analgesics, birth weight, perineal laceration, delivery of placenta, postpartum hemorrhage, congenital anomaly, urinary tract infection, thromboembolic event or endometritis. MCS was influenced only mildly by these parameters.

Conclusions

IUGR and hypertensive disorders lead to lower HRQoL scores postpartum than PPH. In a heterogeneous obstetric population, only mode of delivery by cesarean section has a profound, negative impact, on physical HRQoL (PCS). No profound impacts on MCS were detected.

Keywords: Health-related quality of life, Obstetric labor complications, Postpartum period, Pregnancy complications.

Introduction

Health-related quality of life (HRQoL) postpartum is potentially influenced by socio-demographic parameters, clinical parameters and obstetric complications. Socio-demographic parameters described to influence HRQoL postpartum negatively are black ethnicity [1] , low education [2] , low income [3] and large number of children at home [3] . A supportive social network influences postpartum HRQoL positively[1], [4], and [5]. The influence of mode of delivery on HRQoL varies in literature though HRQoL seems either similar or compromised following cesarean section compared to vaginal delivery[3], [5], [6], [7], and [8]. Common obstetric complications are intra-uterine growth restriction (IUGR), hypertensive disorders of pregnancy and postpartum hemorrhage (PPH)[9], [10], and [11]. Pregnancies with these complications are at increased risk for neonatal and/or maternal morbidity and mortality[12], [13], [14], and [15]. Poor physical and mental health have been described in mothers with obstetric complications like preterm birth[16], [17], and [18]. HRQoL is also compromised in women with postpartum complications like postpartum depression[5], [19], and [20], pregnancy-related deep vein thrombosis [2] and urinary and/or fecal incontinence[21], [22], [23], [24], and [25].

Recently, three multicenter trials were conducted that investigated maternal and/or neonatal outcomes and measured HRQoL in the postpartum period. The DIGITAT and HYPITAT trial primarily investigated the effect of induction of labor on neonatal and maternal outcome in pregnancies complicated by, respectively, IUGR and hypertensive disorders[26] and [27]. The WOMB trial primarily studied the effect of red blood cell transfusion (RBC) on physical fatigue in women after PPH [28] . The availability of such a large numbers of postpartum HRQoL data provided a unique opportunity to assess which parameters influence postpartum HRQoL after obstetric complications by combining data of the three trials.

We hypothesized that several socio-demographic and clinical parameters, as well as obstetric complications, affect postpartum HRQoL. Insight in these parameters will contribute to postpartum care and will provide the opportunity to develop individual strategies after obstetric complications.

Materials and methods

We used data of three randomized controlled trials, conducted within the Dutch Obstetric Consortium: the DIGITAT, HYPITAT and WOMB trial. Details of these studies and their ethic approval have been previously published[29], [30], and [31]. In the DIGITAT, HYPITAT and WOMB trial 52, 38 and 37 Dutch hospitals participated, respectively. In each trial, women who refused randomization were asked to participate as non-randomized women. Results of the trials have been described elsewhere[26], [27], and [28].

The ‘Disproportionate-Intrauterine-Growth-Intervention-Trial-At-Term’ (DIGITAT) included women with a singleton pregnancy, a fetus in cephalic presentation, between 36 + 0 and 41 + 0 weeks gestational age, with suspected IUGR (defined as fetal abdominal circumference below the 10th percentile, estimated fetal weight below the 10th percentile and/or a decreased relative growth) [26] . Women were allocated to induction of labor or expectant management. Primary outcome was composite neonatal adverse outcome.

The ‘Hypertension-and-Preeclampsia-Intervention-Trial-At-Term’ (HYPITAT) included women with a singleton pregnancy, a fetus in cephalic presentation, between 36 + 0 and 41 + 0 weeks of gestation, complicated by gestational hypertension (defined as diastolic blood pressure ≥95 mmHg, measured on two occasions) or mild preeclampsia (defined as diastolic blood pressure ≥90 mmHg measured on two occasions, in combination with predefined levels of proteinuria) [27] . Again, women were allocated to induction of labor or expectant management. Primary outcome was a composite measure of maternal outcome.

The ‘Well-being of Obstetric patients on Minimal Blood transfusions’ (WOMB) studied women after PPH (defined as peripartum blood loss ≥1000 mL and/or decrease in Hb concentration ≥1.9 g/dL), with an Hb concentration between 4.8 and 7.9 g/dL (3.0–4.9 mmol/L) 12 to 24 h after delivery. Women were allocated to RBC transfusion or expectant management. Primary outcome was physical fatigue at day 3 postpartum, scored using the HRQoL measure multidimensional fatigue inventory.

