Heat Exposure During Pregnancy and Risk of Preterm Birth: A Systematic Review and Meta-analysis

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Concurrently, climate change is increasing the frequency, intensity, and duration of extreme heat events, yet pregnant individuals remain an under-recognized climate-vulnerable population. Although growing evidence suggests that heat exposure during pregnancy may increase the risk of preterm birth, findings have not been consistently synthesized. Methods: We conducted a systematic review and meta-analysis in accordance with PRISMA 2020 guidelines. PubMed and Google Scholar were searched from database inception to December 2025 for observational studies examining the association between heat exposure during pregnancy and preterm birth. Eligible studies included cohort and time-series designs reporting quantitative effect estimates. Risk of bias was assessed using the Newcastle–Ottawa Scale. A random-effects meta-analysis was performed to pool comparable effect estimates. Results: A total of 2,635 records were identified, of which seven studies met the inclusion criteria for qualitative synthesis and four studies were included in the final meta-analysis. All studies included in the quantitative synthesis reported positive associations between heat exposure during pregnancy and preterm birth, with adjusted hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08. Despite heterogeneity in exposure definitions and study settings, the direction of association was consistent across studies. Overall, the included studies were judged to have low to moderate risk of bias. Conclusions: This systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. As climate change continues to intensify global heat exposure, integrating maternal health considerations into heat–health action plans and climate adaptation strategies is essential to reduce preventable adverse birth outcomes. Heat Exposure Preterm Birth Pregnancy Climate Change Maternal Health Systematic Review Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Preterm birth remains one of the leading causes of neonatal morbidity and mortality worldwide and contributes substantially to long-term neurodevelopmental impairment and chronic disease across the life course [ 1 ]. Despite advances in obstetric and neonatal care, global rates of preterm birth have declined only modestly, with disproportionate burdens borne by low- and middle-income countries. Identifying modifiable environmental risk factors is therefore critical to reducing preventable adverse birth outcomes and advancing maternal–child health equity. Concurrently, climate change has emerged as one of the most significant public health threats of the 21st century, driven by rising global temperatures and an increasing frequency, duration, and intensity of extreme heat events [ 2 ]. Heatwaves are now occurring with greater regularity across most regions of the world, a trend projected to worsen under current emission trajectories [ 3 ]. While the health impacts of extreme heat on older adults and individuals with chronic disease are well established, pregnant individuals remain a comparatively under-recognized climate-vulnerable population within climate–health frameworks [ 4 ]. Pregnancy involves complex physiological adaptations, including increased metabolic heat production, expanded plasma volume, and altered thermoregulation, which may reduce tolerance to thermal stress. Growing epidemiological evidence suggests that exposure to elevated ambient temperatures or heatwaves during pregnancy may increase the risk of adverse birth outcomes, particularly preterm birth [ 5 ]. Given the widespread nature of heat exposure, even modest relative increases in risk could translate into substantial population-level impacts, especially as climate change intensifies thermal extremes globally. Although multiple observational studies have examined the association between heat exposure and preterm birth across diverse geographic settings, findings have not been consistently synthesized. Prior reviews have often combined heterogeneous outcomes, included non-quantitative evidence, or addressed climate change broadly without isolating heat exposure as a distinct environmental risk factor [ 6 ]. Consequently, uncertainty remains regarding the magnitude, consistency, and generalizability of the association between maternal heat exposure and preterm birth. Clarifying this relationship is essential for informing public health preparedness, climate adaptation strategies, and maternal health policy. As heat exposure becomes increasingly unavoidable in many regions, robust synthesis of epidemiological evidence is needed to guide preventive interventions and protect pregnant populations from climate-related health risks. The hypothesized pathways linking climate change–related heat exposure during pregnancy to preterm birth are illustrated in Fig. 1 . Therefore, we conducted a systematic review and meta-analysis to synthesize the available epidemiological evidence on the association between heat exposure during pregnancy and the risk of preterm birth. 2. METHODS This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. 2.1 Search strategy A comprehensive literature search was performed using Google Scholar and PubMed to identify relevant studies examining the association between heat exposure during pregnancy and adverse birth outcomes. For Google Scholar, a 20-year publication window (2005–2025) was applied to improve relevance. The search strategy combined controlled vocabulary terms and free-text keywords related to heat exposure, pregnancy, and birth outcomes. Search terms included combinations of: “heatwave”, “extreme temperature”, “heat exposure”, “climate change”, “pregnancy”, “pregnant”, “maternal”, “preterm birth”, “low birth weight”, and “stillbirth” . Boolean operators (AND/OR) were used to refine the search. Google Scholar was used to enhance sensitivity and capture environmental health studies not indexed in PubMed, consistent with prior climate–health systematic reviews. A 20-year (2005-2025) publication window was applied to Google Scholar searches to focus on contemporary evidence. Reference lists of eligible articles were also screened to identify additional relevant studies. The full electronic search strategy is provided in the Supplementary Material. 2.2 Eligibility criteria (PICOS framework) Studies were selected based on the following criteria: Population: Pregnant individuals and their offspring in human populations. Exposure: Heat exposure, including ambient temperature, extreme temperature, or heatwave events assessed using meteorological data. Comparator: Lower temperature periods or reference temperature ranges, as defined by individual studies. Outcomes: Preterm birth, defined as delivery before 37 completed weeks of gestation. Studies reporting related adverse birth outcomes (e.g., stillbirth) were included in the qualitative synthesis. Study design: Observational epidemiological studies, including cohort and time-series designs. Exclusion criteria Systematic reviews, meta-analyses, scoping reviews, conference abstracts without full manuscripts, theses, non-English publications, animal or laboratory studies, and studies without extractable quantitative effect estimates were excluded. 2.3 Study selection All records retrieved from the database searches were screened in a two-stage process. First, titles and abstracts were screened to exclude clearly irrelevant studies. Second, full-text articles of potentially eligible studies were assessed against the predefined inclusion and exclusion criteria. Study selection was performed independently by the authors, and discrepancies were resolved through discussion and consensus. The study selection process is illustrated using a PRISMA 2020 flow diagram (Figure 2). 2.4 Data extraction Data were extracted from included studies using a standardized data extraction form. Extracted information included: Author and year of publication Country and study setting Study design and study period Sample size Heat exposure definition and assessment method Outcome definition Effect estimates (hazard ratios, odds ratios, or relative risks) with 95% confidence intervals Covariates included in the adjusted models When multiple estimates were reported, the most fully adjusted estimate was extracted for analysis. 2.5 Risk of bias assessment The methodological quality and risk of bias of included observational studies were assessed using the Newcastle–Ottawa Scale (NOS) (Table 1). The NOS evaluates studies across three domains: Selection of study groups Comparability of groups Outcome assessment Each study was independently assessed, and studies were categorized as having low, moderate, or high risk of bias based on their NOS scores. The results of the risk of bias assessment are summarized in a dedicated table provided in the Supplementary Material. 2.6 Statistical analysis A meta-analysis was conducted for studies reporting comparable quantitative effect estimates for the association between heat exposure during pregnancy and preterm birth. Hazard ratios (HRs), odds ratios (ORs), and relative risks (RRs) were pooled assuming rare outcomes, consistent with epidemiological meta-analytic practice for preterm birth. A random-effects model was applied to account for between-study heterogeneity arising from differences in study design, exposure definitions, and populations. Statistical heterogeneity was assessed using the I² statistic, with higher values indicating greater heterogeneity. Sensitivity analyses and assessment of publication bias were not performed due to the limited number of studies included in the quantitative synthesis, in accordance with methodological recommendations. 