Abstract
Background
Whether the number and quality of births have been changed after the COVID-19 pandemic remains unclear. We aimed to examine whether the number of births, gestation weeks, and birth weight changed after COVID-19 in Chongqing, the largest municipality by area in China.
Methods
Birth registration data of Chongqing from January 2015 to July 2022 were used to compare the quantity and quality (gestation week, preterm birth rate, birth weight, low birth weight rate) of births before and after the pandemic by interrupted time series analysis by autoregressive average moving models (ARIMA) and linear models of interrupted time series analysis (ITSA). October 2020, which was nine months after the onset of the first-wase of COVID-19 pandemic, was designated as the cut point to account for the gestation duration. Data from the Chongqing Preconception Reproductive Health and Birth Outcome Cohort were then utilized to analyze the temporal changes in pre-pregnancy body mass index (BMI) among reproductive-age women before (January 2019 to January 2020) and after the pandemic (March 2020 to March 2023).
Results
There were 2,099,898 birth records included. Before the pandemic, there were monthly declining trends in the number of births (β=-100.44, 95% CI: -181.82 to -14.06, P = 0.022) and gestation weeks (β=-4.7 × 10− 3, 95% CI: -6.3 × 10− 3weeks to -1.6 × 10− 3weeks, P < 0.001), and increasing trends in the rates of preterm births (β = 0.02%, 95% CI: 0.02% to 0.03%, P < 0.001) and low birth weight (β = 1.2 × 10− 2%, 95% CI: 8.9 × 10− 3% to 1.6 × 10− 2%, P < 0.001). Interrupted time-series analyses, after adjusting for seasonality and trend, showed that the declining trend in the number of births and gestation weeks did not change after COVID-19 (P = 0.428 and 0.492). Similarly, the upward trend in preterm birth rates did not change after COVID-19 (P = 0.135). However, the birth weight decreased faster after the pandemic, with an additional 1.48 g (95%CI: -2.81 g to -0.16 g, P = 0.028) per month compared to the pre-pandemic period. Similarly, the low birth weight rate increased at an accelerated pace after the pandemic, with an additional monthly increase of 0.03% (95%CI: 0.01% to 0.06%, P = 0.010) compared to the pre-pandemic period. Pre-pregnancy body mass index of reproductive-age women shifted from an increasing trend in the pre-epidemic period to a declining trend in the post-pandemic period (β=-0.05, 95%CI: -0.10 to -0.01, P = 0.039), in line with the accelerated decline of birth weight nine months later.
Conclusions
The long-term trend of birth quality after the pandemic has changed and deserves attention.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12884-025-08337-x.
Keywords: COVID-19, Birth number, Birth weight, Preterm birth
Background
Coronavirus disease 2019(COVID-19) pandemic persisted for a considerable time and exerted broad impacts on the economy and physiology [1, 2]. Economic repercussions such as increased unemployment and reduced income may have adversely affected couples’ fertility intentions and reproductive planning, while blockade and control measures may have induced lifestyle changes that could alter both the quantity and quality of births in the post-pandemic period [3]. In Western countries, studies have documented a sharp decline in fertility rates and number of births following the implementation of COVID-19 mitigation policies, although a rebound was observed in some regions at a later stage [4]. It suggests that post-pandemic birth outcomes may vary across regions and cultural contexts, however, there has been no report of this in China. Concurrently, decreases in preterm birth(PTB) and low birth weight(LBW) rates have been reported in multiple countries after the onset of COVID-19, a trend also reported by a national study in China [5]. However, a study conducted in eastern China reported that COVID-19 lockdown measures were associated with an increased risk of preterm birth, contrasting with the national findings [6]. Currently, studies on changes in the number and quality of newborns after the COVID-19 pandemic have produced conflicting conclusions [5, 7, 8].
As a mega-municipality and a representative sample of southwest China, Chongqing is characterized by its distinct geographic, economic, and cultural features. This study examines whether the quantity and quality (gestation week, preterm birth rate, birth weight, low birth weight rate) of births changed after the COVID-19 pandemic by analyzing birth registration data from January 2015 to July 2022 in Chongqing, using interrupted time series analysis (ITSA) methods. The present study may provide novel evidence concerning the effect of the COVID-19 pandemic on birth outcome, and suggest a clue of the potential reason for the population in southwest China.
