Introduction

Chronic obstructive pulmonary disease (COPD) is a substantial public health concern worldwide1 and is an irreversible progressive disease characterized by persistent airflow limitation2. COPD has been identified as the fourth leading cause of death worldwide and is projected to be the third leading cause of death in middle-income countries by 20303. COPD is also defined as a disease with one of the largest health economic burdens in many countries, including China4. The Chinese government spent more than $73 billion caring for and treating patients with several chronic diseases, including COPD5. Moreover, the prevalence of COPD among Chinese individuals aged 40 years or older increased from 7.6% in 2009 to 13.7% in 20186,7. The mortality rate was 79.4 per 100,000 population in 2013, which was higher than the global mortality rate (50.7 per 100,000 people) in the same year8. In the context of an aging society, including economic development based on industry, many people will suffer from COPD in China9.

The main problem for COPD patients is quality of life (QOL)10. Several factors contribute to the level of QOL among COPD patients, including its pathogenesis according to patients’ traits, socioeconomic status, and family support. Most COPD patients often suffer from poor QOL beyond suffering from its pathogenesis, such as symptoms and limited medical access9,11,12,13. A large proportion of COPD research conducted in China focuses on treatment and care, while a few publications emphasize the improvement in QOL in these populations by using the St. George's Respiratory Questionnaire (SGRQ)14,15. However, the QOL of COPD patients should be one of the most important issues for public health, particularly during the pandemic of COVID-19 due to both diseases’ impact on human lungs16. The suffering of COPD patients in China increased because of the incomplete function of healthcare services in China, ultimately leading to poor QOL.

COPD prevalence varies across different areas in China. The prevalence of COPD in Zhejiang Province, which is one of the largest, high-density, and industrial areas, ranges between 12.8 and 14.5% among people aged 40 or older17,18. COPD was reported as the main public health problem in Zhejiang Province, and its healthcare services system was the most highly impacted in China6,7,18,19. Zhejiang Province is the third largest industrial province in China with high levels of industrial emissions19. A large proportion of people aged 40 years and over smoke, and the environment has very poor air quality20,21, including exposure to outdoor air pollution from industrial factories and agricultural burning by residents; COPD patients face a problem regarding QOL22,23. Nevertheless, there is no scientific information about QOL among COPD patients living in areas with poor air pollution, such as Zhejiang Province, China. Therefore, this study aimed to assess QOL and determine the factors associated with good QOL among COPD patients in Zhejiang Province, China.

Methods

Study design and setting

An analytical cross-sectional study was used to assess the level of QOL among COPD patients and determine the factors associated with good QOL among COPD patients in the respiratory departments of six tertiary hospitals in Zhejiang Province, Southeast China.

Study population and study sample

The study population was COPD patients who attended one of six hospitals in Zhejiang Province, China. The inclusion criteria were those aged 40 years and over and who were diagnosed with COPD by a physician. However, those who had been diagnosed with lung cancer, bronchiectasis, pneumoconiosis, or other restrictive lung ventilation dysfunction were excluded from this study.

The sample size was calculated by the standard formula for a cross-sectional study24, n = [Z2α/2 PQ]/e2, where \(Z\) = the value of the standard normal distribution corresponding to the desired confidence level (\(Z=\) 1.96 for 95% CI); P is the prevalence of good QOL among COPD patients in China at 14.1%, which was 0.1425; Q is the difference of one and P (1-P); and e is the desired precision (0.05 or 5%). Allowing for 15% error throughout the study process, at least 213 individuals were required for the analysis.

After the sample size was calculated, six tertiary hospitals were randomly selected from among 108 hospitals by a computer-generated randomization method, as shown in the following flowchart (Fig. 1). To ensure that each sample site had an equal probability of providing a sample, simple random sampling with a proportional allocation of 0.25% was used to select the sample at each study site. Those who were selected were screened according to the inclusion and exclusion criteria before the initiation of data collection.

Figure 1
figure 1

Flow of the study samples selection from six selected hospitals.

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Research instruments

A validated questionnaire and the standardized SGRQ26 were used for data collection. The validated questionnaire was developed according to the relevant literature and guidelines and discussed with experts in the field. The questionnaire consisted of three parts: general information about the participants, environmental factors, and the stage and treatment of COPD. In part one, twelve questions were used to collect general information about the participants, such as age, sex, marital status, educational level, occupational status, and household income. In part two, five questions were used to collect information on environmental factors such as residence, distance to the hospital, and hospital transport method. In the last part, five questions were used to collect information on the COPD stage and treatment of the participants.

