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* From the Department of Epidemiology (Drs. Xie, Li, Zhou, Zhang, and Wu), Cardiovascular Institute and Fu Wai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College; and the Shijingshan Center for Disease Control and Prevention (Dr. Shi), Beijing, Peoples Republic of China.
Correspondence to: Yangfeng Wu, MD, PhD, Department of Epidemiology, Cardiovascular Institute and Fu Wai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, #167, Beilishi Rd, Xicheng, Beijing, 100037, ROC; e-mail: Yangfengwu{at}263.net
| Abstract |
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Methods: We collected baseline pulmonary function data in 1993 and 1994, and assessed QOL using the Chinese 35-Item Quality of Life Instrument in 2002 in a cohort of 1,356 participants. We used Pearson correlation analysis, multivariate analysis of variance, and multivariate linear regression analysis to assess the relationship between pulmonary function and QOL.
Results: The baseline percentage of age- and height-predicted FEV1 (FEV1%) was significantly correlated with the resurvey total QOL score (r = 0.126, p < 0.001) and with QOL scores for the general (r = 0.074, p = 0.006), physical (r = 0.085, p = 0.002), independence (r = 0.178, p < 0.001), and psychological (r = 0.064, p = 0.018) domains but not with the social and environmental domains after adjusting for age and sex. These associations were weaker for the percentage of age- and height-predicted FVC. Multiple linear regression showed that the above associations were independent of baseline and resurvey smoking status. Inclusion of respiratory symptoms in the model reduced the regression coefficients from 0.82 to 0.41 for the total QOL score and from 1.43 to 0.94 for the independence domain score, for a 10% change in FEV1%. The age- and sex-adjusted mean total QOL scores were 78, 76, 76, and 69, respectively (p < 0.001), for the groups of normal, symptomatic only, impaired pulmonary function only, and both symptomatic and impaired pulmonary function. This trend was also significant for the general, physical, independence, and psychological domain scores.
Conclusion: Impaired baseline pulmonary function has a significant negative impact on QOL in later life that is independent of age, sex, height, and smoking status and is largely mediated through the development of chronic respiratory symptoms.
Key Words: Chinese prospective study pulmonary function quality of life
| Introduction |
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Because impaired pulmonary function due to cigarette smoking and other factors is highly prevalent in most countries,3 it has been extensively studied as a predictor of decreased QOL.456789101112131415 Such study is of particular significance for China, which is the largest consumer of tobacco in the world.16 Although many studies, mostly cross-sectional surveys,456789101112131415 have shown mild-to-moderate positive correlations between pulmonary function and QOL in patients with COPD, asthma, cystic fibrosis, and other lung diseases, Engström and colleagues6 found that QOL was not significantly affected in patients with mild-to-moderate impairment of pulmonary function, possibly due to sufficient pulmonary reserve capacity. However, data are scarce on the association between QOL and pulmonary function in normal populations.456789101112131415 In this article, the relationship between pulmonary function at baseline and QOL 9 years after baseline in a middle-aged Chinese natural population was investigated to understand the long-term effects of impaired pulmonary function.
| Materials and Methods |
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In the 1993-to-1994 survey, serum insulin was added to the laboratory tests for the Beijing urban and rural participants to study its association to cardiovascular risk factors. In 2002, only the Beijing rural population from the PRC-USA joint study who participated in the 1993-to-1994 survey were resurveyed to study the longitudinal association of baseline insulin to incidence of hypertension. This sample included all age-eligible (35 to 64 years) men and women in all 11 villages in the Shijingshan District of Beijing. Of the 2,313 participants with available baseline pulmonary data and information about smoking, 39 participants died and 648 participants had missing baseline serum insulin data (nonresponders due to insufficient volume of serum collected at phlebotomy); the remaining 1,626 participants were invited to the resurvey in 2002. Of these 1,626 invited participants, 1,356 consented and underwent the resurvey in 2002, at which time QOL assessment was added to study its associates and predictors. The remaining 270 subjects who did not return for follow-up are considered dropouts. In this article, we studied the association of baseline pulmonary function in this cohort of 1,356 responding and consenting adults with their QOL 9 years later. To evaluate the possible bias induced by the dropouts and nonresponders, a detailed comparison of baseline characteristics such as age, sex, height, smoking status, pulmonary function, and pulmonary diseases was made between the responders and nonresponders and the dropouts.