Six hundred fifty-eight DIGITAT women (60%), 818 HYPITAT women (71%) and all WOMB women participated in the HRQoL study. Questionnaires were completed at several time points; the only common time point in the trials was six weeks postpartum. Each trial used the ShortForm-36 version 1 (SF-36v1), a generic HRQoL measure with eight scales (physical functioning, role limitations due to physical health problems [role-physical], bodily pain, general health, vitality, social functioning, role limitations due to emotional health [role-emotional], and mental health), ranging from 0 to 100; higher scores indicate better well-being. The SF-36v1 has been validated in a random nationwide sample of the Dutch population [32] . For this study, age and gender matched reference scores were provided by this research group (unpublished data based on 367 women aged 16–40 years, Aaronson et al.). The pilot study of the WOMB trial [8] provides postpartum reference scores based on 141 women that subsequently delivered in three Dutch hospitals.

The SF-36v1 allows for computation of the summary scores physical component score (PCS) and mental component score (MCS). These are norm-based with a mean of 50 and a standard deviation of 10, based on US population reference scores [33] . No Dutch population reference scores are available for the summary scores.

Statistical analysis

We studied the PCS and MCS at six weeks postpartum in women who suffered obstetric complications. To create a homogeneous cohort, women from the WOMB trial that delivered before 36 + 0 weeks of gestation and multiple gestations were excluded. We used multiple imputations to handle missing values of all socio-demographic and clinical parameters [34] : ten imputed data sets were created using a fully conditional specified model. Imputations were based on the relations between the covariates in the study. Data were analyzed separately in each imputed data set to obtain the effect estimates. Pooled estimates were generated from these ten imputed data sets and used to report estimates and their corresponding 95% confidence intervals.

SF-36v1 subscale scores were compared to Dutch population reference scores and to postpartum reference scores. As no Dutch population reference scores are available for the summary scores PCS and MCS, these were compared to US population references [33] .

We used univariable linear regression analysis to investigate parameters that were assumed to be related to HRQoL postpartum. The following socio-demographic and clinical parameters were analyzed: randomization status, age, BMI, country of birth (Dutch vs non-Dutch), highest education, parity, hypertensive disorders, gestational age at birth, induction of labor, analgesics, mode of delivery, perineal laceration, manual placenta removal, birth weight, PPH, admission of the neonate, congenital anomaly of the neonate, urinary tract infection, thrombo-embolic event, endometritis and hospital setting. To investigate the relationship of these parameters with HRQoL, we performed multivariable linear regression analysis, including those parameters with a significant relation to primary outcome measures in the univariable analyses (p < 0.10). Data were managed using SPSS version 20.0.

Results

A total of 3191 women were included in the three trials. Fig. 1 shows the flowcharts of this study. A total of 2310 participated: 1399 (61%) were randomized while 911 women (39%) refused randomization but participated as non-randomized women. HRQoL data at six weeks postpartum were available in 1391 women as the response at this time point was 60% (61%, 65% and 55% in the DIGITAT, HYPITAT and WOMB trial, respectively). We will refer to responding women as responders while women with no HRQoL data at six weeks postpartum will be referred to as non-responders.

gr1

Fig. 1 Flowchart of women participating in this study.awomen that delivered before 36 + 0 weeks of gestation and multiple gestations.

Socio-demographic and clinical parameters

The mean age of women was 30 years and 64% was primiparous. About 85% of women delivered vaginally, 46% had a hypertensive disorder while 41% suffered from a PPH. Among our study population, one maternal death occurred. This patient, allocated to induction of labor in the DIGITAT trial, died at home 10 days after delivery. A cause for her death could not be found. Furthermore, one perinatal death occurred in the DIGITAT trial, among the non-randomized women.

Table 1 shows socio-demographic and clinical parameters and the differences between responders and non-responders. Compared to non-responders, responders were significantly older, more frequently born in The Netherlands and had a higher education. Also, differences were found in clinical parameters like parity, perineal laceration, rate of hypertensive disorders and rate of PPH.

Table 1 Socio-demographic and clinical parameters.

