| Literature DB >> 35646987 |
Chongyi Hao1,2,3,4, Feng Jin5, Chanjuan Hao1,2,3,4, Xiaofen Zhang5, Limin Xie5, Yawei Zhang6, Xuanshi Liu1,2,3,4, Xin Ni4,5,7, Wei Li1,2,3,4.
Abstract
Background: People's lifestyles may have changed during the COVID-19 pandemic, which may have a profound impact on pregnant women and newborns. This study aims to assess the effects of the COVID-19 pandemic on uninfected pregnant women and their newborns, including potential environmental factors.Entities:
Keywords: COVID-19; adverse pregnancy outcomes; birth cohort; lifestyle; nested case-control study
Year: 2022 PMID: 35646987 PMCID: PMC9131041 DOI: 10.3389/fmed.2022.842826
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Figure 1Questionnaires, routine tests and biological samples were collected at different time points in the CHALLENGE birth cohort. Six types of questionnaires including baseline information, environmental exposures, physical exercise sleep quality, depression scale, and dietary information were collected. After the baseline information was collected, routine tests were conducted in 5 follow-up visits including three routine prenatal testing at 12–13 weeks, 24–28 weeks and 34–35 weeks, one postpartum checkup, and one postnatal checkup at 42 days after parturition. During these visits, blood pressure, blood tests, urine tests and additional tests such as group B streptococcus infection screening, ultrasound exam, nuchal translucency (NT) scan, and electrocardiogram were conducted. The biological samples were collected as shown at different time points.
Figure 2A flowchart of participant selection and exclusion in this study, China, 2018-2020.
Characteristics of 1,604 pregnant women before and during the COVID-19 pandemic, China, 2018-2020.
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| 32.48 ± 3.85 | 32.40 ± 3.82 | 32.56 ± 3.88 | −0.355 | 0.722 | ||
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| 0.837 | 0.658 | |||||
| Han | 1,500 | 746 | 93.0 | 754 | 94.0 | ||
| Man | 50 | 28 | 3.5 | 22 | 2.7 | ||
| Other | 54 | 28 | 3.5 | 26 | 3.2 | ||
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| 0.36 | 0.548 | |||||
| Junior college degree or below | 850 | 419 | 52.2 | 431 | 53.7 | ||
| Bachelor degree or above | 754 | 383 | 47.8 | 371 | 46.3 | ||
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| 0.012 | 0.914 | |||||
| yes | 1,066 | 532 | 67.1 | 534 | 66.8 | ||
| no | 526 | 261 | 32.9 | 265 | 33.2 | ||
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| 3.442 | 0.064 | |||||
| Employed | 1,360 | 669 | 83.4 | 691 | 86.2 | ||
| Stay-at-home | 235 | 131 | 16.3 | 104 | 13.0 | ||
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| 161.79 ± 5.04 | 161.71 ± 5.00 | 161.86 ± 5.08 | −0.445 | 0.656 | ||
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| 59.20 ± 10.41 | 59.19 ± 10.28 | 59.22 ± 10.54 | −0.117 | 0.907 | ||
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| 22.61 ± 3.79 | 22.63 ± 3.78 | 22.59 ± 3.80 | −0.31 | 0.756 | ||
| Underweight <18.5 | 124 | 52 | 6.6 | 72 | 9.0 | ||
| Normal 18.5–24.9 | 1,107 | 566 | 71.4 | 541 | 67.9 | ||
| Overweight 25–29.9 | 290 | 142 | 17.9 | 148 | 18.6 | ||
| Obese ≥ 30 | 69 | 33 | 4.2 | 36 | 4.5 | ||
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| 5.774 | 0.016 | |||||
| yes | 498 | 226 | 28.5 | 272 | 34.1 | ||
| no | 1,091 | 566 | 71.5 | 525 | 65.9 | ||
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| 33.65 ± 4.41 | 33.50 ± 4.24 | 33.81 ± 4.58 | −0.52 | 0.603 | ||
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| 0.518 | 0.772 | |||||
| Han | 1,500 | 750 | 94.0 | 750 | 93.6 | ||
| Man | 59 | 27 | 3.4 | 32 | 4.0 | ||
| Other | 40 | 21 | 2.6 | 19 | 2.4 | ||
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| 0.248 | 0.618 | |||||
| Junior college degree or below | 901 | 445 | 55.8 | 456 | 57.0 | ||
| Bachelor degree or above | 697 | 353 | 44.2 | 344 | 43.0 | ||
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| 10.946 | 0.010 | |||||
| Employed | 1,316 | 636 | 79.3 | 680 | 84.8 | ||
| Stay-at-home | 233 | 140 | 17.5 | 93 | 11.6 |
P < 0.05.
