{"paper_id":"b9589729-86db-4426-995c-e571c3b7adca","body_text":"R E S E A R C H Open Access\nHealth-related quality of life in pregnancy\nwith uterine fibroid: a cross-sectional study\nin China\nWai-Kit Ming 1,2*†, Huailiang Wu 1,3†, Yanxin Wu 1†, Hanqing Chen 1, Tian Meng 1,3, Yiwei Shen 1,3, Ziyu Wang 1,3,\nXinyu Huang 1,3, Weiwei Sun 1,3, Tik Sang Chow 1,3, Yuan Wang 1,3, Wenjing Ding 1, Haitian Chen 1, Zhuyu Li 1\nand Zilian Wang 1*\nAbstract\nBackground: Uterine fibroids (UFs) are the most common benign tumors in women. They are likely to cause\nnumerous clinical symptoms, such as pain, menorrhagia, and other obstetric complications in pregnant women.\nThis study aimed to determine the health-related quality of life (HRQoL) during pregnancy with uterine fibroids (UF)\n, thus providing a utility-based case value in pregnant women with UF and understanding of whether HRQoL is\nassociated with clinical outcomes in pregnant women with UFs.\nMethod: This study was conducted in a cross-sectional manner. This study was based on questionnaire surveys\ncompleted by sequential out- and in-patients and was conducted in a regional university hospital in Guangzhou,\nChina. The EuroQoL five-dimension-five-level (EQ-5D-5 L) questionnaire was used, and demographic data were collected.\nAn electronic record of the clinical outcomes of pregnant women with UF was retrieved from the hospital’se l e c t r o n i c\nmedical record system. The association between UFand HRQoL was evaluated by ordered regression.\nResults:Seven-hundred-sixty-seven pregnant women with a mean age (SD) of 32.7 (4.8) years completed 707\nquestionnaires. Overall, when comparing the UF with non-UF groups, we detected statistical differences in age, body mass\nindex (BMI), gravidity and abortion times, partner’s smoking and alcoholic habits, advanced maternal age, and uterine scars\n(p < 0.05). Furthermore, pregnant women without UF scored significantly higher than those with UF on the EQ-5D value\nsystem (0.84 versus 0.79;p = 0.017). Moreover, pregnant women with UF suffered more health-related problems, especially\nwith respect to self-care (odds ratio [OR] = 3.69,p < 0.01) and usual activity dimensions (OR = 2.11; p = 0.01).\nConclusion:We found that UF has a negative impact on the HRQoL of pregnant women with respect to self-care and\nusual activity dimensions. Also, the EQ-5D score was a better index than the EQ-VAS score for HRQoL when evaluating of\nthe QoL of our population of pregnant women.\nIntroduction\nBackground\nUterine fibroids (UFs), also known as uterine myomas,\nfibromyomas, or leiomyomatas, are the most common\nbenign tumors in women and have clinical morbidity\nrates of 20 to 40% and prevalence rates of 3 to 12% dur-\ning pregnancy. The common causes of UFs are variable\nfactors, such as genetics, endocrine factors and lifestyle\nfactors [ 1–3]. The clinical outcomes range from asymp-\ntomatic to presentation of pain, menorrhagia, and ob-\nstetric complications such as infertility, miscarriage, and/\nor scarred uterus [ 3, 4]. However, these symptoms can\naffect the quality of life for pregnant women [ 5].\nIn a recent study, pregnant women were shown to suf-\nfer from an increase in the risk of depression [ 6], and\ndepressive symptoms correlate with impairment of\nHRQoL [ 7]. According to prior studies, pain was shown\nto be the most common symptom of UF during preg-\nnancy, and the risk of depression could increase in this\n© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0\nInternational License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and\nreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to\nthe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver\n(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.\n* Correspondence: mingwj@mail.sysu.edu.cn; wkming@connect.hku.hk;\nwangzil@mail.sysu.edu.cn\n†Wai-Kit Ming, Huailiang Wu and Yanxin Wu contributed equally to this work.\n1Department of Obstetrics and Gynaecology, The First Affiliated Hospital of\nSun Yat-sen University, Guangzhou, China\nFull list of author information is available at the end of the article\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 \nhttps://doi.org/10.1186/s12955-019-1153-6\n\nsituation [ 3, 8]. Some past studies used the EuroQoL\nGroup’s five-dimension questionnaire (EQ-5D) to meas-\nure and assess the relationship between pain, depressive\nsymptoms, and quality of life (QoL) [ 7, 9, 10]. Consider-\ning that most pregnant women do not have fatal dis-\neases, it was suitable to use a generalized questionnaire\nto assess their HRQoL values. Therefore, as one of the\nmost common instruments for measuring the overall\nbody health state, the EQ-5D is a powerful and popular\ntool, especially for assessing pain and anxiety/depression\nsymptoms [ 11, 12]. The symptoms and clinical outcomes\ncaused by UFs might correlate with HRQoL; therefore,\nclinicians can use HRQoL as an index to evaluate the ef-\nfectiveness of treatment [ 13, 14].