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A Simple Method to Establish Sufficiency and Stability in Meta-Analyses: With Application to Fine Particulate Matter Air Pollution and Preterm Birth

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  • Gavin Pereira

    (Curtin School of Population Health, Curtin University, Perth, WA 6102, Australia
    enAble Institute, Curtin University, Perth, WA 6102, Australia
    Centre for Fertility and Health (CeFH), Norwegian Institute of Public Health, 0473 Oslo, Norway)

Abstract

Fine particulate matter air pollution (PM 2.5 ) is a potential cause of preterm birth. Inconsistent findings from observational studies have motivated researchers to conduct more studies, but some degree of study heterogeneity is inevitable. The consequence of this feedback is a burgeoning research effort that results in marginal gains. The aim of this study was to develop and apply a method to establish the sufficiency and stability of estimates of associations as they have been published over time. Cohort studies identified in a recent systematic review and meta-analysis on the association between preterm birth and whole-pregnancy exposure to PM 2.5 were selected. The estimates of the cohort studies were pooled with cumulative meta-analysis, whereby a new meta-analysis was run for each new study published over time. The relative risks (RR) and 95% confidence interval (CI) limits needed for a new study to move the cumulative RR to 1.00 were calculated. Findings indicate that the cumulative relative risks (cRR) for PM 2.5 (cRR 1.07, 95% CI 1.03, 1.12) converged in 2015 (RR 1.07, 95% CI 1.01, 1.14). To change conclusions to a null association, a new study would need to observe a protective RR of 0.93 (95% CI limit 1.02) with precision equivalent to that achieved by all past 24 cohort studies combined. Preterm birth is associated with elevated PM 2.5, and it is highly unlikely that any new observational study will alter this conclusion. Consequently, establishing whether an observational association exists is now less relevant an objective for future studies than characterising risk (magnitude, impact, pathways, populations and potential bias) and interventions. Sufficiency and stability can be effectively applied in meta-analyses and have the potential to reduce research waste.

Suggested Citation

  • Gavin Pereira, 2022. "A Simple Method to Establish Sufficiency and Stability in Meta-Analyses: With Application to Fine Particulate Matter Air Pollution and Preterm Birth," IJERPH, MDPI, vol. 19(4), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2036-:d:747202
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    References listed on IDEAS

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    1. Yin Feng & Jinhua Cheng & Jun Shen & Han Sun, 2019. "Spatial Effects of Air Pollution on Public Health in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(1), pages 229-250, May.
    2. Mikati, I. & Benson, A.F. & Luben, T.J. & Sacks, J.D. & Richmond-Bryant, J., 2018. "Disparities in distribution of particulate matter emission sources by race and poverty status," American Journal of Public Health, American Public Health Association, vol. 108(4), pages 480-485.
    3. Muellerleile, P. & Mullen, B., 2006. "Sufficiency and stability of evidence for public health interventions using cumulative meta-analysis," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 515-522.
    4. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
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