Abstract
Exploring the quality of life and factors affecting hospitalized pregnant and postpartum women with SARS-CoV-2 infection and thus providing a basis for improving the quality of health services. Hospitalized pregnant and postpartum women with SARS-CoV-2 infection in Suzhou City between October 2022 and December 2024 were taken as the study subjects, and questionnaires were administered to 512 patients using self-designed questionnaires and the EQ-5D scale. Univariate chi-square test, multivariate Logistic regression, and quantile regression analysis methods were used to analyze the quality of life and its influencing factors in hospitalized patients with SARS-CoV-2 infection. Of the five dimensions related to quality of life, the highest percentage of problems occurred with pain/discomfort (15.1%), followed by mobility impact (10.4%); median VAS score was 89. The results of multifactorial analysis showed that seven factors, including different stages of pregnancy, pre-pregnancy BMI, disease severity, and different stages of epidemic development, influenced the physical dimension-related EQ-5D; family income and disease severity had an effect on the psychological dimension-related EQ-5D. The education level and the presence of severe infection were identified as influencing factors for the 25th percentile of VAS scores, and being in the early stage of the epidemic and the presence of severe infection were influencing factors for the median VAS score. During the hospitalization of patients with SARS-CoV-2 infection, indicators of physical and psychological dimensions related to quality of life were affected to some extent, and as the epidemic progressed, the proportion of re-infected persons increased, and the impact on VAS scores decreased. Special attention should be paid to the fact that during the period of hospitalization, the indicators of psychological dimensions are influenced by the economic level of the family, in addition to the severity of the disease.
Subject terms: Infectious diseases, Risk factors, Public health, Quality of life
Introduction
Coronavirus disease 2019 (COVID-19) is a new acute respiratory infectious disease1, which has experienced three waves of major rebound epidemics in China since November 2022, when optimized prevention and control measures were implemented. Pregnant women have always been considered vulnerable during infectious diseases due to physiologic changes in the immune, cardiovascular, and respiratory systems2. Moreover, the quality of life during hospitalization of pregnant and postpartum women with SARS-CoV-2 infection is related to the quality of health services. Currently, there is still a gap in research on the quality of life of hospitalized pregnant and postpartum women with SARS-CoV-2 infection in the Suzhou region.
The EuroQoL-5 Dimensions (EQ-5D) is a widely used health-related quality of life measurement tool internationally, providing an objective measure of health-related quality of life designed to describe and evaluate the health status of patients in a variety of disease areas3. The EQ − 5D has been translated into Chinese, its validity and reliability Validity was tested and examined4,5, and it has also become a suitable and valid instrument for measuring HRQoL in Chinese people. This study aims to analyze the quality of life and its influencing factors of pregnant and postpartum women with SARS-CoV-2 infection during hospitalization in the Suzhou region. Thereby, it provides a basis for better guiding the health management of pregnant and postpartum women with SARS-CoV-2 infection and offers scientific evidence for formulating relevant medical and health care policies.
Methods
Study population
From October 2022 to December 2024, this study utilized the “Active Population-based Surveillance of Influenza-associated Hospitalizations” previously established in Suzhou. It screened the daily uploaded case information from all hospitals that admit pregnant and postpartum women across 10 districts of Suzhou. The screening criteria were as follows: female cases aged 20–50 years; having a recorded body temperature of ≥ 37.3 °C within 48 h of admission; and/or having an admission diagnosis that matches the codes related to acute respiratory or febrile illnesses (ARFI) in the ICD-10 diagnostic codes. After doctors or nurses confirmed the pregnancy status of the patients, a total of 4,219 hospitalized pregnant and postpartum women with ARFI were enrolled in the surveillance cohort. Subsequent steps included conducting questionnaires and collecting specimens (nasopharyngeal swabs and serum). The collected specimens were sent to the laboratory of Suzhou Center for Disease Control and Prevention (Suzhou CDC) for RT-PCR testing of SARS-CoV-2 and influenza viruses. Pregnant and postpartum women laboratory-confirmed to have SARS-CoV-2 infection were defined as the study subjects. After excluding 6 patients with co-positive nucleic acids for both influenza and SARS-CoV-2, a total of 512 hospitalized pregnant and postpartum women with positive SARS-CoV-2 nucleic acids were identified. All patients signed an informed consent form. The flow chart of the study is shown in Fig. 1.
Fig. 1.
Study flow chart.
Definition of related indicators
According to the case definition for active surveillance, all patients were ≥ 18 and < 50 years of age. Maternal state was based on the patient’s gestational week at the time of admission, with a gestational week < 28 weeks as non-third trimester and a gestational week ≥ 28 weeks as the third trimester6, and taking into account the impact on disease severity, the early postpartum women inclusion range was up to 2 weeks postpartum. Pre-pregnancy BMI was calculated based on the height and weight recorded in the patients’ medical records from their first prenatal check-up; using China’s BMI classification standards: pre-pregnancy BMI < 18.5 is lean, pre-pregnancy BMI ≥ 18.5 and < 24 is normal, pre-pregnancy BMI ≥ 24 is overweight, and pre-pregnancy BMI ≥ 28 is obese7. A case of severe infection is defined as any one of three conditions: admission to the ICU, use of mechanical ventilation or shortness/difficulty of breathing during hospitalization8. Definition of fever during this hospitalization Maximum temperature ≥ 37.3℃ (skin temperature)9. Based on the proportion of reinfected patients and the monitoring data from the local Center for Disease Control and Prevention (CDC), all hospitalized cases were divided into three stages according to the time of admission to the hospital, which were Stage 1 (October 2022 ~ February 2023), Stage 2 (March ~ December 2023), and Stage 3 (January ~ December 2024) of the epidemic development.