  Total Responders Non-responders p-Value responders vs non-responders
n = 2310 n = 1391 n = 919
Socio-demographic        
Maternal age in years, mean (SD) 29.9 (5.2) 30.5 (4.9) 28.9 (5.5) <0.001
 Missing, n (%) 7 (0.3%) 2 (0.1%) 5 (0.5%)  
BMI       0.05
 <18.5 98 (4%) 59 (4%) 39 (4%)  
 18.5–25 1168 (51%) 698 (50%) 470 (51%)  
 >25 763 (33%) 483 (35%) 280 (31%)  
 Missing 281 (12%) 151 (11%) 130 (14%)  
Country of birth (%)       <0.001
 Dutch 1838 (80%) 1199 (86%) 639 (70%)  
 Non-Dutch 287 (12%) 111 (8%) 176 (19%)  
 Missing 185 (8%) 81 (6%) 104 (11%)  
Highest education       <0.001
 None/primary education 178 (8%) 91 (7%) 87 (10%)  
 Secondary education 848 (37%) 506 (36%) 342 (37%)  
 Higher professional education/university 520 (23%) 376 (27%) 144 (16%)  
 Missing 764 (33%) 418 (30%) 346 (38%)  
 
Pregnancy        
Parity, n %       0.004
 Primiparous 1476 (64%) 922 (66%) 554 (60%)  
 Multiparous 834 (36%) 469 (34%) 365 (40%)  
 Missing 0 0 0  
Hypertensive disorder       <0.001
 None 1298 (56%) 747 (54%) 551 (60%)  
 Gestational hypertension 619 (27%) 412 (30%) 207 (23%)  
 Preeclampsia 373 (16%) 225 (16%) 148 (16%)  
 Missing 20 (1%) 7 (0.5%) 13 (1%)  
 
Delivery        
Gestational age, mean (SD) 39 + 4 (10) 39 + 4 (10) 39 + 4 (10) 0.16
Induction of labor 1300 (56%) 822 (59%) 478 (52%) <0.001
 None 964 (42%) 554 (40%) 410 (45%)  
 Missing 46 (2%) 15 (1%) 31 (3%)  
Mode of delivery       0.003
 Vaginal, spontaneous 1590 (69%) 966 (69%) 624 (68%)  
 Vaginal, operative 346 (15%) 227 (16%) 119 (13%)  
 Elective CS 57 (3%) 26 (2%) 31 (3%)  
 Emergency CS 317 (14%) 172 (12%) 145 (16%)  
 Missing 0 0 0  
Fetal position       0.03
 Cephalic 2250 (97%) 1364 (98%) 886 (96%)  
 Other position 20 (1%) 11 (1%) 9 (1%)  
 Missing 40 (2%) 16 (1%) 24 (3%)  
Analgesics       0.01
 None 1298 (56%) 818 (59%) 480 (52%)  
 Opiates 288 (13%) 165 (12%) 123 (13%)  
 Epidural/spinal 593 (26%) 343 (25%) 250 (27%)  
 General anesthesia 13 (0.6%) 5 (0.4%) 8 (1%)  
 Missing 118 (5%) 60 (4%) 58 (6%)  
Birth weight       0.002
 <10th percentile 596 (26%) 362 (26%) 234 (26%)  
 10–90 percentile 1418 (61%) 856 (62%) 562 (61%)  
 >90 percentile 266 (12%) 165 (12%) 101 (11%)  
 Missing 30 (1%) 8 (0.6%) 22 (2%)  
Perineal laceration       0.001
 None or first degree a   1069 (46%) 605 (44%) 464 (51%)
 Second degree or higher 1228 (53%) 781 (56%) 447 (49%)  
 Missing 13 (0.6%) 5 (0.4%) 8 (1%)  
Hospital setting       0.05
 Academic 644 (28%) 367 (26%) 227 (30%)  
 Teaching 1563 (68%) 954 (69%) 609 (66%)  
 Non-teaching 103 (5%) 70 (5%) 33 (4%)  
 Missing 0 0 0  
 
Postpartum        
Delivery placenta       0.13
 Spontaneous a 1990 (86%) 192 (14%) 124 (14%)  
 MPV or curettage 316 (14%) 1195 (86%) 795 (87%)  
 Missing 4 (0.2%) 4 (0.3%) 0  
PPH, n % 940 (41%) 523 (38%) 417 (45%) 0.001
 No 1339 (58%) 849 (61%) 490 (53%)  
 Missing 31 (1%) 19 (1%) 12 (1%)  
RBC transfusion 386 (17%) 224 (16%) 162 (18%) <0.001
 No RBC transfusion 1379 (60%) 873 (63%) 506 (55%)  
 Missing 545 (24%) 294 (21%) 251 (27%)  
Neonatal admission, n % 1240 (54%) 764 (55%) 476 (52%) 0.32
 No neonatal admission 1066 (46%) 625 (45%) 441 (48%)  
 Missing 4 (0.2%) 2 (0.1%) 2 (0.2%)  
Congenital anomaly (severe) 22 (1%) 12 (1%) 10 (1%) 0.74
 None 2288 (99%) 1379 (99%) 909 (99%)  
 Missing 0 0 0  
 
