Cited by 167Smoking Behavior and CessationAir Quality and Health ImpactsChronic Obstructive Pulmonary Disease (COPD) Research

The DOI matches its Crossref record; 470 of the 470 references it cites were found in a registry or an index; 15 of the 20 sources its claims cite were checked for support.

Health effects associated with exposure to secondhand smoke: a Burden of Proof study

Open access

Flor, Luisa S., Anderson, Jason A., Ahmad, Noah, Aravkin, Aleksandr, Carr, Sinclair, Dai, Xiaochen, Gil, Gabriela F., Hay, Simon I., Malloy, Matthew J., McLaughlin, Susan A., Mullany, Erin C., Murray, Christopher J. L., O’Connell, Erin M., Okereke, Chukwuma, Sorensen, Reed J. D., Whisnant, Joanna, Zheng, Peng, Gakidou, Emmanuela·2024·Nature Medicine

DOI 10.1038/s41591-023-02743-4PMC PMC10803272

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Abstract

Despite a gradual decline in smoking rates over time, exposure to secondhand smoke (SHS) continues to cause harm to nonsmokers, who are disproportionately children and women living in low- and middle-income countries. We comprehensively reviewed the literature published by July 2022 concerning the adverse impacts of SHS exposure on nine health outcomes. Following, we quantified each exposure–response association accounting for various sources of uncertainty and evaluated the strength of the evidence supporting our analyses using the Burden of Proof Risk Function methodology. We found all nine health outcomes to be associated with SHS exposure. We conservatively estimated that SHS increases the risk of ischemic heart disease, stroke, type 2 diabetes and lung cancer by at least around 8%, 5%, 1% and 1%, respectively, with the evidence supporting these harmful associations rated as weak (two stars). The evidence supporting the harmful associations between SHS and otitis media, asthma, lower respiratory infections, breast cancer and chronic obstructive pulmonary disease was weaker (one star). Despite the weak underlying evidence for these associations, our results reinforce the harmful effects of SHS on health and the need to prioritize advancing efforts to reduce active and passive smoking through a combination of public health policies and education initiatives.

AI snapshot

Written from the paper’s full text.

TL;DR

This Burden of Proof meta-analysis synthesized evidence through July 2022 on secondhand smoke (SHS) exposure and nine health outcomes, finding statistically significant associations with all nine when not accounting for between-study heterogeneity. Under conservative BPRF estimates, SHS exposure was associated with at least around 8%, 5%, 1% and 1% higher risk of ischemic heart disease, stroke, type 2 diabetes and lung cancer, respectively, with these four rated two stars and the remaining five outcomes rated one star.

Key findings

Across 410 included publications and 623 observations from over 178 locations, all nine outcomes showed statistically significant associations with SHS exposure before accounting for between-study heterogeneity.
Conservative BPRF estimates: ischemic heart disease RR 1.26 (1.05–1.52), BPRF 1.08, ROS 0.04, two stars, at least 8% higher risk; stroke RR 1.16 (1.03–1.32), BPRF 1.05, ROS 0.02, two stars, at least 5% higher risk; type 2 diabetes RR 1.16 (0.98–1.37), BPRF 1.01, ROS 0.005, two stars, at least 1% higher risk; lung cancer RR 1.37 (0.94–1.99), BPRF 1.00, ROS 0.001, two stars at the lower threshold, around 1% higher risk.
The evidence for otitis media (BPRF 0.95, ROS −0.03), asthma (BPRF 0.93, ROS −0.04), lower respiratory infections (BPRF 0.88, ROS −0.06), breast cancer (BPRF 0.81, ROS −0.11) and COPD (BPRF 0.75, ROS −0.14) was weaker, each rated one star.
No publication bias was detected in the primary models; publication bias was found for otitis media in one prospective-cohort sensitivity analysis.

Methods

PRISMA systematic review in PubMed and Web of Science for studies published 1 January 1970 to 31 July 2022, plus citation searching; 7,109 unique records and 1,972 additional records were screened, yielding 410 publications. Included designs were mostly case–control (n = 235) and prospective cohort (n = 156), with smaller numbers of nested case–control, retrospective cohort, case–cohort and case-crossover studies.
The Burden of Proof Risk Function (BPRF) framework used MR-BRT meta-regression to estimate pooled relative risks for dichotomous SHS exposure, adjust for selected bias covariates, quantify unexplained between-study heterogeneity (gamma), test publication bias with Egger’s regression, and derive BPRF, ROS and star ratings.
Sensitivity analyses restricted models to prospective cohort studies, never-smoking samples, and both restrictions combined; asthma also had a children-only sensitivity analysis.

Limitations

The paper states that SHS exposure was self-reported or proxy-reported, risking exposure misclassification; most surveys captured current rather than cumulative exposure, so formerly exposed individuals could be misclassified as unexposed; and dichotomous exposure may oversimplify intensity and frequency.
The paper also states that input studies used varied exposure definitions and locations, public-setting exposure was not included, modeled RRs were not disaggregated by geography, sex or age group, and the nine outcomes do not capture the full disease burden of SHS.
The text makes evident that several associations were sensitive to data restrictions: stroke was downgraded to one star when restricted to prospective cohorts of never smokers, lung cancer to one star in prospective cohorts, breast cancer showed no significant association in prospective cohorts without gamma, and COPD showed no significant association in prospective cohorts or never-smoking populations without gamma.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41591-023-02743-4