2.7 Software All statistical analyses were conducted using R (version 4.3.2). Forest plots were generated using standard meta-analysis packages. Figure design and formatting were supported by AI-assisted tools; however, all data extraction, analyses, and interpretations were performed and verified by the authors. 3. RESULTS 3.1 Study selection The literature search identified 2,410 records from Google Scholar and 225 records from PubMed. After applying a 20-year publication filter and removing secondary studies, grey literature, non-English publications, and records with incomplete or irrelevant data, 11 full-text articles from Google Scholar were assessed for eligibility. From Google Scholar alone, two studies met the criteria for quantitative synthesis; however, after combining eligible studies from PubMed and Google Scholar, a total of four studies were included in the final meta-analysis. From the PubMed database, most records were excluded during title and abstract screening because they were review articles, commentaries, non-original research, or did not assess heat exposure in relation to pregnancy outcomes. Following title, abstract, and full-text assessment, three primary studies from PubMed met the eligibility criteria and were included in the systematic review. Overall, seven studies were included in the qualitative synthesis, and four studies were included in the meta-analysis. The study selection process is summarized in Figure 2. 3.2 Characteristics of included studies The characteristics of the included studies are presented in Table 2. The studies were published between 2014 and 2023 and consisted of population-based cohort studies and time-series analyses conducted in Australia, the United States, Iran, and China (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021; Gordon et al., 2023; Liang et al., 2018). Sample sizes varied substantially, ranging from regional population-based daily birth counts to nationwide cohorts comprising more than 32 million singleton births (Sun et al., 2019). Heat exposure was operationalized using multiple metrics, including percentile-based heatwave definitions, daily mean ambient temperature, and extreme temperature thresholds. Across studies, preterm birth, most commonly defined as delivery before 37 completed weeks of gestation, was the primary outcome of interest. 3.3 Qualitative synthesis of findings 3.3.1 Heat exposure and preterm birth Across the included studies, exposure to elevated ambient temperatures or heatwave conditions during pregnancy was consistently associated with an increased risk of preterm birth (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021). All four studies included in the meta-analysis reported adjusted effect estimates above the null, with hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08 (Table 2). Large population-based cohort studies conducted in Australia and the United States demonstrated higher risks of preterm delivery associated with heatwave exposure or increasing ambient temperature (Wang et al., 2019; Sun et al., 2019). Time-series analyses similarly reported short-term increases in preterm birth following periods of extreme temperature exposure (Mohammadi et al., 2019). The consistency and magnitude of these associations are further illustrated in the forest plot (Figure 3). 3.3.2 Susceptible exposure windows Several studies evaluated potential windows of heightened vulnerability during pregnancy. Positive associations between heat exposure and preterm birth were frequently observed during late gestation, particularly in the final weeks preceding delivery (Wang et al., 2019; Choi et al., 2021). In time-series analyses, short-term exposure to extreme temperatures over lag periods of a few days was associated with increases in daily preterm birth counts (Mohammadi et al., 2019). 3.3.3 Population characteristics and contextual factors Some studies reported heterogeneity in heat-related preterm birth risk across population subgroups. Differences were observed according to socioeconomic characteristics, residential context, and geographic location, with higher risks reported among socioeconomically disadvantaged populations in certain settings (Choi et al., 2021; Gordon et al., 2023). However, subgroup analyses were not consistently performed across all studies. A quantitative summary of individual study findings is provided in Table 2. 3.4 Quantitative synthesis (meta-analysis) 3.4.1 Main meta-analysis Four studies were included in the meta-analysis examining the association between heat exposure during pregnancy and preterm birth (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021). A random-effects model was used to account for between-study variability in exposure definitions and study design. All included studies demonstrated effect estimates greater than one, indicating a positive association between heat exposure and preterm birth. Statistical heterogeneity was assessed using the I² statistic and interpreted cautiously due to the limited number of included studies. Individual study estimates and their corresponding 95% confidence intervals are displayed in Figure 3. 3.4.2 Heterogeneity assessment Moderate heterogeneity was observed across studies, reflecting differences in geographic context, exposure assessment, and analytical approaches. Statistical heterogeneity was assessed using the I² statistic and interpreted cautiously due to the limited number of studies included in the quantitative synthesis. 3.4.3 Sensitivity analyses Sensitivity analyses were not performed owing to the small number of studies included in the meta-analysis. 3.4.4 Publication bias Assessment of publication bias using funnel plots or statistical tests was not conducted because fewer than ten studies were included in the meta-analysis. 4. DISCUSSION 4.1 Principal findings This systematic review and meta-analysis synthesizes evidence from diverse geographic and climatic contexts and provides evidence of a consistent association between maternal heat exposure and increased risk of preterm birth. Across the four studies included in the quantitative synthesis, all adjusted effect estimates exceeded the null, with hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08 [ 7 ]. Although these effect sizes are modest at the individual level, they are highly relevant at the population level, given the widespread and increasing exposure to extreme heat and the substantial global burden of preterm birth. The qualitative synthesis further supported these findings, with additional studies reporting elevated preterm birth rates following heatwave events or extreme temperature episodes [ 8 ]. Taken together, the results indicate that heat exposure during pregnancy is a reproducible and globally relevant environmental exposure associated with preterm birth. 4.2 Findings in the context of climate change The observed associations must be interpreted within the broader context of global climate change, which is driving an increase in the frequency, duration, and intensity of heatwaves worldwide [ 9 ]. Pregnant individuals represent a climate-vulnerable population, yet maternal and perinatal outcomes have historically been underrepresented in climate–health research and policy frameworks [ 10 ]. Findings of this study align with and extend prior evidence linking ambient temperature extremes to adverse reproductive outcomes, including stillbirth, low birth weight, and neonatal mortality [ 11 ]. As climate change accelerates, even small relative increases in preterm birth risk may translate into substantial absolute increases in adverse outcomes, particularly in regions already experiencing high baseline rates of preterm delivery. 4.3 Biological plausibility and mechanistic pathways Several biologically plausible mechanisms support the observed association between heat exposure and preterm birth. Maternal heat stress may lead to dehydration and hemoconcentration, reducing uteroplacental blood flow and potentially triggering uterine contractions [ 12 ]. Elevated temperatures have also been linked to systemic inflammatory activation, oxidative stress, and endocrine disruption, all of which are implicated in the initiation of parturition [ 13 ]. Additionally, thermal stress may impair placental function, alter fetal thermoregulation, and increase the release of stress hormones such as cortisol and catecholamines, which can precipitate early labor [ 14 ]. Although mechanistic pathways were not directly assessed in the included epidemiological studies, the convergence of biological and observational evidence strengthens the plausibility of a causal relationship. 4.4 Susceptible exposure windows and population heterogeneity Several studies identified late pregnancy as a particularly susceptible window, with positive associations observed during the final weeks preceding delivery [ 15 ]. This temporal specificity is consistent with the hypothesis that acute environmental stressors may act as triggers of labor once pregnancy approaches term. Evidence also suggests that the impact of heat exposure on preterm birth is not evenly distributed across populations. Studies have reported higher risks among individuals with lower socioeconomic status, limited access to cooling, and residence in highly urbanized or low-greenness environments [ 16 ]. These findings highlight the intersection between climate change, social vulnerability, and reproductive health, reinforcing the importance of equity-focused adaptation strategies. 