: Gravidity not included. Missing data: pre-pregnancy education, 12 (0.75%); maternal occupation 9 (0.5%); maternal height, 12 (0.75%); pre-pregnancy weight, 14 (0.87%); pre-pregnancy BMI 14 (0.87%); gravidity 15 (0.94%); spouse age 6 (0.37%); spouse ethnicity 6 (0.37%); spouse education 6 (0.37%); spouse occupation 55 (3.4%).
Pregnancy outcomes before and during the COVID-19 pandemic, China, 2018-2020.
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| Anemia | 374 | 46.6 | 298 | 37.2 | 15.178 | <0.001 | ||
| Vaginitis | 57 | 7.1 | 19 | 2.400 | 21.829 | <0.001 | ||
| Infection | 97 | 12.1 | 117 | 14.6 | 2.192 | 0.139 | ||
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| Gestational diabetes mellitus | 93 | 11.6 | 114 | 14.200 | 2.446 | 0.118 | ||
| Gestational hypertension | 16 | 2.0 | 28 | 3.500 | 3.370 | 0.070 | ||
| Preeclampsia | 27 | 3.4 | 23 | 2.900 | 0.330 | 0.565 | ||
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| Placental and fetal membrane abnormalities | 219 | 27.3 | 213 | 26.600 | 0.155 | 0.694 | ||
| Umbilical cord abnormalities | 198 | 24.7 | 226 | 28.200 | 2.513 | 0.113 | ||
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| Adverse pregnancy outcomes | 172 | 21.4 | 139 | 17.3 | 4.344 | 0.037 | ||
| Preterm birth | 47 | 5.9 | 26 | 3.2 | 6.329 | 0.012 | ||
| Macrosomia | 81 | 10.1 | 73 | 9.1 | 0.460 | 0.498 | ||
| Large for gestational age | 70 | 8.7 | 51 | 6.4 | 3.227 | 0.072 | ||
| Small for gestational age | 27 | 3.4 | 25 | 3.1 | 0.080 | 0.778 | ||
| Fetal death | 1 | 0.1 | 2 | 0.2 | — | — | ||
| Low weight infants | 1 | 0.1 | 5 | 0.6 | — | — | ||
| Congenital anomalies | 20 | 2.5 | 17 | 2.1 | 0.249 | 0.618 | ||
| Fetal distress | 72 | 9.0 | 70 | 8.7 | 0.031 | 0.86 | ||
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| Postpartum hemorrhage | 169 | 21.1 | 213 | 26.6 | 6.652 | 0.010 | ||
| Laceration of cervix during labor | 12 | 1.5 | 22 | 2.7 | 3.005 | 0.083 | ||
| Perineal laceration during delivery unspecified | 322 | 40.1 | 360 | 44.9 | 3.683 | 0.055 | ||
| Shoulder dystocia | 31 | 3.9 | 6 | 0.7 | 17.291 | <0.001 |
P < 0.05;
P < 0.001.
: vaginal candidiasis (pandemic group n = 47, pre-pandemic group n = 12), mycoplasma vaginitis (5 vs. 6), others (5 vs. 1).
: Group B streptococcal infection, mycoplasma infection, intrauterine infection, chorioamnionitis and others.
: Placenta previa (pandemic group n = 5, pre-pandemic group n = 2), Placental abruption (10:10), Premature rupture of membranes (208:206).
: Umbilical cord abnormalities include cord winding, cord torsion, cord true knot, etc.
