Archived Comments for:
Blood lead is significantly associated with metabolic syndrome in Korean adults: an analysis based on the Korea National Health and Nutrition Examination Survey (KNHANES), 2008
Appropriate survey design analysis and exclusion criteria are required to confirm the association between blood lead concentration and metabolic syndrome in Korean adults
Yangho Kim, Ulsan University Hospital
27 June 2013
Authors:
Byung-Kook Lee1, YanghoKim2*
1Korean Industrial Health Association, Hyesan Bldg., #1490-32 Seocho-3-Dong, Seocho-Gu, Seoul, 153-801 South Korea
bklee@kiha21.or.kr
2*Correspondence: Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, #290-3 Cheonha-Dong, Dong-Gu, Ulsan 682-060,South Korea
yanghokm@nuri.net
Main texts
To the Editor:
We read with interest this article, which concluded that a higher prevalence of metabolic syndrome (MS) is associated with higher blood lead levels in the Korean population. We have two concerns on the article. First, the authors used the Modified National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria for subjects with a diagnosis of MS. However, they excluded people who took medications for hypertension, DM, or dyslipidemia (n = 307) although ATP III criteria included people who took medications for hypertension, DM, or dyslipidemia. The number of 307 which is not a small number out of total number of 1791, may have affected an association between lead and MS. Second, the authors analyzed data from the 2008 Korean National Health and Nutrition Survey (KNHANES), which was a nationally representative cross-sectional survey of the civilian, non-instutionalized Korean population. KNHANES used a sampling design that involved a complex stratified, multistage, probability cluster survey method, and special statistical methods such as sample weighting, are thus required to properly analyze the survey data (Kim et al., 2013). However, it is not clear whether the authors analyzed the data with consideration of sample weighting. Analyses of these data using traditional statistical software (such as SPSS) that use ordinary and generalized least squares estimation techniques tendto result in an underestimated standard error, inappropriate confidence intervals, and misleading tests of significance (Brogan, 2005). When we reanalyzed the study subjects including people who took medications for hypertension, DM, or dyslipidemia using a sample-weighted data analysis with the SUDAAN program, the results differed from those of this article. Aproper statistical analysisof the appropriate study subjects with consideration of sample weighting did not provide a consistent positive association between blood lead levels and MS in regression and logistic regression analyses after adjusting for covariates. Thus, further studies with appropriate survey design analysis and exclusion criteria are needed to confirm the association.
References
Brogan D. Software for sample survey data, misuse of standard packages. In: Armitage P, Colton T, editors. Encyclopedia of biostatistics. 2nd ed. Estados Unidos: John Wiley and Sons; 2005, p. 5057-5064.
Kim Y, Park S, Kim NS, Lee BK.Inappropriate survey design analysis of the Korean National Health and Nutrition Examination Survey may produce biased results.JPrev Med Public Health 2013, 46(2):96-104.
Korea Centers for Disease Control and Prevention. Guideline for the Evaluation of the Fourth Korea National Health and Nutrition Survey. Korea Centers for Disease Control and Prevention, Ministry of Health and Welfare, Korea. 2009.
Competing Interests
The authors declare that they have no competing interests.
Competing interests
The authors declare that they have no competing interests.
Cardiovascular Diabetology
Appropriate survey design analysis and exclusion criteria are required to confirm the association between blood lead concentration and metabolic syndrome in Korean adults
27 June 2013
Authors:
Byung-Kook Lee1, YanghoKim2*
1Korean Industrial Health Association, Hyesan Bldg., #1490-32 Seocho-3-Dong, Seocho-Gu, Seoul, 153-801 South Korea
bklee@kiha21.or.kr
2*Correspondence: Department of Occupational and Environmental Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, #290-3 Cheonha-Dong, Dong-Gu, Ulsan 682-060,South Korea
yanghokm@nuri.net
Main texts
To the Editor:
We read with interest this article, which concluded that a higher prevalence of metabolic syndrome (MS) is associated with higher blood lead levels in the Korean population. We have two concerns on the article. First, the authors used the Modified National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria for subjects with a diagnosis of MS. However, they excluded people who took medications for hypertension, DM, or dyslipidemia (n = 307) although ATP III criteria included people who took medications for hypertension, DM, or dyslipidemia. The number of 307 which is not a small number out of total number of 1791, may have affected an association between lead and MS. Second, the authors analyzed data from the 2008 Korean National Health and Nutrition Survey (KNHANES), which was a nationally representative cross-sectional survey of the civilian, non-instutionalized Korean population. KNHANES used a sampling design that involved a complex stratified, multistage, probability cluster survey method, and special statistical methods such as sample weighting, are thus required to properly analyze the survey data (Kim et al., 2013). However, it is not clear whether the authors analyzed the data with consideration of sample weighting. Analyses of these data using traditional statistical software (such as SPSS) that use ordinary and generalized least squares estimation techniques tendto result in an underestimated standard error, inappropriate confidence intervals, and misleading tests of significance (Brogan, 2005). When we reanalyzed the study subjects including people who took medications for hypertension, DM, or dyslipidemia using a sample-weighted data analysis with the SUDAAN program, the results differed from those of this article. Aproper statistical analysisof the appropriate study subjects with consideration of sample weighting did not provide a consistent positive association between blood lead levels and MS in regression and logistic regression analyses after adjusting for covariates. Thus, further studies with appropriate survey design analysis and exclusion criteria are needed to confirm the association.
References
Brogan D. Software for sample survey data, misuse of standard packages. In: Armitage P, Colton T, editors. Encyclopedia of biostatistics. 2nd ed. Estados Unidos: John Wiley and Sons; 2005, p. 5057-5064.
Kim Y, Park S, Kim NS, Lee BK.Inappropriate survey design analysis of the Korean National Health and Nutrition Examination Survey may produce biased results.JPrev Med Public Health 2013, 46(2):96-104.
Korea Centers for Disease Control and Prevention. Guideline for the Evaluation of the Fourth Korea National Health and Nutrition Survey. Korea Centers for Disease Control and Prevention, Ministry of Health and Welfare, Korea. 2009.
Competing Interests
The authors declare that they have no competing interests.
Competing interests
The authors declare that they have no competing interests.