The Temporal Relationship Between the Coronavirus Disease 2019 (COVID-19) Pandemic and Preterm Birth

It has been well demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of particular risk to the obstetric population. Pregnant individuals with SARS-CoV-2 infection are more likely to have more severe COVID-19 and mortality than their nonpregnant counterparts.1–4 Moreover, after infection with SARS-CoV-2, pregnant individuals are more likely to have obstetric complications such as hypertensive disorders of pregnancy, as well as morbidity related to these complications when they occur.5–7 For example, Metz et al7 have demonstrated that pregnant individuals who have had coronavirus disease 2019 (COVID-19), in particular those with at least moderate disease, have a greater risk of complications related to obstetric hemorrhage, infection, and hypertension.

It is not as clear whether larger social changes wrought by the COVID-19 pandemic have affected obstetric outcomes, in particular preterm birth, among the wider population. There are several reasons why the frequency of preterm birth, attributable to both spontaneous and medically indicated causes, may be expected to change. For example, the increased stress and economic deprivation that have accompanied the COVID-19 pandemic have been posited as risk factors for preterm birth.8–11 Conversely, the pandemic, particularly during the most extensive lockdowns, has resulted in less pollution and other adverse environmental factors that are considered to be potentially protective of preterm birth.12–14 Nevertheless, the epidemiologic studies that have evaluated the relationship between the COVID-19 pandemic and preterm birth have had inconsistent results. Some have shown no change, some have shown a decreased risk, and some have shown an increased risk of preterm birth after the onset of the pandemic.15–39

The reason for the inconsistency in these results is not known, although there are several possibilities. Many of the studies have used data from large populations but have been unable to adjust for potentially important confounding factors. Another potential reason is that social changes associated with the COVID-19 pandemic may affect different societies, or even groups with a single society, differently on the basis of such factors as the extensiveness of the social safety net or socioeconomic status. Thus, in the present analysis, we have used data from a large, diverse, and highly detailed U.S. cohort to evaluate whether preterm birth rates changed in relation to the onset of the COVID-19 pandemic and whether any change depended on socioeconomic status. We hypothesized that the overall preterm birth rate would decline during the pandemic because of lesser exposure among a general population to environmental factors such as pollution but that there would be effect modification of this association such that this decrease would not be as great in magnitude (or even a decrease at all) among populations with greater social vulnerability.

METHODS

This is a secondary analysis of an observational cohort study of pregnant individuals who delivered in the years 2019 and 2020 during the months of March through December at one of the U.S. hospitals participating in the Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units (MFMU) Network GRAVID (Gestational Research Assessments for COVID-19) study.7 Sixteen of the 17 hospitals that participated in the study also provided data with regard to residential location of the individuals, and data from these hospitals formed the basis for this analysis. For the cohort, all individuals who delivered on randomly selected days had their medical records abstracted. Before the COVID-19 pandemic (ie, during 2019), three weekdays and one weekend day per month were randomly selected from March through December 2019. After the pandemic began (ie, during 2020), six weekdays and two weekend days per month were sampled from March through May 2020 (when it had been anticipated during the planning of the study that the largest surge of COVID-19 would occur), and three weekdays and one weekend day per month were randomly selected from June through December 2020 to identify the pandemic cohort. March was selected as the month to denote when the COVID-19 pandemic started in the United States given that this was the month when the virus began to spread more widely in the United States and public health mitigation strategies (eg, stay-at-home orders) began to be put into place.40 Random selection was based on a uniform distribution in which each weekday and each weekend day would have equal probability of random selection. All MFMU sites used the same randomly selected delivery dates. All data, including patient characteristics, antepartum and intrapartum course, pregnancy complications, and residential address during pregnancy, were abstracted from the medical record by centrally trained and certified perinatal research staff. Full details of the sampling strategy and medical record abstraction have been previously described.7

The present analysis includes patients in the cohort who had singleton gestations and a residential address with corresponding geocode data available, regardless of whether they had confirmed SARS-CoV-2 infection with any degree of clinical severity of COVID-19 or no known infection. The primary exposure for this analysis was temporal epoch in relation to the onset of the COVID-19 pandemic. Those who delivered before its onset (ie, in 2019) were compared with those who delivered after its onset (ie, in 2020). The primary outcome for this analysis was preterm birth before 37 weeks of gestation, and we secondarily examined preterm birth before 32 weeks of gestation. For each preterm birth outcome, medically indicated (eg, those with delivery initiated by induction or cesarean delivery without labor because of conditions such as hypertensive disorders of pregnancy or fetal growth restriction) and spontaneous (eg, attributable to preterm rupture of the membranes or onset of labor) preterm births also were tabulated. Twins were excluded from this analysis given that their rate of preterm birth is very different from that of singletons, and the purpose of this analysis was not to detect changes in the preterm birth rate in relation to changes in gestational plurality.