Questionnaire
A self-designed epidemiological questionnaire was used to conduct surveys among pregnant and postpartum women with SARS-CoV-2 infection during their hospitalization and at the time of discharge. The questionnaire included basic information (age, height, weight, education, occupation, etc.), date of hospitalization and diagnosis, antecedent history, EQ-5D-3 L rating scale, pregnancy history, treatment and regression, etc. The EQ-5D-3 L scale consisted of two parts, the five-dimensional health description system and the VAS scoring system. The five-dimensional health description system includes five questions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression, with three options for each question, ranging from no impact, mild impact, and serious impact, which are used to investigate whether the patient has impact in the five dimensions and the severity of the impact. The first four of the five dimensions are categorized as physical and anxiety/depression is categorized as psychological. The VAS scoring system is a visual analogue scale that represents subjective health status on a scale of 100 (best health status in mind) to 0 (worst health status in mind).
Quality control
The research team of this study consists of professionals from multiple institutions, including CDC, medical institutions, and maternal and child health care institutions. Before the project was launched, all investigators were required to receive unified standardized training, which covered the study’s operating procedures and key precautions. Only those who passed the assessment were allowed to formally participate in the work. During the survey and sample collection process, uniformly formatted questionnaires and sample collection record forms were used. In the data collation and analysis phase, a mechanism of double independent data entry and cross-verification was implemented to ensure data accuracy.
Statistical analysis
Questionnaire entry was performed using the Suzhou City Disease Surveillance Information System, and a two-person parallel entry was used EXCEL and SPSS 26.0 were used to process the data. Continuous variables with non-normal distribution were described using median and interquartile range, while categorical variables were described using counts and percentages. In order to compare the differences in the distribution of the five dimensions among different populations, the dimensions were categorized as “with/without impact”, and mild and serious impacts were combined to form the “with impact” category. One-way χ² test (with Fisher’s exact test used when the conditions are not met) was employed to analyze the distribution differences of the five dimensions across different variable categories. Variables with P < 0.10 in the univariate analysis results were included as independent variables in the binary logistic stepwise regression equation for multivariate analysis, with the presence or absence of the five dimensions results as the dependent variable (0 = without impact, 1 = with impact). In the VAS scores section, because of the skewed distribution of the data, quantile regression analyses were used to assess the factors influencing VAS scores at the 25%, 50%, and 75% quartiles, respectively. The test level was taken as 0.05.
Results
Basic information
Among the 512 pregnant women with SARS-CoV-2 infection, the mean age (29.91 ± 4.40) years, and the < 35 age group was predominant (85.2%); the mean gestational week (30.99 ± 9.45) weeks, and the third trimester (≥ 28 weeks) was predominant (71.1%). The patients with a normal BMI were overrepresented (63.7%), followed by those who were overweight (18.8%); educational composition was dominated by patients with bachelor’s degree or above (44.3%) and total annual household income was dominated by ≥ 100,000 RMB (86.5%). In addition, 67% of the patients have a vaccination history.
Of the 512 hospitalized pregnant and postpartum women with SARS-CoV-2 infections, 27%, 36.1% and 36.9% of patients in the three different waves of the epidemic, respectively. 32.4% of patients had experienced symptoms of ILI with acute respiratory infection within the past year; the median length of hospitalization was 4 days; 84.2% of patients had a temperature of 37.3 °C or higher at the time of the current hospitalization; Antibiotics were used in 53.1% of patients and COVID-19 antivirals drug in < 1% of patients. Oxygen therapy, including nasal cannula oxygen and mask oxygen, was used in 49.6% of hospitalized patients, respectively (Table 1).
Table 1.
Baseline table of 512 pregnant and postpartum women with SARS-CoV-2 infection.