Cites

470 of 470 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Fig. 1 Modified funnel plots for SHS exposure and two cardiovascular outcomes. a,b, These modified funnel plots show the residuals of the reported mean RR relative to 0, the null value, on the x axis and the residuals of the standard error, as estimated from both the reported standard error and gamma, relative to 0 on the y axis, for IHD (a) and stroke (b). The light-blue vertical interval corresponds to the 95% uncertainty interval incorporating between-study heterogeneity; the dark-blue vertical interval corresponds to the 95% uncertainty interval (UI) without between-study heterogeneity; the dots are each included observation; the red Xs are outliered observations; the gray dotted line reflects the null log(RR); the blue line is the mean log(RR) for SHS and the outcome of interest; and the red line is the Burden of Proof function at the fifth quantile for these harmful risk–outcome associations.CC BY · PubMed Central

Fig. 2 Modified funnel plots for SHS exposure and two cancer outcomes. a,b, These modified funnel plots show the residuals of the reported mean RR relative to 0, the null value, on the x axis and the residuals of the standard error, as estimated from both the reported standard error and gamma, relative to 0 on the y axis, for lung cancer (a) and breast cancer (b). The light-blue vertical interval corresponds to the 95% uncertainty interval incorporating between-study heterogeneity; the dark-blue vertical interval corresponds to the 95% uncertainty interval (UI) without between-study heterogeneity; the dots are each included observation; the red Xs are outliered observations; the gray dotted line reflects the null log(RR); the blue line is the mean log(RR) for SHS and the outcome of interest; the red line is the Burden of Proof function at the fifth quantile for these harmful risk–outcome associations.CC BY · PubMed Central

Fig. 3 Modified funnel plots for SHS exposure and three respiratory outcomes. These modified funnel plots show the residuals of the reported mean RR relative to 0, the null value, on the x axis and the residuals of the standard error, as estimated from both the reported standard error and gamma, relative to 0 on the y axis, for asthma (a), lower respiratory infections (b) and COPD (c). The light-blue vertical interval corresponds to the 95% uncertainty interval incorporating between-study heterogeneity; the dark-blue vertical interval corresponds to the 95% uncertainty interval (UI) without between-study heterogeneity; the dots are each included observation; the red Xs are outliered observations; the gray dotted line reflects the null log(RR); the blue line is the mean log(RR) for SHS and the outcome of interest; the red line is the Burden of Proof function at the fifth quantile for these harmful risk–outcome associations.CC BY · PubMed Central

Fig. 4 Modified funnel plots for SHS exposure and type 2 diabetes and otitis media. a,b, These modified funnel plots show the residuals of the reported mean RR relative to 0, the null value, on the x axis and the residuals of the standard error, as estimated from both the reported standard error and gamma, relative to 0 on the y axis, for type 2 diabetes (a) and otitis media (b). The light-blue vertical interval corresponds to the 95% uncertainty interval incorporating between-study heterogeneity; the dark-blue vertical interval corresponds to the 95% uncertainty interval (UI) without between-study heterogeneity; the dots are each included observation; the red Xs are outliered observations; the gray dotted line reflects the null log(RR); the blue line is the mean log(RR) for SHS and the outcome of interest; the red line is the Burden of Proof function at the fifth quantile for these harmful risk–outcome associations.CC BY · PubMed Central

Extended Data Fig. 1 Forest plot of the association between secondhand smoke exposure and ischemic heart disease. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (two-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 4 for more details on included observations from each study (n = 37 studies).CC BY · PubMed Central

Extended Data Fig. 2 Forest plot of the association between secondhand smoke exposure and stroke. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (two-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 5 for more details on included observations from each study (n = 20 studies).CC BY · PubMed Central

Extended Data Fig. 3 Forest plot of the association between secondhand smoke exposure and lung cancer. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (two-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 6 for more details on included observations from each study (n = 104 studies).CC BY · PubMed Central

Extended Data Fig. 4 Forest plot of the association between secondhand smoke exposure and breast cancer. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (one-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 7 for more details on included observations from each study (n = 51 studies).CC BY · PubMed Central

Extended Data Fig. 5 Forest plot of the association between secondhand smoke exposure and asthma. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (one-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 8 for more details on included observations from each study (n = 125 studies).CC BY · PubMed Central

Extended Data Fig. 6 Forest plot of the association between secondhand smoke exposure and lower respiratory infections. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (one-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 9 for more details on included observations from each study (n = 50 studies).CC BY · PubMed Central

Extended Data Fig. 7 Forest plot of the association between secondhand smoke exposure and chronic obstructive pulmonary disease. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (one-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 10 for more details on included observations from each study (n = 21 studies).CC BY · PubMed Central

Extended Data Fig. 8 plot of the association between secondhand smoke exposure and type 2 diabetes mellitus. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (two-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 11 for more details on included observations from each study (n = 9 studies).CC BY · PubMed Central

Extended Data Fig. 9 plot of the association between secondhand smoke exposure and otitis media. This forest plot presents the estimated mean relative risk, its 95% uncertainty intervals (UI), and the data points underlying the estimates for ischemic heart disease in association with secondhand smoke exposure (one-star rating of the risk-outcome relationship). The color of the point indicates whether the point was detected and trimmed as an outlier. The light blue interval corresponds to the 95% UI incorporating between-study heterogeneity; the dark blue interval corresponds to the 95% UI without between-study heterogeneity. The black vertical dotted line reflects the null relative risk value (one) and the red vertical line is the burden of proof function at the 5th quantile for this harmful risk-outcome association. The black data points and horizontal lines each correspond to a mean effect size and 95% UI from the included study identified on the y-axis. We included multiple observations from a single study when effects were reported by location or source of exposure and/or separately by sex or other subgroups. See Supplementary Table 12 for more details on included observations from each study (n = 24 studies).CC BY · PubMed Central

