Air Pollution and Birth Outcomes: Health Impact and Economic Value Assessment in Spain

Round 1

Reviewer 1 Report

This study addresses an interesting topic, and this study can gain high scientific validity in the future. The Authors systematical assessed the estimate of the health impact and the economic value on birth outcomes based on meeting the recommendations of the EU and WHO guidelines, as well as an attributable reduction of 15% and 50% in annual PM₁₀ levels in Spain. Several important concerns were raised when I read through the manuscript.

Major comments:

Methods:

1.       How did the author calculate OR value every 5 μg/m³ interval of PM₁₀? Is it by assigning a median value to each interval to assess OR by ∆Ct=0, Ct≤C0; Ct-C0, Ct>C0, or expβ*∆C? Please describe details in the Methods section.

2.       Could the author elaborate on the number of infants that exit LBW in Methods resection?

3.       The author estimated the economic loss of LBW due to PM₁₀ exposure with reference to 2020. Considering inflation, this estimation may overestimate the true value. It is recommended to consider the calculation using the economy of the year of study.

4.       What is the inclusion-exclusion criteria of fetuses (Does it contain stillbirths?)?

5.       Whether the authors consider the multi-pollutant model when calculating the OR value to demonstrate the stability of the model.

Results:

6.       I wonder whether the percentiles of LBW, SGA, and PTB were correct (e.g., 8611/288229=3% [not you mentioned in the Results, 4%]), and I further doubt all results, including characteristics in table 1, PAF and economic value. (Please check all the results carefully).

7.       What is the confidence interval for the attributable disease burden?

Minor comments:

8.       It is recommended to show more numerical results in the results section of the abstract.

9.       The OR in the 2.3 and 2.5 sections should be in the result section.

 

10.    It is better to make the total name of the feature left justified in Characteristics in Table 1.

Author Response

Dear Editor,

 

First and foremost, we would like to thank the journal for considering our paper entitled, “Air pollution and birth outcomes: Health impact and economic value assessment in Spain”, for publication. We appreciate you and the reviewers for your effort and valuable time in reviewing out paper and providing insightful and relevant comments that have helped to improve the current manuscript.

We tried our best to improve the manuscript and edited some lines of the paper to address the questions, comments and advice bought up by the reviewers.We have reorganize the results reducing the number of tables and introducing the 95% confidence intervals. And finally, an Ingles native speaker scholar have checked and corrected the language and style.

We have marked up all the modifications by using MS Word´s Track Changes.

 

Below we provide a point-by-point response as per your requests.

 

Response to Reviewer 1

This study addresses an interesting topic, and this study can gain high scientific validity in the future. The Authors systematical assessed the estimate of the health impact and the economic value on birth outcomes based on meeting the recommendations of the EU and WHO guidelines, as well as an attributable reduction of 15% and 50% in annual PM10 levels in Spain. Several important concerns were raised when I read through the manuscript.

1. How did the author calculate OR value every 5 μg/m3 interval of PM10? Is it by assigning a median value to each interval to assess OR by ∆Ct=0, Ct≤C0; Ct-C0, Ct>C0, or expβ*∆C? Please describe details in the Methods section.

In order to calculated the OR associated to every 5 μg/m3 interval we first used the results from the parallel analysis within the same project (references 48 & 49). In these studies, we showed OR associated to an increase of 10 μg/m3 and in order to get the 5 μg/m, we used the expβ*∆C, with ∆=5/10=0.5. This methodology is described in lines 158 -68, however we have add some information to make clearer.  

“For changes associated to ∆C =5 µg/m³ , OR = OR_o^(5C/10)”

47. Dries, M.A.V.D.; Granés, L.; Ambrós, A.; Binter, A.C.; Tell, J.S.; Ramis, R.; Guxens, M. Prenatal Air Pollution Exposure and Adverse Birth Outcomes: Windows of Susceptibility and Socio-Economic Inequalities. ISEE Conf. Abstr. 2021, doi:10.1289/isee.2021.O-TO-150.
48. L. Granés, A. Ambrós, A. Binter, J. Segu-Tell, R. Ramis, M. Guxens. Exposición a contaminación del aire y salud perinatal. Gaceta Sanitaria XXXIX Reunión Anual de la Sociedad Española de Epidemiología (SEE) y XVI Congresso Da Associação Portuguesa de Epidemiología (APE) Available online: https://www.gacetasanitaria.org/es-pdf-X0213911121008300 (accessed on 14 November 2022).