| Variant | First trimester n(%) (n = 48) | Second trimester n(%) (n = 84) | Third trimester n(%) (n = 364) | Postpartum women n(%) (n = 16) | Total n(%) (n = 512) |
|---|---|---|---|---|---|
| Advanced maternal age (age ≥ 35) | |||||
| Yes | 6(12.5) | 10(11.9) | 56(15.4) | 4(25.0) | 76(14.8) |
| No | 42(87.5) | 74(88.1) | 308(84.6) | 12(75.0) | 436(85.2) |
| Pre-pregnancy BMI | |||||
| Underweight | 10(20.8) | 8(9.5) | 45(12.4) | 1(6.3) | 64(12.5) |
| Normal | 32(66.7) | 56(66.7) | 226(62.1) | 12(75.0) | 326(63.7) |
| Overweight | 5(10.4) | 18(21.4) | 71(19.5) | 2(12.5) | 96(18.8) |
| Obese | 1(2.1) | 2(2.4) | 22(6.0) | 1(6.3) | 26(5.1) |
| Education | |||||
| Senior middle school and below | 23(47.9) | 28(33.3) | 86(23.6) | 4(25.0) | 141(27.5) |
| College | 11(22.9) | 19(22.6) | 110(30.2) | 4(25.0) | 144(28.1) |
| University and above | 14(29.2) | 37(44.0) | 168(46.2) | 8(50.0) | 227(44.3) |
| Family income (RMB) | |||||
| < 100,000 | 10(20.8) | 15(17.9) | 42(11.5) | 2(12.5) | 69(13.5) |
| ≥ 100,000 | 38(79.2) | 69(82.1) | 322(88.5) | 14(87.5) | 443(86.5) |
| Vaccination history | 33(68.8) | 52(61.9) | 244(67.0) | 14(87.5) | 343(67.0) |
| Median length of hospital stay (IQR), days | 4.0(3.0–6.8.0.8) | 4.0(3.0–6.0) | 4.0(3.0–6.0) | 4.0(2.3–6.8) | 4.0(3.0–6.0) |
| ILI symptoms | 24(50.0) | 42(50.0) | 190(52.2) | 8(50.0) | 264(51.6) |
| Fever | 40(83.3) | 70(83.3) | 304(83.5) | 16(100.0) | 430(84.0) |
| Antibiotics used | 21(43.8) | 50(59.5) | 191(52.5) | 10(62.5) | 272(53.1) |
| Oxygen therapy | 4(8.3) | 26(31.0) | 220(60.4) | 4(25.0) | 254(49.6) |
Quality of life profile of pregnant and postpartum women with SARS-CoV-2 infection
Among the five dimensions, the highest proportion of the population of pregnant women with SARS-CoV-2 infection had problems with pain/discomfort (15.1%), followed by mobility (10.4%), and the lowest proportion had problems with self-care (4.5%). 1.0% of the pregnant and postpartum women with SARS-CoV-2 infection had serious impact in the self-care and usual activities dimensions, respectively (Table 2). The median VAS score was 89, with an interquartile spacing of 89 (80, 90) and a range of scores from 45 to 100.
Table 2.
Distribution of the composition of the levels of each of the five dimensions in patients [n (%), n = 512].
| Dimension | No problem | Mild problem | Serious problem |
|---|---|---|---|
| Mobility | 459(89.6) | 50(9.8) | 3(0.6) |
| Self-care | 489(95.5) | 18(3.5) | 5(1.0) |
| Usual activities | 471(92.0) | 36(7.0) | 5(1.0) |
| Pain/discomfort | 435(85.0) | 74(14.5) | 3(0.6) |
| Anxiety/depression | 481(93.9) | 30(5.9) | 1(0.2) |
Univariate analysis of the five dimensions of pregnant and postpartum women with SARS-CoV-2 infection
Of the five dimensions, mobility, self-care, usual activities, and pain/discomfort primarily reflect physical health, and anxiety/depression reflect mental health. In the mobility dimension, the proportion of patients affected was higher in the third trimester, with college education, in the epidemic stage 1 at the time of admission, and with antibiotic use and oxygen therapy than in the other groups (all P < 0.05). In terms of self-care, the proportion of patients affected by a pre-pregnancy BMI classification of underweight and the occurrence of severe infections was higher than in the other groups (all P < 0.05). In terms of usual activities, the proportion of patients affected was higher in the 2 weeks postpartum period and in those who developed severe infections than in the other groups (all P < 0.05). In the pain/discomfort dimension, the proportion of patients affected by the occurrence of severe infections and fever was higher than in the other groups (all P < 0.05), and in the anxiety/depression dimension, the proportion of patients with problems was higher than in the other groups for patients with an annual family income of < 100,000 RMB and the occurrence of severe infections (all P < 0.05). The results are shown in Table 3.
Table 3.
Percentage of reported any problem in 5dimensions of EQ-5D.