Extended Data Fig. 10 Summarized results of the primary model and sensitivity analyses conducted across all nine health outcomes. This heatmap reports the summarized results of the main model and the sensitivity analyses (columns) conducted for each of the nine health outcomes (rows) reported in this study. Detailed results for each of the sensitivity models are presented in the Supplementary Information (Supplementary Tables 13–16). Sensitivity analyses reflect the impact of restricting the input data to 1) prospective cohort studies, 2) observations associated with never-smokers, and 3) both prospective cohort studies and never-smoking samples. For asthma, we additionally restrict the data to children population aged 16 or less. General model parameters remained constant across models; we trimmed 10% of the data if more than 10 observations were available for the specific model. The color of the blue boxes and the number depicted in each box corresponds to the resulting risk-outcome score (ROS) calculated for models in which the estimates of association without incorporating between-study heterogeneity were statistically significant. Grey boxes depict models that did not pass this threshold and, thus, ROS did not apply (NA). For models that did pass this threshold, the ROS reflects a conservative interpretation of the data that aligns with the Burden of Proof approach incorporating between-study heterogeneity and other sources of uncertainty. The ROS is translated into a star rating from 1 to 5 stars based on thresholds outlined in Zheng et al. The star rating for each model result is reported as the yellow stars in each box. A one-star association suggests that there is weak evidence supporting estimates of an association between the risk and the outcome. A two-star association reflects that there is weak-to-moderate evidence suggesting an association between the risk and outcome, and additional stars illustrate increasing strength of evidence.CC BY · PubMed Central

Claims the paper makes

53 Own result · 41 Own method · 9 Own interpretation · 5 No basis given · 3 Supported · 2 Supported so far · 2 Partly supported · 2 No full text of the sources · 1 Sources not found · accuracy not yet measured