\nIn contrast to traditional clinical outcomes, HRQoL\nduring pregnancies with UFs can be used as an outcome\nindicator in health policy research, facilitating the im-\nprovement of clinical UF management. Utility data are\nkey factors for cost-utility analysis and quality-adjusted\nlife-year analysis in healthcare-related economics but\nhave not been addressed in the literature; therefore, this\nstudy could provide a utility-based case value in preg-\nnancies with UFs.\nObjectives\nWe aimed to evaluate several parameters: (1) determine\nthe HRQoL in pregnancies with UFs; (2) provide a\nutility-based case value in pregnancies with UF; and (3)\nunderstand whether HRQoL is associated with the clin-\nical outcomes of pregnant women with UFs.\nMethod\nStudy design\nA cross-sectional study was performed as a part of a lon-\ngitudinal project that studied pregnant women who re-\nceived prenatal care during different gestational ages at\none of the largest regional university hospitals in south\nChina (The First Affiliated Hospital of the Sun Yat-sen\nUniversity) from May 2017 to February 2018. Ethical ap-\nproval was granted by the Institutional Review Board of\nThe First Affiliated Hospital of Sun Yat-sen University\n(ICE-2017-296). All procedures were conducted in ac-\ncordance with the Declaration of Helsinki. All partici-\npants signed the informed consent documents before\nparticipation in this study.\nStudy population\nAll participants came from The First Affiliated Hospital\nof the Sun Yat-sen University. Eligible participants were\nincluded if they were pregnant. Only the first record for\neach participant was included in this study. Participants\nwere excluded when they had missing personal informa-\ntion and/or clinical data. Furthermore, if any participants\ncompletes more than one EQ5D questionnaire, all add-\nitional records were excluded, except for the first one.\nMeasurement\nPatient-evaluated HRQoL is an important index in the\nassessment of a patient ’s health and functional states\n[15]. The EuroQoL Group ’s five-dimension question-\nnaire (EQ-5D) with EuroQoL Group ’s visual analog scale\nquestionnaire (EQ-VAS) is a common questionnaire for\nmeasuring the quality of life, making cost-efficiency cal-\nculations, and evaluating economic issues in the public\nhealth field. The EuroQoL Group ’s five-dimension\nfive-level questionnaire (EQ-5D-5 L) is a more reliable\nand sensitive instrument for measuring HRQoL than the\nEQ-5D-3 L [ 16]. The EQ-5D-5 L instrument contains a\ndescriptive system for assessing a participant ’s health\nstate over five dimensions based on five levels in each di-\nmension and utilizes a self-determined visual analog\nscale (VAS). These two parts were used throughout this\nstudy. The Chinese version of the EQ-5D-5 L has been\nshown to be valid and effective and is commonly used to\nmeasure HRQoL [ 17, 18]. EQ-VAS can provide a\nself-reported global measure of overall health and\nbroader dimensions of assessment than EQ-5D although\nmore than half the participants do not accurately evalu-\nate themselves when using these types of scoring sys-\ntems [ 19, 20]. This study might help to identify which of\nthese two independent tools is more suitable for asses-\nsing pregnant women with UFs and provide detailed\nHRQoL data for future studies.\nParticipants were administered the EQ-5D question-\nnaire the first time that they visited the hospital for pre-\nnatal care. The EQ-5D assessed five dimensions\n(mobility, self-care, usual activity, pain/discomfort, and\nanxiety/depression) and it was based on five problem\nlevels: (1) none; (2) slight; (3) moderate; (4) severe; and\n(5) extreme/unable. As examples, the self-care dimen-\nsion asks about the degree of problems experienced\nwhen “washing and dressing by yourself ”, and the usual\nactivity dimension asks about the degree of problems in\n“work, study, housework, family, or leisure activities in\ndaily life ”. The five levels of response were represented\nby integer values (such as 1 –5 with values of 2 –5 indi-\ncating health-related problems) [ 16, 17, 19]. Each re-\nsponse pattern was calculated into a single EQ-5D index\nvalue (such as 11,221) through the EQ-5D-5 L Crosswalk\nIndex Value Calculator to produce a final QoL value.\nThe value ranged from − 0.224 to 1 with 1 indicating the\nbest health state of people, whereas 0 represents death.\nMost patients are in the range from 0 to 1; however, it is\nstill possible to achieve scores < 0, and these negative\nvalues correspond with overall health states (both phys-\nical and mental) that are considered worse than death\n[18]. We then measured each dimension and compared\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 2 of 11\n\nresponses between pregnant women with and without\nUF. The EQ-VAS was a self-assessment of health state\nacross five dimensions based on five levels of response.