Interaction analyses were conducted to determine whether the magnitude of the main effect for the association of epoch with preterm birth was similar for patients of different socioeconomic characteristics. Characteristics evaluated in the interaction analysis were selected a priori and included two patient-level characteristics (ie, race and ethnicity; insurance status) and one community-level characteristic (ie, the Social Vulnerability Index (SVI) of the census tract within which the patient lived according to the address in the medical record at the time of delivery). The SVI provides an overall score and a score for each of four subthemes (ie, socioeconomic status, household composition and disability, minority status and language, housing type and transportation). Race and ethnicity were determined according to the designation in the medical record and were defined as non-Hispanic Black, non-Hispanic White, Hispanic, and more than one race for those who did not identify as a member of one of the aforementioned three groups. Insurance status was categorized according to whether an individual had commercial insurance or noncommercial insurance (ie, self-pay, uninsured, or government-assisted). The Centers for Disease Control and Prevention's SVI was examined by quartile both for the overall composite score and each of its four subtheme scores (socioeconomic status, household composition, minority status and language, housing type and transportation). Stratified analyses were conducted for outcomes only if there was evidence of statistically significant effect modification.

Two planned sensitivity analyses were performed. In one sensitivity analysis, to evaluate only those without known infection, we excluded those with documented SARS-CoV-2 infection at any time during pregnancy through 42 days postpartum. An additional sensitivity analysis was performed in which missing values for body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) at delivery were imputed according to a generalized linear model. The imputation modeled the liner, quadratic, and cubic natural-log scale BMI at delivery calculated from the most recent pregnancy weight before delivery.

For the primary objective, outcomes of patients who delivered before the COVID-19 pandemic were compared with those of patients who delivered after the onset of the pandemic. Descriptive summary statistics were calculated for baseline characteristics. Bivariable comparisons were performed with the Wilcoxon rank-sum test for continuous variables and χ2 or Fisher exact test for categorical variables, as appropriate. For multivariable models, covariates were selected a priori on the basis of clinical relevance and included maternal age, BMI at first prenatal visit or (if that was not available) the self-reported prepregnancy value, major medical comorbidity (asthma of any severity or chronic obstructive pulmonary disease, chronic hypertension, or pregestational diabetes), obstetric history (no prior pregnancy, prior pregnancy without preterm birth, or prior pregnancy with preterm birth), and birth month. Interaction analyses for the SVI and its subthemes also included county-level random intercepts to account for correlations among census tracts within the same counties. Likelihood ratio tests were used to evaluate interactions between the exposure (birth after the onset of the COVID-19 pandemic) and the prespecified subgroup. To account for the random sampling of individuals, weighted analyses were performed. Poisson regression models were used to estimate relative risks and 95% CIs.

Nominal two-sided P values are reported. P<.05 was considered statistically significant. No adjustment was made for multiple comparisons. Statistical analyses were performed with SAS 9.4. IRB approval was obtained from all sites before initiation of the study.

RESULTS

Overall, 21,832 patients who delivered in 2019 and 2020 on randomly selected days during March through December were included in the study cohort. The proportion of those with missing geocode data was similar between the two groups who delivered before and during the COVID-19 pandemic (1,271/9,477 [13.4%] and 1,532/11,852 [12.9%], respectively). After the exclusion of individuals without geocoded addressed and those who had twins, 18,526 remained for this analysis (Fig. 1). Of these, 8,206 delivered on randomly selected days before the COVID-19 pandemic, and 10,320 delivered on randomly selected dates after the onset of the pandemic. Of those who delivered after the COVID-19 pandemic, 360 (3.5%) had SARS-CoV-2 infection documented by testing. Compared with individuals who delivered before the COVID-19 pandemic, those who delivered after the pandemic began had a slightly older mean age, were more likely to be employed or to have a major medical comorbidity, and were less likely to report substance use (Table 1).

