The impact of nausea and vomiting on health related quality of life during pregnancy: a systematic review

Abstract

Background

Nausea and vomiting (NV) is the most common health condition experienced by up to 80% of pregnant women. Although nausea and vomiting during pregnancy (NVP) is a natural condition and self-limiting, it has many negative impacts on the women’s overall health particularly quality of life (QoL). However, there is no summarized evidence that provides comprehensive information about the impact of NVP on health-related quality of life (HRQoL).

Objective

The objective of this study was to summarize the available empirical evidence on the impact of NV on QoL during pregnancy.

Methods

Five electronic databases (MEDLINE, Embase, MIDIRS, PsycINFO, Web of Science) were searched using keywords and index terms identified in the first step. All databases were searched for studies published in English from January 2010 to February 2025. Studies were included if they assessed the impact of NVP on QoL among pregnant women. The National Institute of Health (NIH) quality assessment tool was used for risk of bias and quality assessment. The overall quality of the evidence was rated based on the GRADE approach.

Results and Discussion

Following screening against the inclusion and exclusion criteria nine full-text studies were included for final analysis. In most studies pregnant women with NVP had significantly lower quality of life scores in most domains of the QoL components including, MCS and PCS of SF-36 and SF-12 and the NVPQoL compared with women without NVP. The increasing severity of NV was significantly correlated with poor QoL among pregnant women particularly in their first trimester as reported in most of the studies.

Conclusions

NVP significantly affects QoL in pregnant women. Routine evaluation and management of NVP needs to be part of antenatal care for better QoL during pregnancy.

Introduction

During pregnancy, significant physiological changes occur in every organ system following conception [1–4]. Although physiological changes during pregnancy may resolve in later stages, some can significantly affect women’s daily lives [4]. Nausea and vomiting (NV) are common conditions experienced by pregnant women that may result from the physiological changes during pregnancy [5–9]. Nausea and vomiting during pregnancy (NVP) usually start in the first trimester (6–8 weeks of gestation) and mostly abate by 16–20 weeks of gestation [7]. The etiology of NVP remains uncertain. However, evidence suggests the causes are multifactorial. The most commonly cited etiology of NVP is changes in hormone level called human chorionic gonadotropin (hCG) which peaks at 10–14 weeks of gestation and declines after 20 weeks of gestation [10–12]. Other factors such as the physiological changes in the gastrointestinal tract, psychological perceptions and genetics could contribute to the occurrence of NVP [13–15]. Empirical studies report that 50%–90% of pregnant women experience NVP with variable degree of severity [8, 16, 17].

Both pharmacological and non-pharmacological treatments may help reduce the symptoms of NVP and provide acute relief [18–21]. However, the safety of taking medications for NVP is a concern for both the pregnant women and the fetus [22–24]. In addition, considerable number of pregnant women experiencing NVP refuse to take medications after considering risks and benefits [24, 25]. Misperceptions among pregnant women and disinformation by health professionals have been cited in the literature as a reason for not taking medications for NVP [25, 26]. The misconceptions and misinformation about taking pharmacological treatments during pregnancy might be due to the historical trauma of thalidomide tragedy, despite the availability of safe antiemetics for NVP [24, 27].

NVP can cause multiple health conditions in addition to loss of quality of life (QoL) such as severe nutritional deficiencies and electrolyte abnormalities. Nutritional deficiencies secondary to NVP further cause loss of important vitamins such as thiamine (vitamin B1) with a subsequent impact on brain function of women [28, 29]. Dietary supplementation of foods containing thiamine is recommended to prevent the permanent damage to the brain function. For example, evidence shows that daily intake of foods such as beef, pork and eggs could replace the lost thiamine during NVP. Hypokalemia and hyponatremia are the most documented electrolyte imbalances caused by NVP [30]. These electrolyte imbalances usually result from dehydration due to severe NVP (hyperemesis gravidarum[HG]) and may cause cardiac dysfunction, often evident on electrocardiography[28, 30, 31]. For example, potassium is vital for myocardial contraction [30]; if dehydration-related hypokalaemia is left untreated, cardiac arrhythmia may occur. Therefore, electrolyte levels should be checked promptly to prevent cardiac complications and potential death.

In addition to the effect on pregnant women, NVP can further affect the health of the fetus. Evidence suggests that poor perinatal outcomes may occur among pregnant women who had severe NVP [32]. Preterm birth and low birth weight have been reported among pregnant women with complicated HG. Vitamin deficiencies due to NVP also indirectly affect the fetus [31]. Overall, severe NVP can affect multiple health conditions of the pregnant women and the fetus.