Materials and methods
Data and population
We conducted an ecological study using birth registration data from Chongqing, covering the period from January 1, 2015 to July 31, 2022. The birth information was sourced from medical records of participating hospitals and electronically submitted to the online birth registration system, which includes only live births. The database comprises maternal age, date of birth, birth weight, and gestation week. Records were excluded under the following conditions: Maternal age < 13 years or > 50 years; missing maternal age, birth weight, or gestation week of birth. A total of 2,099,899 records were included in this study. The PTB was defined as delivery at < 37 weeks gestation. The LBW was defined as < 2500 g. Maternal age was stratified into five groups: ≤19 years, 20–24 years, 25–29 years, 30–34 years, 35–39 years, and ≥ 40 years.
In addition, we analyzed pre-pregnancy body mass index (BMI), a factor influencing birth outcomes. As BMI data were unavailable for birth registration, the data from the Chongqing Preconception Reproductive Health and Birth Outcome Cohort (PREBIC)was used to reflect the situation of the entire population of women recorded in the birth registration of the municipality. The PREBIC cohort is a representative sample of reproductive-age couples with breeding plans in Chongqing. As an ongoing cohort, its participants recruited from January 1, 2019 to March 31, 2023 were used for the present study. The PREBIC cohort begins at the pre-pregnancy stage and is a prospective cohort that focuses equally on the effects of environmental, psychological, and behavioral exposures of both men and women on reproductive health and adverse pregnancy outcomes. Detailed descriptions of the PREBIC cohort have been reported elsewhere [9]. Participants with the following conditions were excluded in the study: Missing height data or < 140 cm, missing weight, < 30 kg, or >150 kg. A total of 4914 women were included. Height and weight were obtained from self-reports of participants, and then BMI was calculated for each participant before pregnancy according to the formula BMI = weight (kg)/height (m)2.
Pandemic period definition
The first confirmed case of COVID-19 in Chongqing was reported on January 21, 2020, after followed by rapid spread of the pandemic. The period prior to January 31, 2020 was defined as the pre-pandemic period, and the time thereafter as the post-pandemic period. No participants were enrolled in PREBIC cohort in February 2020 because of the blockade activities in Chongqing. Considering that the gestation period from conception to delivery is approximately nine months, the time before September 30, 2020 was regarded as the pre-pandemic period for analyzing birth quantity and quality outcomes, whereas the period from October 2020 onward was defined as the post-pandemic period. Birth numbers and quality parameters were counted as monthly averages or percentages.
Statistical analysis
To estimate whether the number of births, birth quality, and pre-pregnancy BMI in each month after the COVID-19 pandemic differ from the pre-pandemic period, we used autoregressive average moving models (ARIMA) and linear models of interrupted time series analysis (ITSA). ITSA is a quasi-experimental method. Its hypothesis is that the pre-intervention trend can be extrapolated to post-intervention period if the intervention did not impact the trend. We applied the methodology outlined by Bernal for evaluating public health interventions [10, 11]. The advantage of ARIMA models is that they account for nonstationarity, autocorrelation, and seasonality in time-series data. Seasonal ARIMA models can eliminate seasonal influences through seasonal difference, but they impose stricter requirements on the model. In this study, the optimal ARIMA model structure was automatically identified using the auto.arima() function, which selects the best-fitting model based on the Akaike Information Criterion (AIC). To ensure a comprehensive evaluation, residual diagnostics were rigorously conducted to Accordingly, for each of the following variables—the number of births, birth weight, gestational week, low birth weight rate, and preterm birth rate—we constructed both unadjusted and seasonally-adjusted models for fitting and analysis. assess the model’s adequacy and validity. In addition, ARIMA models do not require a linear trend in the data, making them a more flexible and widely used method for analyzing time series data [12]. As pre-pregnancy BMI data were missing for February 2020 and were unsuitable for ARIMA modeling, a linear model was used for this variable. All statistical analyses were performed using SPSS (version 26.0) and R (version 4.2.1).