| Variant | Mobility | Self-care | Usual activities | Pain/discomfort | Anxiety/depression | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| n (%) | P value | n (%) | P value | n (%) | P value | n (%) | P value | n (%) | P value | |
| Advanced maternal age (age ≥ 35) | ||||||||||
| Yes | 8(10.5) | 0.957 | 1(1.3) | 0.251 | 6(7.9) | 0.969 | 8(10.5) | 0.233 | 2(2.6) | 0.273 |
| No | 45(10.3) | 22(5.0) | 35(8.0) | 69(15.8) | 29(6.7) | |||||
| Maternal state | ||||||||||
| Non-third trimester | 1(0.8) | < 0.01 | 2(1.5) | 0.089△ | 4(3.0) | 0.046 | 22(16.7) | 0.738 | 9(6.8) | 0.813△ |
| Third trimester | 51(14.0) | 20(5.5) | 35(9.6) | 52(14.3) | 21(5.8) | |||||
| Postpartum women | 1(6.3) | 1(6.3) | 2(12.5) | 3(18.8) | 1(6.3) | |||||
| Pre-pregnancy BMI | ||||||||||
| Underweight | 10(15.6) | 0.317 | 6(9.4) | 0.040 △ | 7(10.9) | 0.531 | 9(14.1) | 0.367 | 6(9.4) | 0.680△ |
| Normal | 34(10.4) | 9(2.8) | 22(6.7) | 46(14.1) | 19(5.8) | |||||
| Overweight | 8(8.3) | 7(7.3) | 10(10.4) | 15(15.6) | 5(5.2) | |||||
| Obese | 1(3.8) | 1(3.8) | 2(7.7) | 7(26.9) | 1(3.8) | |||||
| Education | ||||||||||
| Senior middle school and below | 6(4.3) | 0.005 | 2(1.4) | 0.107 | 8(5.7) | 0.437 | 18(12.8) | 0.575 | 7(5.0) | 0.687 |
| College | 23(16.0) | 9(6.3) | 14(9.7) | 21(14.6) | 8(5.6) | |||||
| University and above | 24(10.6) | 12(5.3) | 19(8.4) | 38(16.7) | 31(6.1) | |||||
| Family income (RMB) | ||||||||||
| <100,000 | 4(5.8) | 0.182 | 2(2.9) | 0.708 | 4(5.8) | 0.467 | 6(8.7) | 0.113 | 9(13.0) | 0.019 |
| ≥100,000 | 49(11.1) | 21(4.5) | 37(8.4) | 71(16.0) | 22(5.0) | |||||
| Vaccination history | ||||||||||
| Yes | 33(9.6) | 0.439 | 15(4.4) | 0.853 | 25(7.3) | 0.393 | 50(14.6) | 0.677 | 23(6.7) | 0.379 |
| No | 20(11.8) | 8(4.7) | 16(9.5) | 27(16.0) | 8(4.7) | |||||
| Stages of the epidemic | ||||||||||
| 1 | 30(21.7) | < 0.01 | 7(5.1) | 0.802 | 13(9.4) | 0.604 | 17(12.3) | 0.365 | 10(7.2) | 0.619 |
| 2 | 10(5.4) | 9(4.9) | 12(6.5) | 33(17.8) | 12(6.5) | |||||
| 3 | 13(6.9) | 7(3.7) | 16(8.5) | 27(14.3) | 9(4.8) | |||||
| Number of ILI symptoms in the past year | ||||||||||
| 0 | 42(12.1) | 0.055 | 19(5.5) | 0.115 | 30(8.7) | 0.425 | 52(15.0) | 0.993 | 22(6.4) | 0.677 |
| ≥1 | 11(6.6) | 4(2.4) | 11(6.6) | 25(15.1) | 9(5.4) | |||||
| Severe infection | ||||||||||
| Yes | 8(11.4) | 0.750 | 7(10.0) | 0.037 | 12(17.1) | 0.002 | 20(28.6) | 0.001 | 11(15.7) | 0.001 |
| No | 45(10.2) | 16(3.6) | 29(6.6) | 57(12.9) | 20(4.5) | |||||
| Fever | ||||||||||
| Yes | 43(10.0) | 0.521 | 22(5.1) | 0.211 | 37(8.6) | 0.267 | 73(16.9) | 0.006 | 30(7.0) | 0.084 |
| No | 10(12.3) | 1(1.2) | 4(4.9) | 4(4.9) | 1(1.2) | |||||
| Antibiotics used | ||||||||||
| Yes | 37(13.6) | 0.010 | 16(5.5) | 0.106 | 26(9.6) | 0.169 | 44(16.2) | 0.443 | 18(6.6) | 0.570 |
| No | 16(6.7) | 7(2.9) | 15(6.3) | 33(13.8) | 13(5.4) | |||||
| Oxygen therapy | ||||||||||
| Yes | 34(13.4) | 0.025 | 11(4.3) | 0.861 | 20(7.9) | 0.912 | 37(14.6) | 0.767 | 12(4.7) | 0.210 |
| No | 19(7.4) | 12(4.7) | 21(8.1) | 40(15.5) | 19(7.4) | |||||
p-values obtained from the one-way χ² test.△p values is the probability of Fisher’s exact test.
Multifactorial analysis of the five dimensions of pregnant and postpartum women with SARS-CoV-2 infection
Variables with P < 0.10 from the results of the univariate analysis were entered into a binary logistic regression equation for multivariate analysis, with the presence or absence of the five dimensions results as the dependent variable (0 = without impact, 1 = with impact). The results are shown in Table 4.
Table 4.
Multifactorial analysis of five dimensions of quality of life in hospitalized pregnant and postpartum patients.
