OBJECTIVES: To investigate the impact of measuring a single home then imputing information from another home among subjects who lived in two homes in a subset of the National Cancer Institute/Children's Cancer Group (NCI/CCG) investigation of residential exposure to magnetic fields and risk of childhood leukaemia. METHODS: Each subject's summary time weighted average (TWA) exposure was derived from measurements of two homes, weighted by the fraction of the reference period lived in the residence. The three cost efficient field work strategies examined were measuring: (a) the longer lived in home; (b) the currently lived in home; and (c) the former lived in home. Two different methods were used for imputing the missing values: (a) control mean imputation, (b) status specific mean imputation. The subject's summary exposure to magnetic fields estimated with each approach was compared with the subject's TWA calculated from measurements in both homes. The association between estimated exposure to magnetic fields and the risk of leukaemia under different approaches was examined with unconditional logistic regression analysis. RESULTS: The Pearson correlation coefficient between the two measurements within subjects was 0.31 (p < 10(-4), indicating a lack of independence of measurements. Differences were found between mean exposures in current and former homes of cases, and between longer and shorter lived in homes of controls. All methods with measurements from one of the homes in conjunction with imputation of measurements for the second home led to marked attenuation of risk estimates at the highest exposure category, particularly when measurements from current homes were used and those from former homes were imputed. CONCLUSION: Results argue against attempting to estimate lifetime magnetic field exposure from imputed values derived from current residences to fill in gaps caused by unmeasured residences previously lived in.
OBJECTIVES: To investigate the impact of measuring a single home then imputing information from another home among subjects who lived in two homes in a subset of the National Cancer Institute/Children's Cancer Group (NCI/CCG) investigation of residential exposure to magnetic fields and risk of childhood leukaemia. METHODS: Each subject's summary time weighted average (TWA) exposure was derived from measurements of two homes, weighted by the fraction of the reference period lived in the residence. The three cost efficient field work strategies examined were measuring: (a) the longer lived in home; (b) the currently lived in home; and (c) the former lived in home. Two different methods were used for imputing the missing values: (a) control mean imputation, (b) status specific mean imputation. The subject's summary exposure to magnetic fields estimated with each approach was compared with the subject's TWA calculated from measurements in both homes. The association between estimated exposure to magnetic fields and the risk of leukaemia under different approaches was examined with unconditional logistic regression analysis. RESULTS: The Pearson correlation coefficient between the two measurements within subjects was 0.31 (p < 10(-4), indicating a lack of independence of measurements. Differences were found between mean exposures in current and former homes of cases, and between longer and shorter lived in homes of controls. All methods with measurements from one of the homes in conjunction with imputation of measurements for the second home led to marked attenuation of risk estimates at the highest exposure category, particularly when measurements from current homes were used and those from former homes were imputed. CONCLUSION: Results argue against attempting to estimate lifetime magnetic field exposure from imputed values derived from current residences to fill in gaps caused by unmeasured residences previously lived in.
Authors: M S Linet; E E Hatch; R A Kleinerman; L L Robison; W T Kaune; D R Friedman; R K Severson; C M Haines; C T Hartsock; S Niwa; S Wacholder; R E Tarone Journal: N Engl J Med Date: 1997-07-03 Impact factor: 91.245
Authors: R A Kleinerman; M S Linet; E E Hatch; S Wacholder; R E Tarone; R K Severson; W T Kaune; D R Friedman; C M Haines; C R Muirhead; J D Boice; L L Robison Journal: Epidemiology Date: 1997-09 Impact factor: 4.822
Authors: Carlotta Malagoli; Sara Fabbi; Sergio Teggi; Mariagiulia Calzari; Maurizio Poli; Elena Ballotti; Barbara Notari; Maurizio Bruni; Giovanni Palazzi; Paolo Paolucci; Marco Vinceti Journal: Environ Health Date: 2010-03-30 Impact factor: 5.984