4.5 Public health implications From a public health perspective, the findings underscore the need to explicitly recognize pregnant individuals as a high-risk group in heat-health warning systems. While existing heat action plans often prioritize older adults and individuals with chronic disease, maternal health considerations are frequently absent [ 17 ]. Targeted interventions may include anticipatory guidance during antenatal care, public messaging focused on hydration and heat avoidance, and ensuring access to cooling during extreme heat events. Integrating heat exposure risk into routine prenatal counseling particularly during warmer months and late gestation could represent a low-cost, high-impact preventive strategy. 4.6 Policy relevance and climate adaptation At the policy level, the findings support the inclusion of maternal and perinatal outcomes in climate adaptation and mitigation frameworks. Urban planning strategies that reduce ambient temperatures such as increasing green spaces, improving housing insulation, and mitigating urban heat islands may yield co-benefits for maternal and infant health [ 18 ]. In low- and middle-income countries, where heat exposure often coincides with limited health system capacity, targeted investments in maternal health services and climate-resilient infrastructure are essential. More broadly, mitigating greenhouse gas emissions remains fundamental to reducing long-term heat-related health risks, reinforcing the close linkage between climate policy and reproductive health outcomes. 4.7 Strengths and limitations This review has several strengths, including adherence to PRISMA 2020 guidelines, comprehensive database searching, and the application of a random-effects meta-analysis to account for between-study heterogeneity. Nevertheless, limitations should be acknowledged. The relatively small number of studies included in the quantitative synthesis limited the ability to conduct subgroup and sensitivity analyses. Exposure definitions varied across studies, and residual confounding particularly by air pollution cannot be entirely excluded. Additionally, most evidence originated from high-income settings, potentially limiting generalizability to regions with different climatic and social contexts. 4.8 Future research directions Future research should prioritize standardized definitions of heat exposure, improved spatial and temporal exposure assessment, and greater representation of low-income and highly climate-vulnerable regions. Prospective cohort studies incorporating biological markers of heat stress may further elucidate causal pathways. Importantly, evaluating the effectiveness of heat-mitigation interventions during pregnancy will be critical for translating epidemiological evidence into actionable policy. 4.9 Summary of Findings In summary, this systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. As climate change continues to intensify global heat exposure, protecting pregnant populations should be recognized as a public health and policy priority. Integrating maternal health into climate adaptation strategies offers an important opportunity to reduce preventable adverse birth outcomes in a warming world. 5. CONCLUSION This systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. Across diverse geographic settings and study designs, the direction of association was consistent, suggesting that elevated ambient temperatures and heatwave events represent a meaningful environmental risk factor for adverse birth outcomes. Although the observed effect sizes were modest, their potential population-level impact is substantial given the widespread and increasing exposure to extreme heat. These findings have important implications in the context of climate change, which is intensifying global heat exposure and disproportionately affecting vulnerable populations. Integrating maternal health considerations into heat–health warning systems, antenatal care practices, and climate adaptation strategies is essential. Protecting pregnant individuals from extreme heat should be recognized as a public health priority to reduce preventable preterm births in a warming world. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Clinical trial number: Not applicable. Availability of data and materials The data supporting the findings of this study are derived from previously published studies and are available within the article and its supplementary materials. No new primary datasets were generated. Competing interests The authors declare no competing interests. Funding The authors received no specific funding for this work. Authors’ contributions AS conceptualized the study, conducted the literature search, performed data extraction and analysis, and drafted the manuscript. All authors contributed to study design, interpretation of results, critical revision of the manuscript, and approved the final version. Acknowledgements The authors acknowledge the use of AI-assisted tools for figure design and language refinement. All data extraction, analyses, and interpretations were performed and verified by the authors. References Wang J, Tong S, Williams G, Pan X. Exposure to heat wave during pregnancy and adverse birth outcomes: an exploration of susceptible windows. Epidemiology. 2019;30(Suppl 1):S115–S121. https://doi.org/10.1097/EDE.0000000000000995 Sun S, Weinberger KR, Spangler KR, Eliot MN, Braun JM, Wellenius GA. Ambient temperature and preterm birth: a retrospective study of 32 million US singleton births. 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Exposure to heat during pregnancy and preterm birth in North Carolina: disparities by residential greenness, urbanicity, and socioeconomic status. Environmental Research. 2021;198:111579. https://doi.org/10.1016/j.envres.2021.111579 World Health Organization. Preterm birth. Geneva: World Health Organization; 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/preterm-birth Intergovernmental Panel on Climate Change. Climate Change 2023: Synthesis Report. Geneva: IPCC; 2023. Available from: https://www.ipcc.ch/report/ar6/syr/ Romanello M, Di Napoli C, Drummond P, et al. The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future. The Lancet. 2021;398(10311):1619–1662. https://doi.org/10.1016/S0140-6736(21)01787-6 Watts N, Amann M, Ayeb-Karlsson S, Belesova K, Bouley T, Boykoff M, Byass P, Cai W, Campbell-Lendrum D, Chambers J, Cox PM. 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Associations between high temperatures in pregnancy and risk of preterm birth, low birth weight, and stillbirths: a systematic review and meta-analysis. BMJ. 2020;371:m3811. https://doi.org/10.1136/bmj.m3811 Meherali S, Nisa S, Aynalem YA, Kennedy M, Salami B, Adjorlolo S, et al. Impact of climate change on maternal health outcomes: an evidence gap map review. PLOS Global Public Health. 2024;4(8):e0003540. https://doi.org/10.1371/journal.pgph.0003540 Kovats RS, Hajat S. Heat stress and public health: a critical review. Annu Rev Public Health . 2008;29:41–55. https://doi.org/10.1146/annurev.publhealth.29.020907.090843 Bekkar B, Pacheco S, Basu R, DeNicola N. Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the US: a systematic review. JAMA Netw Open . 2020;3(6):e208243. https://doi.org/10.1001/jamanetworkopen.2020.8243 Rylander C, Odland JØ, Sandanger TM. Climate change and the potential effects on maternal and pregnancy outcomes: an assessment of the most vulnerable—the mother, fetus, and newborn child. Glob Health Action . 2013;6:19538. https://doi.org/10.3402/gha.v6i0.19538 Tables Table 1. Risk of bias assessment of included studies using the Newcastle–Ottawa Scale (NOS) Study (Author, Year) Selection (0–4) Comparability (0–2) Outcome (0–3) Total Score (0–9) Overall Risk of Bias Wang et al., 2019 4 2 3 9 Low Sun et al., 2019 4 2 3 9 Low Mohammadi et al., 2019 3 2 3 8 Low Choi et al., 2021 4 2 2 8 Low Gordon et al., 2023 3 1 2 6 Moderate Liang et al., 2018 3 1 2 6 Moderate Abbreviations: NOS, Newcastle–Ottawa Scale. The Newcastle–Ottawa Scale assesses observational studies across three domains: selection of study groups (maximum 4 points), comparability of groups (maximum 2 points), and outcome assessment (maximum 3 points). Studies scoring 7–9 points were considered at low risk of bias, scores of 5–6 at moderate risk, and scores below 5 at high risk of bias. Table 2. Characteristics of included studies Author (Year) Country / Region Study design Study period Sample size Exposure definition Outcome Wang et al. (2019) Australia (Brisbane) Population-based cohort 2000–2010 277,133 births Heatwave defined as ≥2 consecutive days with daily mean temperature above the 95th percentile Preterm birth, stillbirth Sun et al. (2019) United States (nationwide) Retrospective cohort 1969–1988 ~32 million singleton births Ambient temperature assessed as daily mean temperature and percentile-based extremes Preterm birth Mohammadi et al. (2019) Iran (Sabzevar) Time-series analysis 2007–2014 Population-based daily births Extreme temperature defined using high and low temperature thresholds Preterm birth Choi et al. (2021) United States (North Carolina) Population-based cohort 2004–2016 546,441 births Daily mean temperature; heat exposure assessed per 1 °C increase Preterm birth Gordon et al. (2023) United States (Chicago) Ecological time-series July 1995 City-level births Extreme heatwave event Preterm birth Liang et al. (2018) China (Guangdong Province) Time-series analysis 2006–2010 Population-based births Cold spell defined as consecutive days below temperature thresholds Preterm birth Abbreviations: °C, degree Celsius. Heat exposure definitions varied across studies, including percentile-based heatwave thresholds, ambient temperature increments, and extreme temperature events. The cold-spell study was included for qualitative synthesis only and not pooled in the meta-analysis Table 3. Summary of quantitative findings