| Dimensions of EQ-5D | Influence factors (reference group) | B | SE | P value | Odds ratio | 95%CI |
|---|---|---|---|---|---|---|
| Mobility | Maternal state(Non-third trimester) | |||||
| Third trimester | 2.780 | 1.028 | 0.007 | 16.119 | (2.149–120.924.149.924) | |
| Postpartum women | 2.028 | 1.467 | 0.167 | 7.602 | (0.429–134.786.429.786) | |
| Education(Senior middle school and below) | ||||||
| College | 1.018 | 0.498 | 0.041 | 2.767 | (1.043–7.343) | |
| University and above | 0.919 | 0.490 | 0.061 | 2.508 | (0.960–6.553) | |
| Stages of the epidemic(3) | ||||||
| 1 | 1.226 | 0.407 | 0.003 | 3.407 | (1.533–7.572) | |
| 2 | −0.357 | 0.451 | 0.429 | 0.700 | (0.289–1.694) | |
| Number of ILI symptoms in the past year(≥ 1) | ||||||
| 0 | 0.205 | 0.393 | 0.602 | 1.227 | (0.568–2.650) | |
| Antibiotics used(No) | ||||||
| Yes | 1.014 | 0.341 | 0.003 | 2.756 | (1.412–5.380) | |
| Oxygen therapy(No) | ||||||
| Yes | 0.032 | 0.337 | 0.924 | 1.033 | (0.533–2.000.533.000) | |
| Self-care | Maternal state(Non-third trimester) | |||||
| Third trimester | 1.441 | 0.759 | 0.058 | 4.224 | (0.954–18.715) | |
| Postpartum women | 1.983 | 1.286 | 0.123 | 7.263 | (0.584–90.264) | |
| Pre-pregnancy BMI(Normal) | ||||||
| Underweight | 1.257 | 0.557 | 0.024 | 3.515 | (1.180–10.469.180.469) | |
| Overweight | 0.936 | 0.526 | 0.075 | 2.549 | (0.908–7.151) | |
| Obese | 0.099 | 1.084 | 0.927 | 1.105 | (0.132–9.244) | |
| Severe infection(No) | ||||||
| Yes | 1.092 | 0.490 | 0.026 | 2.980 | (1.140–7.794) | |
| Usual activities | Maternal state(Non-third trimester) | |||||
| Third trimester | 1.305 | 0.543 | 0.016 | 3.688 | (1.273–10.690) | |
| Postpartum women | 1.834 | 0.923 | 0.047 | 6.257 | (1.024–38.212) | |
| Severe infection(No) | ||||||
| Yes | 1.196 | 0.381 | 0.002 | 3.307 | (1.569–6.971) | |
| Pain/discomfort | Severe infection(No) | |||||
| Yes | 0.962 | 0.303 | 0.002 | 2.617 | (1.445–4.740) | |
| Fever(No) | ||||||
| Yes | 1.331 | 0.531 | 0.012 | 3.783 | (1.336–10.709) | |
| Anxiety/depression | Family income(≥ 100,000 RNB) | |||||
| <100,000 RNB | 1.274 | 0.441 | 0.004 | 3.576 | (1.508–8.482) | |
| Severe infection(No) | ||||||
| Yes | 1.506 | 0.418 | < 0.01 | 4.507 | (1.988–10.220) | |
| Fever(No) | ||||||
| Yes | 1.800 | 1.036 | 0.082 | 6.051 | (0.794–46.109) | |
This study found that severe infection is an independent risk factor for significant decreases in multiple dimensions of patients’ quality of life, affecting both the physical dimension and the psychological dimension. Severe infections were a risk factor for the self-care dimension (OR = 2.980,95%CI: 1.140–7.794), the usual activities dimension (OR = 3.307,95%CI: 1.569–6.971), the pain/discomfort dimension (OR = 2.617,95%CI: 1.445–4.740), and the anxiety/depression dimension (OR = 4.507,95%CI: 1.988–10.220). Notably, the risk of severe anxiety or depressive symptoms in patients with severe infection was 4.507 times that of patients in the non-severe infection group.
Risk factors affecting the mobility dimension include the third trimester (OR = 16.119,95%CI: 2.149–120.924.149.924), being in the developmental stage of an epidemic 1 (OR = 3.407,95%CI: 1.533–7.572), college education (OR = 2.767,95%CI: 1.043–7.343), and antibiotic use (OR = 2.756,95%CI: 1.412–5.380). Among these groups, the wide 95% CI in the third-trimester pregnancy group indicates that the results are imprecise. A potential reason for this is the insufficient sample size, with only 16 participants in the postpartum group. Patients with a pre-pregnancy BMI of underweight had a 3.515 times greater risk of compromised self-care dimensions than patients with a BMI in the normal range. Risk factors affecting the usual activities dimension include the 2 weeks postpartum period (OR = 6.257,95% CI: 1.024–38.212) and the third trimester (OR = 3.688,95% CI: 1.273–10.690). Patients with fever were 3.783 times more likely to be affected in the pain/discomfort dimension than patients without fever. Patients with an annual family income < 100,000 RMB had a 3.576 times greater risk of being affected in the anxiety/depression dimension than patients with an annual family income ≥ 100,000 RMB per year.
Analysis of VAS in hospitalized pregnant and postpartum women with SARS-CoV-2 infection
Regression analysis of VAS scores at 25%, 50% and 75% quartiles was performed with age group, maternal state, pre-pregnancy BMI, education, family income, stage of development of the epidemic, number of ILI symptoms in the past year, severe infections, fever, use of antibiotics, and oxygen therapy as independent variables and VAS scores as dependent variables. The results are shown in Table 5.
Table 5.
