diabetes research and clinical practice 108 (2015) e7
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Letter to the Editor Air pollution and diabetes mellitus
Keywords: Air pollution Diabetes mellitus Meta-analysis
model is usually used when the treatment protocol of each study is the same [5]. Their meta-analysis showed no heterogeneity based on reported I2 statistics. Finally, there is a procedure of compiling cohort studies and cross-sectional studies for the meta-analysis with presenting overall risk ratio. But the procedure of dividing cohort studies and cross-sectional studies for meta-analysis is still common. The causality of the association by Balti et al. would be validated by gathering more cohort studies for metaanalysis.
references Balti et al. [1] reported a positive relationship between air pollution and diabetes mellitus occurrence by meta-analysis of five prospective and five cross-sectional studies with randomeffects models. Similar studies were also reported with special emphasis on the causality of the association with cohort studies [2,3], I have some queries on the study by Balti et al. First, the authors described that the overall effect of gaseous air pollutants (NO2 and NOx) and particulate matter pollutants (PM2.5 and PM10) for diabetes occurrence in prospective investigations were significant with hazard ratios (95% confidence intervals) of 1.13 (1.01–1.22, p < 0.001) and 1.11 (1.03–1.20, p < 0.001), respectively. In addition, odds ratios by two cross-sectional studies showed significant association between indicators of air pollution and diabetes, and the authors concluded that there was a prospective association of main air pollutants with an increased risk for type 2 diabetes. In contrast, Park and Wang [4] recently conducted the same meta-analysis with six prospective studies on the effect of air pollution on incident diabetes mellitus, concluding that the causality was not sufficient by summing up the past studies. Park and Wang pointed out that data from women were predominant in the cohort studies and there is an ethnic bias in subjects from North America or Europe. Regarding statistical significance, each meta-analysis showed a different number of samples. Balti et al. selected one study having a weight of 36.7% for PM2.5 and 41.0% for NO2, and metaanalysis with more studies is recommended to avoid the effect of a specific study on pooled risk estimates. As a second concern, it is not clear why Balti et al. used a random-effect model for their meta-analysis. A fixed-effect
[1] Balti EV, Echouffo-Tcheugui JB, Yako YY, Kengne AP. Air pollution and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract 2014;106:161–72. [2] Wang B, Xu D, Jing Z, Liu D, Yan S, Wang Y. Mechanisms in endocrinology: effect of long-term exposure to air pollution on type 2 diabetes mellitus risk: a systemic review and meta-analysis of cohort studies. Eur J Endocrinol 2014;171:R173–82. [3] Puett RC, Hart JE, Schwartz J, Hu FB, Liese AD, Laden F. Are particulate matter exposures associated with risk of type 2 diabetes. Environ Health Perspect 2011;119:384–9. [4] Park SK, Wang W. Ambient air pollution and type 2 diabetes: a systematic review of epidemiologic research. Curr Environ Health Rep 2014;1:275–86. [5] Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods 2010;1:97–111.
Tomoyuki Kawada* Nippon Medical School, Hygiene and Public Health, 1-1-5, Sendagi, Bunkyo-ku, Tokyo 1138602, Japan * Tel.: +81 338222131; fax: +81 356853065 E-mail address: [email protected] (T. Kawada)
28 October 2014 Available online 20 January 2015 http://dx.doi.org/10.1016/j.diabres.2015.01.002 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
Contents available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Letter to the Editor Air pollution and diabetes mellitus
Keywords: Air pollution Diabetes mellitus Meta-analysis
model is usually used when the treatment protocol of each study is the same [5]. Their meta-analysis showed no heterogeneity based on reported I2 statistics. Finally, there is a procedure of compiling cohort studies and cross-sectional studies for the meta-analysis with presenting overall risk ratio. But the procedure of dividing cohort studies and cross-sectional studies for meta-analysis is still common. The causality of the association by Balti et al. would be validated by gathering more cohort studies for metaanalysis.
references Balti et al. [1] reported a positive relationship between air pollution and diabetes mellitus occurrence by meta-analysis of five prospective and five cross-sectional studies with randomeffects models. Similar studies were also reported with special emphasis on the causality of the association with cohort studies [2,3], I have some queries on the study by Balti et al. First, the authors described that the overall effect of gaseous air pollutants (NO2 and NOx) and particulate matter pollutants (PM2.5 and PM10) for diabetes occurrence in prospective investigations were significant with hazard ratios (95% confidence intervals) of 1.13 (1.01–1.22, p < 0.001) and 1.11 (1.03–1.20, p < 0.001), respectively. In addition, odds ratios by two cross-sectional studies showed significant association between indicators of air pollution and diabetes, and the authors concluded that there was a prospective association of main air pollutants with an increased risk for type 2 diabetes. In contrast, Park and Wang [4] recently conducted the same meta-analysis with six prospective studies on the effect of air pollution on incident diabetes mellitus, concluding that the causality was not sufficient by summing up the past studies. Park and Wang pointed out that data from women were predominant in the cohort studies and there is an ethnic bias in subjects from North America or Europe. Regarding statistical significance, each meta-analysis showed a different number of samples. Balti et al. selected one study having a weight of 36.7% for PM2.5 and 41.0% for NO2, and metaanalysis with more studies is recommended to avoid the effect of a specific study on pooled risk estimates. As a second concern, it is not clear why Balti et al. used a random-effect model for their meta-analysis. A fixed-effect
[1] Balti EV, Echouffo-Tcheugui JB, Yako YY, Kengne AP. Air pollution and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract 2014;106:161–72. [2] Wang B, Xu D, Jing Z, Liu D, Yan S, Wang Y. Mechanisms in endocrinology: effect of long-term exposure to air pollution on type 2 diabetes mellitus risk: a systemic review and meta-analysis of cohort studies. Eur J Endocrinol 2014;171:R173–82. [3] Puett RC, Hart JE, Schwartz J, Hu FB, Liese AD, Laden F. Are particulate matter exposures associated with risk of type 2 diabetes. Environ Health Perspect 2011;119:384–9. [4] Park SK, Wang W. Ambient air pollution and type 2 diabetes: a systematic review of epidemiologic research. Curr Environ Health Rep 2014;1:275–86. [5] Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods 2010;1:97–111.
Tomoyuki Kawada* Nippon Medical School, Hygiene and Public Health, 1-1-5, Sendagi, Bunkyo-ku, Tokyo 1138602, Japan * Tel.: +81 338222131; fax: +81 356853065 E-mail address: [email protected] (T. Kawada)
28 October 2014 Available online 20 January 2015 http://dx.doi.org/10.1016/j.diabres.2015.01.002 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.
