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Characteristics and health burden of the undiagnosed population at risk of chronic obstructive pulmonary disease in China

Koch, M; Butt, T; Guo, W; Li, X; Chen, Y; Tan, D; Liu, GG; (2019) Characteristics and health burden of the undiagnosed population at risk of chronic obstructive pulmonary disease in China. BMC Public Health , 19 (1) , Article 1727. 10.1186/s12889-019-8071-8. Green open access

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Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality in China. However, identifying patients has proved challenging, resulting in widespread under-diagnosis of the condition. We examined the prevalence of COPD diagnosis and COPD risk among adults in urban mainland China, the factors associated with having a COPD diagnosis or COPD risk, and the healthcare resource use and health outcomes of these groups compared with controls. METHODS: Respondents to the 2017 National Health and Wellness Survey in China (n = 19,994) were classified into three groups: 'COPD Diagnosed', 'COPD Risk (undiagnosed)', and Control (unaffected), based on their self-reported diagnosis and Lung Function Questionnaire (LFQ) score. The groups were characterised by sociodemographic, health-related quality of life (HRQoL), productivity impairment, and healthcare resource use. Pairwise comparisons (t tests and chi-squared tests) and multivariable regression analyses were used to investigate factors associated with being at risk of, or diagnosed with, COPD. RESULTS: 3320 (16.6%) respondents had a suspected risk of COPD but did not report receiving a diagnosis. This was projected to 105.3 million people, or 16.9% of adult urban Chinese. Of these respondents with an identified risk, only 554 (16.7%) were aware of COPD by name. Relative to those without COPD, those with a risk of COPD (undiagnosed) had significantly greater healthcare resource use, lower productivity and lower HRQoL not only compared to those without COPD, but also compared to people with a COPD diagnosis. Factors associated with increased odds of being at risk of COPD were older age, smoking, alcohol consumption, overweight BMI, occasional exercise, higher comorbidities, asthma diagnosis, being female, lower education, not being employed, and living in a high pollution province (p < 0.05). CONCLUSIONS: There is a substantial group of individuals, undiagnosed, but living with a risk of COPD, who have impaired HRQoL, lower productivity and elevated healthcare resource use patterns. Case-detection tools such as the LFQ may prove a quick and cost-effective approach for identifying these at-risk individuals for further definitive testing and appropriate treatment in China.

Type: Article
Title: Characteristics and health burden of the undiagnosed population at risk of chronic obstructive pulmonary disease in China
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/s12889-019-8071-8
Publisher version: http://doi.org/10.1186/s12889-019-8071-8
Language: English
Additional information: Copyright © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords: Case detection, China, Chronic obstructive pulmonary disease, Health-related quality of life, Lung function questionnaire, National health and wellness survey, Productivity, Resource use, Screening
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
URI: https://discovery.ucl.ac.uk/id/eprint/10088554
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