 

2. Could the author elaborate on the number of infants that exit LBW in Methods resection?

On methods in the birth outcomes section, we added the description of exit LBW as following:

“The term exit LBW was used to describe the number of infants that could have been born without LBW if a reduction of PM₁₀ levels meet the proposed scenarios.”

 

3. The author estimated the economic loss of LBW due to PM10 exposure with reference to 2020. Considering inflation, this estimation may overestimate the true value. It is recommended to consider the calculation using the economy of the year of study.

We calculated the economic loss of LBW using the register of activity data from hospitals from the Spanish National Health System in 2020 because it was the most recent update available of price list with the estimated values of hospitalization associated with attending a neonate born with LBW. Other earlier hospital cost lists are available but all are after 2016. Therefore, we felt that the most recent list was appropriate to give a more up-to-date view of what the savings could represent. 

“Furthermore, we decided to use the cost for year 2020 since we did not have costs for the studied period. This decision could produce an overestimation of the economic impact, nevertheless we thought that most recent values were more appropriate to show an up-to-date view of what the savings could represent.” 

4. What is the inclusion-exclusion criteria of fetuses (Does it contain stillbirths?)?

As described in materials and methods lines 97 to 100: “The study population included a total of 288,229 live-born singleton children (defined as a birth of a child showing signs of life at a gestational age of at least 22 completed weeks or weighting 500 grams or more) born between June 2009 and October 2010, from all Spanish territory except Canary Islands, Ceuta and Melilla”. Therefore, were excluded: Multiple birth, stillbirths, fetuses born with earlier than 22 weeks of gestational age or weighting less than 500 grams.

 

5. Whether the authors consider the multi-pollutant model when calculating the OR value to demonstrate the stability of the model.

As we mention in the answer to question 1. The OR for this study came from a parallel analysis. It’s not the aim of the present study to estimate OR, nevertheless in the model for OR estimation there were no other pollutants such as NO2 or O3 because we didn’t have such information for every women in the study.

We have include the lack of information of exposure to other air pollutants in the lists of limitation in the Discussion Section.

 

6. I wonder whether the percentiles of LBW, SGA, and PTB were correct (e.g., 8611/288229=3% [not you mentioned in the Results, 4%]), and I further doubt all results, including characteristics in table 1, PAF and economic value. (Please check all the results carefully).

Thanks for your observation, those percentage were a mistake in the calculation using a previous erroneous total of births as denominator in that table. We check carefully all of our results and corrected the mistake in the manuscript that was only the total percentage of LBW, SGA and PTB in table 1, the data of the rest of the table is correct.  

7. What is the confidence interval for the attributable disease burden?

The internal baselines association rates:

• LBW: OR = 1.03, CI 0.96, 1.10
• SGA: OR = 1.05, CI 1.00, 1.09
• PTB: OR = 1.22, CI 1.16, 1.28

We have rewritten the method section to introduce the 95%CI values and we have included the 95%CI in the tables.

“In a parallel analysis within the same project (“Air pollution and birth outcomes: windows of exposure and health and economic impact assessment – the APBO project”) that include this study [47,48], linear and logistic regression models were adjusted to obtain the needed parameters to computed the health impact. A lineal model between pregnancy-average levels of each PM pollutant and birth weight showed that a reduction of 10 µg/m3 of PM10 was associated with an increase of 22 grams (95%CI= 17.2-28). Logistic models estimated the odds ratio (OR) associated to LBW at term, SGA, and PTB. Their results showed an OR of 1.03 (95%CI= 0.96-1.1) of being born with LBW at term associated with an increase of 10 µg/m3 of PM10. An OR of 1.05 (95%CI= 1-1.09)  for SGA was also observed at baseline for an increase of 10 µg/m3 of PM10, showing similar results as LBW. For PTB, an association with PM levels was found, showing an Odds of been born with PTB of 1.22 (95%CI= 1.16-1.28)  for an increase of 10 µg/m3 of PM10 exposure at baseline scenario. “

 

8. It is recommended to show more numerical results in the results section of the abstract.

We have rewritten the abstract to included some numerical results.