The impact of NVP is beyond physical discomfort, which also affects multiple components of heath-related quality of life (HRQoL) [33, 34]. The NVP further extends its negative impact on pregnant women’s daily life by limiting paid work performance. Usually, pregnant women who experience NV are either absent from work or doing without their full capacity [33, 35]. It is also reported that pregnant women with NVP demonstrated poor social and daily life functioning [33–36]. It has also been reported that NVP causes anxiety and depression [37–39]. In general, the negative impact of NVP on psychological wellbeing, occupational functioning, social functioning, daily life functioning, depression, and anxiety are linked with poor HRQoL [34, 36, 37, 39].

One of the main goals of the agenda set by the United Nations (UN) Sustainable Development Goals (SDGs) is reduction of maternal mortality by improving the health of pregnant women [40, 41]. However, pregnancy related symptoms such as NV are not prioritized despite causing negative health outcomes [41]. The negative impacts of NVP on pregnant women extends its extent from poor HRQoL to a degree of resulting pregnancy termination [42]. The multidimensional and deleterious consequences of unmanaged NVP on pregnant women’s HRQoL needs a clear and prompt professional support. The lack of attention in addressing NVP might be due to the scarcity of published summarized evidence.

A preliminary search identified a gap in the literature regarding the impact of NVP on HRQoL. While one systematic review exists, it presents methodological limitations, including the lack of standardized NVP quantification, the absence of validated HRQoL measures, and the failure to analyze longitudinal HRQoL changes across pregnancy. Furthermore, a recent review on general pregnancy HRQoL excluded studies using disease-specific instruments, such as the NVPQoL, potentially underestimating the impact of NVP. This review will address these gaps. Specifically, for a better understanding of the impact of NVP on HRQoL, this review will synthesize information from empirical studies that utilized disease-specific measurement instruments, such as the NVPQoL, to address the limitations of previously published reviews. In general, summarized information regarding the impact of NVP on HRQoL is needed for evidence-based policy development and advocacy. Therefore, this systematic review aims to assess the impact of NVP during pregnancy by summarizing published studies that quantified both NVP and HRQoL using validated measurement tools, including disease-specific instruments. This review will employ rigorous methodology to provide a more accurate assessment of the relationship between NVP and HRQoL.

Methods

This systematic review employed Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) and Joanna Briggs Institute (JBI) reviewer's manual for evidence synthesis [43–45].

Inclusion criteria

The inclusion was based-on PICO frame: Population, Intervention/Exposure, Comparator and Outcome.

Population = Pregnant women experiencing NVP

Exposure = NVP

Comparator = Pregnant women without NVP or the general population.

Outcome = HRQoL as measured by different validated tools of both generic and disease-specific.

This review considered empirical studies of any study design (qualitative, quantitative, and mixed-method studies including questionnaires, surveys, interviews, focus groups, and observations) that reported the impact of NVP on HRQoL during pregnancy or among pregnant women. Studies published in English language, from the selected databases from January 2010 to February 2025 were included. Studies were included if they assessed the impact of NVP on HRQoL during pregnancy. Further, articles were included if they only assessed QoL using validated measurement tools (specific to pregnancy or generic).

Exclusion criteria

• ✓ If the primary focus/objective was not on the impact of NVP on HRQoL among pregnant women.

• ✓ Not peer reviewed

• ✓ Not in the English language

• ✓ Studies such as study protocol, reviews, expert opinion were excluded

• ✓ If the HRQoL was not measured using validated measurement tools

Search strategy

The search strategy utilized a three-step method as recommended by JBI [46]. The initial step involved preliminary searching for studies in MEDLINE through the OVID database. The articles obtained in the initial searches from MEDLINE were analyzed for relevance of the search terms. After a few modifications of the search terms, the MEDLINE database was searched again. In the second step, other databases (Embase, (Maternity & Infant Care Database (MIDIRS), PsycINFO, Web of Science) were searched using keywords and index terms identified in the first step. All databases were searched from inception to February 2025 (Ovid MEDLINE < 1946 to February 27, 2025 >, Embase < 1974 to 2025 February 27 >, MIDIRS < 1971 to February 27, 2025 >, APA PsycInfo < 1806 to February Week 3 2025 > and Web of Science < 1900-February 27, 2025 >). The final search was limited to articles published in English language and from the year 2010 to February 27, 2025. Thirdly, a manual search of the reference lists for studies included in the review was conducted to identify potential studies that might have been missed from the database search. The following search terms were used during the database search: Pregnancy [MeSH Terms] OR Pregnan$3[Free text] OR Pregnant women [MeSH Terms] OR Pregnant ADJ wom?n [Free text] AND Nausea [MeSH Terms] OR Nausea [Free text] OR Vomiting [MeSH Terms] OR Vomiting [Free text] OR Nausea ADJ2 vomiting [Free text] OR Morning sickness [MeSH Terms] OR Morning ADJ sickness [Free text] OR Emesis [Free text] AND Quality of life [MeSH Terms] OR QoL [Free text] OR Quality ADJ2 life [Free text] OR Health ADJ related ADJ quality ADJ2 life [Free text] OR HRQoL [Free text] OR NVPQoL [Free text]. Additional features (Truncation and Wildcard) were used to restrict or increase the search.