Maternal complications        
Urinary tract infection 47 (2%) 27 (2%) 20 (2%) <0.001
 No urinary tract infection 2058 (89%) 1280 (92%) 778 (85%)  
 Missing 205 (9%) 84 (6%) 121 (13%)  
Thrombo-embolic event 6 (0.3%) 4 (0.3%) 2 (0.2%) <0.001
 No thrombo-embolic event 2100 (91%) 1301 (94%) 799 (87%)  
 Missing 204 (9%) 86 (6%) 118 (13%)  
Endometritis 21 (1%) 11 (1%) 10 (1%) <0.001
 No endometritis 2086 (90%) 1296 (93%) 790 (86%)  
 Missing 203 (9%) 84 (6%) 119 (13%)  

a Including cesarean sections.

BMI—body mass index, CS—cesarean section, PPH—postpartum hemorrhage, MPV—manual placenta removal, RBC—red blood cell.

Table 2 demonstrates the SF-36v1 scores (total and per trial) and available reference scores. Fig. 2 presents the PCS and MCS per trial. Maximal differences between trials for these summary scores were 4.6 and 3.2 points, respectively (bothp-values <0.001). Women in the WOMB trial had higher PCS and MCS than women in the HYPITAT and DIGITAT trial; though only the differences in MCS were significant (p-values for the difference in MCS 0.01 and <0.001, respectively).

Table 2 SF-36v1 summary and subscale scores: This study, Dutch population reference scores and postpartum reference scores.

  This study, Total This study, DIGITAT This study, HYPITAT This study, WOMB Dutch population reference [32] Postpartum reference [8]
N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) Mean (SD) Mean (SD)
Summary scores
PCS 1364 46 (9) 393 45 (10) 526 44 (9) 445 48 (9) NA NA
MCS 1364 53 (9) 393 51 (10) 526 52 (9) 445 54 (8) NA NA
 
Subscales
Physical functioning 1383 86 (17) 403 86 (18) 528 85 (16) 452 86 (17) 92 (13) 85 (19)
Role-physical 1379 60 (42) 401 57 (42) 528 50 (42) 450 73 (38) 86 (29) 74 (37)
Bodily pain 1385 61 (28) 401 77 (19) 528 54 (25) 456 73 (28) 79 (19) 78 (28)
General health 1379 78 (18) 398 76 (19) 527 78 (17) 454 79 (18) 77 (17) 78 (18)
Vitality 1382 60 (18) 401 57 (18) 527 57 (17) 454 66 (18) 68 (16) 68 18)
Social functioning 1386 78 (23) 402 75 (25) 528 75 (23) 456 84 (20) 86 (19) 86 (19)
Role-emotional 1379 84 (33) 399 82 (34) 528 83 (33) 452 85 (32) 82 (33) 83 (34)
Mental health 1382 82 (15) 401 79 (16) 527 80 (15) 454 86 (15) 76 (15) 86 (14)

SF-36v1—36-item short form, PCS—physical component score, MCS—mental component score, NA—not available.

No Dutch references for the summary scores were available. However, US population reference scores for the PCS and MCS, with a mean of 50 and a standard deviation of 10, are previously published [33] .

For SF-36v1 subscales, Dutch population reference scores, matched for both gender and age, were made available by Aaronson et al. (unpublished data, the Materials and methods section) [32] .

Also, postpartum reference scores are presented; these scores were derived from the pilot study of the WOMB trial [8] .

gr2

Fig. 2 The SF-36v1 summary scores PCS and MCS, demonstrated per trial.

With regard to the SF-36v1 summary scores, the average PCS in our study population was 4 points lower than the US population reference score[33] and [35]while the average MCS in our study was 3 points higher (bothp-values <0.001).

Dutch population reference scores for the SF-36v1 subscales were made available for women aged from 16 to 40 years (unpublished data, see the Materials and methods section). Average general health and role-emotional scores in our study were comparable to these reference scores (p = 0.04 andp = 0.053, respectively) while the mental health score in our study was six points higher (p < 0.001). The remaining subscales in our study population had lower average scores than their Dutch reference (allp-values <0.001). Largest differences between subscale scores in our study and Dutch population reference scores were found for the subscales role-physical and bodily pain (26 and 18 points, respectively).

Comparing scores in our study to postpartum reference scores demonstrated that all SF-36v1 subscale scores in our study had a lower average (allp-values <0.001), except for the subscales physical functioning and role-emotional that were similar, and general health that was equal. Again, largest differences were found for the subscales role-physical and bodily pain (14 and 17 points, respectively).