The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Studies of the effects of smoke-free laws found that hospital admission and mortality rates for cardiovascular and respiratory conditions decreased after the implementation of smoking bans455–459.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
What the sources say
- Supported
  The Introduction reports that studies found post-ban reductions in cardiovascular mortality and in hospital admissions for cardiovascular and respiratory conditions. The Discussion reports this study’s reductions in ischemic heart disease and respiratory mortality, and cites post-ban reductions in cardiac and pulmonary admissions. The paper therefore supports the broad claim, though the admissions findings come from studies it discusses rather than its own analysis. (LLM, conf=0.92)
  cites [455] Stallings-Smith, S., Zeka, A., Goodman, P., Kabir, Z. & Clancy, L. Reductions in cardiovascular, cerebrovascular, and respiratory mortality following the National Irish Smoking Ban: interrupted time-series analysis. PLoS ONE 8, e62063 (2013). source
- Supported
  The Results (Meta-Analysis; page not provided) report reduced cardiovascular mortality following smoke-free legislation. The Discussion (page not provided) reports reductions in cardiovascular hospitalizations and in both mortality and hospitalizations for respiratory conditions. (LLM, conf=0.93)
  cites [456] Akter, S. et al. Evaluation of population-level tobacco control interventions and health outcomes: a systematic review and meta-analysis. JAMA Netw. Open 6, e2322341 (2023). source
- Partly supported
  The Introduction reports reductions in cardiovascular mortality after some smoking bans, and the Results report reduced stroke admissions in Xi’an. But the paper’s findings are mixed for cardiovascular admissions, and its text does not report a reduction in respiratory admissions or mortality; respiratory outcomes appear only in cited reference titles. No page numbers are available in our copy. (LLM, conf=0.86)
  cites [457] Chu, M. et al. Effects of a smoke-free policy in Xi’an, China: impact on hospital admissions for acute ischemic heart disease and stroke. Front. Public Health 10, 898461 (2022). sourceExperimental — accuracy not yet measured
- Partly supported
  The Introduction (page not supplied) reports consistent reductions in cardiac events and hospitalizations after smoke-free legislation, while the Results report reduced respiratory admissions and respiratory mortality in some groups. The claim overstates the mortality evidence: the Introduction calls cardiovascular mortality findings conflicting, and the respiratory mortality reductions were limited to subgroups. (LLM, conf=0.90)
  cites [458] Rando-Matos, Y. et al. Smokefree legislation effects on respiratory and sensory disorders: a systematic review and meta-analysis. PLoS ONE 12, e0181035 (2017). sourceExperimental — accuracy not yet measured
- Partly supported
  The Conclusion (page unavailable) reports a decline in acute myocardial infarction mortality after smoke-free legislation, supporting the cardiovascular-mortality part of the claim. The paper does not report findings for hospital admissions or respiratory conditions; those outcomes appear in titles in its References (page unavailable). (LLM, conf=0.86)
  cites [459] Gao, M. et al. The effect of smoke-free legislation on the mortality rate of acute myocardial infarction: a meta-analysis. BMC Public Health 19, 1269 (2019). sourceExperimental — accuracy not yet measured
plain
direct
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Moreover, private homes remain a major source of SHS exposure, particularly for women and children3,460”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
What the sources say
- Partly supported
  The Objective states that homes remain the major place where children may be exposed to secondhand smoke, and the Results document substantial exposure at home among children in 21 countries. The paper does not establish the corresponding claim for women. Section labels are available in our copy, but page numbers are not. (LLM, conf=0.88)
  cites [3] Mbulo, L. et al. Secondhand smoke exposure at home among one billion children in 21 countries: findings from the Global Adult Tobacco Survey (GATS). Tob. Control 25, e95–e100 (2016). sourceExperimental — accuracy not yet measured
- Supported
  The “Level of SHS exposure at home” section states the claim directly and gives exposure estimates for women and children in their homes. (LLM, conf=0.95)
  cites [460] Huque, R. & Siddiqi, K. Smoke-free homes: the final frontier. Tob. Prev. Cessat. 7, 1–3 (2021). source
plain
correlational
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Previous studies have found different effect sizes for SHS exposure at home and at work442,443,462, a factor that was not investigated in our analysis.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
What the sources say
- Supported
  Table 4 reports separate effect-size estimates for exposure at home (1.17) and at work (1.11), supporting the part of the citing sentence attributed to this source. The paper says those estimates were not significantly different. The statement that the citing authors did not investigate this factor describes their own analysis, not this source. (LLM, conf=0.90)
  cites [442] He, J. et al. Passive smoking and the risk of coronary heart disease—a meta-analysis of epidemiologic studies. N. Engl. J. Med. 340, 920–926 (1999). source
- Not checked — no full text of the sourcecites [443] Lee, P. N., Forey, B. A., Hamling, J. S. & Thornton, A. J. Environmental tobacco smoke exposure and heart disease: a systematic review. World J. Meta-Anal. 5, 14–40 (2017). source
- Supported
  The Results section (“The PAF for lung cancer due to passive smoking in women, based on exposure source”) reports different pooled effect estimates for exposure at home and at work among female never smokers: odds ratios of 1.42 and 1.58, respectively. The statement that the citing authors did not investigate this factor concerns their own analysis, not a finding attributed to this source. (LLM, conf=0.92)
  cites [462] Du, Y. et al. Lung cancer occurrence attributable to passive smoking among never smokers in China: a systematic review and meta-analysis. Transl. Lung Cancer Res. 9, 204–217 (2020). source
plain
Every source the paper cites for this claim was checked and supports it.
In the paper
“The validity of the BPRF approach to meta-analyze data extracted across studies has been extensively and rigorously evaluated by Zheng and colleagues430.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Model validation
What the sources say
- Supported
  The Methods section (‘Model validation’; page not specified) describes 1,800 simulations testing the accuracy of the meta-analytic approach, including BPRF estimation. The Results section reports that the approach outperformed existing methods, particularly for non-log-linear relationships. (LLM, conf=0.93)
  cites [430] Zheng, P. et al. The Burden of Proof studies: assessing the evidence of risk. Nat. Med. 28, 2038–2044 (2022). source
boosted
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The BPRF and ROS were 0.93 and −0.04”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Respiratory conditions
plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The evidence supporting the harmful associations between SHS and otitis media, asthma, lower respiratory infections, breast cancer and chronic obstructive pulmonary disease was weaker (one star).”
- Also stated in: § Other health outcomes · plain
  “which equates to a ROS of −0.03 and a one-star rating (weak evidence of association)”
- Also stated in: § Discussion · plain
  “these risk–outcome pairs were classified as one-star associations”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Abstract
plain
correlational
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with the evidence supporting these harmful associations rated as weak (two stars)”
- Also stated in: § Other health outcomes · plain
  “translating to a two-star risk”
- Also stated in: § Discussion · plain
  “corresponding to two-star associations with SHS”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Abstract
plain
correlational
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We conservatively estimated that SHS increases the risk of ischemic heart disease, stroke, type 2 diabetes and lung cancer by at least around 8%, 5%, 1% and 1%, respectively”
- Also stated in: § Cardiovascular diseases · hedged
  “indicating that exposure to tobacco smoke was associated with at least a 5% higher risk of stroke”
- Also stated in: § Discussion · plain
  “being exposed to SHS increased the risk of IHD, stroke and type 2 diabetes by a minimum of 8%, 5% and 1%, respectively”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Abstract
plain
direct
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the estimated RR incorporating between-study heterogeneity into the uncertainty was 1.21 (0.88–1.66)”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Respiratory conditions
hedged
correlational
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The evidence supporting the harmful associations between SHS and otitis media, asthma, lower respiratory infections, breast cancer and chronic obstructive pulmonary disease was weaker (one star).”
- Also stated in: § Cancer · plain
  “one-star rating”
- Also stated in: § Discussion · plain
  “these risk–outcome pairs were classified as one-star associations”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Abstract
plain
correlational

Show all 82 claims

Probably not a substantial claim. 24
It may state two separate claims as one. 15
The quote only partly states this claim. 2

