{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T07:06:06Z","timestamp":1780556766384,"version":"3.54.1"},"update-to":[{"DOI":"10.12688\/wellcomeopenres.23909.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000}}],"reference-count":55,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["wellcomeopenresearch.org"],"crossmark-restriction":false},"short-container-title":["Wellcome Open Res"],"abstract":"<ns3:p>Background Pregnant individuals and children are particularly vulnerable to the adverse health consequences of exposure to heat. Leveraging the robust ecosystem of Brazilian linked administrative data, we aim to advance our understanding of how high temperatures and heatwaves influence birth outcomes and child nutrition. Objectives Investigate the association between high ambient temperatures\/ heatwaves and 1) birth outcomes (low birth weight (LBW), small for gestational age (SGA), large for gestational age (LGA), and preterm birth), 2) child nutrition (growth), and 3) breastfeeding practices and complementary feeding in children. Methods We will triangulate results from complementary analytical approaches, including time-stratified case-crossover designs and time-to-event techniques. We will explore the influence of high temperatures and heatwaves at different periods (or lags) preceding the event and apply distributed lag non-linear models to account for delayed and non-linear effects. We will conduct subgroup analyses to identify the population groups most at risk. Results and Conclusions Our study will generate new insights into the relationship between heat, birth outcomes, and child nutrition in Brazil. By providing evidence from a middle-income country with diverse ecosystems and climate zones in a context of social inequalities, this research will contribute to advancing the current knowledge base. Additionally, by identifying critical windows of vulnerability and at-risk groups, our findings can potentially inform targeted and equitable climate adaptation policies.<\/ns3:p>","DOI":"10.12688\/wellcomeopenres.23909.2","type":"journal-article","created":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T09:20:09Z","timestamp":1756372809000},"page":"169","update-policy":"https:\/\/doi.org\/10.12688\/wellcomeopenres.crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Impact of Heat on Birth Outcomes and Child Nutrition: Study Protocol using the CIDACS Birth Cohort"],"prefix":"10.12688","volume":"10","author":[{"given":"Rita de C\u00e1ssia","family":"Ribeiro-Silva","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0379-4745","authenticated-orcid":false,"given":"Maxine","family":"Pepper","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priscila","family":"Ribas de Farias Costa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taisa","family":"Rodrigues Cortes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lais","family":"Sacramento","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2974-7955","authenticated-orcid":false,"given":"Lais Helena","family":"Ribeiro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1287-0623","authenticated-orcid":false,"given":"Lisianne","family":"Passos Luz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Otavio T.","family":"Ranzani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9168-6022","authenticated-orcid":false,"given":"Liam","family":"Smeeth","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth B.","family":"Brickley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aline","family":"dos Santos Rocha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia","family":"M. 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status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.21956\/wellcomeopenres.27286.r130878, Ana Bonell, London School of Hygiene and Tropical Medicine Faculty of Epidemiology and Population Health, London, 04 Sep 2025, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/10-169\/v2#referee-response-130878","order":0,"name":"referee-response-130878","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.26377.r123928, John Molitor, Oregon State University, Corvallis, Oregon, 23 Jun 2025, version 1, 2 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/10-169\/v1#referee-response-123928","order":1,"name":"referee-response-123928","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Enny Paixao Cruz<\/b>; \n<i>Posted: 31 Jul 2025<\/i>; This study protocol outlines a highly promising and timely investigation into the health impacts of heat exposure on birth outcomes, child nutrition, and feeding practices in Brazil. The research team leverages a remarkable array of linked administrative datasets, and the analytical plan demonstrates thoughtful consideration of time-varying exposures and lagged effects. The project is especially important in the context of low- and middle-income countries, where such large-scale evidence is scarce yet urgently needed. The proposed methodology is largely sound and appropriately ambitious, including use of distributed lag non-linear models (DLNMs), case-crossover designs, and time-to-event analyses. Thank you very much for your review  However, one critical limitation is the absence of spatial statistical modeling. The current approach aggregates exposures at the municipality level, but this overlooks two important concerns: spatial correlation in both exposures and outcomes and how these correlations affect associations.  