Regression analyses

Results of the univariable analyses are tabulated in Online Resource 1. Following these analyses, multivariable regression analyses were performed to assess the influence of socio-demographic and clinical parameters on PCS and MCS. Gestational hypertension, elective cesarean section, emergency cesarean section, neonatal admission and delivery at an academic hospital were negatively related to PCS ( Table 3 ): the PCS was on average 1.5 points lower in women with gestational hypertension, 1.3 points lower in case of neonatal admission, 1.2 points lower after delivery at an academic hospital and, respectively, 5.6 and 6.3 points lower after elective or emergency cesarean section. As demonstrated in Table 3 , the MCS was found to be influenced negatively by a foreign country of birth (1.9 points lower) and induction of labor (1.4 points lower) while the score of women who had had a PPH was 1.8 points higher than the score of women who had not suffered PPH.

Table 3 Multivariable associations between socio-demographic parameters, clinical parameters and obstetric complications, and the physical and mental component score.

  Physical component score Mental component score
Estimate SE p-Value Estimate SE p-Value
Intercept 48.142 0.975 <0.001 53.694 0.866 <0.001
 
BMI            
 <18.5 −0.682 1.337 0.61      
 18.5–25 Ref 1.057        
 >25 −0.889 0.588 0.13      
 
Country of birth            
 Dutch       Ref    
 Not Dutch       −1.943 0.855 0.02
 
Highest education            
 None/primary education 0.318 1.069 0.77 −1.761 1.230 0.16
 Secondary education Ref     Ref    
 Higher professional education/university 0.874 0.634 0.17 −0.034 0.592 0.95
 
Parity            
 Primiparous Ref          
 Multiparous 1.087 0.583 0.06      
 
Hypertensive disorder            
 None Ref     Ref    
 Gestational hypertension −1.519 0.711 0.03 0.246 0.707 0.73
 Preeclampsia −1.335 0.773 0.08 −0.144 0.782 0.85
 
Induction of labor            
 No Ref     Ref    
 Yes −0.161 0.517 0.76 −1.405 0.520 0.01
 
Mode of delivery            
 Vaginal, spontaneous Ref          
 Vaginal, operative −0.615 0.705 0.38      
 CS, elective −5.566 1.868 0.003      
 CS, emergency −6.331 0.891 <0.001      
 
Analgesics            
 None Ref          
 Opiates −0.226 0.777 0.77      
 Epidural/spinal −0.066 0.626 0.92      
 General anesthetics −1.263 1.904 0.51      
 
Birth weight            
 <10th Percentile −0.173 0.668 0.80 −0.192 0.675 0.78
 10th–90 percentile Ref     Ref    
 >90 Percentile −0.053 0.795 0.95 −1.172 0.788 0.14
 
Perineal laceration            
 None or first degree a Ref     Ref    
 Second degree or higher −0.345 0.608 0.58 0.669 0.513 0.19
 
Hospital setting            
 Non-teaching 0.277 1.118 0.80 0.952 1.142 0.40
 Teaching Ref     Ref    
 Academic −1.174 0.565 0.04 −0.762 0.575 0.19
 
Delivery placenta            
 Spontaneous a Ref     Ref    
 MPV or curettage −0.473 0.809 0.56 −0.580 0.814 0.48
 
PPH            
 No Ref     Ref    
 Yes 1.231 0.769 0.11 1.845 0.761 0.02
 
Neonatal admission            
 No Ref     Ref    
 Yes −1.320 0.631 0.04 −0.892 0.643 0.17
 
Congenital anomaly (severe)            
 No       Ref    
 Yes       −4.233 2.647 0.11

a Including cesarean sections.

BMI—body mass index, CS—cesarean section, MPV—manual placenta removal, PPH—postpartum hemorrhage.

Comment

Determinants of postpartum HRQoL after obstetric complications were investigated. We found that women with pregnancies complicated by IUGR and hypertensive disorders overall had lower mental HRQoL scores than PPH. Gestational hypertension, delivery by cesarean section, neonatal admission and delivery in an academic hospital were found to be negatively related to PCS in this study. The impact of a cesarean section was the largest. MCS was, only mildly, influenced by foreign country of birth, induction of labor and PPH.

For the interpretation of results, it is important to realize that a significant difference in HRQoL score does not necessarily indicate that this difference is meaningful. The magnitude of the difference determines whether the difference is of clinical importance. Estimates of the minimal clinical important change in the scores PCS and MCS vary from 5 to 10 [36] . This implies that the differences in average scores between trials, as found in this study, were relatively small. Also, all effects on PCS and MCS seem small, except for the negative influence of mode of delivery by cesarean section on PCS: after elective and emergency cesarean section women scored on average 6 points lower than after spontaneous vaginal delivery. Consequently, only mode of delivery seems to have a profound impact on HRQoL postpartum.