The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Additionally, previous research, including meta-analyses, found suggestive evidence of an association between SHS exposure and breast cancer13–15.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Main
What the sources say
- Supported
  The Results (§3.3, Subgroup Analysis) report a statistically significant association between secondhand smoke exposure and breast cancer across 15 studies. The claim’s cautious wording is consistent with the limitations acknowledged in the Discussion (§4). (LLM, conf=0.94)
  cites [13] Kim, A.-S., Ko, H.-J., Kwon, J.-H. & Lee, J.-M. Exposure to secondhand smoke and risk of cancer in never smokers: a meta-analysis of epidemiologic studies. Int. J. Environ. Res. Public Health 15, 1981 (2018). source
- Supported
  The Discussion says exposure to environmental tobacco smoke seems associated with a moderately increased breast cancer risk, while noting difficulties in assessing second-hand smoke exposure and the small number of studies. The Passive smoking section also reports a statistically significant increase in the meta-analysis of prospective cohorts, supporting the claim's cautious wording. (LLM, conf=0.93)
  cites [14] Macacu, A., Autier, P., Boniol, M. & Boyle, P. Active and passive smoking and risk of breast cancer: a meta-analysis. Breast Cancer Res. Treat. 154, 213–224 (2015). source
- Not checked — no full text of the sourcecites [15] Carreras, G. et al. Burden of disease attributable to second-hand smoke exposure: a systematic review. Prev. Med. 129, 105833 (2019). source
hedged
correlational
Probably not a substantial claim. The paper’s conclusions may not depend on it.
Every source the paper cites for this claim was checked and supports it.
In the paper
“The present study complies with the PRISMA guidelines19 (Supplementary Tables 17 and 18 and Supplementary Figs. 1–9) and Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) recommendations (Supplementary Table 19)468.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Overview
What the sources say
- Supported
  The Abstract identifies this paper as the PRISMA 2020 reporting guideline and says it presents its checklists and reporting recommendations. Citation 19 is attached to “PRISMA guidelines”; the citing authors’ assertion that their study complies with them is not a claim this source is asked to verify. The GATHER recommendations have separate citations. (LLM, conf=0.92)
  cites [19] Page, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372, n71 (2021). source
- Supported
  The Summary identifies this paper as the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) and describes its reporting checklist. The citation supports the identification of the GATHER recommendations; the citing authors’ assertion that their study complies with them is not a finding attributed to this source. PRISMA has a separate citation in the citing sentence. (LLM, conf=0.91)
  cites [468] Stevens, G. A. et al. Guidelines for accurate and transparent health estimates reporting: the GATHER statement. Lancet 388, e19–e23 (2016). source
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
Every source the paper cites for this claim was checked and supports it.
In the paper
“Furthermore, the BPRF framework employed in this study addresses many of the limitations of existing meta-analytical approaches18.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
What the sources say
- Supported
  In “Reply to: Concerns about the Burden of Proof studies” (page not provided), the authors say the BoP approach was designed to address key problems in current analytical frameworks. They describe how it accounts for between-study heterogeneity and avoids imposing a log-linear relationship, supporting the broad paraphrase. (LLM, conf=0.91)
  cites [18] Aravkin, A. Y. et al. Reply to: concerns about the Burden of Proof studies. Nat. Med. 29, 826–827 (2023). source
plain
direct
Probably not a substantial claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, we found SHS to have small to moderate quantitative impacts on health—mean effect sizes range from 1.12 for otitis media to 1.44 for COPD—which is in line with previous assessments13,431–441 and anticipated on the basis of mechanistic processes leading to diseases5.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
plain
correlational
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“when restricting our analysis to prospective cohort studies, the ROS was slightly higher, elevating the risk–outcome relationship to a two-star rating, with no bias covariates found statistically significant”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Other health outcomes
plain
correlational
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“which equates to a ROS of −0.03”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Other health outcomes
plain
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the ROS for COPD was also negative (−0.14)”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Respiratory conditions
plain
correlational
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our study contributes to previous iterations of the GBD by not only increasing the number of studies informing each of the existing SHS–outcome associations but by assessing the relationship between passive smoking and asthma, a risk–outcome pair not yet incorporated into the GBD but deemed eligible for further consideration.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
plain
correlational
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In particular, we found insufficient evidence to support an association with SHS when restricting to prospective cohort studies (breast cancer) and never smokers (COPD), even when not incorporating between-study heterogeneity in our estimates of uncertainty.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
plain
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We did not detect publication bias, as identified by Egger’s regression test, in the primary analysis or in any of the sensitivity analyses for the cardiovascular outcomes”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Cardiovascular diseases
plain
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The potential existence of publication bias, which, if present, would affect the validity of the results, was tested using Egger’s regression.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Overview
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“the automated covariate selection did not find any significant bias covariates for inclusion in the main or alternative final models”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Other health outcomes
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The covariate selection algorithm flagged studies performed among populations that were not generalizable and those that used exposure definitions other than current SHS (for example, ever exposure to SHS) to be adjusted in our final model (Table 2).”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Respiratory conditions
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The bias covariate algorithm selected observations that did not originally control for smoking to be adjusted in the final model (Table 2).”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Cancer
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although some of the SHS–disease associations we estimated were relatively weak, this is due in part to inconsistencies in methods and results across input studies.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Main
hedged
direct
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The selected bias covariates were chosen for inclusion in the model using an algorithm that systematically detects bias covariates that correspond to significant sources of bias in the included observations.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Overview
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We found no publication bias in our primary model, but a statistically significant evidence of publication bias was found in our prospective cohort sensitivity analysis.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Results > Other health outcomes
plain
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We systematically tested for the effect of bias covariates using a selection algorithm, which uses a step-wise Lasso strategy to identify statistically significant covariates at a threshold of 0.05, and adjusted for the selected bias covariates in the final model used to generate the RR estimates.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Testing and adjusting for biases across study designs and characteristics
plain
Probably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In the included studies, those not exposed at work or home may be exposed to SHS at other settings, and this bias, similar to our first limitation above, will tend to underestimate the true RR.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
hedged
direct
It may state two separate claims as one.
In the paper
“However, comprehensive smoke-free legislation (that is, covering all indoor public places) is in place in only 67 countries, protecting less than 25% of the world’s population7.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
What the sources say
- Not matched
  Couldn’t be matched to a paper in Crossref, so it can’t be checked.
  cites [7] WHO Report on the Global Tobacco Epidemic 2021: Addressing New and Emerging Products. (World Health Organization, 2021).
plain
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Bias covariates were created to capture the impact of using alternate exposure definitions.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Estimating pooled RRs for each risk–outcome pair
plain
direct
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This study did not engage in primary data collection, randomization or blinding. Therefore, data exclusions were not relevant to the present study, and, as such, no data were excluded from the analyses.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Statistical analysis and reproducibility
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Finally, despite the inclusion of asthma, a new health outcome to be considered for inclusion in the GBD, the outcomes assessed here do not necessarily reflect the harms associated with SHS in full.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
hedged
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All extracted data underwent manual quality assurance by the research team to verify accuracy.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Systematic review
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In this study, the RR metric of primary interest was the pooled RR with 95% uncertainty intervals that are inclusive (using gamma) of the effect of between-study heterogeneity.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Quantifying remaining between-study heterogeneity
plain
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We flagged the potential publication bias but did not correct for it in the model.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Evaluating publication and reporting bias
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Following the BPRF methodology, we applied a 10% likelihood-based data-trimming algorithm to detect and remove outliers that may otherwise over-influence the model. This approach is suggested for all analyses with more than ten data points; therefore, it was implemented across all of our primary risk–outcome assessments and most of our sensitivity analyses470.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Estimating pooled RRs for each risk–outcome pair
What the sources say
- Not checked — no full text of the sourcecites [470] Zheng, P., Barber, R., Sorensen, R. J. D., Murray, C. J. L. & Aravkin, A. Y. Trimmed constrained mixed effects models: formulations and algorithms. J. Comput. Graph. Stat. 30, 544–556 (2021). source
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, our findings also suggest that the risk of lung cancer and type 2 diabetes are also elevated for those exposed to SHS.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Discussion
hedged
correlational
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To reduce the influence on our model of multiple observations coming from the same study, we adjusted the standard errors of effect sizes reported for multiple non-mutually exclusive exposure groups in each study by a factor matching the number of repeated measurements within each age–sex–smoking status group (Supplementary Information Section 2.2).”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Estimating pooled RRs for each risk–outcome pair
plain
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For the present study, we conducted three main sensitivity analyses to examine the robustness of our primary findings to our data input in which we kept most of the model parameters consistent but (1) restricted our analysis to studies with a prospective cohort design; (2) subset our input data to never-smoking samples only; and (3) applied both these restrictions in conjunction.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Model validation
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For asthma, specifically, we ran an additional model in which we restrict the data to those studies performed among children only (≤16 years old).”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Model validation
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We have made our data and code available to foster reproducibility.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Statistical analysis and reproducibility
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“After adjusting for study-level bias covariates, we used a linear mixed-effects model to capture the remaining unexplained between-study heterogeneity, in which we included a study-level random slope (gamma) and a study-level random intercept for within-study correlation.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Quantifying remaining between-study heterogeneity
plain
Probably not a substantial claim.
In the paper
“We also assessed each study for risk of potential bias following the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and recorded the information in the extraction template469.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Systematic review
What the sources say
- Not checked — no full text of the sourcecites [469] Guyatt, G. H. et al. GRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias). J. Clin. Epidemiol. 64, 407–415 (2011). source
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“As a component of the GBD, the present analysis was approved by the University of Washington institutional review board committee (study no. 9060).”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Overview
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“No statistical method was used to predetermine sample size. For each health outcome, we included all studies that met our inclusion criteria.”
§ Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Statistical analysis and reproducibility
plain
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

