Author Identifier

wei wang

https://orcid.org/0000-0002-1430-1360

Document Type

Journal Article

Publisher

Nature Publishing Group

School

School of Medical and Health Sciences

RAS ID

25631

Funders

National Natural Science Foundation of China (NSFC) (81673247, 81473057, 81370083)

Joint Project of the Australian National Health & Medical Research Council (NHMRC) and the NSFC (NHMRC APP1112767, NSFC 81561128020)

Beijing Nova Program (Z141107001814058)

Grant Number

NHMRC Number : 1112767

Comments

Wang, Y., Liu, X., Qiu, J., Wang, H., Liu, D., Zhao, Z., ... & Wang, W. (2017). Association between ideal cardiovascular health metrics and suboptimal health status in Chinese population. Scientific Reports, 7(1), Article 14975.

https://doi.org/10.1038/s41598-017-15101-5

Abstract

Suboptimal health status (SHS) is a physical state between health and illness, and previous studies suggested that SHS is associated with majority components of cardiovascular health metrics defined by American Heart Association (AHA). We investigated the association between SHS and cardiovascular health metrics in a cross-sectional analysis of China suboptimal health cohort study (COACS) consisting of 4313 participants (60.30 % women) aged from 18 to 65 years old. The respective prevalence of SHS is 7.10 %, 9.18 %, 10.04 % and 10.62 % in the first, second, third and fourth quartiles of ideal cardiovascular health (CVH) metrics (P for trend = 0.012). Participants in the largest quartile of ideal CVH metrics show a lower likelihood of having optimal SHS score compared to those in the smallest quartile (odds ratio (OR), 0.43; 95% confidence interval (CI), 0.32 – 0.59), after adjusting for age, gender, marital status, alcohol consumption, income level and education. Four metrics (smoking, physical inactivity, poor dietary intake and ideal control of blood pressure are significantly correlated with the risk of SHS. The present study suggests that ideal CVH metrics are associated with a lower prevalence of SHS, and the combined evaluation of SHS and CVH metrics allows the risk classification of cardiovascular disease, and thus consequently contributes to the prevention of cardiovascular diseases.

DOI

10.1038/s41598-017-15101-5

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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