of included studies Author (Year) Exposure contrast Effect measure Effect estimate (95% CI) Exposure window Key covariates adjusted Wang et al. (2019) Heatwave vs non-heatwave days HR 1.08 (1.00–1.18) Whole pregnancy; strongest in late gestation Maternal age, parity, seasonality, long-term trends Sun et al. (2019) Extreme ambient temperature vs reference OR 1.05 (1.03–1.07) Whole pregnancy Maternal characteristics, temporal trends, geographic region Mohammadi et al. (2019) Extreme temperature days vs non-extreme days RR 1.04 (1.01–1.07) Short-term exposure (lag days) Seasonality, long-term trends, meteorological factors Choi et al. (2021) Per 1 °C increase in daily mean temperature HR 1.01 (1.00–1.02) Late pregnancy (final weeks) Maternal age, socioeconomic status, urbanicity, greenness Gordon et al. (2023) Extreme heatwave event vs non-event period Rate ratio Increased preterm birth rates following heatwave (estimate not pooled) Heatwave period Area-level demographic factors Liang et al. (2018) Cold spell vs non-cold period RR Increased preterm birth risk during cold spells (not pooled) Short-term exposure Seasonality, meteorological variables Abbreviations: HR, hazard ratio; OR, odds ratio; RR, relative risk; CI, confidence interval; °C, degree Celsius. Studies reporting heat exposure were eligible for quantitative synthesis. Studies examining cold exposure or reporting non-comparable effect metrics were included in qualitative synthesis only and were not pooled in the meta-analysis. Additional Declarations No competing interests reported. Supplementary Files PRISMA2020Checklist.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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03:59:51","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84603,"visible":true,"origin":"","legend":"","description":"","filename":"c16374fa95b64c798934ee58b0cccfdb1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/6973b066010d9df8dbfc0407.xml"},{"id":100748047,"identity":"9b0d5fb7-0a7b-4666-ba2f-a1a9714cba69","added_by":"auto","created_at":"2026-01-21 04:00:26","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94035,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/eaa4cb8143a21f87357eb3d4.html"},{"id":100747981,"identity":"e2fb99fd-1de0-4f35-8885-3c23cacacc92","added_by":"auto","created_at":"2026-01-21 04:00:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1611073,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework illustrating the relationship between climate change–related heat exposure during pregnancy and the risk of preterm birth. Rising global temperatures and increasing heatwave frequency may contribute to maternal heat stress, which can activate physiological pathways including dehydration, inflammation, endocrine stress responses, and placental dysfunction. Pregnancy is depicted as a climate-vulnerable state, with the association potentially modified by socioeconomic, environmental, and gestational factors. This figure presents hypothesized pathways and does not depict study results.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/d0f9f777bed99a882855f658.png"},{"id":100747969,"identity":"a3336a44-9de2-4713-a800-19b0072b5ced","added_by":"auto","created_at":"2026-01-21 03:59:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1374217,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePRISMA 2020 flow diagram illustrating the identification, screening, eligibility assessment, and inclusion of studies examining the association between heat exposure during pregnancy and adverse birth outcomes. Records were identified through searches of Google Scholar and PubMed, followed by sequential exclusion of secondary studies, grey literature, non-English publications, and records with incomplete or non-extractable data. The diagram summarizes the final number of studies included in the qualitative synthesis and those included in the quantitative meta-analysis.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/3648328b0ee81fb377e06d75.png"},{"id":100748029,"identity":"9c5d8952-8a95-4675-8204-9ef8aa623ec4","added_by":"auto","created_at":"2026-01-21 04:00:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10788,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eForest plot showing individual and pooled effect estimates for the association between heat exposure during pregnancy and the risk of preterm birth. Effect estimates are presented as hazard ratios (HRs), odds ratios (ORs), or relative risks (RRs) with corresponding 95% confidence intervals. A random-effects model was applied to account for between-study heterogeneity. The vertical dashed line represents the null value (effect estimate = 1.0).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/ee0d484e35926fbb84f4ae68.png"},{"id":102673723,"identity":"129a191f-1af9-47f9-8743-305fdce22901","added_by":"auto","created_at":"2026-02-14 15:55:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4094333,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/9d601784-30a0-43ae-b40f-e926a9404923.pdf"},{"id":100747984,"identity":"ad98526b-2f57-432b-97b6-774d56a43f6b","added_by":"auto","created_at":"2026-01-21 04:00:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":178940,"visible":true,"origin":"","legend":"","description":"","filename":"PRISMA2020Checklist.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8455131/v1/57c6691b5695ba66607b5670.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Heat Exposure During Pregnancy and Risk of Preterm Birth: A Systematic Review and Meta-analysis","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003ePreterm birth remains one of the leading causes of neonatal morbidity and mortality worldwide and contributes substantially to long-term neurodevelopmental impairment and chronic disease across the life course [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite advances in obstetric and neonatal care, global rates of preterm birth have declined only modestly, with disproportionate burdens borne by low- and middle-income countries. Identifying modifiable environmental risk factors is therefore critical to reducing preventable adverse birth outcomes and advancing maternal\u0026ndash;child health equity.\u003c/p\u003e \u003cp\u003eConcurrently, climate change has emerged as one of the most significant public health threats of the 21st century, driven by rising global temperatures and an increasing frequency, duration, and intensity of extreme heat events [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Heatwaves are now occurring with greater regularity across most regions of the world, a trend projected to worsen under current emission trajectories [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While the health impacts of extreme heat on older adults and individuals with chronic disease are well established, pregnant individuals remain a comparatively under-recognized climate-vulnerable population within climate\u0026ndash;health frameworks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePregnancy involves complex physiological adaptations, including increased metabolic heat production, expanded plasma volume, and altered thermoregulation, which may reduce tolerance to thermal stress. Growing epidemiological evidence suggests that exposure to elevated ambient temperatures or heatwaves during pregnancy may increase the risk of adverse birth outcomes, particularly preterm birth [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Given the widespread nature of heat exposure, even modest relative increases in risk could translate into substantial population-level impacts, especially as climate change intensifies thermal extremes globally.\u003c/p\u003e \u003cp\u003eAlthough multiple observational studies have examined the association between heat exposure and preterm birth across diverse geographic settings, findings have not been consistently synthesized. Prior reviews have often combined heterogeneous outcomes, included non-quantitative evidence, or addressed climate change broadly without isolating heat exposure as a distinct environmental risk factor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, uncertainty remains regarding the magnitude, consistency, and generalizability of the association between maternal heat exposure and preterm birth.\u003c/p\u003e \u003cp\u003eClarifying this relationship is essential for informing public health preparedness, climate adaptation strategies, and maternal health policy. As heat exposure becomes increasingly unavoidable in many regions, robust synthesis of epidemiological evidence is needed to guide preventive interventions and protect pregnant populations from climate-related health risks. \u003cem\u003eThe hypothesized pathways linking climate change\u0026ndash;related heat exposure during pregnancy to preterm birth are illustrated in\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTherefore, we conducted a systematic review and meta-analysis to synthesize the available epidemiological evidence on the association between heat exposure during pregnancy and the risk of preterm birth.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cp\u003eThis systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1 Search strategy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comprehensive literature search was performed using Google Scholar and PubMed to identify relevant studies examining the association between heat exposure during pregnancy and adverse birth outcomes. For Google Scholar, a 20-year publication window (2005\u0026ndash;2025) was applied to improve relevance.