[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.29220/CSAM.2021.28.2.119

Study of age specific lung cancer mortality trends in the US using functional data analysis

Tharu, Bhikhari (Department of Mathematics, Spelman College)
Pokhrel, Keshav (Department of Mathematics and Statistics, University of Michigan-Dearborn)
Aryal, Gokarna (Department of Mathematics and Statistics, Purdue University Northwest)
Kafle, Ram C. (Department of Mathematics and Statistics, Sam Houston State University)
Khanal, Netra (Department of Mathematics, University of Tampa)

Publication Information

Communications for Statistical Applications and Methods / v.28, no.2, 2021 , pp. 119-134 More about this Journal

Abstract

Lung cancer is one of the leading causes of cancer deaths in the world. Investigation of mortality rates is pivotal to adequately understand the determinants causing this disease, allocate public health resources, and apply different control measures. Our study aims to analyze and forecast age-specific US lung cancer mortality trends. We report functions of mortality rates for different age groups by incorporating functional principal component analysis to understand the underlying mortality trend with respect to time. The mortality rates of lung cancer have been higher in men than in women. These rates have been decreasing for all age groups since 1990 in men. The same pattern is observed for women since 2000 except for the age group 85 and above. No significant changes in mortality rates in lower age groups have been reported for both gender. Lung cancer mortality rates for males are relatively higher than females. Ten-year predictions of mortality rates depict a continuous decline for both gender with no apparent change for lower age groups (below 40).

Keywords

functional data analysis; lung cancer; mortality rate; principal component analysis; basis function; time series;

Citations & Related Records

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