\nIt presented as a vertical line with demarcations from\n100 (best imaginable health state) to 0 (worst imaginable\nhealth state) [ 21]. Respondents were asked to draw a line\nfrom the bottom line 0 to the score line based on their\nopinion of their health states and fill the score in the\nblank beside.\nVariables\nBasic independent covariates of the study population in\nthe models included age, body mass index (BMI), living\nlocation, gravidity, parity, abortion, gestational trimester\n(first, second, or third), and advanced maternal age (in-\ndicated the age of pregnant women > 35 years old) [ 22].\nA meta-analysis showed no significant impact of smok-\ning on risk of UFs [ 23]. However, we wanted to detect\nwhether the smoking state of pregnant women could\naffect the HRQoL in those pregnant women with UF.\nFurthermore, the partners ’ lifestyle habits, such as smok-\ning status and alcohol consumption, were also included\nin this study. Also, multipara, uterine scar, hepatitis B\nhistory, heart disease, and surgical history were included\nas part of the index for pre-pregnancy conditions.\nThroughout the study, participants were categorized by\ngestational trimester in which the first trimester was\ntaken when the pregnant women were at the gestational\nage of < 13 weeks, the second was the gestational age of\n13 to 28 weeks, and the third was a gestational age > 28\nweeks. In generalized situations, we use transvaginal\nultrasonography to detect and diagnose uterine fibroids.\nHowever, on rare occasions, such as suspected carcin-\noma (indicated by elevated cancer biomarker levels), a\npathological examination might need to be performed to\ndistinguish the uterine fibroids from uterine carcinoma\nunder the current guideline in our hospital. In this situ-\nation, the risk of miscarriage due to the procedure needs\nto be balanced [ 24]. In this study, we did not have any\ncases that needed to undergo pathological examinations.\nBias\nThe EQ-5D questionnaire was a subjective measurement\nof pregnant women ’s HRQoL, and self-reported bias\nmay be the main bias in this study. Based on the popula-\ntion, this study also minimized selection bias but had\nnon-response, volunteer, and ascertainment biases.\nStatistical methods\nData analysis was performed using the STATA/SE 14.0\nfor Windows. Normally distributed continuous variables\nwere described using the means + standard deviations\n(SDs), and ranges. Non-normal variables were presented\nas the median, and categorical variables were described\nusing counts and percentages. The dependent variables\nwere the EQ-5D score utility and EQ5D-VAS. EQ-5D\nscores were in a skewed distribution; therefore, we used\na non-parametric approach to analyze the data.\nParticipants’ demographic data were reported (age, ad-\nvanced maternal age, BMI, local, gravity, party, abortion,\nsmoking, partner smoking status and alcoholic con-\nsumption, multipara, surgery history, hepatitis B, and\nheart disease). The clinical outcomes were retrieved\nfrom the hospital electronic medical system after deliv-\nery. Since the EQ5D values present a skewed distribu-\ntion, we divided these values into two groups based for\nstatistical analysis on the median EQ5D values: (1) above\nthe median and (2) below the median [ 25]. Analysis of\nvariance and t- and the chi-squared tests were used to\ncompare continuous and qualitative variables among the\nthree different trimesters. Health quality, as measured by\nthe EQ5D-VAS scores or EQ5D values, and multiple lin-\near regressions was used. Potential confounders were ad-\njusted. An ordered logistic regression with odds ratios\n(ORs) and 95% confidence intervals (CIs) is an appropri-\nate method to use when examining the effects of inde-\npendent risk factors on various dimensions in the EQ5D\nindex when complementary dimensions are taken into\naccount [ 26, 27]. ORs, 95% CIs, and p-values were ob-\ntained using an ordered logistic regression analysis. All\ntests were two-sided, and a p-value of 0.05 was consid-\nered as statistically significant.\nResults\nParticipants\nIn total, all 767 pregnant women agreed to participate in\nthis study, but of these 60 were excluded due to missing\nclinical data or personal information. We only reserved\nthe first record as their HRQoL. Therefore, 707 of the\nincluded pregnant women provided 707 EQ-5D-5 L valid\nquestionnaires for the analysis. Using electronic medical\nrecords, we identified 105 pregnant women with UFs. Of\nthese, 103 were included in the study because two\nwomen did not deliver within the period under analysis\n(Fig. 1).