Data management and study selection

Three levels of screening were conducted, which involved a title and abstract review followed by full-text screening. A review management software (CADIMA) was used for data management [47–49]. []. Study selection, data extraction and result synthesis were performed using the web-based interface of CADIMA. Only one reviewer independently screened titles, abstracts, and full texts of the studies for eligibility. Study selection is summarized in the PRISMA 2020 flow diagram. [43].

Risk of bias and methodological quality assessments

The risk of bias and methodological quality of each study has been critically appraised using the NIH methodological quality assessment tool for observational cohort study and cross-sectional study designs [50].

Data extraction

Data were extracted from studies included in the review using a data extraction format created in the CADIMA web-based software. To ensure that data extraction tools capture all the necessary information, a preliminary extraction was conducted in two studies. Data collection encompassed publication details, study characteristics, study populations, outcome measures, and key findings.

Data synthesis

Although the included studies were quantitative, statistical pooling was not possible due to the variable nature of each study. The main source of their differences was the types of outcomes measurements, trimester/gestational age, the age group of the population and the inclusion criteria they used. To be more specific, studies were using different types of QoL measurements (SF-12, SF-36, NVPQoL and GQoLS). Although some studies were using same QoL measurement tools, they were different in the characteristics of study population such as one used first trimester while the other used all trimesters. In such cases, statistical pooling of studies was not possible. Therefore, the findings were analyzed and presented in narrative form including tables. In narrating the results of this systematic review, the ‘Guidance on the Conduct of Narrative Synthesis in Systematic Reviews’ was used. The main findings were organized in five sections:

• ▪ Prevalence of NVP among pregnant women

• ▪ QoL scores among pregnant women with NVP versus without NVP

• ▪ QoL scores based on severity of NVP

• ▪ Transformation of the QoL across trimesters/gestational age

• ▪ QoL of pregnant women compared with the general population

Results

Literature search results

A total of 838 citations were identified through database searching. The citations were searched from four databases: MEDLINE, Embase, PsycInfo through OVID platform (714 citations) and Web of Science (89 citations). After removing duplicates, a total of 677 citations were left for title and abstract screening. After title and abstract screening, 635 citations were excluded, and 42 citations were left for full text screening. The 42 full text articles were further screened against the inclusion/exclusion criteria. A total of 30 were excluded after full-text screening. During data extraction, another three articles were excluded due to limited information about the outcomes of interest. Finally, nine studies were included for final analysis. The main reason for excluding studies during the extraction stage was due to lack of clarity on the outcome’s measurements. The study selection procedure is outlined in Fig. 1 using the PRISMA 2020 flow diagram.

Fig. 1.

Study selection process-PRISMA 2020 flow diagram

Study characteristics

The studies were conducted in diverse geographical locations. Of the nine included studies, four were from Asia (Taiwan = 1, Hong Kong = 1, Japan = 1, Iran = 1); three were from Europe (Turkey = 1, Norway = 1, the Netherlands = 1); and two were from the USA and Australia (one each). No studies were reported from Africa or South America. Regarding study design, all the included studies were observational studies in which four studies were prospective cohort [51–54] and five studies were cross-sectional in design [55–59]. No randomized controlled studies were identified. Additional details about the study characteristics are presented in Table 1.

Table 1.

Study characteristics

Study	Study period	Study design	Inclusion criteria	Exclusion criteria
Liu. et al [51]	Between August 2012 and April 2015	A longitudinal design	Pregnant women with: ▪ 8–12 gestational weeks ▪ A score of INVR higher than 3 ▪ Can reading and writing Chinese	Participants had mental illnesses or chronic diseases
Tan. et al [35]	From 1 April to 31 July, 2015	Observational prospective cohort study	Pregnant women: ▪ Aged 18–55 ▪ with 9–16 weeks pregnancy ▪ who understood English	Participants who had condition interfering with their ability to understand study requirements
Heitmann. et al [55]	From 10th November 2014 to 31 st January 2015	Cross-sectional	▪ Pregnant women experienced NVP ▪ New mothers: ✓ with a child of < 1 year of age ✓ experienced NVP during their last pregnancy	Not described clearly
Munch. et al [56]	Not specified	An exploratory study designed	Pregnant women in first trimester and experienced NVP	Not described
Chan. et al [57]	Over a 2-month period starting in December 2006	A prospective cross-sectional study	Pregnant Chinese women with 10 −14 weeks of gestation	Non-Chinese or those who refused to participate
Hirose. et al [53]	Between August 2018 and February 2019	Prospective cohort study	Singleton pregnant women: ▪ Aged 20 years or older ▪ Ability to read and write in Japanese	Participants with complications and those admitted to hospital
Vakilian. et al [58]	Not specified the duration but it was reported as the study was conducted in 2015	A cross-sectional study	Pregnant women with: ▪ Desired pregnancy ▪ Gestational age between 8–14 weeks ▪ Absence of acute and chronic illness ▪ Living with spouse ▪ Not having a history of mental illness	Not described
Yilmaz. et al [59]	From July-December 2015	A prospective cross-sectional study	Pregnant women: ▪ Aged between 15–19 ▪ Having singleton pregnancy ▪ Gestational age ≤ 20 weeks ▪ Absence of congenital anomalies and systemic diseases	▪ Maternal age ≥ 20 years ▪ Fetal death and threatened abortion ▪ Women with HG
Bai. et al [54]	From April 2002 until January 2006	A prospective cohort study	Not described	Pregnancies with outcomes of: ▪ Twin pregnancies, ▪ Induced abortion ▪ Fetal deaths before 20 weeks of gestation

