Impact of climate change and air pollution on cardiovascular disease: A systematic review and meta-analysis protocol

Abstract

Background

Climate change and increasing environmental pollution are emerging as significant threats to global health, notably through their impact on cardiovascular diseases (CVD). The World Health Organization (WHO) attributes millions of premature deaths annually to air pollution and extreme temperatures. Despite extensive research on air pollution and temperature extremes separately, their combined effects on cardiovascular health remain inadequately explored.

Methods

We plan to conduct a systematic review and meta-analysis to assess the impact of climate change, including extremes of temperature and air pollution, on CVD. We will search PubMed, CINAHL, SCOPUS, ClinicalTrials.gov, and additional databases for studies published between August 12, 2019, and August 11, 2024. The review will include observational and quasi-experimental (pre and post-test) studies. Data extraction and quality assessment will be performed using EndNote, Rayyan.ai, and the National Heart, Lung, and Blood Institute (NHLBI) quality appraisal tool. The statistical analysis will be conducted using RevMan 5.4, with risk ratios, mean differences, and heterogeneity evaluated.

Discussion

This review aims to synthesize evidence on how ambient air pollutants (PM_2.5, CO, O₃) and extreme temperatures contribute to cardiovascular morbidity and mortality. It will highlight the synergistic effects of air pollution and temperature extremes, with a particular focus on low- and middle-income countries where the burden is most pronounced.

Conclusion

By integrating the impacts of both climate change and air pollution on cardiovascular health, this review will provide comprehensive insights into the global health burden of CVD. The findings will inform public health strategies and interventions to mitigate the adverse effects of environmental factors on cardiovascular health.

Introduction

The World Health Organization (WHO) states that global climate change and increasing levels of environmental pollution are affecting human health both directly through its toxic effect and indirectly through air, water and food being consumed. ¹ There is extensive literature that shows strong association between air pollution and increase in morbidity and mortality from various ailments such as cardiovascular diseases (CVD).^2,3 The WHO attributes approximately 7 million premature deaths alone to indoor and ambient air pollution. ¹ The World Air Quality report of 2022 showed that 118 out of the 131 ⁴ countries reviewed did not meet the air quality guidelines set by WHO, exposing about 99% ¹ of the world's population to injurious levels of particulate matter (PM) which is a common air pollutant.^1–4 The low-and-middle income countries (LMICs) share the greatest burden of air pollution with Chad, Iraq and Pakistan having a concentration of PM_2.5 over 70 µg/m³, which is 14 times greater than the upper limit set by WHO.^1–4

In simple terms, an air pollutant is a biological, chemical or physical agent that significantly changes the natural properties of the air we breathe. ⁵ PM, carbon monoxide (CO), ozone (O₃), nitrogen dioxide NO₂) and sulfur dioxide (SO₂) are the major miscreants that can cause serious harm to human health. ⁵ PM is further sub-classified based on its size in micrograms (µg) for example PM_2.5 and PM₁₀; any size smaller than PM_2.5 constitutes as ultra-fine particles (UFP).^1–5 UFP has been identified in neurons near the olfactory bulb proving that these particles, due to their ultra-small size, easily cross the blood brain barrier and are linked with stroke, cognitive impairment and Alzheimer's disease.^3,6,7 Moreover, substantial studies have accumulated on the association of air pollutants and cardiovascular diseases ranging from hypertension, myocardial infarction (MI), endothelial dysfunction and congenital heart diseases.^8–10 A meta-analysis conducted in 2022 showed that pollutants like PM_2.5, CO and O₃ can cause significant increases in CVD morbidity with a minimum of only 3 h of exposure. ¹¹ A study conducted across several cities in China, where average PM_2.5 concentration is over 60 µg/m³, showed increased rates of hospital admissions for heart failure, highlighting, the role of pollutants on increased healthcare costs. ¹² WHO has estimated healthcare costs to go up to 4 billion dollars by the year 2030 with LMICs covering the larger proportion of costs.¹