\nDescriptive data\nGeneral characteristics of patients\nOf 707 pregnant women, the ages ranged from 21.3 to\n47.4 years, and the mean age was 32.7 ± 4.8 years. Of\nthose, in UF group, 105 women (14.9%) were included\nand were 35.6 ± 4.8 years on average, while the non-UF\ngroup of pregnant women ’ s mean age was 32.3 (4.5)\nyears (Table 1). The mean BMI across those with UFs\nwas 26.4 + 4.0 and was significantly lower (23.5 + 3.9)\namong those without UFs.\nOf the 707 eligible pregnant women, most (90.9%)\nlived locally (living in Guangzhou). The mean values for\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 3 of 11\n\ngravidity, parity, and abortion times across the entire\npopulation were 2.2 ± 1.1, 0.5 ± 0.5, and 0.6 ± 0.9,\nrespectively. All 707 pregnant women denied smoking\nduring pregnancy. Some women ’s partners (15.4%) were\nsmokers, and 8.1% of the partners consumed alcohol.\nFifteen percent of the sample population was multipara,\n24.8% had surgical histories, 30.3% were of advanced\nmaternal age, 23.2% had scars on the uterus, 2.1% had\nhepatitis B, and 0.9% had chronic heart disease. Table 1\nshows these risk factors for th e sample population. Signifi-\ncant differences were found in age between those with and\nwithout UFs ( p 0.01), BMI ( p < 0.01), gravidity ( p =0 . 0 3 ) ,\nabortion ( p = 0.01), partner smoking ( p = 0.02), partner\nalcoholism ( p = 0.03), scarred uterus ( p =0 . 0 3 ) , m u l t i p a r a\n(p < 0.01), and advanced maternal age (p <0 . 0 1 ) .\nOutcome data\nThe characteristics of clinical outcomes in pregnant women\nwith UFs\nTwo of the study participants did not deliver at the time\npoint of analysis. Thus, these results only included clin-\nical outcomes of 98.15% (103 out of 105) pregnant\nwomen with UFs. Among those pregnant women en-\nrolled in the study (except for the two that had not de-\nlivered), about 44.7% belonged to the below median\nEQ-5D score group while 55.3% came from the above\nmedian EQ-5D score group (Table 2). The mean +S D\ngestational ages for the below median and above median\nEQ-5D score groups were 37.8 + 1.7 and 38.0 + 1.6\nweeks, respectively. For pregnancy complications, no\nstatistical difference was found between two groups.\nMain results\nThe EQ-5D and EQ-VAS values assessed using the EQ-5D-5 L\nThe EQ-5D and EQ-VAS value distributions are shown\n(Figs. 2 and 3). Of the total 707 EQ-5D and EQ-VAS re-\ncords (707 pregnant women), the mean (SD) EQ-5D in-\ndices for those with and without UFs were 0.79 ± 0.21\nand 0.84 ± 0.18, respectively ( p = 0.017) and the mean of\nEQ-VAS with and without UFs were 88.0 ± 8.6 and 87.3 ±\n9.9, respectively ( p =0 . 4 8 0 ) ( T a b l e3). Besides, the groups\nalso showed differences in age and BMI (both p <0 . 0 1 )\n(T able 1). Therefore, age and BMI were adjusted in the\nFig. 1 Selection of the study population\nTable 1 Demographic characteristics\nUF\n(n = 105)\nNon-UF\n(n = 602)\nAll patients\n(n = 707)\np-value\nAge (SD) 35.6(4.8) 32.3(4.5) 32.7(4.8) < 0.01\nAdvanced maternal age 53(50.5%) 161(26.7%) 214(30.3%) < 0.01\nBMI (SD) 26.4(4.0) 23.5(3.9) 23.9(4.1) < 0.01\nLiving location\n(Guangzhou)\n96(91.4%) 547(90.9%) 643(90.9%) 0.85\nGravidity (SD) 2.4(1.2) 2.1(1.1) 2.2(1.1) 0.03\nParity (SD) 0.6 (0.5) 0.5(0.5) 0.5(0.5) 0.57\nAbortion (SD) 0.8(0.9) 0.6(0.8) 0.6(0.9) 0.01\nSmoking 0(0.0%) 0(0.0%) 0(0.0%) –\nPartner Smoking 24(22.9%) 85(14.1%) 109(15.4%) 0.02\nPartner Alcoholics 14(13.3%) 43(7.1%) 57(8.1%) 0.03\nMultipara 5(4.8%) 101(16.8%) 106(15.0%) < 0.01\nSurgical history 26(24.8%) 149(24.8%) 175(24.8%) 1.00\nUterine scar 33(31.4%) 131(21.8%) 164(23.2%) 0.03\nHepatitis B 1(1.0%) 14(2.3%) 15(2.1%) 0.37\nHeart disease 1(1.0%) 5(0.8%) 6(0.9%) 0.90\nUF Uterine fibroids, BMI Body mass index. Bold represented p value < 0.05.\nData with SD indicates “mean” value. Data without SD indicates “number”\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 4 of 11\n\nanalysis. After adjustment, EQ-5D scores were signifi-\ncantly different between women with and without UFs ( p\n= 0.007), while the EQ-VAS score showed no statistically\nsignificant difference between the two groups (p =0 . 4 8 6 ) .\nThe EQ-5D and EQ5D-VAS scores varied across the\ndifferent gestational trimesters (Figs. 4 and 5). Pregnant\nwomen with UFs scored lower indices on the EQ-5D\ncompared to those without UFs, regardless of the tri-\nmester. Among those without UFs, the mean EQ5D in-\ndices were 0.75, 0.88, and 0.82 in the first, second, and\nthird trimesters, respectively. In the first, second, and\nthird trimesters, mean EQ5D indices were 0.56, 0.83,\nand 0.78, respectively, among those pregnant women\nwith UF. The mean EQ5D-VAS scores were lower\namong those with UFs compared to those without, ex-\ncept in the third trimester. Also, women from both\ngroups (non-UF versus UF) presented the greatest\nEQ-5D indices (0.88 versus 0.83) and EQ5D-VAS scores\n(88.1 versus 88.0) in the second trimester.