Results
Temporal trend in the quantity of births before and after the COVID-19 pandemic
A continuous decline in the number of births was observed from 2015 to 2022, with an average monthly reduction of 100.44 births (95% CI: −181.82 to −14.06, P = 0.022). A transient increase in births occurred in October 2016, likely attributable to the implementation of the “two-child policy” in China in January 2016. No significant difference was observed in the declining trend of births before versus after the pandemic (Fig. 1 A). After adjusting for seasonality, the declining trend in the number of births remained unchanged (Table 1). Stratified analysis revealed no significant changes in any of the subgroups (Supplementary Table S1). To exclude the potential impact of the “two-child policy,” we reanalyzed the data from 2017 to 2022. During this period, the pre-pandemic monthly decline averaged 171.45 births (95% CI: −229.38 to −113.52, P < 0.001), and again, no significant change in this trend was detected following the onset of the pandemic (Fig. 1B).
Fig. 1.
ITSA for the changes of the births number before and after the COVID-19 pandemic. A For the period from January 2015 to July 2022; B For the period from January 2017 to July 2022
Table 1.
Comparison of birth quantity and quality before and after the COVID-19 pandemic (adjust for seasonality) by ITSA
| Stratification | Intercept | Slop | ||||
|---|---|---|---|---|---|---|
| beta | 95% Confidence interval (CI) | P value | beta | 95% Confidence interval (CI) | P value | |
| Birth number | −948.25 | (−7628.42, 5731.92) | 0.781 | −199.59 | (−6930.04, 293.82) | 0.428 |
| Birthweight | 2.85 | (−5.71, 11.40) | 0.514 | −1.48 | (−2.81, −0.16) | 0.028 |
| Gestation week | 0.02 | (−0.04,0.07) | 0.614 | 0.00 | (−0.01,0.01) | 0.492 |
| preterm birth rates | −0.05 | (−0.339,0.230) | 0.706 | 0.02 | (0.00,0.04) | 0.135 |
| low birth weight rates | −0.03 | (−0.35,0.29) | 0.863 | 0.03 | (0.01,0.06) | 0.010 |
Temporal trend in the quality of births before and after the COVID-19 pandemic
Additionally, from 2015 to 2022, the gestation week showed a declining trend, averaging about 4.7 × 10− 3 weeks per month (95% CI: −6.2 × 10− 3 to −3.1 × 10− 3, P < 0.001), whereas the PTB rate showed an increasing trend, rising by an average of 0.02% per month (95% CI: 0.02% to 0.03%, P < 0.001), both of which remained unchanged after the pandemic (Fig. 2 A and B). Similarly, after controlling for seasonal factors, the rising trend in the PTB rate and the declining trend in the gestation week did not change following the onset of the pandemic (Table 1). Stratified analysis indicated no significant changes across subgroups except among mothers aged ≥ 40 years (Supplementary Tables S2–S3).
Fig. 2.
ITSA for the changes of the quality before and after the COVID-19 pandemic. A gestation week; B preterm birth rate; C birth weight; D low birth weight rate
However, there was an accelerated decline in birth weight since nine months post-pandemic (Fig. 2 C), with an additional decrease of 1.43 g/month (95%CI: −1.85 to − 1.01, P < 0.001). Similarly, after adjusting for seasonal factors, birth weight continued to exhibit an accelerated declining trend, with an additional reduction of 1.48 g/month (95%CI: −2.81 to − 0.16, P = 0.028) (Table 1). Stratified analyses by maternal age and gestation week indicated no significant interactions, except for a notable decline in birth weight among infants with gestation week < 37w (Supplementary Table S5). The LBW rate increased at an average monthly rate of 0.01% (95% CI: 0.01% to 0.02%, P < 0.001) before the pandemic, while after adjusting for seasonal factors, the LBW rate increased by an average of 0.03% per month (95%CI: 0.01% to 0.06%, P < 0.010). Although a transient decrease of 0.46% (95%CI: −0.92% to − 0.01%, P = 0.048) occurred in the ninth month post-pandemic, the overall increasing trend remained unchanged, with no significant difference between the pre- and post-pandemic periods (Fig. 2D). No significant interaction were identified across stratified analyses, except for a moderate difference in slope among different age groups (Supplementary Table S5), which did not survive multiple-testing correction.