The global climate change has caused the world to experience extremes of both hot and cold temperatures caused by heat waves, wildfires or snowstorms. ¹ It is reported that 2 out of 1000 of all CVD deaths are attributed to extreme hot weather and 9 out of 1000 CVD deaths are attributed to cold weather. ¹² Extreme heat contributes to an estimated 10,000–15,000 additional cardiovascular deaths, especially coronary artery disease annually, with higher risks for elderly and vulnerable populations. This increase in morbidity and mortality may not necessarily be due to direct effect of hyper or hypothermia but more likely due to the adaptive changes of the body in response to the changing environment. ¹² One such adaptive change that has been observed in several studies is the inverse relation between heart rate variability (HRV) and temperature.¹⁵ The decreased HRV coupled with inflammatory agents released from the respiratory epithelium due to air pollutants can precipitate cardiac events like MI or cardiac arrest in susceptible population.^12–14 A Chinese study showed that heat waves and PM_2.5 have synergistic relationship in claiming 2.8% of deaths due to MI. ¹⁵ Diurnal temperature range is defined as difference between the highest and lowest temperature recorded in a day, regardless of season. A 3% increase in CVD admission was reported per 1°C increase in diurnal temperature range. ¹⁶

We are conducting this review to gather latest evidence on deleterious effects of climate change including extremes of temperature and ambient air pollution on cardiovascular health outcomes. This review aims to highlight the risk factors associated with climate change and air pollution that increase the risk of CVD morbidity and mortality. The review will delve into how various factors, such as particulate matter (PM_2.5), carbon monoxide (CO), and ozone (O₃), contribute to increased cardiovascular morbidity and mortality. Furthermore, the review will explore the effects of extreme weather conditions and air pollutants, which exacerbate the burden on cardiovascular health, especially in low- and middle-income countries (LMICs) where the greatest burden is observed. To the best of our knowledge, this will be the first systematic review and meta-analysis from Pakistan and South Asia that specifically investigates exposure to climate change factors and air pollution as risk factors for cardiovascular disease (CVD).

Methods

Study registration

The review protocol has been registered with the International Prospective Register for Systematic Reviews (PROSPERO) under the registration number CRD42024574539. This protocol adheres to the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement (Table 1). As this study relies solely on previously published research, ethical approval is not required. In case of any deviation from this protocol, the amendment will be reported in the final manuscript of this review.

Table 1.

PRISMA 2020 checklist.

Section and Topic	Item #	Checklist item	Location where item is reported
TITLE
Title	1	Identify the report as a systematic review.
ABSTRACT
Abstract	2	See the PRISMA 2020 for Abstracts checklist.
INTRODUCTION
Rationale	3	Describe the rationale for the review in the context of existing knowledge.
Objectives	4	Provide an explicit statement of the objective(s) or question(s) the review addresses.
METHODS
Eligibility criteria	5	Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses.
Information sources	6	Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted.
Search strategy	7	Present the full search strategies for all databases, registers and websites, including any filters and limits used.
Selection process	8	Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.
Data collection process	9	Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process.
Data items	10a	List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect.
	10b	List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information.
Study risk of bias assessment	11	Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process.
Effect measures	12	Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results.
Synthesis methods	13a	Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)).
	13b	Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions.
	13c	Describe any methods used to tabulate or visually display results of individual studies and syntheses.
	13d	Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.
	13e	Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression).
	13f	Describe any sensitivity analyses conducted to assess robustness of the synthesized results.
Reporting bias assessment	14	Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases).
Certainty assessment	15	Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome.
RESULTS
Study selection	16a	Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram.
	16b	Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded.
Study characteristics	17	Cite each included study and present its characteristics.
Risk of bias in studies	18	Present assessments of risk of bias for each included study.
Results of individual studies	19	For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g. confidence/credible interval), ideally using structured tables or plots.
Results of syntheses	20a	For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies.
	20b	Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision (e.g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect.
	20c	Present results of all investigations of possible causes of heterogeneity among study results.
	20d	Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results.
Reporting biases	21	Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed.
Certainty of evidence	22	Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed.
DISCUSSION
Discussion	23a	Provide a general interpretation of the results in the context of other evidence.
	23b	Discuss any limitations of the evidence included in the review.
	23c	Discuss any limitations of the review processes used.
	23d	Discuss implications of the results for practice, policy, and future research.
OTHER INFORMATION
Registration and protocol	24a	Provide registration information for the review, including register name and registration number, or state that the review was not registered.
	24b	Indicate where the review protocol can be accessed, or state that a protocol was not prepared.
	24c	Describe and explain any amendments to information provided at registration or in the protocol.
Support	25	Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review.
Competing interests	26	Declare any competing interests of review authors.
Availability of data, code and other materials	27	Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review.