The standardized SGRQ26 was used to assess QOL among the participants. The SGRQ contains 50 items for assessing QOL in 3 domains: symptoms, activity, and impact. Each questionnaire response has a unique empirically derived ‘weight’26. SGRQ scores range from “0” to “100”, and “0” represents the best QOL. Finally, the participants were divided into three levels of QOL according to their scores: poor (scores of 66.68–100.00), moderate (scores of 33.34–66.67), and good (scores of 0.00–33.33)27. The Mandarin Chinese version of the SGRQ was provided by St. George’s, University of London, and had been tested as a valid and responsive tool for assessing the QOL of Chinese COPD patients in China28.

Research instrument development

All questions were examined for validity and reliability by the item-objective congruence (IOC) method29 and verified by three external experts in the field: a medical doctor, an epidemiological expert, and a nurse. Each expert evaluated each item, and the scores ranged from − 1 to + 1 (if a question complied with the study scope and objective, it was scored + 1, suspicious = 0, and inconsistent = − 1). For the evaluation results, questions that scored an average score ≥ 0.70 were included in the questionnaire. The questions with average scores between 0.51 and 0.70 were modified before being included in the questionnaire. Questions with an average score below 0.5 were excluded from the questionnaire.

Before data collection, a pilot test was conducted at two selected tertiary hospitals in Zhejiang Province with 30 samples (15 samples from each) who had similar characteristics to the study sample. Only the questions with Cronbach’s alpha value ≥ 0.75 were included in the questionnaire. Finally, all the questions were reviewed by the research team before the data collection began.

Measures

Body mass index (BMI) was classified into three categories: less than 18.50 (underweight), 18.5–23.9 (normal weight), and ≤ 24.0 (overweight)30. The airflow limitation severity in COPD was classified into four levels: mild (forced expiratory volume in one second (FEV1) ≥ 80% of predicted), moderate (50% predicted ≤ FEV1 < 80% predicted), severe (30% predicted ≤ FEV1 < 50% predicted) and very severe (FEV1 < 30% predicted)2. The QOL among COPD patients was classified by the standardized SGRQ into three levels: poor, moderate, and good.

Data collection procedure

Six tertiary hospitals from among 108 hospitals with respiratory departments listed by the Ministry of Health and Population were randomly selected by a computer-generated randomization method and divided into two categories: tertiary class A hospitals and tertiary class B hospitals. Permission to assess the hospital was granted by the department director after sending official letters. The respiratory department staff were contacted to explain the purpose and questionnaire again to obtain their agreement to collect data in both outpatient and inpatient departments.

The purpose of this study and the content of the questionnaire were explained to the selected participants. Afterward, a written informed consent form was signed before starting data collection. The questionnaires were completed by the researcher. One hundred ninety-one participants were interviewed face-to-face, and 229 participants were interviewed by telephone due to coronavirus disease 2019 (COVID-19). Each face-to-face interview took 30 min, and each telephone interview took 40 min. Before ending the interview, completed questionnaires were checked again to ensure that there were no missing data. Data were collected between October and December 2021.

Statistical analysis

Data were entered into the spreadsheet and checked for any errors before being imported into the SPSS program (Version 24, Chicago, IL). Continuous data were analyzed and are presented as frequencies, means, maximums, minimums, and standard deviations to describe the participants’ characteristics. Categorical data are presented as percentages. QOL was divided into three levels: low, moderate, and high.

A chi-square test and Fisher’s exact test were used to preliminarily test the associations between factors and good QOL. Logistic regression was used to determine the associations of factors and good QOL at a significance level α = 0.05 in both univariate and multivariate analyses. In the multivariate analysis, all predicted variables were entered into the model before non-statistical variable(s) were considered to exclude from the model. In this step, one most non-statistical variable was excluded from the model first, and considered the fit of the model by using the Hosmer–Lemeshow chi-square test before excluding the remaining non-statistical variable(s) in the model. The Cox-Snell R2 and Nagelkerke R2 were used to determine the fitness of the model before interpreting the final model.

Ethics approval and consent to participate

Ethical approval was obtained from Mae Fah Luang University (No. EC 21073-18). Participants were recruited on a voluntary basis. On the date of data collection, each participant received all the necessary information about the study protocol, the purpose of the survey and the potential risks. Participants were asked to sign consent forms before starting the interview. The study procedures were performed in accordance with the relevant guidelines, regulations, and within the Declaration of Helsinki of 1975, as revised in 2000 (5).