\nUterine fibroids and other factors contributing to health\nquality\nThe 707 EQ-5D records were classified based on the\npresence of UFs in the participant. Table 4 shows that\nTable 2 Clinical outcomes of pregnant women with uterine fibroids\nBelow median\nEQ5D score\n(n = 52)\nAbove median\nEQ5D score\n(n = 51)\nAll UF patients\n(n = 103)\np-value\nCesarean Section 39(75.0) 31(60.8) 70(68.0) 0.91\nPreterm labor 5(9.6) 9(17.6) 14(13.6) 0.67\nPrecipitate labor 0(0.0) 3(5.9) 3(2.9) 0.11\nPlacenta adherence 8(15.4) 7(13.7) 15(14.6) 0.34\nNuchal cord around neck 10(19.2) 15(29.4) 25(24.3) 0.19\nPROM 11(21.2) 15(29.4) 26(25.2) 0.28\nPostpartum hemorrhage 1(1.9) 2(3.9) 3(2.9) 0.44\nAmniotic fluid turbidity 6(11.5) 6(11.8) 12(11.7) 0.31\nPerineal laceration 7(13.5) 10(19.6) 17(16.5) 0.83\nHypertensive disorders 14(26.9) 9(17.7) 23(22.3) 0.90\nGestation age at birth 37.8(1.4) 38.1(1.9) 37.9(1.7) 0.73\nApgar score - 1 min 9.85(0.5) 9.75(0.63) 9.8(0.57) 0.13\nFetal distress 5(9.6) 12(23.5) 17(16.5) 0.07\nPROM Premature rupture of membrane\nFig. 2 Distribution of EQ-5D values of all pregnant women\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 5 of 11\n\n23.8% of the records for those with UFs also indicated\nproblems with mobility, 20.0% with self-care, 29.5% with\nusual activity, 52.4% with pain/discomfort, and 35.2%\nwith anxiety/depression. Additionally, 18.9% of the preg-\nnant women without UFs suffered mobility problems,\n7.3% had self-care problems, 16.0% had problems with\ntheir usual activities, 45.7% had pain/discomfort prob-\nlems, and 30.1% had anxiety/depression problems. The\nresults indicate that pain and discomfort during preg-\nnancy were major problems for pregnant women, while\nproblems with self-care were of the least concern. Be-\nsides, there were about 13.5% more health-related prob-\nlems with respect to the usual activity dimension in the\nUFs group than that in non-UFs group, which was a no-\nticeable difference between pregnant women with and\nwithout UFs for the five dimensions. For the overall sta-\ntus, there was a greater proportion of those with UFs\nwho experienced health-related problems (regardless of\nthe dimensions) when compared to those without UFs.\nAn ordered logistic regression analysis was used for\neach dimension in the EQ-5D (Table 5). Women in their\nsecond or third trimesters reported more problems with\nmobility (OR = 1.77; p < 0.01) and pain/discomfort (OR\n= 1.46; p < 0.01) than those in their first trimester. UFs\nwere related to self-care problems (OR = 3.69; p < 0.01)\nand usual activity problems (OR = 2.11; p < 0.01).\nFig. 3 Distribution of EQ5D-VAS values of all pregnant women\nTable 3 EQ-5D Index and EQ-VAS scores with and without UF\nEQ5D Index ( n = 707)\nUnadjusted Age adjust Age & BMI adjusted\nUF group 0.79(0.21) 0.79(0.00) 0.79(0.00)\nNon-UF group 0.84(0.18) 0.84(0.00) 0.84(0.00)\np-value 0.017 0.002 0.007\nEQ5D-VAS (n = 707)\nUnadjusted Age-adjusted Age & BMI adjusted\nUF group 88.0(8.6) 88.0(0.01) 88.0(0.01)\nNon-UF group 87.3(9.9) 87.2(0.00) 87.3(0.00)\np-value 0.480 0.522 0.486\nUF Uterine fibroids, BMI Body mass index\nFig. 4 EQ5D index and its 95% confidence interval (CI) on\ngestational trimesters. a.The first-trimester group contains 30\npregnant women, 27 pregnant women without UFs, and 3 pregnant\nwomen with UFs. b.The second-trimester group contains 263\npregnant women, 220 pregnant women without UFs, and 43\npregnant women with UFs. c.The third-trimester group contains 414\npregnant women, 355 pregnant women without UFs, and 59\npregnant women with UFs. d.UFs indicates uterine fibroids\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 6 of 11\n\nPregnant women who were not located locally suffered\nfrom more severe pain/discomfort problems during the\nfirst trimester (OR = 2.16; p < 0.01). More gravidity was\nassociated with problems regarding usual activity (OR =\n1.33; p = 0.01), and less parity was associated with prob-\nlems with usual activity (OR = 0.56; p = 0.03) and anx-\niety/depression (OR = 0.60; p = 0.02).\nDiscussion\nKey results\nThe major finding of the present study indicated that\nuterine fibroids could significantly affect HRQoL of\npregnant women in two dimensions (self-care and usual\nactivities) when compared to women without UF. Preg-\nnant women with UFs had a lower EQ-5D index than\nthose without UFs (0.80 versus 0.84) while their average\nEQ5D-VAS scores were 88.0 versus 87.3. This EQ-VAS\nresult was similar to that found in other research in\nChina in which evaluated health status in a\nsimilarly-aged cohort was evaluated [ 28, 29]. Less than\n15% of pregnant women rated their health status as 100\n(best possible health state) based on the EQ5D-VAS.