The finding that women after PPH were found to have a relatively high MCS was unexpected. All women in our study suffered from an obstetric complication and PPH apparently had a relatively positive effect in comparison to the other complications (IUGR and hypertensive disorders).

Compared to US-based population [33] , our study population demonstrated overall lower PCS though higher MCS. Furthermore, our population had on average lower scores on all subscales, except for general health, role-emotional and mental health, compared to Dutch reference scores (unpublished data, provided by Aaronson et al.) [32] . Presumably physical HRQoL is suboptimal after delivery and even worsened by obstetric complications; while mental HRQoL is most likely positively influenced by new motherhood.

Our population had significantly lower scores on all subscales than the postpartum reference scores demonstrated in Table 2 [8] , except for physical functioning and role-emotional (similar) and general health (equal). The obstetric complications that our study population suffered from, presumably account for these differences.

Factors associated with HRQoL as described in previous literature like ethnicity, education, and preterm birth were not be confirmed in this study. However, HRQoL scores might already have normalized to a large extent at six weeks postpartum: findings in this study and the pilot study indicate that measuring SF-36v1 scores at one or two additional time points (earlier than six weeks postpartum) might have been very informative [8] . Previous literature regarding the influence of mode of delivery on HRQoL is contradictive. Of previous studies that used the ShortForm-36, two studies demonstrated similar results, one study found better HRQoL following a cesarean section than following vaginal delivery and one study described no influence of mode of delivery on physical HRQoL[5], [6], [7], and [8]. These studies however, were based on much smaller populations. Two studies that used different HRQoL measures did not find lower HRQoL after a cesarean section[3] and [37]. Although numbers in these studies were relatively large (n > 1000), results cannot be compared due to the different measurement methods.

The selection of women with an obstetric complication in this study should be taken into consideration. Another limitation of this study is the use of combined data collected in three randomized controlled trials, although no effect of randomization on postpartum HRQoL was detected. Also, no treatment effect on HRQoL was found in women randomized to induction of labor or expectant management in the DIGITAT and HYPITAT trial[38] and [39]while in WOMB trial differences in HRQoL between study groups were small at six weeks postpartum [28] . The effect of randomization and treatment strategy on our results seems therefore minimal. Many differences between responders and non-responders were found. These were partly predictable, as socio-demographic differences like age, ethnicity and education are parameters known to influence response rates [40] . Due to the large numbers many differences were significant even when the magnitude of the difference was small.

The major strengths of this study are the nationally collected data and the large numbers.

In a heterogeneous obstetric population, delivery by elective and emergency cesarean section are the only factors that have a profound, negative impact on physical HRQoL. No profound impacts on mental HRQoL were detected. Of the studied obstetric complications, PPH seems to influence postpartum HRQoL less than IUGR and hypertensive disorders. These results emphasize the need for careful consideration while determining mode of delivery and bring in reliable information to support discussions about (determinants of) HRQoL after obstetric complications.

Condensation

Fetal growth restriction and hypertensive disorders lead to lower health-related quality of life scores postpartum than postpartum hemorrhage. In a heterogeneous obstetric population, only mode of delivery by cesarean section has a profound, negative impact, on the physical health-related quality of life.

Conflict of interest statement

We commit that we did not get any financial, consulting, and personal relationships with other people or organizations that could influence our work.

Acknowledgements

We would like to thank the research nurses, midwives and secretaries of our consortium, the staff of all participating centers, and the women who participated in the trials for their contributions.

The HYPITAT and DIGITAT trial were funded by ZonMw (grant number 945-06-553 and 945-04-558, respectively). The WOMB trial was funded by the Landsteiner Foundation for Blood Transfusion Research (grant number 0904) and Stichting Vrienden van de Bloedtransfusie (grant number 1201.005). Study sponsors had no involvement in collection, analysis and interpretation of data and in the writing of the manuscript.

Appendix A. Supplementary data

 