: Preterm birth is defined as <37 weeks of gestational age at delivery. Macrosomia refers to newborns weighing more than 4,000 g. Large for gestational age (LGA) refers to an infant whose birth weight is above the 90th percentile of the average weight for the same gestational age. Small for gestational age (SGA) refers to an infant whose birth weight falls below the 10th percentile of the average weight for the same gestational age. Low weight infants refer to newborns weighing <2,500 g.
The influence of the COVID-19 pandemic on pregnancy outcomes, China, 2018-2020.
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| Anemia | <0.001 | 1.478 | (1.211–1.804) | <0.001 | 1.474 | (1.200–1.792) | <0.001 | 1.445 | (1.176–1.775) | <0.001 | 1.498 | (1.216–1.846) |
| Vaginitis | <0.001 | 3.153 | (1.858–5.350) | <0.001 | 3.153 | (1.856–5.356) | <0.001 | 3.311 | (1.895–5.785) | <0.001 | 3.294 | (1.878–5.777) |
| Adverse pregnancy outcomes | 0.037 | 1.302 | (1.015–1.670) | 0.035 | 1.310 | (1.019–1.683) | 0.046 | 1.300 | (1.005–1.682) | 0.051 | 1.301 | (0.999–1.695) |
| Postpartum hemorrhage | 0.018 | 0.756 | (0.600–0.953) | 0.020 | 0.758 | (0.600~0.957) | 0.031 | 0.769 | (0.606–0.977) | 0.043 | 0.779 | (0.612–0.992) |
| Shoulder dystocia | <0.001 | 5.334 | (2.213–12.857) | <0.001 | 5.091 | (2.104–12.319) | <0.001 | 5.250 | (2.165–12.732) | <0.001 | 5.117 | (2.098–12.48) |
| Preterm birth | 0.013 | 1.858 | (1.139–3.031) | 0.005 | 2.044 | (1.236–3.382) | 0.007 | 2.071 | (1.225–3.501) | 0.014 | 1.944 | (1.144–3.302) |
Model I: a univariate model without controlling for any confounding factors. Model II: controls for maternal demographic characteristics (maternal age, ethnicity, education and occupation). Model III: based on model II supplemented to control for demographic characteristics of the spouse (age, ethnicity, education and occupation). Model IV: based on model III, supplemented to control for pre-pregnancy BMI, primipara, history of abnormal pregnancy, history of cesarean section.
: based on model IV, supplemented to control for anemia, vaginitis, infection.
Univariate analysis of adverse pregnancy outcomes during pandemic, China, 2018-2020.
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| 32.91 ± 4.04 | 32.71 ± 4.13 | −0.47 | 0.641 | ||
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| 5.07 | 0.024 | |||||
| Employed | 136 / 171 | 79.5 | 122 / 137 | 89.1 | |||
| Stay-at-home | 35 / 171 | 20.5 | 15 / 137 | 10.9 | |||
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| 4.74 | 0.029 | |||||
| Employed | 131 / 163 | 80.4 | 120 / 134 | 89.6 | |||
| Stay-at-home | 32 / 163 | 19.6 | 14 / 134 | 10.4 | |||
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| 0.839 | ||||||
| Junior college degree or below | 98 / 172 | 57.0 | 76 / 139 | 54.7 | 0.17 | 0.685 | |
| Bachelor degree or above | 74 / 172 | 43.0 | 63 / 139 | 45.3 | |||
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| 0.318 | ||||||
| Junior college degree or below | 89 / 170 | 52.4 | 82 / 138 | 59.4 | 1.54 | 0.215 | |
| Bachelor degree or above | 81 / 170 | 47.6 | 56 / 138 | 40.6 | |||
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| 23.27 ± 4.27 | 23.08 ± 3.97 | −0.08 | 0.935 | ||