36 of 36

The paper relies on this without support.
Substantial heterogeneity exists across and within SHS risk–outcome assessments in terms of quantity and quality of studies and reported strength of associations.
“Despite these findings, substantial heterogeneity is detected across and within SHS risk–outcome assessments in terms of quantity and quality of studies and reported strength of associations.”
The paper relies on this without support.
Variation across studies in definitions of risk exposure used is observed.
“Variation across studies in the definitions of risk exposure used is also observed, with some reporting the risk associated with SHS exposure in specific settings16 or from specific sources (that is, maternal, paternal)17.”
The paper relies on this without support.
The units and dose categories reported across studies vary widely due to limited availability of studies with environmental and biological samples and lack of a standard measure of SHS exposure.
“Furthermore, given the limited availability of studies that assess exposure to tobacco smoke on the basis of environmental and biological samples, and the lack of a standard measure of SHS exposure, the units and dose categories reported across studies vary widely.”
The paper relies on this without support.
These inconsistencies limit the comparability and consolidation of evidence concerning the health effects of SHS.
“Together, these inconsistencies can limit the comparability and consolidation of evidence concerning the health effects of SHS.”

4 of 4

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
- § Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Statistical analysis and reproducibility
  “Therefore, data exclusions were not relevant to the present study, and, as such, no data were excluded from the analyses.”
- § Health effects associated with exposure to secondhand smoke: a Burden of Proof study > Methods > Estimating pooled RRs for each risk–outcome pair
  “Following the BPRF methodology, we applied a 10% likelihood-based data-trimming algorithm to detect and remove outliers that may otherwise over-influence the model. This approach is suggested for all analyses with more than ten data points; therefore, it was implemented across all of our primary risk–outcome assessments and most of our sensitivity analyses470.”

