Time trends of non-Hodgkin's lymphoma: are they real? What do they mean?
Factors that need to be considered in the analysis of time trends in disease incidence are age, year of diagnosis, and birth cohort. When these are included in a log-linear model, a nonidentifiability problem arises from the linear dependence among these three time factors so that only specified functions of the parameters can be unambiguously determined. One of these invariant functions is the drift or the sum of the period and cohort trend. Non-Hodgkin's lymphoma incidence rates from Connecticut for the period 1935-1989 were analyzed for males and females. In addition to an age effect, both period and cohort significantly improved the fit of the model. The estimated drift shows that there has been a 10.3% increase in risk every 5 years since 1965 for females and 9.2% for males. It is unlikely that a trend of this magnitude can be attributed entirely to data artifact.
Holford
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Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Connecticut 06510.
Zheng
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Mayne
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McKay
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D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003237:Connecticut / Q000453:epidemiology; D005260:Female; D006801:Humans; D015994:Incidence; D008228:Lymphoma, Non-Hodgkin / Q000175:diagnosis / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D013997:Time Factors