Quartile regression analysis of VAS values.
| Influence factors (reference group) | 25th percentile of VAS scores | 50th percentile of VAS scores | 75th percentile of VAS scores | |||
|---|---|---|---|---|---|---|
| β(95% CI) | P-Value | β(95% CI) | P-Value | β(95% CI) | P-Value | |
| Advanced maternal age (age ≥ 35)(No) | ||||||
| Yes | −0.500(−5.271 ~ 4.271) | 0.837 | 0.000(−1.688 ~ 1.688) | > 0.99 | 0.000(−2.272 ~ 2.272) | > 0.99 |
| Maternal state(Non-third trimester) | ||||||
| Third trimester | 0.000(−4.137 ~ 4.137) | > 0.99 | 0.000(−1.464 ~ 1.464) | > 0.99 | 0.000(−1.970 ~ 1.970) | > 0.99 |
| Postpartum women | −4.500(−14.617 ~ 5.617) | 0.383 | −1.000(−4.580 ~ 2.580) | 0.583 | 0.000(−4.818 ~ 4.818) | > 0.99 |
| Pre-pregnancy BMI(Normal) | ||||||
| Underweight | −2.500(−7.707 ~ 2.707) | 0.346 | 0.000(−1.842 ~ 1.842) | > 0.99 | 0.000(−2.479 ~ 2.479) | > 0.99 |
| Overweight | 2.500(−1.888 ~ 6.888) | 0.264 | 0.000(−1.553 ~ 1.553) | > 0.99 | 0.000(−2.090 ~ 2.090) | > 0.99 |
| Obese | −3.000(−10.768 ~ 4.768) | 0.448 | 0.000(−2.749 ~ 2.749) | > 0.99 | 0.000(−3.699 ~ 3.699) | > 0.99 |
| Education(Senior middle school and below) | ||||||
| College | −2.000(−6.689 ~ 2.689) | 0.402 | 0.000(−1.659 ~ 1.659) | > 0.99 | 0.000(−2.233 ~ 2.233) | > 0.99 |
| University and above | −4.500(−8.926~−0.074) | 0.046 | 0.000(−1.566 ~ 1.566) | > 0.99 | 0.000(−2.107 ~ 2.107) | > 0.99 |
| Family income(≥ 100,000 RNB) | ||||||
| <100,000 RNB | 0.000(−5.237 ~ 5.237) | > 0.99 | 0.000(−1.853 ~ 1.853) | > 0.99 | 0.000(−2.494 ~ 2.494) | > 0.99 |
| Vaccination history(No) | ||||||
| Yes | 2.500(−1.075 ~ 6.075) | 0.170 | 0.000(−1.265 ~ 1.265) | > 0.99 | 0.000(−1.702 ~ 1.702) | |
| Stages of the epidemic(3) | ||||||
| 1 | −2.000(−6.588 ~ 2.588) | 0.392 | −3.000(−4.624~−1.376) | < 0.01 | 0.000(−2.185 ~ 2.185) | > 0.99 |
| 2 | 2.000(−1.989 ~ 5.989) | 0.325 | 0.000(−1.412 ~ 1.412) | > 0.99 | 0.000(−1.900 ~ 1.900) | > 0.99 |
| Number of ILI symptoms in the past year(≥ 1) | ||||||
| 0 | 2.000(−1.714 ~ 5.714) | 0.291 | 0.000(−1.314 ~ 1.314) | > 0.99 | 0.000(−1.769 ~ 1.769) | > 0.99 |
| Severe infection(No) | ||||||
| Yes | −10.000(−15.000~−5.000) | < 0.01 | −10.000(−11.769~−8.231) | < 0.01 | 0.000(−2.381 ~ 2.381) | > 0.99 |
| Fever(No) | ||||||
| Yes | −1.500(−6.129 ~ 3.129) | 0.525 | 0.000(−1.638 ~ 1.638) | > 0.99 | 0.000(−2.204 ~ 2.204) | > 0.99 |
| Antibiotics used(No) | ||||||
| Yes | 2.000(−1.405 ~ 5.405) | 0.249 | 0.000(−1.205 ~ 1.205) | > 0.99 | 0.000(−1.621 ~ 1.621) | > 0.99 |
| Oxygen therapy(No) | ||||||
| Yes | 1.500(−2.115 ~ 5.115) | 0.415 | 0.000(−1.279 ~ 1.279) | > 0.99 | 0.000(−1.721 ~ 1.721) | > 0.99 |
The results showed that among patients with lower VAS scores (at the 25th percentile), those with a university and above education had lower VAS scores than those with a senior middle school and below. Patients with severe infections had lower VAS scores than those without severe infections, and the magnitude of this effect was greater than its effect on the median VAS score. Among patients with moderate VAS scores (at the median), those in stage 1 of the epidemic development and those with severe infections had lower VAS scores relative to the other groups. All P < 0.05.
Discussion
Quality of life status of hospitalized pregnant and postpartum women with SARS-CoV-2 infection
In this study the population of pregnant women with SARS-CoV-2 infection had problems mainly in the dimensions of pain/discomfort and mobility, this is consistent with the results of a study by Ping W et al.10 on health-related quality of life of Chinese residents during the COVID-19 pandemic using the EQ-5D. Pregnant patients may be experiencing pain or discomfort due to symptoms of acute upper respiratory tract infections produced by SARS-CoV-2 infection, which, although not a severe illness, has a sudden onset and produces symptoms such as fever, sore throat, runny nose, headache, and muscle aches and pains that can reduce quality of life11.In addition, pregnancy itself can exacerbate the discomfort. Studies have shown that after a woman becomes pregnant, a series of physical discomforts such as loss of appetite, edema of the hands and feet, and constipation can persist throughout the pregnancy12, and these factors are associated with a reduction in the quality of life of pregnant patients.