Study population

Although most of the studies included all age groups in their studies, three studies investigated the association between NVP and QoL in specific age groups. The study by Tan et al. included pregnant women aged 18–55, Hirose et al. included pregnant women aged 20 years or older to investigate the impact of NVP on QoL [52, 53]. In addition, one study was conducted among adolescent pregnant women aged between 15–19 [59]. Pregnant women’s gestational age/trimester is an important study population characteristic in evaluating the association between NVP and QoL as variation could occur across the gestational age. From the nine studies included in this review, five studies were conducted among pregnant women during their first trimesters with a range of 8–20 weeks of gestation [52, 56–59]. The remaining four studies included all the three trimesters and changes of the outcomes were measured in each trimester [51, 53–55].

Regarding the study settings, seven of the nine studies were conducted in hospital and two of the studies were population based. In recruiting study participants, most of the studies used convenience sampling. Response rate was reported in six studies [51–53, 56–58] in which four studies [52, 56–58] reported a response rate of greater than 90%. The remaining three studies did not report the response rate.

Regarding methods of data collection, five studies [51–53, 56, 57] collected the data using self-reported questionnaires at the study setting, three studies [54, 58, 59] used a combination of self-reported and interviews and one study [55] collected the data through an on-line questionnaire. Details of the study population are found in Table 2.

Table 2.

Study population

Study	Age group	Trimester/gestational age	Study settings	Sampling/recruitment methods	Sample size and response rate	Methods of data collection
Liu. et al [51]	All age	Three trimesters were included: ▪ First (6–13 weeks) ▪ Second (14–28 weeks) ▪ Third (29–40 weeks) trimesters	Hospital based	Convenience sampling	▪ 101 women were recruited and analyzed ▪ 78.92% response rate	Self-reported questionnaire
Tan. et al [35]	Women aged 18–55	9–16 weeks of gestation	Hospital based	Convenience sampling	▪ 135 women were approached ▪ 116 women completed the survey (92% response rate) ▪ Power calculation was used to estimate	Self-reported questionnaire
Heitmann. et al [55]	All age	All trimesters	Population-based	Convenience sampling	712 women completed the questionnaire and were included in the analysis	Anonymous on-line questionnaire through SurveyXact
Munch. et al [56]	All age	First trimester of pregnancy	Hospital based	Convenience sampling	▪ 96 women enrolled ▪ 93 had complete data ▪ 96.8% response rate	Self-reported questionnaire
Chan. et al [57]	All age	10 −14 weeks of gestation	Hospital based	Convenience sampling	▪ 418 women consented to participate ▪ 396 participants were included for analysis ▪ 94.7% response rate	Self-reported questionnaire
Hirose. et al [53]	Women aged 20 years or older	Three Gestational periods: ▪ 5–8 weeks (Gestational 1) ▪ 9–12 weeks (Gestational 2) ▪ 13–20 weeks (Gestational 3)	Hospital based	Convenience sampling	▪ 175 pregnant women recruited ▪ 153 pregnant women were analyzed ▪ Response rate of 87.4%	Self-reported questionnaire
Vakilian. et al [58]	All age	8–14 weeks of gestation	Hospital based	Convenience sampling	▪ 320 pregnant women were enrolled ▪ 310 participates completed and included for analysis ▪ Response rate of 96.8%	Self-completed questionnaire and interviewer administered questionnaire
Yilmaz. et al [59]	Pregnant women aged between 15–19	The first 20 weeks of pregnancy	Hospital based	Convenience sampling	During the study period a total of 250 study participants were recruited and included for the final analysis	Face-to-face interview and self-completed questionnaire
Bai. et al [54]	All age	All trimesters with stratification: ▪ < 18 weeks – early gestation ▪ 18–25 weeks- mid gestation ▪ > 25 weeks- late gestation	Population-based	Study participants were included from the large cohort generation R study- all samples who fulfill the eligibility criteria during the study period were included	▪ 7069 study participants were enrolled ▪ 5079 participants were included for final analysis	Self-reported and interviewers administered questionnaires

