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

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. +10 more·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.

Claims the paper makes

15 of 20 cited sources checked · 11 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    Studies of the effects of smoke-free laws found that hospital admission and mortality rates for cardiovascular and respiratory conditions decreased after implementation of smoking bans.

    “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.”
    Quote in the paperNot a substantial claim5 of 5 sources checked
    • 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
    • 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
    • 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). source

      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)

      Experimental — accuracy not yet measured
    • 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). source

      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)

      Experimental — accuracy not yet measured
    • 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). source

      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)

      Experimental — accuracy not yet measured
  • Premisecitation

    Private homes remain a major source of SHS exposure, particularly for women and children.

    “Moreover, private homes remain a major source of SHS exposure, particularly for women and children3,460”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • 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). source

      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)

      Experimental — accuracy not yet measured
    • cites [460] Huque, R. & Siddiqi, K. Smoke-free homes: the final frontier. Tob. Prev. Cessat. 7, 1–3 (2021). source
  • Study design and conductown data

    The analysis did not investigate differences in effect sizes for SHS exposure at home versus at work.

    “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.”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • 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
    • cites [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
    • 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
  • Premisecitation

    The validity of the BPRF approach has been extensively and rigorously evaluated by Zheng and colleagues.

    “The validity of the BPRF approach to meta-analyze data extracted across studies has been extensively and rigorously evaluated by Zheng and colleagues430.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [430] Zheng, P. et al. The Burden of Proof studies: assessing the evidence of risk. Nat. Med. 28, 2038–2044 (2022). source
  • Findingown data

    The ROS for SHS and asthma is −0.04.

    “The BPRF and ROS were 0.93 and −0.04”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 24
  • May combine two claims. 15
  • The quote only partly states this claim. 2

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous research, including meta-analyses, found suggestive evidence of an association between SHS exposure and breast cancer.

    “Additionally, previous research, including meta-analyses, found suggestive evidence of an association between SHS exposure and breast cancer13–15.”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • 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
    • 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
    • cites [15] Carreras, G. et al. Burden of disease attributable to second-hand smoke exposure: a systematic review. Prev. Med. 129, 105833 (2019). source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation

    The present study complies with PRISMA guidelines and GATHER recommendations.

    “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.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [19] Page, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372, n71 (2021). source
    • cites [468] Stevens, G. A. et al. Guidelines for accurate and transparent health estimates reporting: the GATHER statement. Lancet 388, e19–e23 (2016). source

  • Classified as probably not a substantial claim.

    Premisecitation

    The BPRF framework addresses many of the limitations of existing meta-analytical approaches.

    “Furthermore, the BPRF framework employed in this study addresses many of the limitations of existing meta-analytical approaches18.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [18] Aravkin, A. Y. et al. Reply to: concerns about the Burden of Proof studies. Nat. Med. 29, 826–827 (2023). source

  • May combine two claims.

    Findingown data

    Overall, SHS exposure has small to moderate quantitative impacts on health, with mean effect sizes ranging from 1.12 for otitis media to 1.44 for COPD.

    “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.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When restricting the otitis media analysis to prospective cohort studies, the ROS was slightly higher, elevating the relationship to a two-star rating, with no bias covariates found statistically significant.

    “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”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingreasoning

    The ROS for SHS and otitis media is −0.03.

    “which equates to a ROS of −0.03”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    The ROS for SHS and COPD is −0.14.

    “the ROS for COPD was also negative (−0.14)”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The study increases the number of studies informing existing SHS-outcome associations and assesses the relationship between passive smoking and asthma, a risk-outcome pair not yet incorporated into the GBD.

    “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.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    There was insufficient evidence to support an association between SHS and breast cancer when restricting to prospective cohort studies, and between SHS and COPD when restricting to never smokers, even without incorporating between-study heterogeneity.

    “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.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    No publication bias was detected for the SHS-IHD and SHS-stroke models in the primary analysis or in any sensitivity analyses.

    “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”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The potential existence of publication bias was tested using Egger's regression.

    “The potential existence of publication bias, which, if present, would affect the validity of the results, was tested using Egger’s regression.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The automated covariate selection did not find any significant bias covariates for inclusion in the type 2 diabetes main or alternative final models.

    “the automated covariate selection did not find any significant bias covariates for inclusion in the main or alternative final models”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    For the lower respiratory infections model, the covariate selection algorithm flagged studies performed among populations that were not generalizable and those that used exposure definitions other than current SHS to be adjusted in the final model.