\nHowever, the EQ-VAS scores did not show statistically\nsignificant differences between pregnant women with\nand without UFs, and the different standards of health\nself-evaluation from each part icipant could cause bias in\nt h eE Q 5 D - V A Sr e s u l t s ;t h u s ,t h eE Q 5 Di n d e xm i g h tb ea\nmore suitable index than the EQ-VAS for evaluating\nHRQoL in pregnant women with UFs. Furthermore, preg-\nnant women showed the greatest EQ-5D indices and\nEQ5D-VAS scores during their second gestational trimester\nregardless of UF or non-UF group (Figs. 4 and 5). Figure 2\nshows that the EQ-5D value was the lowest in the first ges-\ntational trimester regardless of UF status. However, this\nfinding was not in agreement with results of some other\npublished studies [30, 31]. This lack of agreement might be\ncaused by the policy of perform ing a full systemic prenatal\nexamination and consultation in the second and third tri-\nmesters in China in addition to health-care appointments\nevery 2 or 4 weeks, which might improve pregnant women’s\nthe HRQoL. Those with UFs had more health-related prob-\nlems across a range of five dimensions (mobility, self-care,\nusual activity, pain/discomf ort, and anxiety/depression)\ncompared to those without (T able 4) .A b o u th a l fo ft h e\npregnant women (46.7%) suffered health problems associ-\nated with pain and discomfort; this was the greatest propor-\ntion of the five dimensions. Thus, it is necessary for the\npublic healthcare system to focus on relieving this pain and\ndiscomfort when designing policies.\nFig. 5 EQ5D-VAS scores and its 95% confidence interval (CI) on\ngestational trimesters. a. The first-trimester group contains 30\npregnant women, 27 pregnant women without UFs, and 3 pregnant\nwomen with UFs. b The second-trimester group contains 263\npregnant women, 220 pregnant women without UFs, and 43\npregnant women with UFs. c The third-trimester group contains 414\npregnant women, 355 pregnant women without UFs, and 59\npregnant women with UFs. d UFs indicates uterine fibroids\nTable 4 The frequencies of pregnant women that report levels\n1 to 5 for the various dimension\nEQ-5D Dimension Uterine fibroid Total (%)\nUF (%) Non-UF (%)\nMobility Level 1 80(76.2) 488(81.1) 568(80.3)\nLevel 2 20(19.1) 91(15.1) 111(15.7)\nLevel 3 1(1.0) 9(1.5) 10(1.4)\nLevel 4 0(0.0) 3(0.5) 3(0.4)\nLevel 5 4(3.8) 11(1.8) 15(1.4)\nSelf-care Level 1 84(80.0) 558(92.7) 642(90.8)\nLevel 2 17(16.2) 29(4.8) 46(6.5)\nLevel 3 1(1.0) 2(0.3) 3(0.4)\nLevel 4 0(0.0) 1(0.2) 1(0.1)\nLevel 5 3(2.9) 12(2.0) 15(2.1)\nUsual Activity Level 1 74(70.5) 505(84.0) 579(81.9)\nLevel 2 26(24.8) 75(12.5) 101(14.3)\nLevel 3 2(1.9) 11(1.8) 13(1.8)\nLevel 4 0(0.0) 3(0.5) 3(0.4)\nLevel 5 3(2.9) 8(1.3) 11(1.6)\nPain/Discomfort Level 1 50(47.6) 327(54.3) 377(53.3)\nLevel 2 49(46.7) 246(40.9) 295(41.7)\nLevel 3 3(2.9) 15(2.5) 18(2.6)\nLevel 4 0(0.0) 6(1.0) 6(0.9)\nLevel 5 3(2.9) 8(1.3) 11(1.6)\nAnxiety/ Depression Level 1 68(64.8) 421(69.9) 489(69.2)\nLevel 2 34(32.4) 157(26.1) 191(27.0)\nLevel 3 0(0.0) 11(1.8) 11(1.6)\nLevel 4 1(1.0) 4(0.7) 5(0.7)\nLevel 5 2(1.9) 9(1.5) 11(1.6)\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 7 of 11\n\nBesides, the EQ5D indices with respect to mobility\nand pain/discomfort dimensions fas reported by women\nwithout UFs were greater than those with UFs regardless\nof the trimester, which might be explained by lower\nlevels of physical activities during the second and third\ntrimesters [ 32]. Increased gravidity significantly corre-\nlated with the rising odds of usual activity problems\n(Table 5) because pregnant women who have increased\ngravidity in China mostly had their second child at ad-\nvanced maternal ages because of the recent start of the\nChinese two-child policy and long period of China ’s\none-child policy. Under these conditions, pregnant\nwomen with advanced maternal ages were more likely to\nreceive more medical care during pregnancy, which\nmight be explain the increase in usual activity problems.\nIn addition, decreased parity (mostly nulliparity) could\ncontribute to the increase in usual activity problems. A\nprevious study had clearly recognized a decrease in par-\nity as a risk factor for the incidence of UFs [ 24], possibly\nbecause the production of estrogen and progesterone de-\nclines in parity and has considerable effects on fibroids ’\ngrowth [ 33].\nThese findings offer additional and detailed evidence\nfor the negative influence of UFs on HRQoL, which is in\nagreement with other cross-sectional studies. One\nweb-based cross-sectional study investigated the HRQoL\nacross 4848 women aged 18 to 49 years using the Uter-\nine Fibroid Symptom-Quality of Life Questionnaire\n(UFS-QoL) and demonstrated a significant reduction in\nHRQoL in women with UFs [ 34]. An online\ncross-sectional study also found that the HRQoL might\ndecrease with UFs and might be significantly impacted\nby UF-related symptoms [ 35]. Our study shows that UFs\nin pregnant women might affect the HRQoL scores in\nthe self-care and usual activity dimensions (Table 5).