1 of 1

The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283
Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019
Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30925-9 · Cited by 19,358 · cited 2×
“This is of particular concern as IHD and stroke are the two major causes of premature death and loss of healthy life worldwide 449 .”
BackgroundSelf-citation
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Murray, C. J. L., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30752-2 · Cited by 9,854
Self-citation
The Health consequences of smoking—50 years of progress : a report of the Surgeon General
Lushniak, B. D., Samet, J. M., Pechacek, T. F., Norman, L., & Taylor, P. A. (2014) · Cited by 4,990
GRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias)
Guyatt, G. H., Oxman, A. D., Vist, G., Kunz, R., Brozek, J., Alonso-Coello, P., Montori, V., Akl, E. A., Djulbegovic, B., & Falck-Ytter, Y. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.07.017 · Cited by 2,798 · cited 1×
“We also assessed each study for risk of potential bias following the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and recorded the information in the extraction template 469 .”
Method
Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016
Gakidou, E., Afshin, A., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulle, A. M., Abera, S. F., Aboyans, V., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)32366-8 · Cited by 2,406 · cited 11×
“Across these outcomes, no significant publication bias was detected in the primary models (Table 2) or in the sensitivity analyses (Supplementary Tables 13–16).”
BackgroundInfluentialSelf-citation
Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019
Kocarnik, J., Compton, K., Dean, F. E., Fu, W., Gaw, B., Harvey, J. D., Henrikson, H. J., Lu, D., Pennini, A., Xu, R., et al. (2021) · JAMA Oncology · doi:10.1001/jamaoncol.2021.6987 · Cited by 2,200 · cited 1×
“Because breast cancer is the most frequent type of cancer in women and accounts for substantial morbidity and mortality, research should continue to examine its association with exposure to SHS 451 .”
Guidelines for accurate and transparent health estimates reporting: the GATHER statement
Stevens, G. A., Alkema, L., Black, R. E., Boerma, J. T., Collins, G. S., Ezzati, M., Grove, J. T., Hogan, D. R., Hogan, M. C., Horton, R., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(16)30388-9 · Cited by 1,798
Self-citation
Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019
Reitsma, M. B., Kendrick, P. J., Ababneh, E., Abbafati, C., Abbasi-Kangevari, M., Abdoli, A., Abedi, A., Abhilash, E. S., Abila, D. B., Aboyans, V., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)01169-7 · Cited by 1,759 · cited 3×
“1–9).”
BackgroundInfluentialSelf-citation
Epidemiology of Otitis Media During the First Seven Years of Life in Children in Greater Boston: A Prospective, Cohort Study
Teele, D. W., Klein, J. O., ROSNER, B. A., & Greater Boston Otitis Media Study Group (1989) · The Journal of Infectious Diseases · doi:10.1093/infdis/160.1.83 · Cited by 1,488

Show all 469 references

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Salama, B. M., Abukanna, A. & Hegazy, A. Risk factors associated with chronic obstructive pulmonary disease in Arar, Saudi Arabia: a case–control study. Med. Sci. 24, 2487–2493 (2020).
Janghorbani, M. & Sadeghigolmakani, N. Passive smoking and the risk of coronary heart disease among married non-smoking women. Med. J. Islam. Repub. Iran 11, 203–208 (1997).
Woo, C. et al. A prospective study of passive cigarette smoke exposure and breast cancer. Am. J. Epidemiol. 151, 11 (2000).
Dina, A. D. & Djuwita, R. The role of exclusive breastfeeding in reducing pneumonia prevalence in children under five. J. Gizi dan Pangan 16, 89–98 (2021).

