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The COVID-19 pandemic has resulted in changes to normal life and disrupted social and economic function worldwide. However, little is known about the impact of social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women during the COVID-19 pandemic.
This study aims to assess the association between social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women in the early stage of the COVID-19 pandemic in China.
In this prospective cohort study, 456 singleton pregnant women in mainland China were recruited during January and February 2020. Sociodemographic characteristics, history of previous health, social media use, and current lifestyles were collected at baseline, and we followed up about the occurrence of miscarriage. Log-binomial regression models were used to estimate the risk ratios (RRs) of miscarriage for women with different exposures to COVID-19–specific information.
Among all the 456 pregnant women, there were 82 (18.0%) who did no physical activities, 82 (18.0%) with inadequate dietary diversity, 174 (38.2%) with poor sleep quality, and 54 (11.8%) spending >3 hours on reading COVID-19 news per day. Women with excessive media use (>3 hours) were more likely to be previously pregnant (
Pregnant women with excessive media use were more likely to have no physical activity, inadequate dietary diversity, and poor sleep quality. Excessive media use and poor sleep quality were associated with a higher risk of miscarriage. Our findings highlight the importance of healthy lifestyles during the COVID-19 pandemic.
The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has resulted in changes to normal life and has disrupted social and economic functions worldwide. It was reported that there were 52,487,476 confirmed cases and 1,290,653 deaths as of November 13, 2020 [
Along with the transmission of SARS-CoV-2, the information related with COVID-19 was also spread rapidly. One of the most accessible and fastest platforms for broadcasting information is social media. It represents a conglomerate of electronic platforms used for creating and sharing information, ideas, messages, etc [
Miscarriage is a common adverse pregnancy outcome and one of the major public health problems. Miscarriage refers to a spontaneous demise of pregnancy before the fetus reaches viability [
This was a prospective cohort study conducted in a tertiary maternal and child health hospital in Beijing, China. The hospital was responsible for the prenatal care of all pregnant women living in Tongzhou district of Beijing. The primary aim of this cohort study is to investigate the short- and long-term health effects of prenatal exposures (eg, poor sleep quality) on mothers and their children. Baseline recruitment was conducted in January and February 2020, and pregnant women who visited the outpatient clinic for the first prenatal examination at Tongzhou Maternal and Child Health Hospital were recruited when they met the following inclusion criteria: <14 gestational weeks, singleton pregnancy, plan to have antenatal care and delivery in Tongzhou Maternal and Child Health Hospital, and resided in Tongzhou during the past half year and have no plan to move out after delivery. The study was approved by the institutional review boards at Peking University (IRB00001052–18003), and all participants gave written informed consent at the enrollment.
Baseline information was collected at the first prenatal visit by trained medical workers through a standardized questionnaire, such as sociodemographic characteristics (age, educational level, region, and family income), history of previous health (cesarean section, preterm birth, miscarriage, and fist pregnancy or not), prepregnancy weight, smoking status, physical activities, dietary diversity, and sleep quality. There were 504 pregnant women that met the inclusion criteria and were recruited at baseline. By August 2020, 11 women moved out of Tongzhou, 27 women were lost to follow-up, and 10 women transferred to other hospitals. Finally, the remaining 456 participants were included in this study.
We collected the information on media use about COVID-19 by the following question: “How long did you spent on reading COVID-19 news every day from social media (official or unofficial)?” Participants were divided into five COVID-19–specific information exposure groups (<0.5 hours, 0.5 hours-1 hour, 1 hour-2 hours, 2-3 hours, and >3 hours) by their answers regarding the time spent on reading COVID-19 news. Because of the similar prevalence of miscarriage in the 0.5 hours-1 hour and 1 hour-2 hours groups in this study, we combined the two groups into one (0.5-2 hours) group as the reference group in the final analysis.