Search strategy

A comprehensive search strategy (Table 2), initially developed for PubMed with the help of a librarian from Aga Khan University, Karachi and utilizing MeSH (Medical Subject Headings) terms, will subsequently be adapted for use in databases for title and abstract searches. The search will be performed across four electronic databases: PubMed, CINAHL, SCOPUS, and Google Scholar which are widely recognized for their reliability in systematic reviews. The reference lists of included studies will be cross-checked via snowball search (cross-referencing) to ensure no pertinent articles are missed. The search will be conducted independently by two reviewers (ZHE and AK).

Table 2.

Search string used for retrieving articles.

Population	(adult* or age* 18 or 18+) AND
Intervention/Exposure	(air pollution OR air quality OR air contamination OR smog OR carbon emissions) AND (temperature* OR extreme cold OR extreme heat) AND
Outcome	(cardiovascular disease OR CVD OR heart disease OR cardiac disease OR coronary heart disease OR ischemic heart disease OR acute coronary syndrome OR cardiac health OR cardiovascular health OR atherosclerosis cardiovascular disease OR ASCVD OR MI OR acute myocardial infarction) AND
Setting	(“developing countries”[MeSH Terms] OR (“developing”[All Fields] AND “countries”[All Fields]) OR “developing countries”[All Fields] OR (“developing”[All Fields] OR (“low middle income countries”[All Fields] AND “country”[All Fields]) OR “developing country”[All Fields])) AND (“developed countries”[MeSH Terms] OR (“developed”[All Fields] AND “countries”[All Fields]) OR “developed countries”[All Fields] OR (“developed”[All Fields] AND “country”[All Fields]) OR “developed country”[All Fields]) AND
Filters	English language; humans; August 12, 2019 to August 11, 2024, RCTs OR Experimental studies AND Reviews

The search terms will be organized into five key categories: population (adults aged 18 years and older), intervention/exposure (air pollution, temperature), outcomes (cardiovascular health, including CVD mortality and morbidity), settings (studies from both developed and developing countries, i.e. high-income and low- and middle-income countries), and the time period (studies published between August 12, 2019, and August 11, 2024).

Eligibility criteria

This review will include studies involving adults aged over 18 years, regardless of sex. Both high-income and low- and middle-income countries will be represented in the selected studies. The review will encompass non-experimental observational studies such as cross-sectional, cohort, case-control, case-series, and case studies. We have decided to exclude quasi-experimental studies from our review. Only observational studies (cohort, case-control, and cross-sectional) will be included. Only studies published between August 12, 2019, and August 11, 2024, will be included, and only those available in English will be included due to the authors’ language proficiency and a lack of funding for translation services. Studies that will be excluded from this review will include randomized controlled trials, commentaries, editorials, symposium proceedings, and systematic reviews.

Data selection

EndNote citation management software will be used to export records from all databases, and duplicates will be manually removed. After deduplication, the articles will be uploaded to Rayyan.ai (https://new.rayyan.ai/) for commencement of screening. The screening process will be conducted in two stages: first by title and abstract, and later by full-text review to exclude studies that do not meet the inclusion criteria. To maintain the reliability of the article selection process between the two reviewers, a screening form will be developed to verify the relevance of each article. Reviewers will be required to provide a justification for excluding any study. In case of disagreement between the two reviewers, a third reviewer will be consulted during a consensus meeting to make the final decision.

Data extraction

A data extraction sheet will be developed. For each of the listed studies, two independent reviewers will extract the data using a customized data extraction form. To ensure that all major findings are included, the data extraction tables of the two reviewers will be matched. In case of any discrepancies in the information collected, a third assessor will be consulted. The study citation (article title, author, publication date), study design, study population, purpose/aim of the study, air pollution and extremes of temperature exposure, and study findings are among the items that will be included in the preliminary data extraction form.

Exposures and outcomes

Exposures (Risk Factors)

• PM2.5

• Ozone (O₃)

• Carbon Monoxide (CO)

• Cold Temperature (extreme low)

• Hot Temperature (extreme high)

Outcomes (Cardiovascular Diseases)

• Ischemic Heart Disease (IHD)

• Atherosclerotic Cardiovascular Disease (ASCVD)

• Myocardial Infarction (MI)

• Coronary Artery Disease (CAD)

Quality assessment of included studies

We will assess the methodological quality of the included studies using the quality assessment tool developed by National Heart, Lung, and Blood Institute for observational cohort and case control studies.¹⁷ Tables 3 and 4 shows the criterion for quality appraisal cohort and case control studies respectively. The quality of the eligible studies will be independently assessed by two reviewers. Any disagreements between the reviewers will be resolved through consensus or by consulting a third reviewer. We will use the Newcastle-Ottawa Scale (NOS) to assess the quality of cohort studies.