“Air pollution is considered an outgoing major public health and environmental issue around the globe, affecting the most vulnerable, such as pregnant women and fetuses. The aim of this study is to estimate the health impact and economic value on birth outcomes, such as low birthweight (LBW), preterm birth (PTB), small for gestational age (SGA), attributable to a reduction of PM10 levels in Spain, based on four scenarios: fulfillment of WHO guidelines and EU limits, and an attributable reduction of 15% and 50% in annual PM10 levels. Retrospective study on 288,229 live-born singleton children born between 2009-2010, data from Spain Birth Registry Statistics database, as well as mean PM10 mass concentrations. Our finding showed that a decrease on annual exposure to PM10 appears to be associated with a decrease in the annual cases of LBW, SGA and PTB, as well as a reduction in hospital cost attributed to been born with LBW. Improving pregnancy outcomes by reducing the number of LBW up to 5% per year, resulting in an estimate associate monetary saving of fifty thousand to seven million euros annually. This study agrees with previous literature and highlights the need of implementing and fulfilling stricter policies that regulates the maximum exposure to outdoor PM permitted in Spain, contributing in decreasing environmental health risk, especially negative birth outcomes”

 

9. The OR in the 2.3 and 2.5 sections should be in the result section.

Thanks for the suggestion however, those ORs are not results of this study and they are taken from a parallel one within the same project. That’s why this OR are presented in the methods section on in the results one.

 

10. It is better to make the total name of the feature left justified in Characteristics in Table 1.

Thanks for the suggestion, we made that changes.

Reviewer 2 Report

IJERPH, “Air pollution and birth outcomes: Health impact and economic value assessment in Spain”

The manuscript “Air pollution and birth outcomes: Health impact and economic value assessment in Spain” calculates the reduction in low birth weight and associated hospital costs estimated to result from four different PM10 reduction scenarios using data on births from 2009-2010. The analysis appears to use existing empirical estimates of the relationship between PM10 during pregnancy and the incidence of LBW in Spain, as well as minimum and maximum hospital cost estimates for LBW. While the topic of the study is very important to global public health, the study does not make any novel contributions in terms of data, empirical estimates, or methodologies. Instead, it identifies existing data and dose-response relationships to compare the health benefits of four scenarios. Nor does it provide a complete accounting of the benefits and costs of achieving the four PM10 reduction scenarios. Without either a substantive original analysis or a more complete benefit-cost analysis of the four scenarios, I do not recommend the analysis for publication in IJERPH. Additional comments on the analysis are listed below.

Comments

·       My understanding of the manuscript is that the analysis is relying heaving on an existing study estimating the association between PM10 and LBW in Spain, as well as existing hospital cost data (citations 47 and 48). What is the unique contribution of this manuscript in terms of original empirical analysis?

·       There is not enough description of the hospital cost data. Are these data from a comprehensive registry of all hospitals and births in Spain, or are they survey data representing a sample of births? Do the cost data correspond to 2009-2010 (matching the birth data), or another time period?  

·       For the cost analysis, I suggest using mean, 5^th percentile, and 95^th percentile hospitals costs of LBW and non-LBW births instead of minimum and maximum costs. Min and max can give a distorted picture if there are large outliers in the data.

·       Please provide a justification for the use of PM10 instead of PM2.5 as the air quality indicator. The Air Pollution Exposure Assessment section says that the model estimates both PM2.5 and PM2.5-10 at 1 km resolution. Fine particles such as PM2.5 are more strongly associated with adverse health effects than coarser particles (https://ww2.arb.ca.gov/resources/inhalable-particulate-matter-and-health).