\nComparative assessments of pregnant women with and\nwithout UFs based on gestational index and chronic condi-\ntions indicate that some of these independent factors con-\ntributed considerably to the i ncidence of UFs, while other\nconditions were in an inverse relation with UFs. Ages and\nB M I sa r eh i g h e ra m o n gt h o s ew i t hU F st h a nt h o s ew i t h o u t ,\nwhich can be explained by a greater age indicating more\ngravidity, abortion, and opportunities for pregnancy during\nTable 5 Ordered logistic regression analysis for each dimension\nin the EQ5D\nOdds ratio 95% CI p-value\nMobility Age 0.98 0.93, 1.02 0.35\nBMI 1.03 0.98, 1.08 0.26\nLocal 0.83 0.48, 1.43 0.50\nGestation trimester 1.77 1.21, 2.60 < 0.01\nPartner smoking 1.10 0.64, 1.87 0.74\nPartner Alcoholics 1.21 0.59,2.51 0.60\nGravidity 1.17 0.95, 1.45 0.15\nParity 0.97 0.60, 1.57 0.90\nUF 1.32 0.77, 2.25 0.31\nSelf-care Age 0.96 0.90, 1.02 0.17\nBMI 1.00 0.94, 1.08 0.94\nLocal 1.15 0.48, 2.76 0.16\nGestation trimester 1.58 0.95, 2.65 0.08\nPartner smoking 0.74 0.38, 1.42 0.36\nPartner alcoholics 1.79 0.59, 5.37 0.30\nGravidity 0.91 0.64, 1.28 0.59\nParity 0.72 0.35, 1.49 0.38\nUF 3.69 1.94, 7.03 < 0.01\nUsual activity Age 0.98 0.93, 1.03 0.47\nBMI 1.03 0.97, 1.08 0.34\nLocal 0.74 0.43, 1.29 0.29\nGestation trimester 1.38 0.94, 2.00 0.10\nPartner smoking 1.46 0.80, 2.66 0.22\nPartner alcoholics 1.16 0.54, 2.49 0.71\nGravidity 1.33 1.07, 1.66 0.01\nParity 0.56 0.33, 0.94 0.03\nUF 2.11 1.25, 3.55 < 0.01\nPain/Discomfort Age 0.96 0.93, 1.00 0.06\nBMI 1.00 0.96, 1.04 0.96\nLocal 2.16 1.26, 3.71 < 0.01\nGestation trimester 1.46 1.11 1.93 < 0.01\nPartner smoking 1.26 0.82, 1.93 0.29\nPartner alcoholics 0.71 0.41, 1.26 0.25\nGravidity 1.07 0.90, 1.29 0.45\nParity 0.75 0.51, 1.10 0.14\nUF 1.47 0.94, 2.28 0.09\nAnxiety/depression Age 1.00 0.96, 1.04 0.93\nBMI 1.01 0.97, 1.06 0.55\nLocal 1.07 0.65, 1.78 0.78\nGestation trimester 0.90 0.68, 1.21 0.49\nTable 5 Ordered logistic regression analysis for each dimension\nin the EQ5D (Continued)\nOdds ratio 95% CI p-value\nPartner smoking 0.85 0.56, 1.31 0.47\nPartner alcoholics 0.97 0.53, 1.76 0.91\nGravidity 1.04 0.86, 1.26 0.68\nParity 0.60 0.39, 0.91 0.02\nUF 1.18 0.74, 1.89 0.75\nBold represented p-value < 0.05\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 8 of 11\n\nadvanced maternal age (T able 1)[ 1, 36]. The incidence of\nUFs (p < 0.05) will cause higher gravidity and abortion rates\naccording to our data (Table1), and this finding could be ex-\nplained by the fact that UFs can significantly lead to more\ninfertility [3]; therefore, gravidity and abortion rates will in-\ncrease correspondingly. We were surprised about the\nself-report smoking status of the pregnant women as none\nof them smoked. This finding might be due to the family\nplanning policy (one-child policy in the past and two-child\npolicy recently) in China, wh ich might increase mothers ’\nconcerns about their baby ’s health status although\nself-report bias is another possible explanation. Also, it\nseemed that there was no statistical significantly impact be-\ntween partner smoker/alcohol consumption and pregnant\nwomen’s HRQoL state in the different dimensions (T able5).\nOne prior study demonstrated that the rate of\nCesarean section has increased from 28.8% in 2008 to\n34.9% in 2014 in China [ 37], and this rate was shown to\nbe related to family income, education, health insurance,\nChinese health policy, and cultural background, among\nother factors [ 38]. In pregnant women with UFs,\nCesarean section rates reached 67.0%, which was much\nhigher than the rate in the normal population world-\nwide. Cesarean section may be the most suitable man-\nagement for pregnant women with other pre-pregnancy\nconditions [ 39]. These findings are consistent with prior\npublished data [ 35, 40–43].\nAlthough there was no significant correlation between\nlow HRQoL and poor clinical outcomes of pregnant\nwomen, further studies need to be done to verify these\nresults. QoL is becoming an increasingly important indi-\ncator of the effectiveness of the medical intervention,\nand we should pay greater attention to QoL during preg-\nnancy in our future practice.\nLimitations\nThere were some limitations to this study. This was a\ncross-sectional study, and the data was obtained from an\nEQ-5D questionnaire in which there was relatively a\nsubjective measurement of pregnant women ’s HRQoL.\nThus, self-report bias may be the main bias in this study.