Blood lead levels and mortality. 2002

Mark Lustberg, and Ellen Silbergeld
Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, 660 W Redwood St, Baltimore, MD 21201, USA. mlustber@umaryland.edu

BACKGROUND Despite declines in blood lead levels during the past 20 years, lead exposure continues to be a public health concern. Studies have linked lead exposure with increased risk for diverse health outcomes. Few studies have evaluated the association of lead exposure and mortality in the general population. METHODS To evaluate the association of lead exposure and mortality in the United States, we used the recently released mortality follow-up data for participants of the Second National Health and Nutrition Examination Survey, a national cross-sectional survey of the general population conducted from 1976 to 1980. Survey participants aged 30 to 74 years with blood lead measurements were followed up through December 31, 1992 (n = 4292). RESULTS After adjustment for potential confounders, individuals with baseline blood lead levels of 20 to 29 microg/dL (1.0-1.4 micromol/L) had 46% increased all-cause mortality (rate ratio [RR], 1.46; 95% confidence interval [CI], 1.14-1.86), 39% increased circulatory mortality (RR, 1.39; 95% CI, 1.01-1.91), and 68% increased cancer mortality (RR, 1.68; 95% CI, 1.02-2.78) compared with those with blood lead levels of less than 10 microg/dL (<0.5 micromol/L). All-cause mortality for those with blood lead levels of 10 to 19 microg/dL (0.5-0.9 micromol/L) was intermediately increased and not statistically significant (RR, 1.17; 95% CI, 0.90-1.52). CONCLUSIONS Individuals with blood lead levels of 20 to 29 micro g/dL in 1976 to 1980 (15% of the US population at that time) experienced significantly increased all-cause, circulatory, and cardiovascular mortality from 1976 through 1992. Thus, we strongly encourage efforts to reduce lead exposure for occupationally exposed workers and the 1.7 million Americans with blood lead levels of at least 20 micro g/dL (> or = 1.0 micromol/L).

UI MeSH Term Description Entries
D007854 Lead A soft, grayish metal with poisonous salts; atomic number 82, atomic weight 207.2, symbol Pb.
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009026 Mortality All deaths reported in a given population. CFR Case Fatality Rate,Crude Death Rate,Crude Mortality Rate,Death Rate,Age Specific Death Rate,Age-Specific Death Rate,Case Fatality Rate,Decline, Mortality,Determinants, Mortality,Differential Mortality,Excess Mortality,Mortality Decline,Mortality Determinants,Mortality Rate,Mortality, Differential,Mortality, Excess,Age-Specific Death Rates,Case Fatality Rates,Crude Death Rates,Crude Mortality Rates,Death Rate, Age-Specific,Death Rate, Crude,Death Rates,Determinant, Mortality,Differential Mortalities,Excess Mortalities,Mortalities,Mortality Declines,Mortality Determinant,Mortality Rate, Crude,Mortality Rates,Rate, Age-Specific Death,Rate, Case Fatality,Rate, Crude Death,Rate, Crude Mortality,Rate, Death,Rate, Mortality,Rates, Case Fatality
D009369 Neoplasms New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms. Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002423 Cause of Death Factors which produce cessation of all vital bodily functions. They can be analyzed from an epidemiologic viewpoint. Causes of Death,Death Cause,Death Causes
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005260 Female Females
D005500 Follow-Up Studies Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease. Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup

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