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Preprocessing histograms of age at menopause using the fast Fourier transform
1Biostatistics, Epidemiology and Scientific Computing Department, King Faisal Specialist Hospital and Research Centre, P.O. Box 3354, Riyadh 11211, Saudi Arabia. greer@kfshrc.edu.sa
Maturitas
|April 17, 2003
Summary
This study introduces a Fast Fourier Transform (FFT) method to remove noise from age at menopause (AAM) data. The processed AAM distribution reveals three underlying peaks, challenging single-distribution assumptions in epidemiological studies.
Area of Science:
- Epidemiology
- Biostatistics
- Signal Processing
Background:
- Age at menopause (AAM) histogram interpretation is hindered by noise, notably last-digit-preference (LDP).
- Effective noise reduction is crucial for accurate analysis of AAM distribution properties.
Purpose of the Study:
- To develop a standardized preprocessing method for AAM histograms.
- To eliminate noise, particularly LDP, for a clearer understanding of AAM distribution.
Main Methods:
- Utilized Fast Fourier Transform (FFT) for noise elimination based on frequency characteristics.
- Applied a low-pass filter (0.15 cycles per year) to simulated and published AAM data.
Main Results:
- FFT preprocessing effectively removed LDP and other high-frequency noise.
- A true AAM signal emerged, characterized by three low-frequency components.
- Identified two major peaks (approx. 51 and 43 years) and a smaller peak (approx. 35 years).
Conclusions:
- FFT is effective for preprocessing AAM histograms, revealing a consistent underlying three-peak distribution.
- The identified peaks lack definitive interpretation but question single-distribution models in AAM research.
- Highlights the need for advanced statistical approaches in analyzing AAM risk factors.