\nThis study design also presents limitation with respect\nto both non-response and volunteer biases. Furthermore,\nwe do not make comparisons against different instru-\nment other than the EQ-5D. There are some studies that\nhave used the UFS-QoL to assess the HRQoL in preg-\nnant women [ 34, 35]. This research could provide\nHRQoL data for pregnant women who were evaluated\nusing the EQ-5D-5 L, and this information could be use-\nful in cost-utility analyses in the healthcare-related eco-\nnomic area. Additionally, the HRQoL is an important\nindicator of a patient ’s overall state and plays an increas-\ningly important role in evaluation in the clinic although\nthere is no significant difference with respect to clinical\noutcomes between women with and without UFs in the\nshort-term. Nevertheless, we believe that better quality\nlife-related studies should be performed in order to fur-\nther investigate the role of QoL in the clinic and moni-\ntor long-term effects on QoL. Future studies will need to\nuse a cohort to observe the changes in HRQoL in preg-\nnant women.\nInterpretation\nTo our knowledge, this is the first clinical study to use\nthe EQ-5D-5 L to focus on HRQoL during pregnancy in\nChina and detect independent factors that could impact\nHRQoL in pregnant women with UFs. Also, this study\nshows that EQ-5D index may be a better index than\nEQ-VAS for pregnant women with uterine fibroids and\npossibly for other medical comorbidities or complica-\ntions. Furthermore, the HRQoL data assessed by the\nEQ-5D-5 L could be used to perform cost-utility analyses\nin the future. The clinical outcomes of pregnant women\nwith UFs could still offer insight for the clinical phys-\nician when considering the possibility of latent complica-\ntions in pregnant women with UFs.\nConclusion\nIn this study, we evaluated the influence of UFs on HRQoL\nin pregnant women and found that the EQ5D assessment\ninstrument outperformed the EQ-VAS. Our findings dem-\nonstrated that UFs significantly affected HRQoL in preg-\nnant women in terms of the self-care and usual activity\ndimensions. Independent factors, such as living locally, gra-\nvidity and parity times, and gestational trimester, could have\na significant impact on the HRQoL. Finally, whether clinical\noutcomes may affect HRQoL scores need to be precisely\nanalyzed and requires further research.\nAbbreviations\nBMI: Body mass index; CIs: Confidence intervals; EQ-5D: The EuroQoL Group ’s\nfive-dimension questionnaire; EQ-5D-3 L: The EuroQoL Group ’s five-\ndimension three-level questionnaire; EQ-5D-5 L: The EuroQoL Group ’s five-\ndimension five-level questionnaire; EQ-VAS: EuroQoL Group ’s visual analog\nscale questionnaire; HRQoL: Health-related quality of life; ORs: Odds ratios;\nPROM: Premature rupture of membrane; QoL: Quality of lfe; UFs: Uterine\nfibroids; UFS-QoL: Uterine Fibroid Symptom-Quality of Life; VAS: Visual\nanalog scale\nAcknowledgments\nThe authors are grateful to Yunyi Jian, Jingyan Zhai, Yu Cheng, Xianghao Cai,\nand Bangsheng Jiang for previous support in collecting data.\nFunding\nThere is no financial support in this study.\nAvailability of data and materials\nThe datasets used and/or analyzed during the current study are available\nfrom the corresponding author on reasonable request.\nAuthors’ contributions\nWM contributed to the idea and design of the whole research process and\ncontributed to the final version of the manuscript. HW contributed to the\ndesign and management of the whole study, data analysis, and final version\nMing et al. Health and Quality of Life Outcomes           (2019) 17:89 Page 9 of 11\n\nof the manuscript. YW contributed to the hypothesis of study and final\nversion of the manuscript. TM, YS, ZW, XH WS, TC, and YW contributed to\ndata collection, data analysis, and final version of the manuscript. WD\ncontributed to data collection and drafting the final version of the\nmanuscript. HC and ZL contributed to data analysis and drafting the final\nversion of the manuscript. ZW contributed to the design of the study, the\nguidance of research, and discussion of the final version of the manuscript.\nAll authors read and approved the final manuscript.\nEthics approval and consent to participate\nEthical approval was granted by the Institutional Review Board of The First\nAffiliated Hospital of Sun Yat-sen University (ICE-2017-296).\nConsent for publication\nNot applicable\nCompeting interests\nThe authors declare that they have no competing interests.\nPublisher’sN o t e\nSpringer Nature remains neutral with regard to jurisdictional claims in\npublished maps and institutional affiliations.\nAuthor details\n1Department of Obstetrics and Gynaecology, The First Affiliated Hospital of\nSun Yat-sen University, Guangzhou, China. 2Pharmacoepidemiology and\nPharmacoeconomic, Department of Medicine, Brigham and Women ’s\nHospital and Harvard Medical School, Boston, MA, USA. 3School of Medicine,\nJinan University, Guangzhou, China.\nReceived: 12 September 2018 Accepted: 1 May 2019\nReferences\n1. 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