F1Fig. 1.:

Flowchart for the composition of the study population. MFMU, Maternal-Fetal Medicine Units Network.

T1Table 1.:

Demographics of the Study Population Stratified by Epoch in Relation to the Coronavirus Disease 2019 (COVID-19) Pandemic

As shown in Table 2, the prevalence of preterm birth before 37 weeks of gestation before the COVID-19 pandemic was similar to that after the onset of the pandemic (11.7% vs 12.5%, adjusted relative risk (aRR) 0.94, 95% CI 0.86–1.03). Findings were similar for preterm birth before 32 weeks of gestation (3.2% vs 3.2%, aRR 0.93, 95% CI 0.78–1.11). Findings were similar when spontaneous preterm birth and medically indicated preterm birth were examined separately. In interaction analyses (Table 3), neither race and ethnicity nor insurance status modified the association between the epoch and the chance of preterm birth before 37 weeks of gestation (all interaction P>.05). Similarly, there was no evidence of effect modification by overall SVI or any of the four SVI subthemes (all interaction P>.05). The results were similar for preterm birth before 32 weeks of gestation, although a statistically significant interaction was noted for the socioeconomic vulnerability subtheme (theme 1) of the SVI (interaction P=0.03). In subgroup analysis (Fig. 2), individuals residing in areas that were the most socioeconomically vulnerable were less likely to have a preterm birth before 32 weeks of gestation during the COVID-19 pandemic than before the pandemic (quartile 4: 4.0% vs 4.9%, aRR 0.70, 95% CI 0.53–0.94).

T2Table 2.:

Association of Preterm Birth With Epoch in Relation to the Coronavirus Disease 2019 (COVID-19) Pandemic

T3Table 3.:

P Values for Effect Modification Between Socioeconomic Factors and Coronavirus Disease 2019 (COVID-19) Pandemic Epoch for the Preterm Birth Outcomes

F2Fig. 2.:

Subgroup analysis for preterm birth before 32 weeks of gestation and Social Vulnerability Index: socioeconomic status subtheme. RD, risk difference; RR, relative risk; aRR, adjusted relative risk.

In sensitivity analysis, the finding that there was no difference in preterm birth rates before either 37 or 32 weeks of gestation in relation to the onset of the COVID-19 pandemic was again noted (Table 4). Results of the interaction and subgroup analyses were largely the same as for the primary analysis (data not shown).

T4Table 4.:

Sensitivity Analyses for the Association of Preterm Birth With Epoch in Relation to the Coronavirus Disease 2019 (COVID-19) Pandemic

DISCUSSION

In this analysis, we have evaluated whether preterm birth rates among a large and diverse population in the United States changed in association with the onset of the COVID-19 pandemic. Our data showed no statistically significant difference in preterm birth rates over time, regardless of whether preterm birth before 37 weeks of gestation or before 32 weeks of gestation was considered. Moreover, we have shown that the lack of an association was largely independent of socioeconomic indicators such as race and ethnicity, insurance status, or the social vulnerability of the residential community in which an individual lived. Although interaction and subgroup analyses indicated that those who lived in neighborhoods with the lowest socioeconomic resources (quartile 4) had a reduction in preterm birth before 32 weeks of gestation after the COVID-19 pandemic began, this finding should be interpreted with caution. Multiple interactions were assessed without consistent evidence of effect modification, and the only interaction that was significant had a P value just below the .05 threshold and a 95% CI of the aRR for the fourth quartile subgroup that approached unity.

These findings are consistent with those of studies from other countries that also have demonstrated no significant change in preterm birth rates despite the dramatic social changes such as stay-at-home orders, remote work, less pollution, and changes in employment status, that occurred in concert with the COVID-19 pandemic.16,18,22,26,32 In contrast, investigations from China and Nepal documented an increased risk of preterm birth,27,39 and other investigators have found a decrease in preterm birth after the COVID-19 pandemic.15,17,19–21,23–25,28–31,33,34 The studies that have suggested a decrease, however, have not yielded a consistent pattern. Although the decrease has been found by some to be applicable for people of different parity, throughout the preterm period, and for different preterm birth phenotypes, Klumper et al20 identified a difference only for medically indicated preterm births, Riley et al24 identified a difference only among multiparous individuals, and De Curtis et al30 noted that the reduction was limited to the late preterm period. Different studies within the same country also have yielded differing results.21,23–26,31,32,35,36,38 These studies, moreover, have had limitations such as not adjusting for potentially important confounding factors or adjusting for confounding factors (eg, birth weight) that are on the causal pathway. In addition, the absolute differences that have been found—often on the order of 1% or less—are of a magnitude such that omitted variable bias cannot easily be dismissed.

