The Association between Air Temperature and Mortality in Two Brazilian Health Regions

Round 1

Reviewer 1 Report

The reviewer suggests that the manuscript should be re-reviewed after major revision. The reviewer lists the major comments for the authors’ improvement.

(1) Where is the innovation point of the paper? It should be described in the "Abstract" and “introduction”.

（2）What is the knowledge gap does this paper fill compared with previous research? the literature review should be extended.

Author Response

Review 1 comments (Climate):

We thank the reviewer for his/her contribution, which we think will allow us to improve the content of this article.

Reviewer 1:

Comments and Suggestions for Authors

Where is the innovation point of the paper? It should be described in the "Abstract" and “introduction”.

Answer: This research applies a very-well documented state-of-the-art methodology (Gasparrini et al., 2015) which is applied to a tropical country. The application of the proposed approach is innovative as: 

It is applied to large Health Regions, instead to only cities, which has the advantage of giving a bigger picture of climate influence on larger and densely populated areas; It compares two completely different Brazilian regions with distinct climate conditions (Northeast and South); It is applied to measure the association between air temperature and all cause and cause specific deaths, in a tropical country, for which results a scarce; Finally, it provides evidence for decision-making by public entities and community empowerment.

Therefore, and following the reviewer suggestions, changes were made in the abstract and introduction to highlight these points Follows changes made in the abstract as suggested

Please be advised that changes were made to line 14, modified to include changes between lines 17-22. We highlight as requested in relation to innovation in the abstract, we include in lines 23 and 24, which is a research that takes into account the administrative distribution of local health across health regions, which comprise a cluster of municipalities, which in this research correspond to 22 for the health region of Recife and 20 for the health region of Florianópolis.

Follows changes made in the introduction as suggested

In relation to the introduction, line 72 was modified, and lines 49-53 and 67-71 were included, highlighting the importance of consolidating evidence and research in countries such as Brazil as a way of understanding climate change and its impacts on health indicators. As well as the transfer of this knowledge to communities as a way to support decision making in the field of health promotion.

What is the knowledge gap does this paper fill compared with previous research? the literature review should be extended

Answer: This research aims to bring up the discussion about climate change and temperature extremes as an impact factor on health indicators, based on a methodology already consolidated, as well as attributable risk indicators that are not commonly used in the country, enabling thus a comparison to results from other studies. In addition, the research proposes to provide public managers with an effective tool in their decision making in order to mitigate the effects of climate change and its impacts on human health. Although some of these points were also already mentioned in the last paragraphs of the introduction, they were emphasised (Please, see lines 49-53) and several new references were added to the text, namely:

Ferreira, L. de C. M.; Nogueira, M. C.; Pereira, R. V. de B.; de Farias, W. C. M.; Rodrigues, M. M. de S.; Teixeira, M. T. B.; Carvalho, M. S. Ambient temperature and mortality due to acute myocardial infarction in Brazil: an ecological study of time-series analyses. Sci. Rep. 2019, 9, doi:10.1038/s41598-019-50235-8. Zhao, Q.; Li, S.; Coelho, M. S. Z. S.; Saldiva, P. H. N.; Hu, K.; Huxley, R. R.; Abramson, M. J.; Guo, Y. The association between heatwaves and risk of hospitalization in Brazil: a nationwide time series study between 2000 and 2015. PLoS Med. 2019, 16, doi:10.1371/journal.pmed.1002753 Gronlund, C. J.; Sullivan, K. P.; Kefelegn, Y.; Cameron, L.; O’Neill, M. S. Climate change and temperature extremes: A review of heat- and cold-related morbidity and mortality concerns of municipalities. Maturitas 2018, 114, 54–59, doi:10.1016/j.maturitas.2018.06.002.(1) Yang, J.; Hu, L.; Wang, C. Population dynamics modify urban residents’ exposure to extreme temperatures across the United States. Sci. Adv. 2019, 5, eaay3452, doi:10.1126/sciadv.aay3452. Achebak, H.; Devolder, D.; Ballester, J. Trends in temperature-related age-specific and sex-specific mortality from cardiovascular diseases in Spain: a national time-series analysis. Lancet Planet. Heal. 2019, 3, e297–e306, doi:10.1016/S2542-5196(19)30090-7

Author Response File: Author Response.pdf

Reviewer 2 Report

The study by Dr. Péres and colleagues is interesting comparing two distinct regions of Brazil for the potential influence of ambient temperature variation on mortality.