·       Is mean PM10 over the entire pregnancy the most relevant exposure metric (as opposed to max PM10)? Please provide citations supporting this choice.  

·       The analysis does not provide any information on how the magnitude of the avoided hospital costs from fewer LBW births compares to the magnitude of avoided costs of other health effects from PM reduction (e.g., mortality). Please provide this information to give the reader a sense of the importance of failing to account for the LBW benefits category.

·       Please provide estimates of the costs of achieving the four PM10 reduction scenarios. The manuscript is not providing a unique empirical contribution, but it could still be informative if it provided a more complete accounting of the full benefits and costs of these scenarios.

·       I have not provided detailed editorial comments, but the study would need a thorough editing for English language and grammar prior to publication.  

Author Response

Response to Reviewer 2

The manuscript “Air pollution and birth outcomes: Health impact and economic value assessment in Spain” calculates the reduction in low birth weight and associated hospital costs estimated to result from four different PM10 reduction scenarios using data on births from 2009-2010. The analysis appears to use existing empirical estimates of the relationship between PM10 during pregnancy and the incidence of LBW in Spain, as well as minimum and maximum hospital cost estimates for LBW. While the topic of the study is very important to global public health, the study does not make any novel contributions in terms of data, empirical estimates, or methodologies. Instead, it identifies existing data and dose-response relationships to compare the health benefits of four scenarios. Nor does it provide a complete accounting of the benefits and costs of achieving the four PM10 reduction scenarios. Without either a substantive original analysis or a more complete benefit-cost analysis of the four scenarios, I do not recommend the analysis for publication in IJERPH. Additional comments on the analysis are listed below.

1. My understanding of the manuscript is that the analysis is relying heaving on an existing study estimating the association between PM10 and LBW in Spain, as well as existing hospital cost data (citations 47 and 48). What is the unique contribution of this manuscript in terms of original empirical analysis?

Thanks for your comment because we can see from it that the text can be confusing. The estimating association between PM₁₀ and LBW used came from a parallel analysis within the same project that it is not published yet. This contribution is original from the project, it can be verified because the main investigators in both citations 47 and 48, and the present manuscript are Ramis R and Guxens M.

We have modified the paragraph in the method section to make this clearer.

 

2. There is not enough description of the hospital cost data. Are these data from a comprehensive registry of all hospitals and births in Spain, or are they survey data representing a sample of births? Do the cost data correspond to 2009-2010 (matching the birth data), or another time period?

We clarify in the text the information about hospital cost as your suggestion, seen that it can be confusing as it was. These data came from the register of activity data from hospitals from the Spanish National Health System, created with data from hospital discharge in all autonomous communities of Spain in 2020. It is a weighted average of the average cost of all cases with a specific condition, calculated by multiplying the number of cases of each condition by its average cost and dividing by the total number of cases in that autonomous community. The cost data correspond to 2020 because it was the most recent update available of price list with the estimated values of hospitalization associated with attending a neonate born with LBW. Other earlier hospital cost lists are available but all are after 2016. Therefore, we felt that the most recent list was appropriate to give a more up-to-date view of what the savings could represent. 

 

3. For the cost analysis, I suggest using mean, 5th percentile, and 95th percentile hospitals costs of LBW and non-LBW births instead of minimum and maximum costs. Min and max can give a distorted picture if there are large outliers in the data.

Thanks for your suggestion, it definitely could be more complete been able to represent the cost in percentile, but due to the data available is not possible. This information cames from the register of activity data from hospitals from the Spanish National Health System, that is a weighted average of the average cost of all cases with the specific condition, therefore is already calculated and expressed in min and max. We do not have accesses to all of the individual data cost of each neonate born with LBW.

 

4. Please provide a justification for the use of PM10 instead of PM2.5 as the air quality indicator. The Air Pollution Exposure Assessment section says that the model estimates both PM2.5 and PM2.5-10 at 1 km resolution. Fine particles such as PM2.5 are more strongly associated with adverse health effects than coarser particles (https://ww2.arb.ca.gov/resources/inhalable-particulate-matter-and-health).