The follow-up of the pregnancy outcomes was conducted by local medical workers. Pregnant women took regular antenatal care and delivered in the hospital. The information on pregnancy outcomes was obtained though the medical electronic information system in the hospital, which automatically recorded information during each antenatal care and delivery. Miscarriage is defined as a pregnancy loss that occurs before 20 completed weeks of gestational age [
Covariates were collected at the first prenatal visit, including age, educational level, region, family income, history of cesarean section, history of preterm birth, history of miscarriage, gravidity, prepregnancy weight, smoking status, physical activities, dietary diversity, and sleep quality. Prepregnancy BMI was calculated using weight (in kilograms) divided by the square of height (in meters). We assessed dietary diversity using nine food groups, as reported in previous studies [
Mean (SD) values and proportions of baseline characteristics were calculated. We calculated the mean (SD) for age. We used proportions to describe baseline characteristics of pregnant women, such as age group, region, and educational levels, and the chi-square test or Fisher exact probability test was used to compare the distributions of baseline characteristics according to time spent on reading COVID-19 news. Prevalence of miscarriage and its 95% CI was calculated. Miscarriage prevalence in women with different characteristics were also compared using chi-square test or Fisher exact probability test.
Multivariable log-binomial regression models were used to estimate the adjusted risk ratios (RRs) and their 95% CIs of miscarriage for women with different exposures of COVID-19–specific information. Women were divided into four exposure groups (<0.5 hours, 0.5-2 hours, 2-3 hours, and >3 hours) by their answers regarding the time spent on reading COVID-19 news. Women who spent 0.5-2 hours on reading COVID-19 news per day were set as the reference group in the final analysis. In the multivariable model, we additionally adjusted for other potential risk factors, including age group (<35 years or ≥35 years), educational level (high school or below, or college or above), region (rural or urban), family income (<¥5000 [US $764], ¥5000-¥10,000 [US $764-$1528], or >¥10,000 [US $1528]), history of cesarean section (no or yes), history of preterm birth (no or yes), history of miscarriage (no or yes), first pregnancy (no or yes), prepregnancy BMI (underweight, normal weight, overweight, or obese), smoking (nonsmoker, previous smoker, or current smoker), physical activities (never, sometimes, usually, or every day), inadequate dietary diversity (no or yes), and poor sleep quality (no or yes) by backward methods. To examine the robustness of our findings, we did sensitivity analyses by adjusted covariates in the multivariable models as continuous variables for several variables (age and DDS), instead of categorical variables. In the subgroup analysis, we divided women into different subgroups by baseline characteristics (region, age group, and history of miscarriage). Among these baseline subgroups, we examined the associations between time spent on reading COVID-19 news and the risk of miscarriage after adjusting for other potential risk factors. All the analyses were done with SAS software, version 9.4 (SAS Institute). Two-sided
Among all the 456 pregnant women included, 84.2% (n=384) were younger than 35 years, 54.4% (n=248) were living in an urban area, 9.2% (n=42) had a history of miscarriage, 56.6% (n=258) were having their first pregnancy, 28.1% (n=128) were overweight or obese, 7.9% (n=36) were a previous or current smoker, 18.0% (n=82) did no physical activity, 18.0% (n=82) had inadequate dietary diversity, and 38.2% (n=174) had poor sleep quality. The mean age at baseline was 30.0 (SD 4.2) years.
The mean time spent on reading COVID-19 news was 1.8 (SD 0.9) hours per day. Of the 456 pregnant women, only 23 (5.0%) spent less than 0.5 hours on reading COVID-19 news per day, whereas 247 (54.2%) women spent 0.5-2 hours and 54 (11.8%) women spent >3 hours on reading COVID-19 news per day. Women with excessive media use (>3 hours) were more likely to be previously pregnant (
Baseline characteristics of pregnant women by time spent on reading COVID-19 news.