My comments regard:

Methods:  Health effects of temperature was 20 vs. 12 days for the two regions studied.  The authors should provide a better explanation - why should the health effect in a region with more variable temperature last longer than in a region with less temperature variation.  It would be better to run the statistical modeling with the number of days for the health effect being the same for each region.

Figure 3 & Figure 4, panels and legend - I would match the panels and the description of the panels .  The panel I00-99-J00-99 is in the figure legend but not in the panels.  

Discussion can be shortened because there are many repeats of the results section.

Language: Abstract, line 14, introduction line60:  this study was designed to analyze

Abstract, results:  I would suggest to use past tense, because the analyzed results are presented.

Author Response

Review 2 comments (Climate):

We would like to thank the reviewer by its contribution, which enables us to improve the quality of the article.

Reviewer:

My comments regard:

Methods:  Health effects of temperature was 20 vs. 12 days for the two regions studied.  The authors should provide a better explanation - why should the health effect in a region with more variable temperature last longer than in a region with less temperature variation.  It would be better to run the statistical modelling with the number of days for the health effect being the same for each region.

Answer: The maximum lag number of days used to model the effect of air temperature on mortality, in the two regions, was selected flowing previous research performed on cities with similar climate characteristics, based on the best fit model criteria (QAIC) and the consistency of the obtained results. Latter to evaluate the sensitivity of these choices we fit different models to each region varying the number of lag days from 20 to 21, for Florianópolis and from 12 to 21 (following the reviewer suggestion) for Recife. For both regions, the model that presented the lowest QAIC was the one with 21 days of delayed effect. However, for Recife the results obtained (see below) did not showed consistent curves of the association between temperature-mortality. Taking these results into consideration, for Recife, we decided to present in the article the results from with the 14 days of delayed effect model. Compared with regions from the north hemisphere, its frequent to choose for tropical regions lower number of days for the lags delayed effect as we can see in the references below. The rational can be based on the fact that these regions present high average temperatures and lower thermal amplitude which are associated with smaller delayed effects.  Additionally, by using similar number of days for the delayed effect of temperature will allow better comparison with other studies developed in tropical and sub-tropical regions (see below).

Cohen, F.; Dechezleprêtre, A. Mortality inequality, temperature and public health provision: evidence from Mexico; 2017; Scovronick, N.; Sera, F.; Acquaotta, F.; Garzena, D.; Fratianni, S.; Wright, C. Y.; Gasparrini, A. The association between ambient temperature and mortality in South Africa: a time-series analysis. Environ. Res. 2018, 161, 229–235, doi:10.1016/J.ENVRES.2017.11.001. Son, J.-Y.; Gouveia, N.; Bravo, M. A.; de Freitas, C. U.; Bell, M. L. The impact of temperature on mortality in a subtropical city: effects of cold, heat, and heat waves in São Paulo, Brazil. Int. J. Biometeorol. 2016, 60, 113–21, doi:10.1007/s00484-015-1009-7. Ferreira, L. de C. M.; Nogueira, M. C.; Pereira, R. V. de B.; de Farias, W. C. M.; Rodrigues, M. M. de S.; Teixeira, M. T. B.; Carvalho, M. S. Ambient temperature and mortality due to acute myocardial infarction in Brazil: an ecological study of time-series analyses. Sci. Rep. 2019, 9, doi:10.1038/s41598-019-50235-8.

Results Recife for 21 days:

Results Recife for 12 days:

Results Recife for 14 days

QAIC, s + MMT for the ranges of:

Figure 3 & Figure 4, panels and legend - I would match the panels and the description of the panels .  The panel I00-99-J00-99 is in the figure legend but not in the panels.  