\u003c/p\u003e\n\u003cp\u003eThe search strategy combined controlled vocabulary terms and free-text keywords related to heat exposure, pregnancy, and birth outcomes. Search terms included combinations of:\u003cbr\u003e\u003cem\u003e\u0026ldquo;heatwave\u0026rdquo;, \u0026ldquo;extreme temperature\u0026rdquo;, \u0026ldquo;heat exposure\u0026rdquo;, \u0026ldquo;climate change\u0026rdquo;, \u0026ldquo;pregnancy\u0026rdquo;, \u0026ldquo;pregnant\u0026rdquo;, \u0026ldquo;maternal\u0026rdquo;, \u0026ldquo;preterm birth\u0026rdquo;, \u0026ldquo;low birth weight\u0026rdquo;, and \u0026ldquo;stillbirth\u0026rdquo;\u003c/em\u003e. Boolean operators (AND/OR) were used to refine the search.\u003c/p\u003e\n\u003cp\u003eGoogle Scholar was used to enhance sensitivity and capture environmental health studies not indexed in PubMed, consistent with prior climate\u0026ndash;health systematic reviews. A 20-year (2005-2025) publication window was applied to Google Scholar searches to focus on contemporary evidence. Reference lists of eligible articles were also screened to identify additional relevant studies. The full electronic search strategy is provided in the Supplementary Material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Eligibility criteria (PICOS framework)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies were selected based on the following criteria:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePopulation:\u0026nbsp;\u003c/strong\u003ePregnant individuals and their offspring in human populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure:\u0026nbsp;\u003c/strong\u003eHeat exposure, including ambient temperature, extreme temperature, or heatwave events assessed using meteorological data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparator:\u0026nbsp;\u003c/strong\u003eLower temperature periods or reference temperature ranges, as defined by individual studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes:\u0026nbsp;\u003c/strong\u003ePreterm birth, defined as delivery before 37 completed weeks of gestation. Studies reporting related adverse birth outcomes (e.g., stillbirth) were included in the qualitative synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design:\u0026nbsp;\u003c/strong\u003eObservational epidemiological studies, including cohort and time-series designs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSystematic reviews, meta-analyses, scoping reviews, conference abstracts without full manuscripts, theses, non-English publications, animal or laboratory studies, and studies without extractable quantitative effect estimates were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Study selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll records retrieved from the database searches were screened in a two-stage process. First, titles and abstracts were screened to exclude clearly irrelevant studies. Second, full-text articles of potentially eligible studies were assessed against the predefined inclusion and exclusion criteria.\u003c/p\u003e\n\u003cp\u003eStudy selection was performed independently by the authors, and discrepancies were resolved through discussion and consensus. The study selection process is illustrated using a PRISMA 2020 flow diagram (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Data extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were extracted from included studies using a standardized data extraction form. Extracted information included:\u003c/p\u003e\n\u003cul type=\"square\"\u003e\n \u003cli\u003eAuthor and year of publication\u003c/li\u003e\n \u003cli\u003eCountry and study setting\u003c/li\u003e\n \u003cli\u003eStudy design and study period\u003c/li\u003e\n \u003cli\u003eSample size\u003c/li\u003e\n \u003cli\u003eHeat exposure definition and assessment method\u003c/li\u003e\n \u003cli\u003eOutcome definition\u003c/li\u003e\n \u003cli\u003eEffect estimates (hazard ratios, odds ratios, or relative risks) with 95% confidence intervals\u003c/li\u003e\n \u003cli\u003eCovariates included in the adjusted models\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWhen multiple estimates were reported, the most fully adjusted estimate was extracted for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Risk of bias assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe methodological quality and risk of bias of included observational studies were assessed using the Newcastle\u0026ndash;Ottawa Scale (NOS) (Table 1). The NOS evaluates studies across three domains:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eSelection of study groups\u003c/li\u003e\n \u003cli\u003eComparability of groups\u003c/li\u003e\n \u003cli\u003eOutcome assessment\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eEach study was independently assessed, and studies were categorized as having low, moderate, or high risk of bias based on their NOS scores. The results of the risk of bias assessment are summarized in a dedicated table provided in the Supplementary Material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA meta-analysis was conducted for studies reporting comparable quantitative effect estimates for the association between heat exposure during pregnancy and preterm birth. Hazard ratios (HRs), odds ratios (ORs), and relative risks (RRs) were pooled assuming rare outcomes, consistent with epidemiological meta-analytic practice for preterm birth.\u003c/p\u003e\n\u003cp\u003eA random-effects model was applied to account for between-study heterogeneity arising from differences in study design, exposure definitions, and populations. Statistical heterogeneity was assessed using the I\u0026sup2; statistic, with higher values indicating greater heterogeneity.\u003c/p\u003e\n\u003cp\u003eSensitivity analyses and assessment of publication bias were not performed due to the limited number of studies included in the quantitative synthesis, in accordance with methodological recommendations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Software\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using R (version 4.3.2).\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eForest plots were generated using standard meta-analysis packages. Figure design and formatting were supported by AI-assisted tools; however, all data extraction, analyses, and interpretations were performed and verified by the authors.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1 Study selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe literature search identified 2,410 records from Google Scholar and 225 records from PubMed. After applying a 20-year publication filter and removing secondary studies, grey literature, non-English publications, and records with incomplete or irrelevant data, 11 full-text articles from Google Scholar were assessed for eligibility. From Google Scholar alone, two studies met the criteria for quantitative synthesis; however, after combining eligible studies from PubMed and Google Scholar, a total of four studies were included in the final meta-analysis.\u003c/p\u003e\n\u003cp\u003eFrom the PubMed database, most records were excluded during title and abstract screening because they were review articles, commentaries, non-original research, or did not assess heat exposure in relation to pregnancy outcomes. Following title, abstract, and full-text assessment, three primary studies from PubMed met the eligibility criteria and were included in the systematic review.\u003c/p\u003e\n\u003cp\u003eOverall, seven studies were included in the qualitative synthesis, and four studies were included in the meta-analysis. The study selection process is summarized in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Characteristics of included studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe characteristics of the included studies are presented in Table 2. The studies were published between 2014 and 2023 and consisted of population-based cohort studies and time-series analyses conducted in Australia, the United States, Iran, and China (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021; Gordon et al., 2023; Liang et al., 2018).\u003c/p\u003e\n\u003cp\u003eSample sizes varied substantially, ranging from regional population-based daily birth counts to nationwide cohorts comprising more than 32 million singleton births (Sun et al., 2019). Heat exposure was operationalized using multiple metrics, including percentile-based heatwave definitions, daily mean ambient temperature, and extreme temperature thresholds. Across studies, preterm birth, most commonly defined as delivery before 37 completed weeks of gestation, was the primary outcome of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Qualitative synthesis of findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.1 Heat exposure and preterm birth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross the included studies, exposure to elevated ambient temperatures or heatwave conditions during pregnancy was consistently associated with an increased risk of preterm birth (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021). All four studies included in the meta-analysis reported adjusted effect estimates above the null, with hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08 (Table 2).