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We aim to explore the link between maternal weekly temperature exposure and CHD in offspring and identify the relative contributions from heat and cold and from moderate and extreme atmospheric temperature. From January 2019 to December 2020, newborns who were diagnosed with CHD by echocardiography in the Network Platform for Congenital Heart Disease (NPCHD) from 11 cities in eastern China were enrolled in the present study. We appraised the exposure lag response relationship between temperature and CHDs in the distributed lag nonlinear model and further probed the pooled estimates by multivariate meta-analysis. We further performed the exposure–response curves in extreme temperature (5 th percentile for cold and 95 th for hot events). We also delve into the cumulative risk ratios (CRRs) of temperature on CHDs in general and subgroups. In this study, 5904 of 983, 523 infants were diagnosed with CHDs. The temperature-CHD combination performed positive significance in two exposure windows, gestational weeks 10–16 and 26–31, and reached the maximum effect in the 28th week. Compared with extreme cold (5 th , 6.14℃), these effects were higher in extreme heat (95 th , 29.26℃). The cumulative exposure–response curve showed a steep nonlinear rise in the hot tail but showed non-significance at low temperatures. In this range, the CRRs of temperature showed an increment to a ceiling of 3.781 (95% CI: 1.460–10.723). The temperature- CHD curves for both sex groups showed a general growth trend. No statistical significance was observed between these two groups ( P = 0.106). The cumulative effect of the temperature related CHD was significant in regions with lower education levels (maximum CRR was 9.282 (3.019–28.535)). A degree centigrade increase in temperature exposure was associated with the increment of CHD risk in the first and second trimesters, especially in extreme heat. Neonates born in lower education regions were more vulnerable to temperature-related CHDs. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-24396-5.

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Objective To describe the temporal trend of the number of new congenital heart disease (CHD) cases among newborns in Jinhua from 2019 to 2020 and explored an appropriate model to fit and forecast the tendency of CHD. Methods Data on CHD from 2019 to 2020 was collected from a health information system. We counted the number of newborns with CHD weekly and separately used the additive Holt-Winters ES method and ARIMA model to fit and predict the number of CHD for newborns in Jinhua. By comparing the mean square error, rooted mean square error and mean absolute percentage error of each approach, we evaluated the effects of different approaches for predicting the number of CHD in newborns. Results A total of 1135 newborns, including 601 baby girls and 534 baby boys, were admitted for CHD from HIS in Jinhua during the 2-year study period. The prevalence of CHD among newborns in Jinhua in 2019 was 0.96%. Atrial septal defect was diagnosed the most frequently among all newborns with CHD. The number of CHD cases among newborns remained stable in 2019 and 2020. There were fewer cases in spring and summer, while cases peaked in November and December. The ARIMA(2,1,1) model relatively offered advantages over the additive Holt-winters ES method in predicting the number of newborns with CHD, while the accuracy of ARIMA(2,1,1) was not very ideal. Conclusions The diagnosis of CHD is related to many risk factors, therefore, when using temporal models to fit and predict the data, we must consider such factors’ influence and try to incorporate them into the models.