Temporal trend in pre-pregnancy BMI before and after the COVID-19 pandemic
Prior to the pandemic, pre-pregnancy BMI exhibited a slight increasing trend, with a monthly increase of 0.03 (95% CI: −0.01 to 0.08). Following the onset of the pandemic, however, this trend reversed, showing a statistically significant decline averaging 0.05 kg/m2 per month (95%CI: −0.10 to − 0.01, P = 0.039, Fig. 3).
Fig. 3.
ITSA for the changes of BMI in reproductive-age women before and after the COVID-19 pandemic
Discussion
This study assessed whether long-term trends in birth quantity and quality in Chongqing changed following the COVID-19 pandemic. We found that the number of births and gestation week continued to decline, whereas the PTB rate continued to increase. Notably, the rate of decline in birth weight accelerated during the post-pandemic period, with an additional reduction of 1.43 g/month. Conversely, pre-pregnancy BMI among reproductive-age women shifted from a pre-pandemic upward trend to a significant decline after the pandemic.
To our knowledge, this is the first study to examine long-term changes in birth trends in China after the COVID-19 pandemic. While several Western countries reported sharp declines in fertility followed by compensatory increases after lockdowns were lifted [4], we observed no substantial disruption in birth numbers in Chongqing. This may be attributable to public confidence in China’s timely and effective pandemic control measures and the anticipation of a swift societal recovery [13–15]. The stability in birth numbers aligns with findings from s other countries [8], suggesting that the pandemic did not significantly alter fertility trends overall. In particular, the infection rate during the early stages of the pandemic, when the dominant strains had higher toxicity, was successfully controlled to a low level in China [16]. This may also be one of the reasons why the long-term trend in births number has not changed.
We observed no significant change in the pre-existing declining trend in gestational age or the rising trend in PTB rates following the pandemic. A study conducted in Beijing reported an increase in PTB rates between April and September of 2020 [17]. Beijing as China’s capital, experienced an outflow of young people back to their hometowns before the pandemic (spring festival), which may have affected the age structure of the reproductive population and the PTB rate. Simultaneously, Chongqing did not meet this condition. A national study demonstrated that the long-term increasing trend of PTB remained unchanged, consistent with our study [5]. Previous studies conducted in 2020 primarily included women who conceived before the pandemic. our study expands this scope by including post-pandemic conceptions, providing a more comprehensive assessment of the pandemic’s impact. The pandemic may influence gestation week through complex effects on maternal behavior, psychology, and other factors [18], though further research is needed to clarify these mechanisms.
Studies in different regions have provided inconsistent conclusions regarding changes in birth weight after the pandemic. A study in North China [19] conducted from February 2019 to April 2020 found that pandemic control measures were associated with increased birth weights among term infants. However, a study from South China [20], between January 2016 and December 2020, reported a decrease in term birth weight during the pandemic. Our study, conducted in Chongqing (Southwestern China), also found an accelerated decline in birth weight aligning with the Southern China findings but contrasting with those from the North. These discrepancies may reflect regional variations in culture, lifestyle, and access to supplies. Interestingly, we observed a reversal in pre-pregnancy BMI trends— from increasing to decreasing— immediately after the pandemic, probably because of lifestyle changes. Given that pre-pregnancy BMI is positively correlated with birth weight [21], it is plausible that the decline in BMI contributed to the accelerated reduction in birth weight. However, this hypothesis requires further investigation.