It is possible that the social effects of the COVID-19 pandemic would have different ramifications for preterm birth rates in countries with different social support systems or within countries among individuals of different socioeconomic status. However, extant data, such as the negative findings in different countries with quite different social-welfare systems and preterm births rates (eg, Sweden, France, Spain, and the United States), do not support this hypothesis. Similarly, in our study, there was no consistent evidence that individual-level or census-level indicators acted as effect modifiers of the relationship between COVID-19 pandemic epoch and preterm birth rates. Although prior evaluation of socioeconomic indicators in this context has been limited, when they have been interrogated, they have not been found to modify the association between COVID-19 pandemic epoch and preterm birth as well.21,28

Further investigation is needed to understand why social changes as dramatic as those that occurred in the context of the COVID-19 pandemic are not associated with changes in preterm birth rates among a large, multicenter population of parturients. It is possible that the social changes, although dramatic from a population perspective, are not sufficient to materially alter individual gestational lengths. Alternatively, it is possible that the varied consequences of the social changes counteract one another. For example, the salutary effects of less air pollution may be counteracted by the negative consequences of increased stress. Similarly, further work is required to better understand whether these results are similar among populations in low- and middle-income countries (which have been under-represented in the studies undertaken so far) and whether the inconsistent results of other studies are related to methodologic limitations or point to some—even if for the moment obscure—important dynamic that could elucidate helpful approaches to the problem of preterm birth.

This study has several strengths. Most prominently, data were from a cohort with highly detailed information that was obtained by direct abstraction from the medical record by research personnel certified specifically for this study. The population was from a wide geographic area, was diverse with regard to patient characteristics, and had information available to allow both person-level and residential-level socioeconomic indicators (ie, SVI) to be assessed as effect modifiers. In addition, although the study examined a time period that bridged the start of the COVID-19 pandemic, subsequent changes, such as the new variants that arose, should not alter the conclusions because this is not a study focusing on the effects of the virus per se but a study evaluating the effects of social and environmental changes related to a pandemic. Thus, the period most closely related to the onset of the COVID-19 pandemic, when the most social and environmental changes occurred, is the best period to study and provides generalizable results, at least as they apply to the question of whether pandemic-related changes in the macroenvironment are associated with alterations in birth outcomes.

Limitations should also be noted. The data were derived from patients at 16 hospitals within the MFMU Network and examined some factors specific to the United States (ie, SVI); it cannot be known whether the results would be similar among other populations in the United States and in other countries. It is possible that different time frames could yield different results, although, as noted, the many studies that have been done and assessed different time periods have not yielded one particular time when a change has been consistently shown or when policy or lifestyle changes across large geographic areas were sufficiently temporally aligned that a different postpandemic time period is the most likely to demonstrate preterm birth changes if they were to exist. The cohort was not composed of every day in the study period but was composed according to a purposeful sampling strategy that oversampled when the major surge of the COVID-19 pandemic was predicted to occur. This is unlikely to have biased the results, however. As noted, most of the population in this study did not have COVID-19, so it is unlikely that changes in the preterm birth rate would be attributable to a slightly higher proportion who had COVID-19 during the surge and whose charts were abstracted. Any bias that would occur in this regard is away from the null; given that our results are consistent with the null hypothesis, it does not support that bias has occurred. Last, although the sampling was predicated on one surge at a specific time, as it turns out, there was not a single surge but multiple recurrent waves of infection, so this sampling strategy does not truly end up oversampling a unique postpandemic time. In addition, even though the study population included more than 18,000 individuals, small differences in preterm birth rates, even if they were to exist, may not have been detected. Nevertheless, given the size of the population in the cohort, there is 85% power (at a two-sided α=.05) to detect an absolute risk difference in preterm birth before 37 weeks of gestation of as little as 1.5% (or a risk ratio of as little as 12%) from the prepandemic baseline. There is less power to detect differences in subsets of preterm birth given the smaller sample sizes.