Thanks for pointing that out. That is a mistake in the text of the Air Pollution Exposure Assessment section. In this study, we only assess PM10. This is because we wanted to study rural and urban areas together. When we studied the spatial distribution of PM10 and PM2.5 we found out that rural areas showed very low levels of PM2.5 unlike PM10.

Accordingly, we have corrected the paragraph in the Air Pollution Exposure Assessment section

 

5. Is mean PM10 over the entire pregnancy the most relevant exposure metric (as opposed to max PM10)? Please provide citations supporting this choice.  

Most of the literature and the current evidence on the association between air pollution exposure and birth outcomes is based on long-term exposure of air pollution using metrics such as pregnancy-average levels (for example, see an extensive systematic review and meta-analysis recently published including 68 studies on birth outcomes: Boogaard et al. Environ Int 2022; 164: 107262). Therefore, we focused our study on the association between pregnancy-average levels of PM10 and low birthweight at term, small for gestational age, and preterm birth.  

 

We have done some changes in the Introduction section to make this clearer (lines 68-70)

 

“Several recent meta-analysis and systemic reviews had describe the associated between the long-term exposure to PM during pregnancy and adverse outcomes, such as risk of stillbirth [12,13], low birthweight (LBW) [14,15], preterm birth (PTB) [16,17], small for gestational age (SGA) [18,19], congenital anomalies [20,21] and other chronic diseases later on the child’s life [22]. ”

 

Also changes in methods, (lines 131-133):

“We focused on the pregnancy-average air pollution levels because it is the most relevant exposure metric for investigating the association between long-term exposure to air pollution and birth outcomes.”

 

6. The analysis does not provide any information on how the magnitude of the avoided hospital costs from fewer LBW births compares to the magnitude of avoided costs of other health effects from PM reduction (e.g., mortality). Please provide this information to give the reader a sense of the importance of failing to account for the LBW benefits category.

There have been other studies on monetary cost calculations related to air-pollution health impacts in Spain, related to all-cause mortality, cardiovascular and respiratory disease, but none related specifically to neonates and birth outcomes.

A previous study analyzed the impact of air pollution and low birthweight in Spain and showed that 6105 cases were attributable to PM10 exposure. This figure related to a PAF of 9.42% attributable to PM10 exposure during pregnancy, nevertheless the authors did not carried out a health impact assessment comparing different scenarios. Moreover, they used aggregated data at province level and used weight at birth not birth weight at term (gestational age <37 weeks). These differences hinder the comparison of the results of the two Spanish studies.

Virginia Arroyo, Julio Díaz, P. Salvador, Cristina Linares. Impact of air pollution on low birth weight in Spain: An approach to a National Level Study. Environ Res. 2019, 171, 69-79, doi.org/10.1016/j.envres.2019.01.030

 

7. Please provide estimates of the costs of achieving the four PM10 reduction scenarios. The manuscript is not providing a unique empirical contribution, but it could still be informative if it provided a more complete accounting of the full benefits and costs of these scenarios.

As it is mention in the text, lines 170-72, we have used all information available to estimate de cost

 “Other economic cost such as indirect cost, costs of pain and suffering, financial costs of long-term complications over the course of life, among others, were not included in this analysis due to the challenge involved in calculating all these costs related to this outcome.”

On the other hand, Figure 1 shows a comparison of the benefits related to each scenario.

 

8. I have not provided detailed editorial comments, but the study would need a thorough editing for English language and grammar prior to publication.  

An Ingles native speaker scholar have checked and corrected the text.

Round 2

Reviewer 1 Report

Accept without revision

Author Response

Response to Reviewer 1 (Round 2)

Accept without revision.

• Thank you for reviewing the manuscript. We are grateful for the time and effort that you have dedicated to providing your valuable feedback on our paper.

Reviewer 2 Report

I appreciate that the authors addressed my comments by providing more details about their use of an existing dose-response relationship from another project and about the cost data. However, my main concerns about lack of original contribution of this study remain. The authors also declined to add more information about the costs or the value of the other health benefits of the policy scenarios.