Outcome measurements

The studies employed different types of outcome measurement tools. In measuring NVP, most of the studies were using PUQE. From the nine studies included, five of them used PUQE [52, 55–58], two studies used INVR [51, 53] one study used the Rhodes test [59]. All the studies used validated tools to measure NVP except a study by Bai et al., which used an unvalidated tool. Regarding the QoL measurements, NVPQoL [51, 52, 56], SF-36 [56–59], SF −12 [52–54] and QoLS [55] were used by the included studies. Pregnant women without NVP [52, 56, 58] and the general population [54, 57, 59] were used to compare QoL of pregnant women with NVP. Three studies [51, 53, 55] did not use a comparator. Details of the outcome measurements of the included studies are found in Table 3.

Table 3.

Outcome measurements

Study	NVP assessment tool used	Quality of life measurement tool used	Comparator used to measure QOL
Liu. et al[51]	INVR	NVPQoL	No comparator used
Tan. et al [35]	PUQE	SF-12 and NVPQoL	Women without NVP
Heitmann. et al [55]	PUQE	QoLS	No comparator used
Munch. et al [56]	PUQE	NVPQoL and the SF36	Women with HG and asymptomatic
Chan. et al [57]	PUQE	SF-36	Healthy Hong Kong Chinese women aged between 18 and 40 years and pregnant women without NVP
Hirose. et al [53]	INVR	SF-12	No comparator used, instead changes in NVP and HRQoL was measured with the increasing gestational age
Vakilian. et al [58]	PUQE	SF-36	Women without NVP
Yilmaz. et al [59]	Rhodes test	SF-36	General Turkish female population
Bai. et al [54]	Self-constructed tool	SF-12	Normative Dutch sample of women aged 30–39 years

Main findings

The main findings are depicted in Table 4. For better understanding, the QoL scores are summarized in four sections based on the presence of NVP, severity of NVP, transformation of QoL in gestational age and comparison with the general population.

Table 4.

Main findings

Study	NVP assessment scores	QoL scores (the association between NVP on QoL scores)
Liu. et al [51]	▪ The mean (SD) severity score for NVP in each trimester: ✓ First trimester = 10.95 (± 6.95) ✓ Second trimester = 2.61(± 4.09) ✓ Third trimester = 2.48 (± 4.13)	▪ The mean (SD) mean NVPQoL was: ✓ First trimester = 133.73 (± 26.09) ✓ Second trimester = 103.64 (± 27.64) ✓ Third trimesters = 105.54(± 31.43) ▪ Worst QoL was reported in the first trimester ▪ The NVPQoL scores of pregnant women were positively and independently associated with the INVR
Tan. et al [35]	✓ The prevalence of NVP during pregnancy was 72% with severity of: ✓ Mild NVP symptoms = 42% ✓ Moderate symptoms = 55% ✓ Severe symptoms = 1%	▪ PCS scores of SF-12 were significantly lower in women with NVP versus not ▪ But there was no significant difference in MCS scores ▪ NVPQoL score was significantly decrease in QoL with increasing NVP severity
Heitmann. et al [55]	▪ Percentages of women with: ✓ Mild NVP = 8.7% ✓ Moderate NVP = 61.7% ✓ Severe = 29.5%	▪ Severity of NVP symptoms was significantly associated with global QoL among pregnant women
Munch. et al [56]	▪ Total numbers of women with NVP were 48/93(51.6%)	▪ The physical summary score for women with NVP were significantly lower than asymptomatic women ▪ In five domains of SF-36, QoL scores among women with NVP were significantly lower than asymptomatic women. Significant domains were: ✓ Role physical ✓ Bodily pain ✓ General health ✓ Vitality ✓ and social function ▪ Increasing severity of NVP as measured by PUQE was associated with low quality of life
Chan. et al [57]	✓ The prevalence of NVP during pregnancy was 90.9% with severity of: ✓ Mild = 37.6% ✓ Moderate/severe = 53.3% ✓ Symptomless = 9%	▪ SF-36 scores were significantly and negatively correlated with PUQE scores ▪ Compared with the general population, pregnant women had significantly lower mean scores in all the domains the except for general health ▪ Compared with women without NVP ▪ Women with ‘mild’ NVP were significantly lower in role-physical, bodily pain, vitality and social functioning than those without symptoms of NVP ▪ Women with ‘severe’ NVP had significantly lower mean scores in all domains compared with those who were ‘symptomless’
Hirose. et al [53]	✓ Severe NVP was highest at G2 followed by G1 and lowest at G3	▪ Both PCS and MCS scores of SF-12 were lower during G2 and G3, but not during G1 ▪ Both PCS and MCS score were significantly higher at G3 when compared with G1
Vakilian. et al [58]	✓ The prevalence of NVP during pregnancy was 77.5% with ✓ Low = 18.8% ✓ Intermediate = 59% ✓ Severe = = 22% ✓ Most of the participants had intermediate NVP	▪ The SF-36 score was among pregnant women with NVP was significantly lower compared to without NVP in all domains of SF-36 except the ‘mental health domain’ ▪ Mean QoL score as measured in SF-36 was decreased as the severity of NV increased ▪ lowest overall mean SF-36 score was observed among pregnant women with severe NVP
Yilmaz. et al [59]	✓ The prevalence of NVP during pregnancy was 74.8% ✓ Mild symptoms = 36.8% ✓ Moderate symptoms = 28.8% ✓ Severe symptoms = 9.2% ✓ Most of the participants had Moderate NVP symptoms	▪ The SF-36 scores were statistically lowered in in the following domains ✓ Physical functioning ✓ Bodily pain ✓ General health ✓ Vitality ✓ Social function ✓ Mental health ▪ Severity of NVP associated with lower QoL in both MCS and PCS of SF-36 ▪ Average SF-36 scores of study subject were lower than the general population
Bai. et al [54]	The prevalence of NVP was 33.6%	▪ Women with NVP had lower PCS and MCS scores of SF- 12 than women without NVP ▪ The average physical component summary score was below the normal population