To address this, the authors should consider spatially varying coefficient (SVC) models, ideally within the R-INLA framework, which is well-suited for large-scale hierarchical models with spatial components. Incorporating spatially structured random effects (e.g., using BYM2) or allowing exposure effects to vary geographically would offer two major advantages: First, it would account for spatial dependence and unmeasured area-level confounding; second, it would allow the team to detect regional variation in the heat-health relationship\u2014variation that is likely to be highly relevant for targeted adaptation policy. Given the availability of rich spatial data through CIDACS, this is a missed opportunity and should be considered as and addition to the analysis strategy. Thank you for highlighting this issue. We plan to explore spatial correlation within a Bayesian framework in future analyses, particularly when evaluating small-areas and or taking advantage of the strengths of such model, as noted by the reviewer \u2013 e.g., for detecting regional variations. We also intend to evaluate the recently formalized Spatial-Bayesian DLNM approach (Quijal-Zamorano et al., 2024). However, due to the current lack of an exposure model with higher resolution and lack of better geocoding (beyond the municipality level), we have left it for a secondary analysis. For now, we have taken a more conservative approach by having strata by municipality. We agree this represents a missed opportunity and have acknowledged it as a limitation in the manuscript: \u201cFurthermore, there are also limitations related to the exposure data. Temperature was assessed at the municipality level, which may lead to measurement error due to the inability to capture within-municipality variation, such as urban heat island effects. However, prior studies on mortality have shown that using city-level average temperatures produces results similar to those obtained with more spatially resolved models, suggesting that municipality-level exposure may still provide reasonable estimates. In future work, finer-scale exposure data \u2013 such as at the census tract level \u2013 may become available through the CIDACS Climate and Health Platform, offering opportunities for more spatially refined analyses, exploring spatial correlation within a Bayesian framework, such as the recently formalised spatial Bayesian DLNM approach.\u201d ll. 466-476 &nbsp;  \n<b>#9<\/b> The authors state: &quot;Two approaches have been employed to perform record linkage between the data sources: (a) deterministic linkage and (b) probabilistic linkage based on a similarity index.&quot; Only the deterministic linkage method appears to be described in the protocol; it would be helpful to clarify whether the probabilistic approach was used in this study. Thank you for this. We have now described both approaches in the manuscript. \u201cThe deterministic approach uses a unique identifier common in the two linked datasets. For example, climatic data from the CIDACS Climate and Health Platform was incorporated into the cohort database through deterministic linkage, using the municipality code of the mother's residence as a common identifier between datasets. To link the CIDACS Birth Cohort baseline with the SISVAN dataset, deterministic linkage was performed using a unique identifier available in both datasets \u2013 the Social Information Number (NIS, N&uacute;mero de Identifica&ccedil;&atilde;o Social). For records with missing NIS data, a non-deterministic linkage approach, similar to the method used to create the CIDACS Birth Cohort, was applied. The non-deterministic linkage process used to create the CIDACS Birth Cohort is described in detail by Almeida et al. (28). Matching criteria included variables such as maternal name, date of birth or age, and place of residence. This linkage was conducted using CIDACS-Record Linkage, an innovative tool developed at the Center for Data and Knowledge Integration for Health (CIDACS-RL) (29). CIDACS-RL utilizes a combination of indexing and search algorithms to identify records in the CIDACS Birth Cohort that closely match each record in the other datasets. The tool conducts pairwise comparisons of candidate linking records, ranks them based on similarity scores, and retains the highest-scoring pair as the potential link. The accuracy of each linkage will be assessed and described through manual verification of a random sample of records, evaluating sensitivity and specificity indexes via receiver operating characteristic curves.\u201d ll. 257-275  \n<b>#10 <\/b>Other aspects of the protocol could benefit from clarification. For instance, it is not clear how the two climate datasets (ERA5-Land and BR-DWGD) will be integrated or reconciled; more detail would be helpful. Please see our response to comment #3  \n<b>#11 <\/b>The representativeness of SISVAN data, which appears to be limited to children engaging with the health system, raises concerns about selection bias. Please see our response to comment #2  \n<b>#12 <\/b>Finally, a dedicated limitations section would improve the transparency of the protocol, especially around spatial misclassification, data representativeness, and the ecological nature of some exposure assignments. Please see our response to comment #5  \n<b>#13 <\/b>Similarly, the growth and nutrition analyses should reflect the biological distinctions between wasting and stunting and their likely differing relationships with heat exposure across child age groups. Please see our response to comment #6 In summary, this protocol represents an important and well-constructed study with the potential for significant impact. Incorporating spatially structured and spatially varying effects would substantially strengthen its methodological rigor and real-world relevance and should be seriously considered as part of the core analytical strategy. Thank you.","URL":"https:\/\/wellcomeopenresearch.org\/articles\/10-169\/v2#referee-comment-6191","order":2,"name":"referee-comment-6191","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.27286.r132426, Sohail Lakhani, The Aga Khan University, Karachi, Sindh, 25 Sep 2025, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/10-169\/v2#referee-response-132426","order":3,"name":"referee-response-132426","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported by Wellcome [226306]; CNPQ\/DECIT\/SECTICS\/MS N\u00ba18\/2023 - Ci\u00eancia de dados: mudan\u00e7as clim\u00e1ticas e impactos para a sa\u00fade [444383\/2023-9]; MS-SCTIE-Decit\/CNPq [25000.148278\/2022-10]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":4,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}