Table 3.

Risk of bias assessment tool is used for cohort and cross-sectional studies.

Criteria	Yes	No	Other (CD, NR, NA) *
1. Was the research question or objective in this paper clearly stated?
2. Was the study population clearly specified and defined?
3. Was the participation rate of eligible persons at least 50%?
4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study prespecified and applied uniformly to all participants?
5. Was a sample size justification, power description, or variance and effect estimates provided?
6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured?
7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed?
8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g. categories of exposure, or exposure measured as continuous variable)?
9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?
10. Was the exposure(s) assessed more than once over time?
11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?
12. Were the outcome assessors blinded to the exposure status of participants?
13. Was loss to follow-up after baseline 20% or less?
14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)?

*CD: cannot determine; NA: not applicable; NR: not reported.

Table 4.

Risk of bias assessment tool is used for cohort and cross-sectional studies.

Criteria	Yes	No	Other (CD, NR, NA) *
1. Was the research question or objective in this paper clearly stated and appropriate?
2. Was the study population clearly specified and defined?
3. Did the authors include a sample size justification?
4. Were controls selected or recruited from the same or similar population that gave rise to the cases (including the same timeframe)?
5. Were the definitions, inclusion and exclusion criteria, algorithms or processes used to identify or select cases and controls valid, reliable, and implemented consistently across all study participants?
6. Were the cases clearly defined and differentiated from controls?
7. If less than 100 percent of eligible cases and/or controls were selected for the study, were the cases and/or controls randomly selected from those eligible?
8. Was there use of concurrent controls?
9. Were the investigators able to confirm that the exposure/risk occurred prior to the development of the condition or event that defined a participant as a case?
10. Were the measures of exposure/risk clearly defined, valid, reliable, and implemented consistently (including the same time period) across all study participants?
11. Were the assessors of exposure/risk blinded to the case or control status of participants?
12. Were key potential confounding variables measured and adjusted statistically in the analyses? If matching was used, did the investigators account for matching during study analysis?

*CD: cannot determine; NA: not applicable; NR: not reported.

Statistical analysis

In this review, we will use RevMan 5.4 software for statistical analysis. For categorical data, we will collect risk ratios along with their 95% confidence intervals (CIs). For continuous outcome data, we will calculate mean differences or standardized mean differences, also with 95% CIs. Heterogeneity among the included studies will be assessed using the I² statistic and the chi-square test. If substantial heterogeneity is detected (I² ≥ 50%), we will apply a random-effect model to pool the data. Otherwise, a fixed-effect model will be used. To assess publication bias, we will create a funnel plot, provided that a sufficient number of studies (more than 10) are included. If publication bias is identified through the funnel plot analysis, we will explore potential causes, such as small-study effects.

Discussion

The proposed systematic review and meta-analysis aims to provide a comprehensive evaluation of the impact of climate change. By synthesizing recent evidence, it will elucidate the contributions of various air pollutants and extreme weather changes to CVD morbidity and mortality, offering a clearer picture of the global health burden, potentially guiding targeted interventions. By focusing on both ambient air pollutants and temperature extremes, this review will fill a critical gap in the literature where separate analyses have been conducted but not amalgamated in a single review.

Despite its strengths, the study has limitations. One significant limitation is the exclusion of randomized controlled trials (RCTs), which might limit the ability to draw causal inferences. The reliance on observational studies and non-randomized designs may introduce variability in the quality of evidence and potential biases. Additionally, the review will only include studies published in English and within a specific time frame, which could lead to language and publication bias. The heterogeneity among included studies regarding methodologies and measurements of air pollution and temperature extremes may affect the comparability of results.

The findings of this review will be instrumental in shaping future research and public health policies. For public health professionals and policymakers, the findings will provide valuable insights to develop and implement strategies aimed at mitigating the adverse health effects of climate change, particularly in vulnerable populations and LMICs where the burden is most pronounced. These include improving air quality standards, enhancing early warning systems for extreme weather conditions, and implementing community-based interventions in high-risk areas. Furthermore, there is a need for continuous monitoring and evaluation of environmental policies to ensure their effectiveness in reducing the cardiovascular health burden.