\u003c/p\u003e\n\u003cp\u003eLarge population-based cohort studies conducted in Australia and the United States demonstrated higher risks of preterm delivery associated with heatwave exposure or increasing ambient temperature (Wang et al., 2019; Sun et al., 2019). Time-series analyses similarly reported short-term increases in preterm birth following periods of extreme temperature exposure (Mohammadi et al., 2019). The consistency and magnitude of these associations are further illustrated in the forest plot (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.2 Susceptible exposure windows\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral studies evaluated potential windows of heightened vulnerability during pregnancy. Positive associations between heat exposure and preterm birth were frequently observed during late gestation, particularly in the final weeks preceding delivery (Wang et al., 2019; Choi et al., 2021). In time-series analyses, short-term exposure to extreme temperatures over lag periods of a few days was associated with increases in daily preterm birth counts (Mohammadi et al., 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.3 Population characteristics and contextual factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome studies reported heterogeneity in heat-related preterm birth risk across population subgroups. Differences were observed according to socioeconomic characteristics, residential context, and geographic location, with higher risks reported among socioeconomically disadvantaged populations in certain settings (Choi et al., 2021; Gordon et al., 2023). However, subgroup analyses were not consistently performed across all studies. A quantitative summary of individual study findings is provided in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Quantitative synthesis (meta-analysis)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.1 Main meta-analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour studies were included in the meta-analysis examining the association between heat exposure during pregnancy and preterm birth (Wang et al., 2019; Sun et al., 2019; Mohammadi et al., 2019; Choi et al., 2021). A random-effects model was used to account for between-study variability in exposure definitions and study design. All included studies demonstrated effect estimates greater than one, indicating a positive association between heat exposure and preterm birth. Statistical heterogeneity was assessed using the I\u0026sup2; statistic and interpreted cautiously due to the limited number of included studies. Individual study estimates and their corresponding 95% confidence intervals are displayed in Figure 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.2 Heterogeneity assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eModerate heterogeneity was observed across studies, reflecting differences in geographic context, exposure assessment, and analytical approaches. Statistical heterogeneity was assessed using the I\u0026sup2; statistic and interpreted cautiously due to the limited number of studies included in the quantitative synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.3 Sensitivity analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSensitivity analyses were not performed owing to the small number of studies included in the meta-analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.4 Publication bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAssessment of publication bias using funnel plots or statistical tests was not conducted because fewer than ten studies were included in the meta-analysis.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Principal findings\u003c/h2\u003e \u003cp\u003eThis systematic review and meta-analysis synthesizes evidence from diverse geographic and climatic contexts and provides evidence of a consistent association between maternal heat exposure and increased risk of preterm birth. Across the four studies included in the quantitative synthesis, all adjusted effect estimates exceeded the null, with hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although these effect sizes are modest at the individual level, they are highly relevant at the population level, given the widespread and increasing exposure to extreme heat and the substantial global burden of preterm birth.\u003c/p\u003e \u003cp\u003eThe qualitative synthesis further supported these findings, with additional studies reporting elevated preterm birth rates following heatwave events or extreme temperature episodes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Taken together, the results indicate that heat exposure during pregnancy is a reproducible and globally relevant environmental exposure associated with preterm birth.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Findings in the context of climate change\u003c/h2\u003e \u003cp\u003eThe observed associations must be interpreted within the broader context of global climate change, which is driving an increase in the frequency, duration, and intensity of heatwaves worldwide [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Pregnant individuals represent a climate-vulnerable population, yet maternal and perinatal outcomes have historically been underrepresented in climate\u0026ndash;health research and policy frameworks [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFindings of this study align with and extend prior evidence linking ambient temperature extremes to adverse reproductive outcomes, including stillbirth, low birth weight, and neonatal mortality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As climate change accelerates, even small relative increases in preterm birth risk may translate into substantial absolute increases in adverse outcomes, particularly in regions already experiencing high baseline rates of preterm delivery.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Biological plausibility and mechanistic pathways\u003c/h2\u003e \u003cp\u003eSeveral biologically plausible mechanisms support the observed association between heat exposure and preterm birth. Maternal heat stress may lead to dehydration and hemoconcentration, reducing uteroplacental blood flow and potentially triggering uterine contractions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Elevated temperatures have also been linked to systemic inflammatory activation, oxidative stress, and endocrine disruption, all of which are implicated in the initiation of parturition [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, thermal stress may impair placental function, alter fetal thermoregulation, and increase the release of stress hormones such as cortisol and catecholamines, which can precipitate early labor [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although mechanistic pathways were not directly assessed in the included epidemiological studies, the convergence of biological and observational evidence strengthens the plausibility of a causal relationship.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Susceptible exposure windows and population heterogeneity\u003c/h2\u003e \u003cp\u003eSeveral studies identified late pregnancy as a particularly susceptible window, with positive associations observed during the final weeks preceding delivery [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This temporal specificity is consistent with the hypothesis that acute environmental stressors may act as triggers of labor once pregnancy approaches term.\u003c/p\u003e \u003cp\u003eEvidence also suggests that the impact of heat exposure on preterm birth is not evenly distributed across populations. Studies have reported higher risks among individuals with lower socioeconomic status, limited access to cooling, and residence in highly urbanized or low-greenness environments [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These findings highlight the intersection between climate change, social vulnerability, and reproductive health, reinforcing the importance of equity-focused adaptation strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Public health implications\u003c/h2\u003e \u003cp\u003eFrom a public health perspective, the findings underscore the need to explicitly recognize pregnant individuals as a high-risk group in heat-health warning systems. While existing heat action plans often prioritize older adults and individuals with chronic disease, maternal health considerations are frequently absent [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTargeted interventions may include anticipatory guidance during antenatal care, public messaging focused on hydration and heat avoidance, and ensuring access to cooling during extreme heat events. Integrating heat exposure risk into routine prenatal counseling particularly during warmer months and late gestation could represent a low-cost, high-impact preventive strategy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Policy relevance and climate adaptation\u003c/h2\u003e \u003cp\u003eAt the policy level, the findings support the inclusion of maternal and perinatal outcomes in climate adaptation and mitigation frameworks. Urban planning strategies that reduce ambient temperatures such as increasing green spaces, improving housing insulation, and mitigating urban heat islands may yield co-benefits for maternal and infant health [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn low- and middle-income countries, where heat exposure often coincides with limited health system capacity, targeted investments in maternal health services and climate-resilient infrastructure are essential. More broadly, mitigating greenhouse gas emissions remains fundamental to reducing long-term heat-related health risks, reinforcing the close linkage between climate policy and reproductive health outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Strengths and limitations\u003c/h2\u003e \u003cp\u003eThis review has several strengths, including adherence to PRISMA 2020 guidelines, comprehensive database searching, and the application of a random-effects meta-analysis to account for between-study heterogeneity. Nevertheless, limitations should be acknowledged. The relatively small number of studies included in the quantitative synthesis limited the ability to conduct subgroup and sensitivity analyses. Exposure definitions varied across studies, and residual confounding particularly by air pollution cannot be entirely excluded. Additionally, most evidence originated from high-income settings, potentially limiting generalizability to regions with different climatic and social contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e4.8 Future research directions\u003c/h2\u003e \u003cp\u003eFuture research should prioritize standardized definitions of heat exposure, improved spatial and temporal exposure assessment, and greater representation of low-income and highly climate-vulnerable regions. Prospective cohort studies incorporating biological markers of heat stress may further elucidate causal pathways. Importantly, evaluating the effectiveness of heat-mitigation interventions during pregnancy will be critical for translating epidemiological evidence into actionable policy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e4.9 Summary of Findings\u003c/h2\u003e \u003cp\u003eIn summary, this systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. As climate change continues to intensify global heat exposure, protecting pregnant populations should be recognized as a public health and policy priority. Integrating maternal health into climate adaptation strategies offers an important opportunity to reduce preventable adverse birth outcomes in a warming world.