QoL scores among pregnant women with NVP versus without NVP

Three studies reported that pregnant women with NVP had significantly lower QoL scores in all domains including, MCS and PCS of SF-36 and SF-12 compared with women without NVP. In another two studies, scores from PCS of SF-36 and SF-12 were found to be significantly lower among pregnant women with NVP compared with women without NVP [52, 56]. In contrast, Tan et al. and Munch et al. reported that, significant differences were not observed in MCS of SF-36 and SF-36 among pregnant women with NVP compared with women without NVP. Overall, QoL of pregnant women with NVP was reported be lower in comparison with asymptomatic women, particularly in the physical related symptoms.

QoL scores based on severity of NVP

Most of the studies measured the association between the increasing severity of NVP and QoL using NVPQoL and SF-36. In three studies [51, 52, 56], the increasing severity of NVP was independently and positively associated with NVPQoL scores of pregnant women which indicates poor QoL. It is reported that, both the total and all domains (Physical symptoms, Limitations, Emotions, and fatigue domain) of NVPQoL scores were increased linearly with the increasing NVP scores [51, 52, 56]. Overall, NVPQoL scores were significantly increased (decrease in QoL) with increasing NVP severity among pregnant women. Similarly, increasing severity of NVP was significantly and negatively correlated with total mean SF-36 score. Both MCS and PCS scores of SF-36 were decreased with severity of NVP indicating poor QoL as reported in four studies [56–59]. Similarly, Heitmann K. et al. reported that severity of NVP symptoms was significantly associated with global QoL among pregnant women. Generally, severity of NVP worsens QoL of pregnant women.

QoL across trimesters/gestational age

From the nine included studies, two studies explicitly measured the transformation of QoL scores in each trimester. In the first study as reported by Liu M-C. et al., the mean NVPQoL score was 133.73 in first trimester, 103.64 in Second trimester and 105.54 in third trimester. Worst QoL score was reported in the first trimester which was significantly higher than those in the second and third trimester, higher NVPQoL scores indicated lower QoL. In the second study reported by Hirose M. et al., both MCS and PCS scores of SF-12 were significantly higher at G3 (13–20 weeks of gestation) compared to G1 (5–8 weeks of gestation). The finding indicates that, pregnant women had better QoL at G3 (13–20 weeks of gestation) compared with the first weeks of gestation, higher SF-12 score indicates better QoL. In general, pregnant women experiencing NVP had lower QoL during the first gestational age/the first trimester.

QoL of pregnant women compared with the general population

Three studies compared QoL of pregnant women during pregnancy with the general population of a country, where the study was conducted. To be more specific, a study by Chan et al., reported that QoL scores of pregnant women with NVP as measured in SF-36 were significantly lower than the Hong Kong general population in all domains of SF-36 except for general health. In addition, Yilmaz E. et al. reported that, average SF-36 scores of 250 pregnant women were lower than the general Turkish female population. Similarly, the average PCS score of pregnant women with daily presence of nausea, vomiting and fatigue was below the average in a normative Dutch sample of women aged 30–39 years as reported in a study by Bai et al. However, the average MCS score was similar with normative with the Dutch sample. In general, QoL of pregnant women with NVP is reported to be lower than the normal population.