In summary, our results indicate that the months after the onset of the COVID-19 pandemic were not associated with discernible differences in the preterm birth rate in a large U.S. population. These results underscore the uncertain cause of preterm birth and its complex relationship to the wider social environment.

REFERENCES 1. Lokken EM, Huebner EM, Taylor GG, Taylor GG, Hendrickson S, Vanderhoeven J,, et al. Disease severity, pregnancy outcomes, and maternal deaths among pregnant patients with severe acute respiratory syndrome coronavirus 2 infection in Washington State. Am J Obstet Gynecol 2021;225:77.e1–14. doi: 10.1016/j.ajog.2020.12.1221 2. Metz TD, Clifton RG, Hughes BL, Sandoval G, Saade GR, Grobman WA,, et al. Disease severity and perinatal outcomes of pregnant patients with coronavirus disease 2019 (COVID-19). Obstet Gynecol 2021;137:571–80. doi: 10.1097/aog.0000000000004339 3. Villar J, Ariff S, Gunier RB, Thiruvengadam R, Rauch S, Kholin A,, et al. Maternal and neonatal morbidity and mortality among pregnant women with and without COVID-19 infection: the INTERCOVID multinational cohort study. JAMA Pediatr 2021;175:817–26. doi: 10.1001/jamapediatrics.2021.1050 4. Rasmussen SA, Smulian JC, Lednicky JA, Wen TS, Jamieson DJ. Coronavirus disease 2019 (COVID-19) and pregnancy: what obstetricians need to know. Am J Obstet Gynecol 2020;222:415–26. doi: 10.1016/j.ajog.2020.02.017 5. Lai J, Romero R, Tarca AL, Iliodromiti S, Rehal A, Banerjee A, et al. SARS-CoV-2 and the subsequent development of preeclampsia and preterm birth: evidence of a dose-response relationship supporting causality. Am J Obstet Gynecol 2021;225:689–93.e1. doi: 10.1016/j.ajog.2021.08.020 6. Papageorghiou AT, Deruelle P, Gunier RB, Rauch S, García-May PK, Mhatre M,, et al. Preeclampsia and COVID-19: results from the INTERCOVID prospective longitudinal study. Am J Obstet Gynecol 2021;225:289.e1–17. doi: 10.1016/j.ajog.2021.05.014 7. Metz TD, Clifton RG, Hughes BL, Sandoval GJ, Grobman WA, Saade GR,, et al. Association of SARS-CoV-2 infection with serious maternal morbidity and mortality from obstetric complications. JAMA 2022;327:748–59. doi: 10.1001/jama.2022.1190 8. Gillespie SL, Christian LM, Mackos AR, Mackos AR, Nolan TS, Gondwe KW,, et al. Lifetime stressor exposure, systemic inflammation during pregnancy, and preterm birth among Black American women. Brain Behav Immun 2022;101:266–74. doi: 10.1016/j.bbi.2022.01.008 9. Stephens JE, Kessler CL, Buss C, Buss C, Miller GE, Grobman WA,, et al. Early and current life adversity: past and present influences on maternal diurnal cortisol rhythms during pregnancy. Dev Psychobiol 2021;63:305–19. doi: 10.1002/dev.22000 10. Keenan-Devlin LS, Smart BP, Grobman W, Adam EK, Freedman A, Buss C,, et al. The intersection of race and socioeconomic status is associated with inflammation patterns during pregnancy and adverse pregnancy outcomes. Am J Reprod Immunol 2022;87:e13489. doi: 10.1111/aji.13489 11. Givens M, Teal EN, Patel V, Manuck TA. Preterm birth among pregnant women living in areas with high social vulnerability. Am J Obstet Gynecol MFM 2021;3:100414. doi: 10.1016/j.ajogmf.2021.100414 12. Zhou W, Ming X, Yang Y, He Z, Chen H, Li Y,, et al. Association between maternal exposure to ambient air pollution and the risk of preterm birth: a birth cohort study in Chongqing, China, 2015-2020. Int J Environ Res Public Health 2022;19:2211. doi: 10.3390/ijerph19042211 13. Ha S, Martinez V, Chan-Golston AM. Air pollution and preterm birth: