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Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population: Methodological issues
Environmental Pollution xxx (2017) 1
Contents lists available at ScienceDirect
Environmental Pollution journal homepage: www.elsevier.com/locate/envpol
Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population: Methodological issues*
To the Editors, We have read with great interest the manuscript entitled “Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population” by Wei et al. published in Environmental Pollution (Wei et al., 2017). The authors aimed to assess the impact of exposure to the cooking oil fumes COFs of Chinese household cooking on sleep quality (Wei et al., 2017). We would like to congratulate the authors on their published results in high quality journal of Environmental Pollution. They provide interesting data on this subject. However, we noticed misclassification bias and unmeasured confounding are main limitations of the study and some methodological and statistical issues should be considered to avoid misinterpretation. The authors mentioned in the limitations of the article that sleep quality was assessed using a self-administrative questionnaire of The Pittsburgh sleep quality index (PSQI) (Buysse et al., 1989), so that, misclassification of sleep quality is unavoidable. In other words, good sleeper individuals may be misclassified as poor sleepers or vice versa. Misclassification of exposures and outcomes are common biases in biomedical researches and it treats the validity of the estimated parameters from regression models (Lyles and Lin, 2010). Efficient methods and tools are available for adjusting misclassification bias (Fox et al., 2005; Lyles and Lin, 2010; Orsini et al., 2008). In these methods the data will be reconstructed and the misclassified exposure or outcome will be correctly classified, given the bias parameters such as sensitivity and specificity. After data reconstruction, OR will be estimated (Fox et al., 2005). We find the crude OR for effect of subjective kitchen ventilation on sleep quality (global score >5) is 1.82. The negligible difference between OR in crude (1.82) and adjusted model (1.76) means there is residual confounding due to unmeasured confounders such as socioeconomic status. However, Orsini and colleagues developed tools to conduct sensitivity analysis to test how the results are influenced by unmeasured confounding (Orsini et al., 2008). As take home message for readers is that due to misclassification in sleep quality and residual confounding, the true effect of subjective kitchen ventilation on sleep quality may be different from OR of 1.75 reported in the article.
*
This paper has been recommended for acceptance by David Carpenter.
Conflict of interest None.
Acknowledgment This work was not supported by any organization.
References Buysse, D.J., Reynolds 3rd, C.F., Monk, T.H., Berman, S.R., Kupfer, D.J., 1989. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 28, 193e213. Fox, M.P., Lash, T.L., Greenland, S., 2005. A method to automate probabilistic sensitivity analyses of misclassified binary variables. Int. J. Epidemiol. 34, 1370e1376. Lyles, R.H., Lin, J., 2010. Sensitivity analysis for misclassification in logistic regression via likelihood methods and predictive value weighting. Stat. Med. 29, 2297e2309. Orsini, N., Bellocco, R., Bottai, M., Wolk, A., Greenland, S., 2008. A Tool for Deterministic and Probabilistic Sensitivity Analysis of Epidemiologic Studies. Wei, F., Nie, G., Zhou, B., Wang, L., Ma, Y., Peng, S., Ou, S., Qin, J., Zhang, L., Li, S., Zou, R., Zeng, X., Zhang, Z., Zou, Y., 2017. Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population. Environ. Pollut. 227, 543e551.
Erfan Ayubi Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Epidemiology & Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Salman Khazaei Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Saeid Safiri* Managerial Epidemiology Research Center, Department of Public Health, School of Nursing and Midwifery, Maragheh University of Medical Sciences, Maragheh, Iran * Corresponding author. E-mail address: saeidsafi[email protected] (S. Safiri).
17 May 2017 Available online xxx
http://dx.doi.org/10.1016/j.envpol.2017.05.049 0269-7491/© 2017 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Ayubi, E., et al.Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population: Methodological issues, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.05.049
Contents lists available at ScienceDirect
Environmental Pollution journal homepage: www.elsevier.com/locate/envpol
Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population: Methodological issues*
To the Editors, We have read with great interest the manuscript entitled “Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population” by Wei et al. published in Environmental Pollution (Wei et al., 2017). The authors aimed to assess the impact of exposure to the cooking oil fumes COFs of Chinese household cooking on sleep quality (Wei et al., 2017). We would like to congratulate the authors on their published results in high quality journal of Environmental Pollution. They provide interesting data on this subject. However, we noticed misclassification bias and unmeasured confounding are main limitations of the study and some methodological and statistical issues should be considered to avoid misinterpretation. The authors mentioned in the limitations of the article that sleep quality was assessed using a self-administrative questionnaire of The Pittsburgh sleep quality index (PSQI) (Buysse et al., 1989), so that, misclassification of sleep quality is unavoidable. In other words, good sleeper individuals may be misclassified as poor sleepers or vice versa. Misclassification of exposures and outcomes are common biases in biomedical researches and it treats the validity of the estimated parameters from regression models (Lyles and Lin, 2010). Efficient methods and tools are available for adjusting misclassification bias (Fox et al., 2005; Lyles and Lin, 2010; Orsini et al., 2008). In these methods the data will be reconstructed and the misclassified exposure or outcome will be correctly classified, given the bias parameters such as sensitivity and specificity. After data reconstruction, OR will be estimated (Fox et al., 2005). We find the crude OR for effect of subjective kitchen ventilation on sleep quality (global score >5) is 1.82. The negligible difference between OR in crude (1.82) and adjusted model (1.76) means there is residual confounding due to unmeasured confounders such as socioeconomic status. However, Orsini and colleagues developed tools to conduct sensitivity analysis to test how the results are influenced by unmeasured confounding (Orsini et al., 2008). As take home message for readers is that due to misclassification in sleep quality and residual confounding, the true effect of subjective kitchen ventilation on sleep quality may be different from OR of 1.75 reported in the article.
*
This paper has been recommended for acceptance by David Carpenter.
Conflict of interest None.
Acknowledgment This work was not supported by any organization.
References Buysse, D.J., Reynolds 3rd, C.F., Monk, T.H., Berman, S.R., Kupfer, D.J., 1989. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 28, 193e213. Fox, M.P., Lash, T.L., Greenland, S., 2005. A method to automate probabilistic sensitivity analyses of misclassified binary variables. Int. J. Epidemiol. 34, 1370e1376. Lyles, R.H., Lin, J., 2010. Sensitivity analysis for misclassification in logistic regression via likelihood methods and predictive value weighting. Stat. Med. 29, 2297e2309. Orsini, N., Bellocco, R., Bottai, M., Wolk, A., Greenland, S., 2008. A Tool for Deterministic and Probabilistic Sensitivity Analysis of Epidemiologic Studies. Wei, F., Nie, G., Zhou, B., Wang, L., Ma, Y., Peng, S., Ou, S., Qin, J., Zhang, L., Li, S., Zou, R., Zeng, X., Zhang, Z., Zou, Y., 2017. Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population. Environ. Pollut. 227, 543e551.
Erfan Ayubi Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Epidemiology & Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Salman Khazaei Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Saeid Safiri* Managerial Epidemiology Research Center, Department of Public Health, School of Nursing and Midwifery, Maragheh University of Medical Sciences, Maragheh, Iran * Corresponding author. E-mail address: saeidsafi[email protected] (S. Safiri).
17 May 2017 Available online xxx
http://dx.doi.org/10.1016/j.envpol.2017.05.049 0269-7491/© 2017 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Ayubi, E., et al.Association between Chinese cooking oil fumes and sleep quality among a middle-aged Chinese population: Methodological issues, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.05.049