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. Across diverse geographic settings and study designs, the direction of association was consistent, suggesting that elevated ambient temperatures and heatwave events represent a meaningful environmental risk factor for adverse birth outcomes. Although the observed effect sizes were modest, their potential population-level impact is substantial given the widespread and increasing exposure to extreme heat.\u003c/p\u003e \u003cp\u003eThese findings have important implications in the context of climate change, which is intensifying global heat exposure and disproportionately affecting vulnerable populations. Integrating maternal health considerations into heat\u0026ndash;health warning systems, antenatal care practices, and climate adaptation strategies is essential. Protecting pregnant individuals from extreme heat should be recognized as a public health priority to reduce preventable preterm births in a warming world.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are derived from previously published studies and are available within the article and its supplementary materials. No new primary datasets were generated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAS conceptualized the study, conducted the literature search, performed data extraction and analysis, and drafted the manuscript. All authors contributed to study design, interpretation of results, critical revision of the manuscript, and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the use of AI-assisted tools for figure design and language refinement. All data extraction, analyses, and interpretations were performed and verified by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang J, Tong S, Williams G, Pan X. Exposure to heat wave during pregnancy and adverse birth outcomes: an exploration of susceptible windows. Epidemiology. 2019;30(Suppl 1):S115\u0026ndash;S121. https://doi.org/10.1097/EDE.0000000000000995 \u003c/li\u003e\n\u003cli\u003eSun S, Weinberger KR, Spangler KR, Eliot MN, Braun JM, Wellenius GA. Ambient temperature and preterm birth: a retrospective study of 32 million US singleton births. Environment International. 2019;126:7\u0026ndash;13. https://doi.org/10.1016/j.envint.2019.02.023 \u003c/li\u003e\n\u003cli\u003eMohammadi D, Naghshineh E, Sarsangi A, Zare Sakhvidi MJ. Environmental extreme temperature and daily preterm birth in Sabzevar, Iran: a time-series analysis. Environmental Health and Preventive Medicine. 2019;24:5. https://doi.org/10.1186/s12199-018-0760-x \u003c/li\u003e\n\u003cli\u003eGordon M, Casey JA, McBrien H, Gemmill A, Hern\u0026aacute;ndez D, Catalano R, et al. Disparities in preterm birth following the July 1995 Chicago heat wave. Annals of Epidemiology. 2023;87:31\u0026ndash;37. https://doi.org/10.1016/j.annepidem.2023.08.003 \u003c/li\u003e\n\u003cli\u003eLiang Z, Wang P, Zhao Q, Wang BQ, Ma Y, Lin H, et al. Effect of the 2008 cold spell on preterm births in two subtropical cities of Guangdong Province, Southern China. Science of the Total Environment. 2018;642:307\u0026ndash;313. https://doi.org/10.1016/j.scitotenv.2018.06.052 \u003c/li\u003e\n\u003cli\u003eChoi HM, Son JY, Bell ML, Miranda ML. Exposure to heat during pregnancy and preterm birth in North Carolina: disparities by residential greenness, urbanicity, and socioeconomic status. Environmental Research. 2021;198:111579. https://doi.org/10.1016/j.envres.2021.111579 \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Preterm birth. Geneva: World Health Organization; 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/preterm-birth \u003c/li\u003e\n\u003cli\u003eIntergovernmental Panel on Climate Change. Climate Change 2023: Synthesis Report. Geneva: IPCC; 2023. Available from: https://www.ipcc.ch/report/ar6/syr/ \u003c/li\u003e\n\u003cli\u003eRomanello M, Di Napoli C, Drummond P, et al. The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future. The Lancet. 2021;398(10311):1619\u0026ndash;1662. https://doi.org/10.1016/S0140-6736(21)01787-6 \u003c/li\u003e\n\u003cli\u003eWatts N, Amann M, Ayeb-Karlsson S, Belesova K, Bouley T, Boykoff M, Byass P, Cai W, Campbell-Lendrum D, Chambers J, Cox PM. The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health. The Lancet. 2018 Feb 10;391(10120):581-630. https://doi.org/10.1016/S0140-6736(18)32594-7 \u003c/li\u003e\n\u003cli\u003eBasu R, Malig B, Ostro B. High ambient temperature and the risk of preterm delivery. American journal of epidemiology. 2010 Nov 15;172(10):1108-17. https://doi.org/10.1093/aje/kwq170 \u003c/li\u003e\n\u003cli\u003eHa S, Liu D, Zhu Y, Kim SS, Sherman S, Grantz KL, Mendola P. Ambient temperature and stillbirth: a multi-center retrospective cohort study. Environmental health perspectives. 2017 Jun 22;125(6):067011. https://doi.org/10.1289/EHP945 \u003c/li\u003e\n\u003cli\u003eBlencowe H, Cousens S, Oestergaard MZ, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis. The Lancet. 2012;379(9832):2162\u0026ndash;2172. https://doi.org/10.1016/S0140-6736(12)60820-4 \u003c/li\u003e\n\u003cli\u003eChersich MF, Pham MD, Areal A, et al. Associations between high temperatures in pregnancy and risk of preterm birth, low birth weight, and stillbirths: a systematic review and meta-analysis. BMJ. 2020;371:m3811. https://doi.org/10.1136/bmj.m3811 \u003c/li\u003e\n\u003cli\u003eMeherali S, Nisa S, Aynalem YA, Kennedy M, Salami B, Adjorlolo S, et al. Impact of climate change on maternal health outcomes: an evidence gap map review. PLOS Global Public Health. 2024;4(8):e0003540. https://doi.org/10.1371/journal.pgph.0003540 \u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eKovats RS, Hajat S.\u003c/strong\u003e Heat stress and public health: a critical review. \u003cem\u003eAnnu Rev Public Health\u003c/em\u003e. 2008;29:41\u0026ndash;55. https://doi.org/10.1146/annurev.publhealth.29.020907.090843\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBekkar B, Pacheco S, Basu R, DeNicola N.\u003c/strong\u003e Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the US: a systematic review. \u003cem\u003eJAMA Netw Open\u003c/em\u003e. 2020;3(6):e208243. https://doi.org/10.1001/jamanetworkopen.2020.8243\u003c/li\u003e\n\u003cli\u003eRylander C, Odland J\u0026Oslash;, Sandanger TM. Climate change and the potential effects on maternal and pregnancy outcomes: an assessment of the most vulnerable\u0026mdash;the mother, fetus, and newborn child. \u003cem\u003eGlob Health Action\u003c/em\u003e. 2013;6:19538. https://doi.org/10.3402/gha.v6i0.19538 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Risk of bias assessment of included studies using the Newcastle\u0026ndash;Ottawa Scale (NOS)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStudy (Author, Year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSelection (0\u0026ndash;4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparability (0\u0026ndash;2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome (0\u0026ndash;3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Score (0\u0026ndash;9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Risk of Bias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWang et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSun et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMohammadi et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChoi et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGordon et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLiang et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;NOS, Newcastle\u0026ndash;Ottawa Scale. The Newcastle\u0026ndash;Ottawa Scale assesses observational studies across three domains: selection of study groups (maximum 4 points), comparability of groups (maximum 2 points), and outcome assessment (maximum 3 points). Studies scoring 7\u0026ndash;9 points were considered at low risk of bias, scores of 5\u0026ndash;6 at moderate risk, and scores below 5 at high risk of bias.