References

  • [1] G.A. Lamarca, C. Leal Mdo, A.T. Leao, A. Sheiham, M.V. Vettore. Oral health related quality of life in pregnant and post partum women in two social network domains; predominantly home-based and work-based networks. Health Qual Life Outcomes. 2012;10:5
  • [2] H.S. Wik, T.R. Enden, A.F. Jacobsen, P.M. Sandset. Long-term quality of life after pregnancy-related deep vein thrombosis and the influence of socioeconomic factors and comorbidity. J Thromb Haemost. 2011;9:1931-1936
  • [3] B. Akyn, E. Ege, D. Kocodlu, N. Demiroren, S. Yylmaz. Quality of life and related factors in women, aged 15–49 in the 12-month post-partum period in Turkey. J Obstet Gynaecol Res. 2009;35:86-93
  • [4] J. Webster, C. Nicholas, C. Velacott, N. Cridland, L. Fawcett. Quality of life and depression following childbirth: impact of social support. Midwifery. 2011;27:745-749
  • [5] D. Da Costa, M. Dritsa, N. Rippen, I. Lowensteyn, S. Khalife. Health-related quality of life in postpartum depressed women. Arch Womens Ment Health. 2006;9:95-102
  • [6] M.R. Safarinejad, A.A. Kolahi, L. Hosseini. The effect of the mode of delivery on the quality of life, sexual function, and sexual satisfaction in primiparous women and their husbands. J Sex Med. 2009;6:1645-1667
  • [7] B. Torkan, S. Parsay, M. Lamyian, A. Kazemnejad, A. Montazeri. Postnatal quality of life in women after normal vaginal delivery and caesarean section. BMC Pregnancy Childbirth. 2009;9:4
  • [8] A.J. Jansen, M.L. Essink-Bot, J.J. Duvekot, D.J. van Rhenen. Psychometric evaluation of health-related quality of life measures in women after different types of delivery. J Psychosom Res. 2007;63:275-281
  • [9] K.S. Khan, D. Wojdyla, L. Say, A.M. Gulmezoglu, P.F. Van Look. WHO analysis of causes of maternal death: a systematic review. Lancet. 2006;367:1066-1074
  • [10] L. Duley. The global impact of pre-eclampsia and eclampsia. Semin Perinatol. 2009;33:130-137
  • [11] J.M. Bais, M. Eskes, M. Pel, G.J. Bonsel, O.P. Bleker. Postpartum haemorrhage in nulliparous women: incidence and risk factors in low and high risk women. A Dutch population-based cohort study on standard (> or =500 ml) and severe (> or =1000 ml) postpartum haemorrhage. Eur J Obstet Gynecol Reprod Biol. 2004;115:166-172
  • [12] World Health Organisation. WHO guidelines for the management of postpartum haemorrhage and retained placenta. (World Health Organisation, Geneva, 2009)
  • [13] D.D. McIntire, S.L. Bloom, B.M. Casey, K.J. Leveno. Birth weight in relation to morbidity and mortality among newborn infants. N Engl J Med. 1999;340:1234-1238
  • [14] M.S. Kramer, M. Olivier, F.H. McLean, D.M. Willis, R.H. Usher. Impact of intrauterine growth retardation and body proportionality on fetal and neonatal outcome. Pediatrics. 1990;86:707-713
  • [15] E.A. Steegers, P. von Dadelszen, J.J. Duvekot, R. Pijnenborg. Pre-eclampsia. Lancet. 2010;376:631-644
  • [16] S.Y. Lee, H.C. Hsu. Stress and health-related well-being among mothers with a low birth weight infant: the role of sleep. Soc Sci Med. 2012;74:958-965
  • [17] E. Mautner, E. Greimel, G. Trutnovsky, F. Daghofer, J.W. Egger, U. Lang. Quality of life outcomes in pregnancy and postpartum complicated by hypertensive disorders, gestational diabetes, and preterm birth. J Psychosom Obstet Gynaecol. 2009;30:231-237
  • [18] P.D. Hill, J.C. Aldag. Maternal perceived quality of life following childbirth. J Obstet Gynecol Neonatal Nurs. 2007;36:328-334
  • [19] C. Zubaran, K. Foresti. Investigating quality of life and depressive symptoms in the postpartum period. Women Birth. 2011;24:10-16
  • [20] R. Setse, R. Grogan, L. Pham, et al. Longitudinal study of depressive symptoms and health-related quality of life during pregnancy and after delivery: the Health Status in Pregnancy (HIP) study. Matern Child Health J. 2009;13:577-587
  • [21] J. Lo, P. Osterweil, H. Li, T. Mori, K.B. Eden, J.M. Guise. Quality of life in women with postpartum anal incontinence. Obstet Gynecol. 2010;115:809-814
  • [22] I.L. Hermansen, B.O. O’Connell, C.J. Gaskin. Women's explanations for urinary incontinence, their management strategies, and their quality of life during the postpartum period. J Wound Ostomy Continence Nurs. 2010;37:187-192