I don’t think the definition of LBW in the Introduction is correct: “a newborn that weighed less than 2,500 grams at term”. I think “at term” should be deleted from the sentence. Even though this study examines LBW at term, the WHO definition of LBW (2,500 grams) applies to both term and preterm infants.  

Section 4, line 264: I think there is a mistake in this sentence when you discuss birth weight at term—the text says “gestational age < 37 weeks,” but I think you mean the opposite.

The manuscript still contains numerous errors in English grammar and usage. It is beyond the scope of my review to identify them all. Looking at just the abstract, there are grammatical errors in almost every sentence. These include:  

·       Use of “outgoing” is the abstract is incorrect. (“Outgoing” means someone with a talkative personality.) Consider replacing with “ongoing” (meaning something that is still happening), or just deleting.

·       3^rd, 4^th, 7^th sentences of the abstract are all incomplete complete sentences. They are missing verbs.

·       5^th sentence, “decrease on annual exposure” should be “decrease in annual exposure;” “attributed to been born with LBW” is not correct, consider editing to “attributed to LBW.”

·       7^th sentence – “associated” should be “associated”

·       8^th sentence – “need of implementing and fulfilling” should be “need to implement and fulfill;” “that regulates” should be “that regulate;” “contributing in” should be “contributing to.”

Author Response

Response to Reviewer 2 (Round 2)

I appreciate that the authors addressed my comments by providing more details about their use of an existing dose-response relationship from another project and about the cost data. However, my main concerns about lack of original contribution of this study remain. The authors also declined to add more information about the costs or the value of the other health benefits of the policy scenarios.

Thank you for reviewing the manuscript. We are grateful for the time and effort that you have dedicated to providing your valuable feedback on our paper.

Just to make it clear, again. The estimation of dose-response relationship is being done within the same project, but in a different analysis.

Regarding the extra costs and values of other potential health benefits. Their estimation have too many assumptions over potential late effects of which we did not have information. That exercise goes beyond the aim of this study.

We have included a sentence in the discussion section (lines 286-288) to clarify this.

“However, we did not include all these expenses because they rely on the assumption of potential late effects of which we did not have information.”

 

1. I don’t think the definition of LBW in the Introduction iscorrect: “a newborn that weighed less than 2,500 grams at term”. I think “at term” should be deleted from the sentence. Even though this study examines LBW at term, the WHO definition of LBW (2,500 grams) applies to both term and preterm infants.

Thanks for your comment because we can see from it that you are correct, the term “at term” does not correspond in that definition. We have modified the sentence as your suggestion.  

 

2. Section 4, line 264: I think there is a mistake in this sentence when you discuss birth weight at term—the text says “gestational age < 37 weeks,” but I think you mean the opposite.  

Thank. We reviewed in the text this information; it was a mistake in the less-than sign, we corrected the text.  

 

3. The manuscript still contains numerous errors in English grammar and usage. It is beyond the scope of my review to identify them all. Looking at just the abstract, there are grammatical errors in almost every sentence. These include:

 

• Use of “outgoing” is the abstract is incorrect. (“Outgoing” means someone with a talkative personality.) Consider replacing with “ongoing” (meaning something that is still happening), or just deleting.
• 3^rd, 4^th, 7^thsentences of the abstract are all incomplete complete sentences. They are missing verbs.
• 5^thsentence, “decrease on annual exposure” should be “decrease in annual exposure;” “attributed to been born with LBW” is not correct, consider editing to “attributed to LBW.”
• 7^thsentence – “associated” should be “associated”
• 8^thsentence – “need of implementing and fulfilling” should be “need to implement and fulfill;” “that regulates” should be “that regulate;” “contributing in” should be “contributing to.”

Thank you very much the effort. An English native speaker scholar have checked and corrected the text, and all modifications are marked up by using MS Word´s Track Changes.

 

Sincerely,

 

Rebeca Ramis

Author Response File: Author Response.docx