Characteristics | Total (N=456) | Time spent on reading COVID-19 news (hours), n (%) | |||||
|
|
<0.5 (n=23) | 0.5-2 (n=247) | 2-3 (n=132) | >3 (n=54) |
|
|
|
.65 | ||||||
|
<35 | 384 (84.2) | 19 (82.6) | 211 (85.4) | 107 (81.1) | 47 (87.0) |
|
|
≥35 | 72 (15.8) | 4 (17.4) | 36 (14.6) | 25 (18.9) | 7 (13.0) |
|
|
.29 | ||||||
|
High school or below | 88 (19.3) | 40 (16.2) | 5 (21.7) | 29 (22.0) | 14 (25.9) |
|
|
College or above | 368 (80.7) | 207 (83.8) | 18 (78.3) | 103 (78.0) | 40 (74.1) |
|
|
.48 | ||||||
|
Rural | 208 (45.6) | 7 (30.4) | 117 (47.4) | 59 (44.7) | 25 (46.3) |
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|
Urban | 248 (54.4) | 16 (69.6) | 130 (52.6) | 73 (55.3) | 29 (53.7) |
|
|
.11 | ||||||
|
<5000 | 76 (16.7) | 2 (8.7) | 47 (19.0) | 17 (12.9) | 10 (18.5) |
|
|
5000-10,000 | 222 (48.7) | 14 (60.9) | 105 (42.5) | 72 (54.5) | 31 (57.4) |
|
|
>10,000 | 158 (34.6) | 7 (30.4) | 95 (38.5) | 43 (32.6) | 13 (24.1) |
|
|
.71 | ||||||
|
No | 394 (86.4) | 18 (78.3) | 215 (87.0) | 114 (86.4) | 47 (87.0) |
|
|
Yes | 62 (13.6) | 5 (21.7) | 32 (13.0) | 18 (13.6) | 7 (13.0) |
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|
.09 | ||||||
|
No | 444 (97.4) | 23 (100.0) | 243 (98.4) | 128 (97.0) | 50 (92.6) |
|
|
Yes | 12 (2.6) | 0 (0.0) | 4 (1.6) | 4 (3.0) | 4 (7.4) |
|
|
.32 | ||||||
|
No | 414 (90.8) | 19 (82.6) | 229 (92.7) | 118 (89.4) | 48 (88.9) |
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|
Yes | 42 (9.2) | 4 (17.4) | 18 (7.3) | 14 (10.6) | 6 (11.1) |
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|
|
||||||
|
No | 198 (43.4) | 8 (34.8) | 99 (40.1) | 58 (43.9) | 33 (61.1) |
|
|
Yes | 258 (56.6) | 15 (65.2) | 148 (59.9) | 74 (56.1) | 21 (38.9) |
|
|
.62 | ||||||
|
Underweight | 58 (12.7) | 4 (17.4) | 34 (13.8) | 13 (9.8) | 7 (13.0) |
|
|
Normal weight | 270 (59.2) | 11 (47.8) | 153 (61.9) | 75 (56.8) | 31 (57.4) |
|
|
Overweight | 82 (18.0) | 6 (26.1) | 36 (14.6) | 28 (21.2) | 12 (22.2) |
|
|
Obese | 46 (10.1) | 2 (8.7) | 24 (9.7) | 16 (12.1) | 4 (7.4) |
|
|
.48 | ||||||
|
Nonsmoker | 420 (92.1) | 23 (100.0) | 226 (91.5) | 121 (91.7) | 50 (92.6) |
|
|
Previous smoker | 32 (7.0) | 0 (0.0) | 17 (6.9) | 11 (8.3) | 4 (7.4) |
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|
Current smoker | 4 (0.9) | 0 (0.0) | 4 (1.6) | 0 (0.0) | 0 (0.0) |
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|
|
||||||
|
Never | 82 (18.0) | 0 (0.0) | 39 (15.8) | 24 (18.2) | 19 (35.2) |
|
|
Sometimes | 230 (50.4) | 10 (43.5) | 124 (50.2) | 73 (55.3) | 23 (42.6) |
|
|
Usually | 124 (27.2) | 10 (43.5) | 73 (29.6) | 31 (23.5) | 10 (18.5) |
|
|
Every day | 20 (4.4) | 3 (13.0) | 11 (4.5) | 4 (3.0) | 2 (3.7) |
|
|
|
||||||
|
No | 374 (82.0) | 21 (91.3) | 209 (84.6) | 107 (81.1) | 37 (68.5) |
|
|
Yes | 82 (18.0) | 2 (8.7) | 38 (15.4) | 25 (18.9) | 17 (31.5) |
|
|
|
||||||
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No | 282 (61.8) | 21 (91.3) | 193 (78.1) | 56 (42.4) | 12 (22.2) |
|
|
Yes | 174 (38.2) | 2 (8.7) | 54 (21.9) | 76 (57.6) | 42 (77.8) |
|
aItalics indicate significant
bDDS: dietary diversity score.
cPSQI: Pittsburgh Sleep Quality Index.