a time-stratified case-crossover study in the San Joaquin Valley of California. Paediatr Perinatal Epidemiol 2022;36:80–9. doi: 10.1111/ppe.12836 14. Fucic A, Duca RC, Galea KS Reproductive health risks associated with occupational and environmental exposure to pesticides. Int J Environ Res Public Health 2021;18:6576. doi: 10.3390/ijerph18126576 15. Yalçin SS, Boran P, Tezel B, Şahlar TE, Özdemir P, Keskinkiliç B, et al. Effects of the COVID-19 pandemic on perinatal outcomes: a retrospective cohort study from Turkey. BMC Pregnancy Childbirth 2022;22:51. doi: 10.1186/s12884-021-04349-5 16. Roberts NF, Sprague AE, Taljaard M, Fell DB, Ray JG, Tunde-Byass M, et al. Maternal-newborn health system changes and outcomes in Ontario, Canada during wave 1 of the COVID-19 pandemic: a retrospective study. J Obstet Gynaecol Can 2022;44:664–74. doi: 10.1016/j.jogc.2021.12.006 17. Hedley PL, Hedermann G, Hagen CM, Bækvad-Hansen M, Hjalgrim H, Rostgaard K,, et al. Preterm birth, stillbirth and early neonatal mortality during the Danish COVID-19 lockdown. Eur J Pediatr 2022;181:1175–84. doi: 10.1007/s00431-021-04297-4 18. Garabedian C, Dupuis N, Vayssière C, Bussières L, Ville Y, Renaudin B,, et al. Impact of COVID-19 lockdown on preterm births, low birthweights and stillbirths: a retrospective cohort study. J Clin Med 2021;10:5649. doi: 10.3390/jcm10235649 19. Leibovitch L, Reichman B, Mimouni F, Zaslavsky-Paltiel I, Lerner-Geva L, Wasserteil N,, et al. Preterm singleton birth rate during the COVID-19 lockdown: a population-based study. Am J Perinatol 2021;39:1020–6. doi: 10.1055/s-0041-1740012 20. Klumper J, Kazemier BM, Been JV, Bloemenkamp KW, de Boer MA, Erwich JJ,, et al. Association between COVID-19 lockdown measures and the incidence of iatrogenic versus spontaneous very preterm births in the Netherlands: a retrospective study. BMC Pregnancy Childbirth 2021;21:767. doi: 10.1186/s12884-021-04249-8 21. Gurol-Urganci I, Waite L, Webster K, Jardine J, Carroll F, Dunn G,, et al. Obstetric interventions and pregnancy outcomes during the COVID-19 pandemic in England: a nationwide cohort study. PLoS Med 2022;19:e1003884. doi: 10.1371/journal.pmed.1003884 22. Oakley LL, Örtqvist AK, Kinge J, Hansen AV, Petersen TG, Söderling J,, et al. Preterm birth after the introduction of COVID-19 mitigation measures in Norway, Sweden, and Denmark: a registry-based difference-in-differences study. Am J Obstet Gynecol 2022;226:550.e1–22. doi: 10.1016/j.ajog.2021.11.034 23. Simeone RM, Downing KF, Wallace B, Galang RR, DeSisto CL, Tong VT,, et al. Changes in rates of adverse pregnancy outcomes during the COVID-19 pandemic: a cross-sectional study in the United States, 2019-2020. J Perinatol 2022;42:617–23. doi: 10.1038/s41372-022-01327-3 24. Riley T, Nethery E, Chung EK, Souter V. Impact of the COVID-19 pandemic on perinatal care and outcomes in the United States: an interrupted time series analysis. Birth 2021;49:298–309. doi: 10.1111/birt.12606 25. Cuestas E, Gómez-Flores ME, Charras MD, Payrano AJ, Montenegro C, et al. Association between COVID-19 mandatory lockdown and decreased incidence of preterm births and neonatal mortality. J Perinatol 2021;41:2566–9. doi: 10.1038/s41372-021-01116-4 26. Wood R, Sinnott C, Goldfarb I, Clapp M, McElrath T, Little S. Preterm birth during the coronavirus disease 2019 (COVID-19) pandemic in a large hospital system in the United States. Obstet Gynecol 2021;137:403–4. doi: 10.1097/aog.0000000000004237 27. Dong M, Qian R, Wang J, Fan J, Ye