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| 2.298 | 0.13 | |||||
| yes | 41 / 167 | 24.6 | 45 / 139 | 32.4 | |||
| no | 126/ 167 | 29.3 | 94 / 139 | 31.7 | |||
| History of abnormal pregnancy | 8 / 172 | 4.7 | 5 / 139 | 3.6 | 0.21 | 0.644 | |
| History of cesarean section | 31 / 172 | 18.0 | 25 / 139 | 18.0 | 0.00 | 0.993 | |
| Anemia | 82 / 172 | 47.7 | 50 / 139 | 36.0 | 4.31 | 0.038 | |
| Vaginal candidiasis | 9 / 172 | 5.20 | 1 / 139 | 0.72 | 3.69 | 0.055 | |
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| Smoking | 4/114 | 3.51 | 3/120 | 2.50 | 0.01 | 0.945 |
| Exposure to smoking | 17 / 114 | 14.9 | 32 / 120 | 26.7 | 4.88 | 0.027 | |
| Alcohol drinking | 3/114 | 2.6 | 1/120 | 0.8 | 0.31 | 0.578 | |
| Tea drinking | 5 / 114 | 4.4 | 19 / 120 | 15.8 | 8.32 | 0.004 | |
| Nutrient supplement | 68 / 112 | 60.7 | 69 / 120 | 57.5 | 0.25 | 0.619 | |
| Using computers(h/day) | 3.02 ± 3.43 | 3.71 ± 3.32 | −1.93 | 0.053 | |||
| Watching TV(h/day) | 1.77 ± 2.15 | 1.95 ± 1.55 | −2.20 | 0.028 | |||
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| 1.50 | 0.220 | |||||
| yes | 14 / 112 | 12.5 | 22 / 119 | 18.3 | |||
| no | 98 / 112 | 87.5 | 97 / 119 | 80.8 | |||
| Walking (h/week) | 4.65 ± 5.95 | 5.69 ± 7.19 | −0.86 | 0.390 | |||
P < 0.05.
: data derived from first trimester.
: Nutrient supplement: refers to vitamin or mineral supplements (e.g., folic acid, calcium tablets, iron, etc).
: Physical activities: Min at least 3 times a week for 30 min each, except walking.
Hierarchical logistic regression predicting adverse pregnancy outcomes from sociodemographic features, medical records and life behaviors, China, 2018-2020.
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| Maternal occupation | 0.178 | 0.614 | 0.303–1.248 | 0.232 | 0.642 | 0.311–1.327 | 0.639 | 0.802 | 0.319–2.017 |
| Spouse occupation | 0.089 | 0.529 | 0.254–1.102 | 0.092 | 0.523 | 0.246–1.112 | 0.115 | 0.48 | 0.193–1.194 |
| Maternal education level | 0.395 | 0.783 | 0.445–1.376 | 0.55 | 0.838 | 0.471–1.493 | 0.674 | 0.849 | 0.396–1.82 |
| Spouse education level | 0.1 | 1.609 | 0.912–2.838 | 0.082 | 1.675 | 0.936–3 | 0.24 | 1.543 | 0.749–3.181 |
| Maternal age | 0.843 | 0.994 | 0.938–1.053 | 0.459 | 0.976 | 0.915–1.041 | 0.215 | 0.95 | 0.877–1.03 |
| Pre-pregnancy BMI | 0.839 | 1.006 | 0.948–1.068 | 0.23 | 1.045 | 0.972–1.124 | |||
| Primipara | 0.053 | 0.556 | 0.306–1.008 | 0.246 | 0.634 | 0.293–1.37 | |||
| History of abnormal pregnancy | 0.864 | 0.901 | 0.272–2.985 | 0.41 | 0.562 | 0.143–2.209 | |||
| History of cesarean section | 0.506 | 0.798 | 0.409–1.554 | 0.629 | 1.22 | 0.544–2.737 | |||
| Anemia | 0.051 | 1.629 | 0.998–2.659 | 0.027 | 2.002 | 1.08–3.708 | |||
| Exposure to smoking | 0.043 | 0.456 | 0.213–0.974 | ||||||
| Tea drinking | 0.008 | 0.193 | 0.057–0.653 | ||||||
| Nutrient supplement | 0.258 | 1.423 | 0.772–2.622 | ||||||
| Using computers, h/day | 0.245 | 0.945 | 0.858–1.04 | ||||||
| Watching TV, h/day | 0.992 | 1.001 | 0.85–1.178 | ||||||
| Physical activities | 0.19 | 0.568 | 0.243–1.325 | ||||||
| Walking, h/week | 0.319 | 0.975 | 0.928–1.025 | ||||||
P < 0.05.