    “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).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    For the lung cancer model, the bias covariate algorithm selected observations that did not originally control for smoking to be adjusted in the final model.

    “The bias covariate algorithm selected observations that did not originally control for smoking to be adjusted in the final model (Table 2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Some of the SHS-disease associations estimated were relatively weak, due in part to inconsistencies in methods and results across input studies.

    “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.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The selected bias covariates were chosen for inclusion in the model using an algorithm that systematically detects bias covariates corresponding to significant sources of bias in the included observations.

    “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.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    No publication bias was found in the primary otitis media model, but statistically significant evidence of publication bias was found in the prospective cohort sensitivity analysis.

    “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.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    Bias covariates were systematically tested using a step-wise Lasso strategy at a threshold of 0.05, and selected covariates were adjusted for in the final model.

    “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.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductreasoning

    In the included studies, those not exposed at work or home may be exposed to SHS at other settings, and this bias will tend to underestimate the true RR.

    “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.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Comprehensive smoke-free legislation covering all indoor public places is in place in only 67 countries, protecting less than 25% of the world's population.

    “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.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [7] WHO Report on the Global Tobacco Epidemic 2021: Addressing New and Emerging Products. (World Health Organization, 2021).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Bias covariates were created to capture the impact of using alternate exposure definitions.

    “Bias covariates were created to capture the impact of using alternate exposure definitions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    The study did not engage in primary data collection, randomization or blinding, and no data were excluded from analyses.

    “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.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The outcomes assessed do not necessarily reflect the harms associated with SHS in full.

    “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.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All extracted data underwent manual quality assurance by the research team to verify accuracy.

    “All extracted data underwent manual quality assurance by the research team to verify accuracy.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The primary RR metric was the pooled RR with 95% uncertainty intervals inclusive of between-study heterogeneity (using gamma).

    “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.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The potential publication bias for otitis media was flagged but not corrected for in the model.

    “We flagged the potential publication bias but did not correct for it in the model.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    A 10% likelihood-based data-trimming algorithm was applied to detect and remove outliers across primary risk-outcome assessments and most sensitivity analyses.

    “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.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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

  • May combine two claims.

    Interpretationown data

    SHS exposure is associated with elevated risk of lung cancer and type 2 diabetes.

    “Similarly, our findings also suggest that the risk of lung cancer and type 2 diabetes are also elevated for those exposed to SHS.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Standard errors of effect sizes for multiple non-mutually exclusive exposure groups were adjusted by a factor matching the number of repeated measurements within each age-sex-smoking status group.

    “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).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Three main sensitivity analyses were conducted to examine robustness of primary findings: restricting to prospective cohort studies, subsetting to never-smoking samples, and applying both restrictions.

    “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.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    For asthma, an additional model restricted data to studies performed among children only (≤16 years old).

    “For asthma, specifically, we ran an additional model in which we restrict the data to those studies performed among children only (≤16 years old).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Data and code were made available to foster reproducibility.

    “We have made our data and code available to foster reproducibility.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    A linear mixed-effects model with a study-level random slope and random intercept was used to capture remaining unexplained between-study heterogeneity.

    “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.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Each included study was assessed for risk of potential bias following the GRADE approach.

    “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.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [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

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The present analysis was approved by the University of Washington institutional review board committee (study no. 9060).

    “As a component of the GBD, the present analysis was approved by the University of Washington institutional review board committee (study no. 9060).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    No statistical method was used to predetermine sample size; all studies meeting inclusion criteria were included for each health outcome.

    “No statistical method was used to predetermine sample size. For each health outcome, we included all studies that met our inclusion criteria.”
    Quote in the paperNot a substantial claim
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.

  • Claim of no data exclusions conflicts with outlier removal

    Minor

    The reproducibility statement says no data were excluded from the analyses, but the methods say an outlier-removal procedure was applied across all primary analyses.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 4

  1. 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).
  2. 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).
  3. Woo, C. et al. A prospective study of passive cigarette smoke exposure and breast cancer. Am. J. Epidemiol. 151, 11 (2000).
  4. 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).

Cited by

Sorted by citations

Related

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
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
Licence
Locations
  • Nature Medicine (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
Funders
Bloomberg Family Foundation
Topics
  • Health Sciences › Medicine › Physiology › 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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-29.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-29.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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