Y, Zhou H, et al. Associations of COVID-19 lockdown with gestational length and preterm birth in China. BMC Pregnancy Childbirth 2021;21:795. doi: 10.1186/s12884-021-04268-5 28. Been JV, Burgos Ochoa L, Bertens LCM, Schoenmakers S, Steegers EAP, Reiss IKM. Impact of COVID-19 mitigation measures on the incidence of preterm birth: a national quasi-experimental study. Lancet Public Health 2020;5:e604–11. doi: 10.1016/s2468-2667(20)30223-1 29. Maeda Y, Nakamura M, Ninomiya H, Ogawa K, Sago H, Miyawaki A. Trends in intensive neonatal care during the COVID-19 outbreak in Japan. Arch Dis Child Fetal Neonatal Ed 2021;106:327–9. doi: 10.1136/archdischild-2020-320521 30. De Curtis M, Villani L, Polo A. Increase of stillbirth and decrease of late preterm infants during the COVID-19 pandemic lockdown. Arch Dis Child Fetal Neonatal Ed 2020;106:456. doi: 10.1136/archdischild-2020-320682 31. Harvey EM, McNeer E, McDonald MF, Shapiro-Mendoza CK, Dupont WD, Barfield W, et al. Association of preterm birth rate with COVID-19 statewide stay-at-home orders in Tennessee. JAMA Pediatr 2021;175:635–7. doi: 10.1001/jamapediatrics.2020.6512 32. Richter F, Strasser AS, Suarez-Farinas M, Zhao S, Nadkarni GN, Jabs EW, et al. Neonatal outcomes during the COVID-19 pandemic in New York City. Pediatr Res 2022;91:477–9. doi: 10.1038/s41390-021-01513-7 33. Meyer R, Bart Y, Tsur A, Yinon Y, Friedrich L, Maixner N, et al. A marked decrease in preterm deliveries during the coronavirus disease 2019 pandemic. Am J Obstet Gynecol 2021;224:234–7. doi: 10.1016/j.ajog.2020.10.017 34. Philip RK, Purtill H, Reidy E, Daly M, Imcha M, McGrath D, et al. Unprecedented reduction in births of very low birthweight (VLBW) and extremely low birthweight (ELBW) infants during the COVID-19 lockdown in Ireland: a “natural experiment” allowing analysis of data from the prior two decades. BMJ Glob Health 2020;5:e003075. doi: 10.1136/bmjgh-2020-003075 35. Main EK, Chang SC, Carpenter AM, Wise PH, Stevenson DK, Shaw GM, et al. Singleton preterm birth rates for racial and ethnic groups during the coronavirus disease 2019 pandemic in California. Am J Obstet Gynecol 2021;224:239–41. doi: 10.1016/j.ajog.2020.10.033 36. Handley SC, Mullin AM, Elovitz MA, Gerson KD, Montoya-Williams D, Lorch SA, et al. Changes in preterm birth phenotypes and stillbirth at 2 Philadelphia hospitals during the SARS-CoV-2 pandemic, March-June 2020. JAMA 2021;325:87–9. doi: 10.1001/jama.2020.20991 37. Arnaez J, Ochoa-Sangrador C, Caserio S, Gutierrez EP, Jimenez MDP, Castanon L, et al. Lack of changes in preterm delivery and stillbirths during COVID-19 lockdown in a European region. Eur J Pediatr 2021;180:1997–2002. doi: 10.1007/s00431-021-03984-6 38. Khalil A, von Dadelszen P, Draycott T, Ugwumadu A, O'Brien P, Magee L. Change in the incidence of stillbirth and preterm delivery during the COVID-19 pandemic. JAMA 2020;324:705–6. doi: 10.1001/jama.2020.12746 39. Kc A, Gurung R, Kinney MV, Sunny AK, Moinuddin M, Basnet O, et al. Effect of the COVID-19 pandemic response on intrapartum care, stillbirth, and neonatal mortality outcomes in Nepal: a prospective observational study. Lancet Glob Health 2020;8:e1273–81. doi: 10.1016/s2214-109x(20)30345-4 40. Moreland A, Herlihy C, Tynan MA, Sunshine G, McCord RF, Hilton C, et al. Timing of state and territorial COVID-19 stay-at-home orders and changes in population movement—United States, March 1–May 31, 2020. MMWR Morb Mortal Wkly Rep 2020;69:1198–203. doi: 10.15585/mmwr.mm6935a2

留言 (0)

沒有登入
gif