Physiological Dysregulation Proceeds and Predicts Health Outcomes Similarly in Chinese and Western Populations

Author:

Li Qing12,Legault Véronique3,Hermann Honfo Sewanou3,Milot Emmanuel4,Jia Qingzhou2,Wang Fuqing2,Ferrucci Luigi5ORCID,Bandinelli Stefania6,Cohen Alan A378ORCID

Affiliation:

1. Center for Innovation Management Research of Xinjiang , Urumqi 830046 , China

2. School of Economics and Management, Xinjiang University , Urumqi 830046 , China

3. PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke , Sherbrooke, Quebec J1H 5N4 , Canada

4. Department of Chemistry, Biochemistry, and Physics, Université du Québec à Trois-Rivières , Trois-Rivières, Quebec G9A 5H7 , Canada

5. Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital , Baltimore, Maryland 21225 , USA

6. Azienda USL Toscana Centro, Geriatric Unit , 50137 Firenze , Italy

7. Research Center on Aging , Sherbrooke, Quebec J1H 4C4 , Canada

8. Research Center of Centre Hospitalier Universitaire de Sherbrooke , Sherbrooke, Quebec J1H 5N4 , Canada

Abstract

Abstract Background A decade ago, we proposed an index of physiological dysregulation based on Mahalanobis distance (DM) that measures how far from the norm an individual biomarker profile is. While extensive validation has been performed, focus was mostly on Western populations with little comparison to developing countries, particularly at a physiological system level. The degree to which the approach would work in other sociocultural contexts and the similarity of dysregulation signatures across diverse populations are still open questions. Methods Using 2 data sets from China and 3 from Western countries (United States, United Kingdom, and Italy), we calculated DM globally and per physiological system. We assessed pairwise correlations among systems, difference with age, prediction of mortality and age-related diseases, and sensitivity to interchanging data sets with one another as the reference in DM calculation. Results Overall, results were comparable across all data sets. Different physiological systems showed distinct dysregulation processes. Association with age was moderate and often nonlinear, similarly for all populations. Mahalanobis distance predicted most health outcomes, although differently by physiological system. Using a Chinese population as the reference when calculating DM for Western populations, or vice versa, led to similar associations with health outcomes, with a few exceptions. Conclusions While small differences were noticeable, they did not systematically emerge between Chinese and Western populations, but rather diffusively across all data sets. These findings suggest that DM presents similar properties, notwithstanding sociocultural backgrounds, and that it is equally effective in capturing the loss of homeostasis that occurs during aging in diverse industrial human populations.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Geriatrics and Gerontology,Aging

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