Sorted by citations

Items 101–167 of 167

Second-hand smoke exposure modulates plasma proteins linked to detoxification, inflammation and atherothrombosis
Neves, S., Pacheco, S., Vaz, F., Valentim-Coelho, C., Saraiva, J., James, P., Simões, T., & Penque, D. (2025) · Environmental Toxicology and Pharmacology · doi:10.1016/j.etap.2025.104864
Attributable mortality to secondhand tobacco smoke exposure in the 27 Brazilian federal units in 2019
Flores, B. W., Rey‐Brandariz, J., Corrêa, P. C. R. P., Guerra-Tort, C., García, G., Gisbert, L. M., Candal‐Pedreira, C., Montes, A., & Pérez‐Ríos, M. (2025) · Tobacco Control · doi:10.1136/tc-2025-059444 · Cited by 1
“…concluded that SHS exposure increased the risk of developing other diseases, such as COPD, asthma, type 2 diabetes mellitus, breast cancer and lower respiratory tract infections, 4 though the evidence that supported the association with these diseases was described as weak or very weak.”
Content analysis of media coverage on smoke-free policy implementation in ten low- and middle-income countries
Xing, E., Kim, S., Cohen, J. E., & Tseng, T. (2025) · Tobacco Induced Diseases · doi:10.18332/tid/211700
Global burden of tracheal, bronchus, and lung cancer attributable to second-hand smoke exposure from 1992 to 2021: an age-period-cohort analysis and 25-year mortality projections
Lin, H., Lin, B., Liao, X.-P., Hong, H., Cai, X.-T., & Zhuang, X. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1625876
Global burden of childhood otitis media attributable to secondhand smoke from 1990 to 2021: a systematic analysis of the global burden of disease study 2021
Li, B., Pan, Q., & Zou, K. (2025) · Frontiers in Pediatrics · doi:10.3389/fped.2025.1619721
“SHS introduces harmful substances, such as nicotine and other irritants, which compromise the respiratory and immune defense systems in children (11).”
Household Tobacco Expenditure and Child Health Outcomes: Causal Evidence from a Transitional Economy
Tran, K.-A., Trang, L. M., Huang, Y., & Do, M. (2025) · Healthcare · doi:10.3390/healthcare13243312
“This impact is expected to be particularly pronounced in younger children, who are more vulnerable to tobacco exposure [37,38].”
Animal models of second-hand cigarette smoke (SHS) exposure in neurodevelopmental disorders and neurodegenerative disease
Kisby, G. E., & Raber, J. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29090-9.00021-0
a systematic analysis for the Global Burden of Disease Study 2023
Hay, S. I., Ong, K. L., Santomauro, D. F., Bhoomadevi, A., Aalipour, M. A., Aalruz, H., Ababneh, H. S., Abaraogu, U. O., Abate, B. B., Abbafati, C., et al. (2025) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Self-citation
Research on Passive Smoking and Cardiovascular Diseases in 21 st Century : A Bibliometric Analysis
Panda, S. N., ROUT, H. K., Pattanaik, A. A., et al. (2025) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-025-02169-8
“Passive smoking causes diseases similar to direct smoking, including cardio-vascular disease, lung cancer, and respiratory conditions [5].”
Impact of Smoking on Respiratory Function in Young Women
Bilici, M. F., & Çelik, M. (2025) · International Journal of Sport Exercise & Training Sciences · doi:10.18826/useeabd.1768180
Penguatan Perilaku Hidup Sehat melalui Edukasi Bahaya Merokok di Desa Nobowetan Kota Salatiga
Saelan, S., Rizky, W., Syukur, B. A., et al. (2026) · Jurnal Masyarakat Madani Indonesia · doi:10.59025/d1pa9v42
Commit to Quit: Essential Elements of a Novel Tobacco Intervention for Arab American Women
Lee, J. P., Inoue-Terris, V., Salam, L., Abdelhalim, G., Mohrez, H., & Alnahari, S. (2026) · Health Promotion Practice · doi:10.1177/15248399261419091
Evaluating the DALY impact of disease associated with second-hand smoke exposure in different socio-demographic index regions
GholamiVeis, R., Moradinazar, M., Mirzaei-Alavijeh, M., et al. (2026) · Substance Abuse Treatment Prevention and Policy · doi:10.1186/s13011-026-00711-y
Second-hand tobacco smoke exposure in Israel: A systematic review and meta-analysis of prevalence data, 2012-2024
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Workplace Exposure to Cigarette Smoking and Secondhand Smoke Associated with Physical Pain among Taiwanese Male Workers: A Cross- Sectional Study from the Taiwan BiobankPreprint
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Determinants of tobacco use among men aged 15 to 59 in Sub Sahara Africa: a multilevel mixed effect logistic regression analysis
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“After not being exposed to nicotine, as complicated as it is considering the effects observed of second and third-hand exposures (23,24), the cessation of the consumption of nicotine products is the most effective measure to combat the harms of such consumption (25).”
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Development and internal validation of a clinical nomogram incorporating quantitative CT features for predicting malignancy in pulmonary nodules ≤ 3 cm
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Paparan asap rokok dan status imunisasi sebagai faktor risiko dominan kejadian infeksi saluran pernapasan akut pada balita di BLUD Puskesmas Timika
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Tıp fakültesi öğrencilerinde üçüncü el sigara dumanına ilişkin inanışlar ve nikotin bağımlılığı düzeylerinin değerlendirilmesi
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Sex-Specific Considerations for Physical Activity, Diet, and Smoking
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Tobacco‐Attributable Burden of Early‐Onset Ischemic Heart Disease From 1990 to 2023: A Global Analysis Using GBD 2023 and Age‐Period‐Cohort Modeling
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Authors: Flor, L. S., Anderson, J. A., Ahmad, N., Aravkin, A., Carr, S., Dai, X., Gil, G. F., Hay, S. I., Malloy, M. J., McLaughlin, S. A., Mullany, E. C., Murray, C. J. L., O’Connell, E. M., Okereke, C., Sorensen, R. J. D., Whisnant, J., Zheng, P., & Gakidou, E.
Affiliations: University of Washington (US)
ORCID: Flor, Luisa S.
Aravkin, Aleksandr
Carr, Sinclair
Dai, Xiaochen
Gil, Gabriela F.
Hay, Simon I.
Murray, Christopher J. L.
O’Connell, Erin M.
Okereke, Chukwuma
Sorensen, Reed J. D.
Whisnant, Joanna
Gakidou, Emmanuela
Venue: Nature Medicine
Publisher: Springer Science and Business Media LLC
Published: 2024-01
Volume: 30
Issue: 1
Pages: 149-167
ISSN: 1078-8956 (ISSN-L)
1546-170X
DOI: 10.1038/s41591-023-02743-4
PMC: PMC10803272
OpenAlex: W4390706631
Semantic Scholar: b2594595aa44eea39d24b194c85ea97e6be58be7
Cited by: 167
References: 469
Citations by year: 2026: 75 · 2025: 71 · 2024: 21
FWCI: 47.64
Type: journal article
Language: en
Update notices: correction (2024-01-30)
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor, 8 d)
Locations: Nature Medicine (publishedVersion, cc-by)
PubMed (publishedVersion)
PubMed Central (submittedVersion, cc-by)
Funders: Bloomberg Family Foundation
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Smoking Behavior and Cessation
Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Chronic Obstructive Pulmonary Disease (COPD) Research
Keywords: passive smoking, non-smokers, health outcomes, ischemic heart disease, stroke, type 2 diabetes, lung cancer, otitis media, asthma, lower respiratory tract infection, breast cancer, chronic obstructive pulmonary disease, quality of evidence
MeSH terms: Asthma, Breast Neoplasms, Child, Diabetes Mellitus, Type 2, Female, Humans, Respiratory Tract Infections, Tobacco Smoke Pollution

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Health effects associated with exposure to secondhand smoke: a Burden of Proof study

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