Attention to the health of pregnant women in the third trimester
Pregnant women in the third trimester are 16.119 and 3.688 times more likely than non-third trimester to have their mobility and usual activities dimensions affected. Although this conclusion may be imprecise due to the influence of the postpartum subgroup, a study by Boutib A et al.13 on the quality of life of pregnant women in different trimesters showed that pregnancy reduces the quality of life of pregnant women even in the case of a normal pregnancy, and that the lowest scores were found in the third trimester. The results of a study showed that the slowed movement and limited mobility of pregnant women in the third trimester may be associated with their poor quality of life in the physiological dimensions14, and that pregnant women in the third trimester and perinatal women are the high-risk groups for severe/critical forms of the novel SARS-CoV-2 infection diagnostic and treatment program, so we should pay attention to the health of the patients in the third trimester, and take care of this group of patients in the diagnostic and treatment process.
Disease severity is a major influence on the quality of life of hospitalized pregnant and postpartum women patients
The results of this study show that severe infection affects the quality of life of pregnant and postpartum patients to a certain extent during their hospitalization. It is not only a risk factor for physical dimensions such as self-care, usual activities, and pain/discomfort, but also for psychological dimensions, as well as for the middle (50%) and low (25%) quartile VAS scores. The study by Rosa RG et al.15 who also showed that the one-year quality of life of patients with SARS-CoV-2 requiring mechanical ventilation during hospitalization was lower than that of patients with SARS-CoV-2 who did not require mechanical ventilation during hospitalization. This illustrates how the severity of the disease not only affects the quality of life during hospitalization, but also has a longer-term effect on the quality of life at discharge. Maternal is a risk group for severe acute respiratory infections16, which makes it particularly important for the prevention of severe illness after SARS-CoV-2 infection in pregnant and postpartum women. Antiviral drugs have a certain preventive effect on the severe disease17,18, but at this stage, there are very few antiviral varieties of COVID-19 applicable to pregnant women19.In the 512 hospitalized cases studied in this paper, the number of people who used antivirals was less than 1.0%, so it is worthy of high attention and further in-depth research on the prevention and treatment of severe disease in pregnant women after SARS-CoV-2 infections.
First-time infection is associated with a reduction in the quality of life of hospitalized pregnant and postpartum women patients
After China enacted the optimized twenty measures for the prevention and control of the COVID-19 epidemic in November 2022, the epidemic experienced three major waves of rebound20, during which the prevalent strains were all Omicron strains and there was no significant change in viral virulence21.The “dynamic zero-COVID” prevention and control policy was implemented until November 2022, all patients included in this study during the first wave of the epidemic were experiencing their first infection. The number of repeat infections among patients in the 2 waves of the rebound epidemic cannot be accurately determined due to the presence of asymptomatic infections, but according to the national surveillance information on SARS-CoV-2 infections, the weekly positivity rate for SARS-CoV-2 viruses in sentinel hospitals in the country peaked during weeks 51 and 52 of 2022 (i.e., from December 19, 2022, to January 1, 2023), which were 60.1% and 60.2%, respectively22.Therefore, it can be determined that in the latter 2 waves of the rebound epidemic, the proportion of repeat infections has been increasing. The quality of life was more significantly affected in those whose hospitalization was in the first wave of the epidemic, with first infection as a risk factor for the mobility dimension and the 50% quartile of the VAS score. The Ministry of Health in Qatar found that initial infection was better at preventing re-infection and re-infection with severe disease by analyzing the data, and it was estimated that the efficiency of initial infection in preventing re-infection with the Omicron (B.1.1.529) variant was 56.0%, and the efficiency of preventing severe disease was 87.8% (Omicron)23. Studies have shown that individuals infected with SARS-CoV-2 develop protective antibodies within 2 weeks, which reach a peak at 3–4 weeks, and this immune response can persist for up to one year after infection24. Due to pre-existing immune memory, reinfection may present with milder clinical manifestations and better pregnancy outcomes25. It was therefore inferred that the quality of life of patients hospitalized for the first infection was significantly affected in relation to the severity of symptoms. Changes in virulence of the virus and changes in herd immunity in the future development of the epidemic are key factors influencing the severity of the disease, as well as the quality of life of the maternal population after infection in the future.