Answer: We acknowledge the reviewer’s comment. IT was a typo and where it reads in Figure 3 and Figure 4, "I00-99-J00-99" should read "(ICD-10: Groups I and J)". (lines 180-181)

Discussion can be shortened because there are many repeats of the results section.

Answer: We acknowledge and agree with the comment. The text was revised and shortened.

Language: Abstract, line 14, introduction line60:  this study was designed to analyse

Answer: Changed accordingly.

Abstract, results:  I would suggest to use past tense, because the analyzed results are presented.

Answer: Changed accordingly.

Author Response File: Author Response.pdf

Reviewer 3 Report

Air temperature extremes both hot and cold, have impacts on mortality rates as well as morbidities.This study proposes to analyse the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil between 2005 and 2014，there are still some issues.

1.table1 and Figure2 are a kind of basic statistical discription, should put in the part of results.

2. To measure the association between mean daily air temperature and the risk of death, we fitted a quasi-Poisson to daily mortality in both regions, adjusting for day of week (categorical), secular trend and seasonality using a natural cubic spline with 8 degrees of freedom per year. why the degree of freedom is 8?why not 6 or 9? you should give a senstive analysis.

3. p176-178,"However, for cardiovascular and cerebrovascular deaths, a clear 'U' shaped curve is observed,  with risk for cold and heat extremes for cerebrovascular, and with a higher risk for extremes of cold in cardiovascular deaths (Figure 4)". In Figure4, we find the RR confidence intervals are include 1 partly. Usually, when RR=1, we think there are no statistical significance. So, how to explain the results? maybe some conclusion should be revised if it is so.

4. the tables are not formal, please corrected according to the journal request.

Author Response

Review 3 comments (Climate):

We thank the reviewer’s contributions which enables to improve the overall quality of paper.

Reviewer:

Comments and Suggestions for Authors

Air temperature extremes both hot and cold, have impacts on mortality rates as well as morbidities. This study proposes to analyse the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil between 2005 and 2014，there are still some issues.

1.table1 and Figure2 are a kind of basic statistical description, should put in the part of results.

Answer: Changed as per Reviewer’s recommendation. (lines162-176)

To measure the association between mean daily air temperature and the risk of death, we fitted a quasi-Poisson to daily mortality in both regions, adjusting for day of week (categorical), secular trend and seasonality using a natural cubic spline with 8 degrees of freedom per year. why the degree of freedom is 8? why not 6 or 9? you should give a sensitive analysis.

Answer: We used a model already proposed and validated previously, and thus, we kept the values for the cubic spline, and these values were adjusted by QAIC test, as described by Gasparrini et al (2015), in a multicentre study called "Mortality risk attributable .to high and low ambient temperature: a multicountry observational study ", which we find in our references. This also served as the basis for further studies.

Gasparrini A, Guo Y, Hashizume M, Lavigne E, Zanobetti A, Schwartz J, et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet. 2015 Jul 25;386(9991):369–75 3. p176-178,"However, for cardiovascular and cerebrovascular deaths, a clear 'U' shaped curve is observed,  with risk for cold and heat extremes for cerebrovascular, and with a higher risk for extremes of cold in cardiovascular deaths (Figure 4)". In Figure4, we find the RR confidence intervals are include 1 partly. Usually, when RR=1, we think there are no statistical significance. So, how to explain the results? maybe some conclusion should be revised if it is so.

Answer: We agree with reviewer that based on figure 4 the estimates of the curve temperature-response risk of death includes the null hypothesis (RR=1) in for several values of the temperature, so we propose to include a sentence referring that these estimates are not statistical significant. Nevertheless, we consider that the reference to these results is worth of note in the main text. We consider this given that, although no statistical significant, in Table 3 it’s possible to observe that the RR at 1% and 99% temperature percentiles, are statistical significant for cerebrovascular deaths and, for cardiovascular deaths, the majority of the confidence interval values support an deleterious effect of high and low temperatures on the risk of cardiovascular deaths.

the tables are not formal, please corrected according to the journal request.

Answer: The figures and tables were adapted to the journal norms as requested

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Reviewer 2 Report

addressed comments

Reviewer 3 Report

The authors had revised according to the comments.