Out of 456 pregnant women, 73 had a miscarriage. The prevalence of miscarriage was 16.0% (95% CI 12.6%-19.4%). Compared with women who spent 0.5-2 hours (25/247, 10.1%) on reading COVID-19 news per day, miscarriage prevalence in women who spent <0.5 hours (5/23, 21.7%), 2-3 hours (26/132, 19.7%), and >3 hours (17/54, 31.5%) were higher (
Comparison of miscarriage prevalence in pregnant women by time spent on reading COVID-19 news.
Prevalence of miscarriage in pregnant women by different baseline characteristics.
Characteristics | Participants, n | Miscarriage prevalence, n (%) | ||
Total | 456 | 73 (16.0) | N/Aa | |
|
.85 | |||
|
<35 | 384 | 62 (16.1) |
|
|
≥35 | 72 | 11 (15.3) |
|
|
.02 | |||
|
High school or below | 88 | 7 (8.0) |
|
|
College or above | 368 | 66 (17.9) |
|
|
.17 | |||
|
Rural | 208 | 28 (13.5) |
|
|
Urban | 248 | 45 (18.1) |
|
|
.06 | |||
|
<5000 | 76 | 7 (9.2) |
|
|
5000-10,000 | 222 | 44 (19.8) |
|
|
>10,000 | 158 | 22 (13.9) |
|
|
.73 | |||
|
No | 394 | 64 (16.2) |
|
|
Yes | 62 | 9 (14.5) |
|
|
.39 | |||
|
No | 444 | 70 (15.8) |
|
|
Yes | 12 | 3 (25.0) |
|
|
.57 | |||
|
No | 414 | 65 (15.7) |
|
|
Yes | 42 | 8 (19.0) |
|
|
.14 | |||
|
No | 198 | 26 (13.1) |
|
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Yes | 258 | 47 (18.2) |
|
|
.13 | |||
|
Underweight | 58 | 4 (6.9) |
|
|
Normal weight | 270 | 51 (18.9) |
|
|
Overweight | 82 | 12 (14.6) |
|
|
Obese | 46 | 6 (13.0) |
|
|
.56 | |||
|
Nonsmoker | 420 | 65 (15.5) |
|
|
Previous smoker | 32 | 7 (21.9) |
|
|
Current smoker | 4 | 1 (25.0) |
|
|
.14 | |||
|
Never | 82 | 19 (23.2) |
|
|
Sometimes | 230 | 30 (13.0) |
|
|
Usually | 124 | 22 (17.7) |
|
|
Every day | 20 | 2 (10.0) |
|
|
.17 | |||
|
No | 374 | 64 (17.1) |
|
|
Yes | 82 | 9 (11.0) |
|
|
.003 | |||
|
No | 282 | 34 (12.1) |
|
|
Yes | 174 | 39 (22.4) |
|
|
<.001 | |||
|
<0.5 | 23 | 5 (21.7) |
|
|
0.5-2 | 247 | 25 (10.1) |
|
|
2-3 | 132 | 26 (19.7) |
|
|
≥3 | 54 | 17 (31.5) |
|
aN/A: not applicable.
bDDS: dietary diversity score.
cPSQI: Pittsburgh Sleep Quality Index.
We observed a U-shape relationship between media use about COVID-19 and the risk of miscarriage (see
The adjusted risk ratios of association between media use about COVID-19 and the risk of miscarriage by a log-binomial regression model. The 0.5-2 hours group was the reference group.
Risk factors related with miscarriage by a log-binomial regression model.