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Characteristics of included studies\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor (Year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCountry / Region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStudy period\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eExposure definition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWang et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAustralia (Brisbane)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePopulation-based cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2000\u0026ndash;2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e277,133 births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeatwave defined as \u0026ge;2 consecutive days with daily mean temperature above the 95th percentile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth, stillbirth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSun et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnited States (nationwide)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRetrospective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1969\u0026ndash;1988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e~32 million singleton births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmbient temperature assessed as daily mean temperature and percentile-based extremes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMohammadi et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIran (Sabzevar)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTime-series analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2007\u0026ndash;2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePopulation-based daily births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExtreme temperature defined using high and low temperature thresholds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChoi et al. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnited States (North Carolina)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePopulation-based cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2004\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e546,441 births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDaily mean temperature; heat exposure assessed per 1 \u0026deg;C increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGordon et al. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnited States (Chicago)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEcological time-series\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJuly 1995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCity-level births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExtreme heatwave event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLiang et al. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChina (Guangdong Province)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTime-series analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2006\u0026ndash;2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePopulation-based births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCold spell defined as consecutive days below temperature thresholds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePreterm birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u0026deg;C, degree Celsius. Heat exposure definitions varied across studies, including percentile-based heatwave thresholds, ambient temperature increments, and extreme temperature events. The cold-spell study was included for qualitative synthesis only and not pooled in the meta-analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Summary of quantitative findings of included studies\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor (Year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eExposure contrast\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEffect measure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEffect estimate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eExposure window\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eKey covariates adjusted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWang et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeatwave vs non-heatwave days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08 (1.00\u0026ndash;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWhole pregnancy; strongest in late gestation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMaternal age, parity, seasonality, long-term trends\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSun et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExtreme ambient temperature vs reference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.05 (1.03\u0026ndash;1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWhole pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMaternal characteristics, temporal trends, geographic region\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMohammadi et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExtreme temperature days vs non-extreme days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.04 (1.01\u0026ndash;1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eShort-term exposure (lag days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSeasonality, long-term trends, meteorological factors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChoi et al. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePer 1 \u0026deg;C increase in daily mean temperature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.01 (1.00\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLate pregnancy (final weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMaternal age, socioeconomic status, urbanicity, greenness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGordon et al. (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eExtreme heatwave event vs non-event period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRate ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIncreased preterm birth rates following heatwave (estimate not pooled)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeatwave period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eArea-level demographic factors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLiang et al. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCold spell vs non-cold period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIncreased preterm birth risk during cold spells (not pooled)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eShort-term exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSeasonality, meteorological variables\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;HR, hazard ratio; OR, odds ratio; RR, relative risk; CI, confidence interval; \u0026deg;C, degree Celsius. Studies reporting heat exposure were eligible for quantitative synthesis. Studies examining cold exposure or reporting non-comparable effect metrics were included in qualitative synthesis only and were not pooled in the meta-analysis.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heat Exposure, Preterm Birth, Pregnancy, Climate Change, Maternal Health, Systematic Review","lastPublishedDoi":"10.21203/rs.3.rs-8455131/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8455131/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePreterm birth is a leading cause of neonatal morbidity and mortality worldwide. Concurrently, climate change is increasing the frequency, intensity, and duration of extreme heat events, yet pregnant individuals remain an under-recognized climate-vulnerable population. Although growing evidence suggests that heat exposure during pregnancy may increase the risk of preterm birth, findings have not been consistently synthesized.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a systematic review and meta-analysis in accordance with PRISMA 2020 guidelines. PubMed and Google Scholar were searched from database inception to December 2025 for observational studies examining the association between heat exposure during pregnancy and preterm birth. Eligible studies included cohort and time-series designs reporting quantitative effect estimates. Risk of bias was assessed using the Newcastle–Ottawa Scale. A random-effects meta-analysis was performed to pool comparable effect estimates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 2,635 records were identified, of which seven studies met the inclusion criteria for qualitative synthesis and four studies were included in the final meta-analysis. All studies included in the quantitative synthesis reported positive associations between heat exposure during pregnancy and preterm birth, with adjusted hazard ratios, odds ratios, or relative risks ranging from 1.01 to 1.08. Despite heterogeneity in exposure definitions and study settings, the direction of association was consistent across studies. Overall, the included studies were judged to have low to moderate risk of bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThis systematic review and meta-analysis provides evidence that heat exposure during pregnancy is associated with an increased risk of preterm birth. As climate change continues to intensify global heat exposure, integrating maternal health considerations into heat–health action plans and climate adaptation strategies is essential to reduce preventable adverse birth outcomes.\u003c/p\u003e","manuscriptTitle":"Heat Exposure During Pregnancy and Risk of Preterm Birth: A Systematic Review and Meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-21 03:58:25","doi":"10.21203/rs.3.rs-8455131/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0028ae42-d9fb-49b2-8f05-0c9d0653a218","owner":[],"postedDate":"January 21st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-14T15:54:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-21 03:58:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8455131","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8455131","identity":"rs-8455131","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}