Risk of bias and methodological quality results

As shown in Table 5, four of the studies were classified as having “high risk” with corresponding quality rating of “poor” quality. Three of the nine studies were “moderate risk” of bias and “fair” quality. Only two the studies were with “low risk” of bias and “good” quality.

Table 5.

Risk of bias and quality ratings

Studies	Overall risk of bias	Overall quality ratings
Liu. et al [51]	High	Poor
Tan. et al [35]	High	Poor
Heitmann. et al [55]	High	Poor
Munch. et al [56]	High	Poor
Chan. et al [57]	Moderate	Fair
Hirose. et al [53]	Low	Good
Vakilian. et al [58]	Moderate	Fair
Yilmaz. et al [59]	Moderate	Fair
Bai. et al [54]	Low	Good

Overall quality of evidence- GRADE

As described in the methods sections, GRADE approach was used to judge the quality of evidence of this systematic review.

Descriptions of each GRADE component are as follows.

• A.Risk of bias: With four studies of “high risk” of bias, three studies of “moderate” of bias and two studies “low risk” of bias, this reviewer judged the overall risk of bias as “moderate”. As per the GRADE approach, the overall evidence is downgraded by one level.
• B.Inconsistency: Inconsistency of results was not observed in most of the studies. In most of the studies the negative impacts of NVP on QoL in pregnant women were established. Considering the GRADE approach, the overall evidence of this review could not be affected by the inconsistency of results.
• C.Indirectness: All the studies used a similar study population. (pregnant women with NVP) and similar outcome measures (QoL). Therefore, the overall evidence will not be affected.
• D.Imprecision: The criterion for OIS was fulfilled for this review. As per GRADE, this reviewer judged the overall evidence as precise.
• E.Publication bias: It is difficult to assess publication bias.

Conclusion: The author would suggest that the overall GRADE rating is moderate. This suggests that “this research provides a good indication of the likely effect. The likelihood that the effect will be substantially different is moderate” [60].

Discussions

Statement on the main findings

Whilst being pregnant alone affects QoL negatively, experiencing NVP further causes additional burden and thereby worsens QoL. Studies revealed that pregnant women with NVP had lower physical and mental aspects of QoL when compared with women without the symptoms of NVP during their pregnancy as measured in SF-36 and SF-12 [53, 54, 57].To expand more, Chan et al. reported that, both PCS and MCS of SF-36 were found to be negatively correlated with NVP among Chinese pregnant women involved in his study. In addition, both PCS and MCS of SF-12 were found to be significantly lowered among pregnant women who experienced NVP in studies by Hirose et al. and Bai et al. [53, 54]. These findings indicate that, the impact of NVP is not only on the physical symptoms but also has significant negative impact on the mental health of pregnant women. The need of paying attention to both physical and mental aspects of QoL of pregnant women with NVP have been suggested in published literature [8, 34].

Severity of NVP has been cited a determinant of poor QoL among pregnant women [33, 61]. In this review the included studies demonstrated that, there is a definitive relationship between severity of NVP and QoL. The increasing severity of NVP was significantly associated with poor QoL as reported in eight of the nine included studies in this review.

Chan et al. compared the QoL of pregnant women based on severity level of NVP which showed that pregnant women with ‘mild’ NVP had lowest scores in role-physical, bodily pain, vitality and social functioning of SF-36 compared with ‘symptomless’ pregnant women [57]. Further, all domains of SF-36 became significantly lowered among pregnant women with ‘severe’ level of NVP compared with women without any symptoms [57]. It is arguable that when a pregnant woman experiences severe NVP, this will limit particularly socialization, domestic life functioning and role physical which all these are components QoL [33, 62]. Further, a decline functionality in some components due to severe NVP could affect other components of QoL. Although pregnancy alone needs care in general, pregnant women with severe NVP needs prompt treatment and professional support to improve their QoL.

In this review the transformation of HRQoL across the gestational age/trimesters was explored [51, 53]. A longitudinal study that evaluated the changes in QoL in distinctive trimesters reported that, pregnant women experiencing NVP had poor QoL in their first trimester compared with second and third trimester [51]. Better QoL status in third trimester has been also reported compared with second and first trimester in a cohort study by Hirose et al. [53] Overall, pregnant women with NVP are experiencing poor QoL particularly in the first trimester. Factors linked with poor QoL in early weeks of pregnancy could be associated with the severity of NVP during the first weeks of gestational age. Other empirical studies also reported that women in first trimester usually worries about their pregnancy that results in psychological distress and poor QoL particularly among multiparous women [63–65]. Considering ‘severe’ NVP usually occurs in the early gestational weeks, pregnant women in the first trimester needs evaluation of their QoL status thereby to provide professional support.

