TY - JOUR
T1 - Associations between ambient temperature and risk of preterm birth in Sweden
T2 - A comparison of analytical approaches
AU - de Bont, Jeroen
AU - Stafoggia, Massimo
AU - Nakstad, Britt
AU - Hajat, Shakoor
AU - Kovats, Sari
AU - Part, Chérie
AU - Chersich, Matthew
AU - Luchters, Stanley
AU - Filippi, Veronique
AU - Stephansson, Olof
AU - Ljungman, Petter
AU - Roos, Nathalie
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/10
Y1 - 2022/10
N2 - Background: Evidence indicates that high temperatures are a risk factor for preterm birth. Increasing heat exposures due to climate change are therefore a concern for pregnant women. However, the large heterogeneity of study designs and statistical methods across previous studies complicate interpretation and comparisons. We investigated associations of short-term exposure to high ambient temperature with preterm birth in Sweden, applying three complementary analytical approaches. Methods: We included 560,615 singleton live births between 2014 and 2019, identified in the Swedish Pregnancy Register. We estimated weekly mean temperatures at 1-km2 spatial resolution using a spatiotemporal machine learning methodology, and assigned them at the residential addresses of the study participants. The main outcomes of the study were gestational age in weeks and subcategories of preterm birth (<37 weeks): extremely preterm birth (<28 weeks), very preterm birth (from week 28 to <32), and moderately preterm birth (from week 32 to<37). Case-crossover, quantile regression and time-to-event analyses were applied to estimate the effects of short-term exposure to increased ambient temperature during the week before birth on preterm births. Furthermore, distributed lag nonlinear models (DLNM) were applied to identify susceptibility windows of exposures throughout pregnancy in relation to preterm birth. Results: A total of 1924 births were extremely preterm (0.4%), 2636 very preterm (0.5%), and 23,664 moderately preterm (4.2%). Consistent across all three analytical approaches (case-crossover, quantile regression and time-to-event analyses), higher ambient temperature (95th vs 50th percentile) demonstrated increased risk of extremely preterm birth, but associations did not reach statistical significance. In DLNM models, we observed no evidence to suggest an increased effect of high temperature on preterm birth risk. Even so, a suggested trend was observed in both the quantile regression and time-to-event analyses of a higher risk of extremely preterm birth with higher temperature during the last week before birth. Conclusions: In Sweden, with high quality data on exposure and outcome, a temperate climate and good quality ante-natal health care, we did not find an association between high ambient temperatures and preterm births. Results were consistent across three complementary analytical approaches.
AB - Background: Evidence indicates that high temperatures are a risk factor for preterm birth. Increasing heat exposures due to climate change are therefore a concern for pregnant women. However, the large heterogeneity of study designs and statistical methods across previous studies complicate interpretation and comparisons. We investigated associations of short-term exposure to high ambient temperature with preterm birth in Sweden, applying three complementary analytical approaches. Methods: We included 560,615 singleton live births between 2014 and 2019, identified in the Swedish Pregnancy Register. We estimated weekly mean temperatures at 1-km2 spatial resolution using a spatiotemporal machine learning methodology, and assigned them at the residential addresses of the study participants. The main outcomes of the study were gestational age in weeks and subcategories of preterm birth (<37 weeks): extremely preterm birth (<28 weeks), very preterm birth (from week 28 to <32), and moderately preterm birth (from week 32 to<37). Case-crossover, quantile regression and time-to-event analyses were applied to estimate the effects of short-term exposure to increased ambient temperature during the week before birth on preterm births. Furthermore, distributed lag nonlinear models (DLNM) were applied to identify susceptibility windows of exposures throughout pregnancy in relation to preterm birth. Results: A total of 1924 births were extremely preterm (0.4%), 2636 very preterm (0.5%), and 23,664 moderately preterm (4.2%). Consistent across all three analytical approaches (case-crossover, quantile regression and time-to-event analyses), higher ambient temperature (95th vs 50th percentile) demonstrated increased risk of extremely preterm birth, but associations did not reach statistical significance. In DLNM models, we observed no evidence to suggest an increased effect of high temperature on preterm birth risk. Even so, a suggested trend was observed in both the quantile regression and time-to-event analyses of a higher risk of extremely preterm birth with higher temperature during the last week before birth. Conclusions: In Sweden, with high quality data on exposure and outcome, a temperate climate and good quality ante-natal health care, we did not find an association between high ambient temperatures and preterm births. Results were consistent across three complementary analytical approaches.
KW - Ambient air temperature
KW - Case-crossover
KW - Climate change
KW - Preterm births
KW - Quantile regression
KW - Time-to-event analyses
UR - http://www.scopus.com/inward/record.url?scp=85132423785&partnerID=8YFLogxK
U2 - 10.1016/j.envres.2022.113586
DO - 10.1016/j.envres.2022.113586
M3 - Article
C2 - 35671796
AN - SCOPUS:85132423785
SN - 0013-9351
VL - 213
JO - Environmental Research
JF - Environmental Research
M1 - 113586
ER -