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Multidimensional Assessment of Health Status in a Dependent Sample: An Exploratory Analysis for Adult Twins in China

Published online by Cambridge University Press:  21 February 2012

Yan Ning ,
Danan Gu ,
Yonghua Hu ,
Wenyan Ji ,
Zengchang Pang  and
Shaojie Wang
Yan Ning
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Danan Gu
Affiliation:
Center for the Study of Aging and Human Development, Duke University, Durham, NC 27705, USA.
Yonghua Hu*
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China. [email protected]
Wenyan Ji
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Zengchang Pang
Affiliation:
Qingdao Center for Disease Control and Prevention, Qingdao 266033, China.
Shaojie Wang
Affiliation:
Qingdao Center for Disease Control and Prevention, Qingdao 266033, China.
*
*Address for correspondence: Professor Yonghua Hu, Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xue Yuan Road, Hai Dian District, Beijing 100191, China.

Abstract

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Health is a multidimensional and continual concept. Traditional latent analytic approaches have inherent deficits in capturing the complex nature of the concept; however, the Grade of Membership (GoM) model is well suited for this problem. We applied the GoM method to a set of 31 indicators to construct ideal profiles of health status based on physical, mental and social support items among 848 adult twins from Qingdao, China. Four profiles were identified: healthy individuals (pure type I), individuals with personality disorders (pure type II), individuals with mental impairments (pure type III) and individuals with physical impairments (pure type IV). The most frequently occurring combination in this population was profiles I, II, IV (14.74%), followed by profiles I, II, III, IV (13.44%), and then type I (11.08%). Only 13.56% of subjects fell completely into one single pure type, most individuals exhibited some of the characteristics of two or more pure types. Our results indicated that, compared to conventional statistical methods, the GoM model was more suited to capture the complex concept of health, reflecting its multidimensionality and continuity, while also exhibiting preferable reliability. This study also made an important contribution to research on GoM application in non-independent samples.

Keywords

twin studyhealth statusmultidimensional assessmentGrade of Membership
Type
Articles
Information
Twin Research and Human Genetics , Volume 13 , Issue 5 , 01 October 2010 , pp. 465 - 474
Copyright
Copyright © Cambridge University Press 2010