R M Merrill1. 1. Department of Health Science, College of Health and Human Performance, Brigham Young University, Provo, UT 84602, USA
Abstract
PURPOSE: A life table method is used for correcting hysterectomy rates and probabilities for prevalent cases of hysterectomies in the population. Both corrected and conventional hysterectomy rates and probabilities are reported. METHODS: Hysterectomy prevalence estimates are derived from cross-sectional hysterectomy and mortality using a life table method. Analysis is based on the Utah Hospital Discharge Data Base and State death certificates. RESULTS: Hysterectomy rates are strongly influenced by age, reaching 150 per 10,000 for ages 45-49 years. The corresponding corrected hysterectomy rate is 196. Differences between the corrected and uncorrected cause-specific hysterectomy rates tend to be most pronounced at their peaks, particularly later in life where the prevalence of hysterectomy is greatest. Probability of hysterectomy approaches slightly above 35% over the life span, whereas the corrected hysterectomy probability approaches 43%. Probability of hysterectomy in the next 10 years is 12.9% for women aged 35 years and 11.7% for women aged 45 years. Corresponding corrected hysterectomy probabilities are 14.3 and 15.1. Higher prevalence of hysterectomy in later ages explains the reverse in magnitude of the rates when the correction is applied to the hysterectomy rates. CONCLUSIONS: Conventional hysterectomy rates are underestimated, particularly in older age groups. A prevalence correction of the rates and probabilities is necessary to fully understand the potential health related consequences and impact of this medical procedure in the population.
PURPOSE: A life table method is used for correcting hysterectomy rates and probabilities for prevalent cases of hysterectomies in the population. Both corrected and conventional hysterectomy rates and probabilities are reported. METHODS: Hysterectomy prevalence estimates are derived from cross-sectional hysterectomy and mortality using a life table method. Analysis is based on the Utah Hospital Discharge Data Base and State death certificates. RESULTS: Hysterectomy rates are strongly influenced by age, reaching 150 per 10,000 for ages 45-49 years. The corresponding corrected hysterectomy rate is 196. Differences between the corrected and uncorrected cause-specific hysterectomy rates tend to be most pronounced at their peaks, particularly later in life where the prevalence of hysterectomy is greatest. Probability of hysterectomy approaches slightly above 35% over the life span, whereas the corrected hysterectomy probability approaches 43%. Probability of hysterectomy in the next 10 years is 12.9% for women aged 35 years and 11.7% for women aged 45 years. Corresponding corrected hysterectomy probabilities are 14.3 and 15.1. Higher prevalence of hysterectomy in later ages explains the reverse in magnitude of the rates when the correction is applied to the hysterectomy rates. CONCLUSIONS: Conventional hysterectomy rates are underestimated, particularly in older age groups. A prevalence correction of the rates and probabilities is necessary to fully understand the potential health related consequences and impact of this medical procedure in the population.
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