  • [23] D.N. Samarasekera, M.T. Bekhit, Y. Wright, et al. Long-term anal continence and quality of life following postpartum anal sphincter injury. Colorectal Dis. 2008;10:793-799
  • [24] V.L. Handa, H.M. Zyczynski, K.L. Burgio, et al. The impact of fecal and urinary incontinence on quality of life 6 months after childbirth. Am J Obstet Gynecol. 2007;197:636 e1-6366e
  • [25] M. Hatem, W. Fraser, E. Lepire. Postpartum urinary and anal incontinence: a population-based study of quality of life of primiparous women in Quebec. J Obstet Gynaecol Can. 2005;27:682-688
  • [26] K.E. Boers, S.M. Vijgen, D. Bijlenga, et al. Induction versus expectant monitoring for intrauterine growth restriction at term: randomised equivalence trial (DIGITAT). BMJ. 2010;341:c7087
  • [27] C.M. Koopmans, D. Bijlenga, H. Groen, et al. Induction of labour versus expectant monitoring for gestational hypertension or mild pre-eclampsia after 36 weeks’ gestation (HYPITAT): a multicentre, open-label randomised controlled trial. Lancet. 2009;374:979-988
  • [28] B.W. Prick, A.J.G. Jansen, E.A.P. Steegers, et al. Transfusion policy after severe postpartum haemorrhage: a randomised non-inferiority trial. BJOG. 2014;121(8):1005-1014
  • [29] K.E. Boers, D. Bijlenga, B.W. Mol, et al. Disproportionate intrauterine growth intervention trial At term: DIGITAT. BMC Pregnancy Childbirth. 2007;7:12
  • [30] C.M. Koopmans, D. Bijlenga, J.G. Aarnoudse, et al. Induction of labour versus expectant monitoring in women with pregnancy induced hypertension or mild preeclampsia at term: the HYPITAT trial. BMC Pregnancy Childbirth. 2007;7:14
  • [31] B.W. Prick, E.A. Steegers, A.J. Jansen, et al. Well being of obstetric patients on minimal blood transfusions (WOMB trial). BMC Pregnancy Childbirth. 2010;10:83
  • [32] N.K. Aaronson, M. Muller, P.D. Cohen, et al. Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol. 1998;51:1055-1068
  • [33] J.E. Ware Jr., M. Kosinski, M.S. Bayliss, C.A. McHorney, W.H. Rogers, A. Raczek. Comparison of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: summary of results from the Medical Outcomes Study. Med Care. 1995;33:AS264-AS279
  • [34] D.B. Rubin. Multiple imputation for nonresponse in surveys. (J Wiley & Sons, New York, NY, 1987)
  • [35] J.E. Ware, M. Kosinski, S.D. Keller. SF-36 physical and mental health summary scales—a user's manual. (New England Medical Center, The Health Institute, Boston, MA, 1994)
  • [36] J.E. Ware, M.A. Kosinski, J.B. Bjorner, et al. User's manual for the SF-36v2 Health Survey. 2nd ed. (Quality Metric Inc., Lincoln, RI, 2007)
  • [37] K. Huang, F. Tao, L. Liu, X. Wu. Does delivery mode affect women's postpartum quality of life in rural China. J Clin Nurs. 2012;21:1534-1543
  • [38] D. Bijlenga, K.E. Boers, E. Birnie, et al. Maternal health-related quality of life after induction of labor or expectant monitoring in pregnancy complicated by intrauterine growth retardation beyond 36 weeks. Qual Life Res. 2011;20:1427-1436
  • [39] D. Bijlenga, C.M. Koopmans, E. Birnie, et al. Health-related quality of life after induction of labor versus expectant monitoring in gestational hypertension or preeclampsia at term. Hypertens Pregnancy. 2011;30:260-274
  • [40] A. Hutchings, J. Neuburger, K. Grosse Frie, N. Black, J. van der Meulen. Factors associated with non-response in routine use of patient reported outcome measures after elective surgery in England. Health Qual Life Outcomes. 2012;10:34

Footnotes

a Department of Obstetrics and Gynecology, Erasmus Medical Centre, Rotterdam, The Netherlands

b Department of Obstetrics and Gynecology, Maasstad Hospital, Rotterdam, The Netherlands

c Department of Public Health, Academic Medical Centre, Amsterdam, The Netherlands

d Sanquin Blood Supply Foundation, Rotterdam, The Netherlands

e Department of Obstetrics and Gynecology, Bronovo Hospital, Den Haag, The Netherlands

f Department of Obstetrics and Gynecology, University Medical Centre Groningen, Groningen, The Netherlands

g Department of Obstetrics and Gynecology, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands

h School of Pediatrics and Reproductive Health, University of Adelaide, Adelaide 5000 SA, Australia

lowast Corresponding author. Tel.:+0031 10 7040704; fax: +0031 10 7036815.

Data of this study were collected in trials that were conducted in a total of 52 hospitals in The Netherlands.