Three studies have compared QoL women experiencing NVP with the normal population; Chan et al. compared 396 pregnant women with the Hong Kong general population, Yilmaz et al. compared 250 pregnant women with general Turkish female population and Bai et al. compared 5079 pregnant women with the normative Dutch sample. In all these three studies, QoL of women with NVP found to be lower than their comparators [54, 57, 59]. Previous study reported from US shows that, QoL of pregnant women was significantly lower than the population norms with a profound difference on the social functioning [33].

Strength and limitations of the study

This systematic review synthesizes evidence from the past decade of research to highlight the significant adverse impact that NVP has on women’s HRQoL. It provides timely and valuable insights that can inform health policy decisions, patient advocacy initiatives, and program implementation strategies aimed at improving support services for pregnant women affected by NVP. A key strength of this review is the application of the GRADE approach to evaluate the overall quality of the evidence base, thereby lending additional rigor and credibility to the findings. Despite these strengths, several limitations should be acknowledged. First, by restricting the inclusion criteria to studies that used validated QoL instruments, the review may have inadvertently excluded research employing non-validated tools, and thus potentially overlooked additional insights into NVP’s impact. For instance, studies using custom or qualitative measures of QoL might offer context-specific perspectives that were not captured. Second, the exclusion of non-English publications introduces a language bias, meaning that relevant studies published in other languages were not considered, which may limit the international applicability of the review’s findings. Third, the included studies exhibited substantial heterogeneity in design (e.g., cross-sectional vs. longitudinal), population characteristics, and the QoL assessment tools used, which complicates the synthesis of evidence across studies and limits the generalizability of the conclusions. Fourth, study selection, data extraction, and quality assessment were performed by a single reviewer without independent verification by a second reviewer, raising the potential for selection bias or errors in data interpretation. Finally, the methodological quality of the included studies varied considerably and was often suboptimal. For example, many studies did not justify their sample sizes and frequently relied on convenience sampling. Blinding of outcome assessment was not commonly implemented, and few studies adequately controlled for confounding variables. Such weaknesses in the primary evidence base may undermine the reliability of this review’s conclusions. On balance, however, this review provides a crucial compilation of recent evidence on NVP and HRQoL that can guide clinical and public health efforts to mitigate the substantial burden of these symptoms on pregnant women’s lives.

Implications for policy, practice and future research

This review underscores the need for policies that integrate routine assessment of NVP into antenatal care, recognizing its multifaceted impact on women’s HRQoL. Clinical guidelines should recommend standardized, disease-specific instruments—such as a validated NVPQoL scale—for early identification and management of moderate to severe symptoms, thereby preventing downstream costs associated with hospitalizations, repeated visits and work absenteeism. Maternal health services must extend beyond traditional morbidity and mortality metrics to encompass QoL outcomes, with healthcare professionals trained and incentivized to address NVP proactively throughout the first trimester and beyond. International bodies (e.g., WHO) and national policymakers should collaborate to develop training modules, fund implementation research and embed NVP management into existing maternal health frameworks, ensuring equitable access to supportive interventions across income settings.

Future research should broaden geographic representation by prioritizing studies in low- and middle-income countries—particularly in Africa—where data on NVP’s QoL burden remain scarce. To strengthen the evidence base for global advocacy, investigators must design adequately powered, methodologically rigorous studies, employing probability sampling and controlling for key confounders (e.g., maternal age, socioeconomic status, parity). Development and validation of disease-specific HRQoL tools are imperative; content validity should be established through qualitative methods that capture women’s lived experiences, thereby ensuring that instruments fully reflect the domains most affected by NVP. In addition, in-depth qualitative inquiries—through interviews or focus groups—can elucidate the contextual factors shaping HRQoL and inform tailored interventions. By combining robust quantitative designs with qualitative insights and expanding the cultural and socioeconomic scope of research, future studies will better equip policymakers and clinicians to mitigate the substantial burden of NVP on pregnant women worldwide.

Conclusions

NVP significantly affects the QoL of pregnant women. Pregnant women who are experiencing NVP symptoms had poorer QoL compared with women without the symptoms. Further, the findings of this review show that the overall QoL of pregnant women was found to be lower than the general population. Both physical and mental components of QoL domains are affected by NVP. Most importantly severity of NVP is significantly associated with negative outcomes of HRQoL. Pregnant women experiencing NVP had the worst QoL during the first trimester. Routine assessment of NVP with its impact on HRQoL during pregnancy using validated disease-specific instrument is needed as part of antenatal care delivery.

Authors’ contributions

K.Y.G. conceived and designed the study, conducted the literature search, performed data extraction and quality assessment, and drafted the manuscript. A.A.A. contributed to the interpretation of findings, provided critical revisions to the manuscript, and supervised the overall review process. Both authors reviewed and approved the final version of the manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

All data generated or analysed during this study are included in this published article.

Declarations

Ethics approval and consent to participate

Human Ethics and Consent to Participate declarations: not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.