Focus on pregnant and postpartum women’s mental health in SARS-CoV-2 infection
Previous studies of the SARS epidemic have shown that pregnant women are more prone to anxiety than non-pregnant women26, which may be due to the stress of the disease itself on the patient and her family, plus the pregnancy factor and the possible fear of adverse effects of the disease and the medication on the fetus. Nguyen et al.27 of also reported similar results. They found that patients infected with the SARS-CoV-2 infection were more likely to suffer from depression than those who were not infected with the SARS-CoV-2 infection (3.69 vs. 1). The causes of anxiety in pregnant women may also be related to stress during pregnancy, 2020 ESTEBSARI et al.28 showed that women are susceptible to stress during pregnancy and develop mental health problems affecting quality of life scores. In this study, indicators affecting psychological dimensions, besides disease severity, low annual family income was also a risk factor, and financial stress at the time of seeking medical care for pregnant and postpartum women with SARS-CoV-2 infection population also needs to be attended to. Lagadec et al.29 showed in a systematic evaluation that the absence of family financial problems improved the quality of life of pregnant women to some extent. Naghizadeh S et al.30 also reported similar results, there was a significant relationship between economic status and quality of life of pregnant women, and the quality of life of pregnant women with moderate family economic status was better than that of pregnant women with poor family economic status. We therefore recommend that a further assessment of the financial burden of hospitalized patients with SARS-CoV-2 infection should be carried out, and that health insurance policies should be tilted, where necessary, towards risk groups such as pregnant and postpartum women. For example, on the premise of ensuring “all eligible low-income rural populations are covered by social security”, the economic and psychological burdens are alleviated through the superposition of the three-pillar security system.
Innovation and limitations
Due to the shortcomings of the existing monitoring system in terms of monitoring population coverage and pregnancy status data collection, the representativeness of the monitored population is limited. As a key protected group, pregnant women possess extremely valuable data related to SARS-CoV-2 infection. In addition, HRQoL assessments are mostly used to explore the impacts of chronic diseases, while research on the impact of SARS-CoV-2 infection—an acute upper respiratory tract infection—on patients’ quality of life remains insufficient. Relying on the previously established “Population-Based Active Surveillance Platform for Acute Respiratory Tract Infections in Pregnant and Postpartum Women”, this study analyzes and explores the current status of quality of life and its influencing factors among all hospitalized pregnant and postpartum women with SARS-CoV-2 infection in Suzhou from 2020 to 2024, thereby providing a basis for better guiding the health management of pregnant and postpartum women with SARS-CoV-2 infection.
There are some limitations to this paper. Considering the comparability with the previous cases of pregnant and postpartum women acute respiratory monitoring, the EQ-5D-3 L scale was used in this study. This scale results in most patients clustering in the high-score range, failing to effectively distinguish subtle differences among them, which may lead to a certain “ceiling effect”. In contrast, the more detailed EQ-5D-5 L scale expands the number of levels in each dimension from 3 to 5, significantly enhancing the ability to differentiate mild to moderate health problems and greatly improving the sensitivity to subtle changes in health status. The design of this study is cross-sectional, lacking baseline data on quality of life or data from a control group, and no follow-up study has been conducted on the quality of life of pregnant and postpartum women with SARS-CoV-2 infection after discharge. The data for this study come from Suzhou City, Jiangsu Province, China, where the main city, as an economically developed mega-city with a resident population of 130,000, is under-represented for areas of different economic levels. Future studies will consider using the EQ-5D-5 L scale and follow-up after discharge will also be added to explore the long-term impact of SARS-CoV-2 infection on the quality of life of pregnant and postpartum women.
Conclusion
During the hospitalization of patients with SARS-CoV-2 infection, indicators of physical and psychological dimensions related to quality of life were affected to some extent, and as the epidemic progressed, the proportion of re-infected persons increased, and the impact on VAS scores decreased. Special attention should be paid to the fact that during the period of hospitalization, the indicators of psychological dimensions are influenced by the economic level of the family, in addition to the severity of the disease. Therefore, for this group of patients, follow-up investigations should be strengthened, and appropriate medications and other means of rehabilitation should be used to promote better recovery of their health; at the same time, the missionary work for patients should be increased, and more measures should be taken for patients to ventilate their negative emotions. In this way, we can help patients recover their physical and mental health more comprehensively and improve their quality of life as much as possible.
Acknowledgements
We would like to thank all the contributing participants and the resources provided directly or indirectly by Nanjing Medical University and Suzhou Center for Disease Control and Prevention.
Author contributions
Wanting Hong: Investigation, Methodology, Writing –original draft, Writing –review & editing; Ningning Du: Investigation, Writing –review & editing; Yuanyuan Zhang: Investigation, Writing –review & editing; Jiarun Jiang: Investigation, Jinghui Sun: Investigation, Rui Wang: Investigation, Liling Chen: Conceptualization, Funding acquisition, Writing –review & editing.
Funding
This work was supported by the Cooperative Agreement Number, 5U01P001106, funded by the United States Center for Disease Control and Prevention; The 27th Batch of Science and Technology Development Plan (Social Development Science and Technology Innovation) of Suzhou in 2022 (2022SS14), and; The 28th Batch of Suzhou Science and Technology Development Plan Project in 2024 (SYW2024143).
Data availability
All research data collected as part of this project is owned by Suzhou CDC. The datasets could be shared and available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Informed consent was obtained from the patient in all our studies. This study followed the tenets of Declaration of Helsinki and was approved by Suzhou Center for Disease Control and Prevention Institutional Review Board (Approval number: SZJK2020-002).
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All research data collected as part of this project is owned by Suzhou CDC. The datasets could be shared and available from the corresponding author on reasonable request.