The uniqueness of this study is that it is based on long-term, large-scale birth records of a mega-municipality. However, this study has some limitations. First, some potential confounders, such as assisted reproductive technology (ART), were unavailable and could not be controlled. Previous study found that medical supply of ART in Spanish was restricted during the pandemic, and there was a compensatory surge of ART shortly after the end of blockade activities [22]. Similar phenomenon was also reported concerning the medical visits of allergic and respiratory infectious diseases [23]. As ART may increase the risk of adverse birth outcome, e.g., ART-related polycyesis may lead to low birth weight, change of ART service supply may introduce confounding bias. Although the ART surgy in Spanish disappeared soon and may not affect the long-term trend of birth weight in the population, but no report of ART supply during the pandemic in Chongqing was available as far as we know, so it is difficult to precisely estimate or control this effect in our study. Other circumstances may have also changed during the study period, including but not limited to medical supplies, health behaviors (such as wearing masks), economic status and psychological stress. These may introduce additional uncertainty to the interpretation of our results. Second, birth and fertility rates, which may be more straightforward indicators of fecundity, could not be calculated. Third, the sample size for some stratifications was small, which may have restricted the detection of possible interactions. The analysis of BMI was also based on a relatively smaller sample size, so the results should also be interpreted carefully. Fourthly, the generalizability of the results derived in Chongqing municipality should be considered with caution, as other regions may have distinct economical and medical status, demographic characteristics and pandemic severity. Future studies are warranted to confirm the findings of the present study. Fifth, we conducted analyses using seasonal ARIMA models; however, the residuals for the number of births, gestational week, and LBT rate did not follow a normal distribution. This may have some influence on the results, and it is recommended that future studies employ more robust models or apply data transformations to improve model fit.
Conclusions
In summary, our study suggests birth weight accelerated its decline in Chongqing after COVID-19 pandemic. While the exact mechanism remains to be answered, it might be necessary to strengthen long-term maternal attention and support to ensure the health of the fetus in the post-pandemic period, such as investigating the reason of decrease in pre-pregnancy weight in the mothers and providing specific risk estimation and scientific guidance of body weight management where appropriate.
Supplementary Information
Supplementary Material 1. Table S1 Stratified analysis for the changes of the birth number before and after the pandemic.
Supplementary Material 2. Table S2 Stratified analysis for the changes of gestation week at birth before and after the pandemic.
Supplementary Material 3. Table S3 Stratified analysis for the changes of preterm birth rates before and after the pandemic.
Supplementary Material 4. Table S4 Stratified analysis for the changes of birth weights before and after the pandemic.
Supplementary Material 5. Table S5 Stratified analysis for the changes of low birth weight rates before and after the pandemic.
Acknowledgements
We thank all the participants in this study and the doctors and staff of the birth registration system and the PREBIC cohort for their great efforts in data collection. We would also like to thank Yingsi Lai of Sun Yat-sen University for her help with the analysis methods.
Abbreviations
- COVID-19
Coronavirus disease 2019
- PTB
Preterm birth
- LBW
Low birth weight
- BMI
body mass index
- PREBIC
The Chongqing Preconception Reproductive Health and Birth Outcome Cohort
- ARIMA
Autoregressive average moving models
- ITSA
Interrupted time series analysis
Authors’ contributions
QC designed the study; YC, HZ and WZ analyzed the data, interpreted the results, and drafted the manuscript; YC and RC cleaned and interpreted the data; QC, HZ and JC edited and revised the manuscript; All authors read approved the final draft of the manuscript.
Funding
The National Key Research & Development Program of China (No. 2022YFC2702902); Chongqing Research Center for Prevention & Control of Maternal and Child Diseases and Public Health.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by the Ethics Committee of Chongqing Maternal and Child Health Hospital (LS(K)020 − 04) and was carried out in compliance with the Declaration of Helsinki. Informed consent was obtained from all the women participants.
Consent for publication
Not applicable.
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.
Yi Chen, Haiyan Zhang and Wenzheng Zhou contributed equally to this work.
Contributor Information
Qing Chen, Email: chenqingforward@126.com.
Jia Cao, Email: caojia1962@126.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1. Table S1 Stratified analysis for the changes of the birth number before and after the pandemic.
Supplementary Material 2. Table S2 Stratified analysis for the changes of gestation week at birth before and after the pandemic.
Supplementary Material 3. Table S3 Stratified analysis for the changes of preterm birth rates before and after the pandemic.
Supplementary Material 4. Table S4 Stratified analysis for the changes of birth weights before and after the pandemic.
Supplementary Material 5. Table S5 Stratified analysis for the changes of low birth weight rates before and after the pandemic.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.