Results

A total of 420 COPD patients were recruited into this analysis: 56.4% were males, 48.1% were aged 70 years and over, and 67.1% were married. Approximately one-fifth (21.2%) were illiterate, 73.3% were unemployed, and 57.9% had an annual family income of less than 100,000 CNY ($14,750). Approximately twenty percent of participants (19.2%) faced problems with medical expenses, 69.8.0% self-paid for medical expenses, 73.3% had comorbidities, and 18.3% were current smokers (Table 1).

Table 1 General information of participants (n = 420).
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Nearly half of the participants (47.6%) lived in rural areas, and 48.3% went to a hospital by themselves. Half of the participants (43.8.0%) lived with others, and 40.5% had experienced exposure to secondhand smoke (Table 2).

Table 2 Environmental factors of participants (n = 420).
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Almost half (49.5%) had severe airflow limitation. A large proportion (61.9%) were reported to have been diagnosed with COPD for 60 months or more, 44.8% did not have home oxygen therapy available, and 49% had been hospitalized at least once in the past three months. A large proportion (62.9%) had visited their doctor 5 times or more in the last three months. Only one-fourth (25.7%) of the participants had good QOL (Table 3).

Table 3 Characteristics of COPD and QOL (n = 420).
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In the univariable analysis, 16 variables were found to be associated with good QOL: age, annual family income, cost of COPD treatment, BMI, medical insurance, number of comorbidities and types of comorbidities, such as hypertension, diabetes, and osteoporosis, current cigarette smoking, duration of smoking, distance from residence to hospital, exposure to secondhand smoke, airflow limitation severity, duration of illness, home oxygen therapy, number of hospitalizations within the past 3 months and doctor visits within the past 3 months. Other variables were not found to be associated with QOL (Table 4).

Table 4 Factors associated with good-QOL in univariate and multivariate analyses (n = 420).
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In the multivariable analysis, six variables were found to be associated with good QOL. Patients who were employed had 2.35 times (95% CI 1.03–5.34) greater odds of having good QOL than those who were unemployed. Those whose family income was higher than 1,00,000 CNY had 2.49 times (95% CI 1.15–5.39) greater odds of having good QOL than those whose family income was lower than 1,00,000 CNY. Those who had treatment expenses of less than 5000 CNY had 4.57 times (95% CI 1.57–13.30) greater odds of having good QOL than those who had treatment expenses of 5000 CNY or higher. Those who had mild or moderate airflow limitation had 5.27 times (95% CI 1.61–17.26) greater odds of having good QOL than those who had severe or very severe airflow limitation. Those who had a duration of illness less than 60 months had 5.57 times (95% CI 1.40–22.12) greater odds of having good QOL than those who had a duration of illness of 120 months or more. Those who had not been hospitalized within the past 3 months had 9.39 times (95% CI 1.62–54.43) greater odds of having good QOL than those who were hospitalized more than twice over the past 3 months (Table 4).

Discussion

Only one-third (24.8%) of the COPD patients who lived in Zhejiang Province, Chinn had poor QOL. Several factors were detected as contributors to having good QOL among COPD including employment status, high income, having been charged low treatment fees, having mild and moderated airflow limitation, having been diagnosed with COPD less than 60 months, and having never been admitted in a hospital.

The majority of people living in Zhejiang Province, China, had an annual family income of $14,750, which was higher than that of people living in other regions of China. COPD patients living in Shandong Province, where people had an annual family income lower than that in Zhejiang, had a lower proportion of good QOL25,31. Those people who lived in higher-income areas had higher levels of health insurance coverage, which supported them in accessing medical care and having better QOL than those who lived in poorer areas and had lower levels of health insurance coverage25,31. This finding confirmed that COPD patients living in high-income areas have better QOL. This means that those who have a higher income would have a better opportunity for early diagnosis, treatment, and continuous care. Once carefully and continuously cared for, patients would have better QOL and less opportunity to be hospitalized due to poor management of the disease. Moreover, we found that COPD patients who were employed had better QOL than those who were not employed. Kupcewicz et al.32 reported that COPD patients who were employed had better QOL than those who were retired. However, a large proportion of COPD patients were not actively working33,34. Due to its pathogenesis, the disease and the burden of medical expenses could be key impact factors of QOL as well33.