Factors | Participants, n | Miscarriage, n (%) | Multivariable modela | ||
|
|
|
Adjusted RRb (95% CI) | ||
|
|||||
|
<0.5 | 23 | 5 (21.7) | 2.23 (0.97-5.13) | .06 |
|
0.5-2 | 247 | 25 (10.1) | 1 (reference) | N/Ac |
|
2-3 | 132 | 26 (19.7) | 1.74 (1.02-2.97) | .04 |
|
>3 | 54 | 17 (31.5) | 2.56 (1.43-4.59) | .002 |
|
|||||
|
No | 282 | 34 (12.1) | 1 (reference) | N/A |
|
Yes | 174 | 39 (22.4) | 2.06 (1.24-3.44) | .006 |
aIn the multivariable model, we adjusted sociodemographic characteristics (age, educational level, region, and family income), history of previous health (cesarean section, preterm birth, miscarriage, and fist pregnancy), prepregnancy BMI, smoking, physical activities, dietary diversity, and sleep quality. The covariates with
bRR: risk ratio.
cN/A: not applicable.
dPSQI: Pittsburgh Sleep Quality Index.
In the sensitivity analysis, the association between excessive media use about COVID-19 and the risk of miscarriage was stable (see
To our knowledge, this is the first study exploring the status of social media use and lifestyles among pregnant women during the COVID-19 pandemic and assessing their associations with the risk of miscarriage in a prospective cohort study. Our results showed a significant association between excessive media use, unhealthy lifestyle, and the risk of miscarriage in Chinese pregnant women. No previous study has assessed the status of social media use during the COVID-19 pandemic among pregnant women. There were some studies that examined the impact of exposure to COVID-19 information on the metal health status among the nonpregnant population (eg, internet users and factory workers) [
It is worth noting that a U-shape relationship between time spent on reading COVID-19 news per day and the risk of miscarriage was found in our study. The risk of miscarriage was significantly higher in the <0.5 hours media use group among women who lived in urban areas, had a history of miscarriage, and had advanced maternal age, and significantly higher in the >3 hours media use group among women who lived in rural areas, had no history of miscarriage, and were younger. Previous history of miscarriage and advanced maternal age are both risk factors for miscarriage in the literature [
In our study, we found that the mean time spent on reading COVID-19 news was 1.8 hours per day for the pregnant women, which was slightly shorter than the general population (2.4 hours) reported in other studies [
The prospective cohort study design, controlling various risk factors related with miscarriage, and the first insight into the association of social media use with miscarriage are the strengths of this study. However, there are several limitations in this study. First, we did not collect information on the time spent on different kinds of social media (eg, official and unofficial web-based media, newspapers, and magazines) and individual behaviors on COVID-19 prevention. Second, genetic and psychological factors associated with miscarriage were not investigated in this study. The results need to be interpreted with caution. The potential intermediation role of psychological factors on the association between time spent on reading COVID-19 news and miscarriage needs to be explored in further studies. Third, this study was a single-center cohort conducted in China. A multicenter cohort study is needed to verify the findings in this study. Despite these limitations, our findings are helpful to better understand the role of social media and lifestyle on health among pregnant women during the COVID-19 pandemic. The role of media and public health communications needs to be correctly understood and explored further, as they will be an essential tool for delivering information and combating COVID-19 and health promotion, especially for vulnerable populations such as pregnant women.
Pregnant women spent about 2 hours a day reading COVID-19 news in the early stage of the COVID-19 pandemic in China. Pregnant women with excessive media use were more likely to having no physical activity, inadequate dietary diversity, and poor sleep quality. Excessive media use and poor sleep quality were associated with a higher risk of miscarriage. Our findings highlight the importance of healthy lifestyles during the COVID-19 pandemic.
Supplemental Table: Sensitivity analysis on the association between media use about COVID-19 and the risk of miscarriage.
Supplemental Figure: Subgroup analysis of the association between media use about COVID-19 and miscarriage.
dietary diversity score
Pittsburgh Sleep Quality Index
risk ratio
This study was funded by the National Natural Science Foundation of China (grant number 81703240), the National Science and Technology Key Projects on Prevention and Treatment of Major Infectious Diseases of China (grant number 2020ZX10001002), and the National Key Research and Development Project of China (grant number 2019YFC1710301; 2020YFC0846300). We sincerely thank the staff of Tongzhou Maternal and Child Health Hospital for their efforts made in data collection.
This study was designed by XZ, NH, and JL. NH, JY, and JL coordinated the acquisition of data. XZ analyzed the data and drafted the manuscript with input from NH, JY, and JL. NH, JY, and JL reviewed and revised the report. All authors gave approval for the final version of the manuscript.
None declared.