Even in our study, smoking was not found to be associated with QOL among COPD patients. However, many studies35,36,37 have reported that smoking is a key factor of poor QOL among COPD patients. Smoking was reported as a significant risk factor for hospitalization among COPD patients38,39, especially among COPD patients with poor economic status39. A study in Korea40,41 reported that COPD patients with a low family income had a greater chance of using cigarettes and had poorer QOL. This could reflect that COPD patients with a poor economic status have a greater chance of stress and start smoking, followed by a severe stage of COPD and low QOL.

Medical expenses or the cost of treatment was a significant factor associated with QOL among COPD patients living in Zhejiang Province, China. Medications account for the highest proportion of total medical costs for COPD patients42,43. Zhu et al.14 and Li et al.44 reported that a high medical cost was a direct factor in reducing QOL among COPD patients. Unaffordable medical costs of COPD patients were associated with a poor stage of COPD and poor QOL14. Basically, COPD patients need to attend a hospital regularly to check their health and obtain medications throughout their lives. If a patient cannot pay for medication, they enter a poor stage of the disease and have difficulty breathing, which directly impacts their QOL. Thus, affordable medical care is a significant factor in good QOL among COPD patients.

Our study clearly showed that the severity of airflow limitation among COPD patients was associated with their QOL. It is well known that impairment of lung function leads to a reduction in patients’ ability to carry out daily activities2,45. COPD patients with severe airflow limitation often experience dyspnea, cough, fatigue, and declining lung function46,47. This affects their participation in social activities, including the limitation of occupational opportunities and interactions with their family members and other social activities. This could develop the individual’s perception of being a burden to others because they need assistance to complete daily activities and finally manifest as impaired QOL48. Several studies49,50 reported that COPD patients had poor QOL due to personal perceptions of their family members’ burden, especially in the mental health domain.

We found that a longer course of disease led to a poorer level of QOL among COPD patients. On the other hand, those who had a shorter period of COPD development had better QOL than those who had a longer COPD diagnosis. Jankowska-Polańska et al.51 also reported that COPD patients who lived for a shorter duration with the disease had a better QOL than those who had lived longer with the disease. Divo et al.50 reported that COPD patients who had lived with the disease longer had a greater opportunity to have a heavy cough in daily life than those who had lived with COPD for a shorter time. The study52 also reported that coughing was a major sign associated with the QOL of COPD patients. Patients diagnosed over a longer period had a greater chance of being hospitalized than those diagnosed over a shorter period52. Several studies53,54,55,56 reported that COPD patients who had been hospitalized presented panic or mental health problems compared with those who did not, eventually resulting in poorer QOL. Patients with longer illness could face a severe decline in mental health due to the stage of pathogenesis, lack of social interaction, and poorer self-confidence, resulting in poor QOL.

A greater number of hospitalizations indicated disease severity and patients with repeated admissions had significantly reduced QOL. Many studies57,58,59 reported that COPD patients who had been hospitalized had poorer QOL. Physical, psychological, and social life impacts were detected among COPD patients who were frequently admitted to a hospital60,61,62, which directly impacted QOL. Some studies showed that patients with frequent exacerbations had a significantly lower QOL than patients with less frequent exacerbations63. Bernhard et al.64 reported that changes in HRQOL were more dependent on the frequency of exacerbation than on FEV1 and DLCO decline. Hospitalization also increased the financial burden and reduced QOL65. Hospitalization among COPD patients could reduce their QOL due to physical, psychological, social life, and economic reasons.

Some limitations were found in this study that could impact the results and interpretations. First, with the nature of a cross-sectional study that assesses both exposures and outcomes at the same time, quality of life might not be the exact consequence of the preceding factors. Good QOL among individuals might be the integrated outcome of many factors, especially living environment and family relations, which were not measured in our study. Second, the size of the study sample obtained from the standard formula for a cross-sectional study might impact the generalizability of the results to the general population. Last, using telephone calls to collect data might impact the completeness of the data and the quality of the data because physical body language could not be evaluated.

Conclusion

A large proportion of COPD patients living in Zhejiang Province, China, suffer from poor QOL. Several personal traits and the unaffordable cost of treatment are the major factors contributing to poor QOL among COPD patients. To improve QOL among COPD patients, public health policy-makers must develop a proper channel to increase accessibility to health care services, including affordable health insurance. Health institutes must consider supportive ways to provide medical services for COPD patients. Implementing measures to help COPD patients obtain a better job and higher income for family members is one of the challenges to ensure that COPD patients will be able to access medical care and have good QOL.