Methods of Measurement
We based our baseline and resurvey data collection on a standardized protocol developed in the PRC-USA study,171819 except for the QOL questionnaire. The methods are described below for key variables used in this article. Training and certification of interviewers/technicians and equipment calibration were done according to a detailed manual of procedures.
Spirometry
Spirometry was performed at baseline in 1993 to 1994 in the sitting position using a Collins Stead-Wells water-filled spirometer (including bell and potentiometer) [Collins 10 Liter Survey II; Warren E. Collins; Braintree, MA], which was interfaced to a portable computer using SPIRO software for quality control. (SPIRO software was developed for the PRC-USA collaborative study by Larry Johnson, Peter Boyle, and Paul Enright). Each participant performed at least three acceptable and two reproducible maneuvers in maximal eight forced expirations. Acceptable maneuvers were defined as those with peak expiratory flow within 10% of the maximum observed, a rapid start, absence of major flow fluctuation, and adequate time of expiration.20 Reproducible maneuvers agreed within 0.1 L or 5% for FVC and the FEV1. FEV1 and FVC values in our analyses were calculated from the best volume-time curve, which was corrected according to room temperature and average pressure of air conditions by computer. These values were used to derive the FEV1/FVC ratio.
In order to adjust for height, age, and sex, FEV1 and FVC were divided by the predicted values for each individual and multiplied by 100 (percentage of age- and height-predicted FEV1 [FEV1%] and percentage of age- and height-predicted FVC [FVC%]). The predicted values were based on multiple linear regression models using age and height in men and women, respectively. These models were developed using data from Chinese asymptomatic, nonsmoking men and women in the PRC-USA collaborative study.171819 In this article, normal pulmonary function was defined as FEV1
80% predicted, FVC
80% predicted, and FEV1/FVC ratio
0.70.
Respiratory Symptoms
At both the baseline survey and the resurvey, individual respiratory symptoms were determined using the same standardized questionnaire. Symptomatic individuals were defined as those with one of the three respiratory symptoms: chronic cough, chronic phlegm, or asthma attack. Chronic cough was defined as a reported chronic cough for at least 3 consecutive months in a year. Chronic phlegm was defined as a reported expectoration of phlegm for at least 3 consecutive months in a year. Asthma attack was defined as having ever reported an attack of shortness of breath with wheezing or asthma that was not associated with a diagnosed pulmonary infection.
Quality of life
QOL was self-evaluated only in the resurvey using the Chinese 35-Item Quality of Life Instrument (QOL-35). The 35 items in the QOL-35 are classified into six domains plus one item on the individuals self-evaluation of the changes in his/her QOL in the past year. A brief explanation of these domains and items is shown in Appendix 1. Scores for items, domains, and the whole instrument were transformed to the range from 0 (indicating the worst QOL) to 100 points (indicating the best QOL).
The QOL-35 was developed from the 100-Item World Health Organization Quality of Life Instrument and the 36-Item Medical Outcomes Study Short-Form Health Status Survey. The QOL-35 was tailored to include only 35 items adapted to the Chinese culture, and was evaluated formally before use in the study. The
index was from 0.86 to 1.00 for items in a test-retest survey in 127 adults selected randomly from a Beijing suburban community neighborhood. The Cronbach
coefficients of internal consistency reliability were > 0.7 for all the six domains. The total QOL score of the QOL-35 had a Pearson correlation coefficient of 0.774 with the total QOL score of the 100-item World Health Organization Quality of Life Instrument, and of 0.790 with that of the 36-item Medical Outcomes Study Short-Form Health Status Survey. The reliability and validity of the QOL-35 was thus considered satisfactory.
Smoking
Smoking status was determined for all participants at both baseline and resurvey. A current smoker was defined as an individual currently smoking an average of one or more cigarettes each day or more than one liang (approximately 50 g) of tobacco leaf each month. An ex-smoker was defined as an individual who previously smoked tobacco leaf or cigarettes but was no longer smoking for at least 1 month. Participants who reported that they were neither current smokers nor ex-smokers were classified as having never smoked.
Height
Body height was measured to the nearest centimeter using a standard right-angle device in both surveys. Each participant was measured standing without shoes.
Statistical Methods
Pearson correlation coefficients, partial correlation coefficients, and multivariate linear regression analysis were used to examine the relationship between baseline pulmonary function and the QOL scores 9 years later. In addition, we compared the differences of mean QOL scores among the following four groups: normal, impaired pulmonary function only, chronic respiratory symptoms only, and impaired pulmonary function plus chronic respiratory symptoms, using multivariate analysis of variance, adjusting for potential confounders. All analyses were done by statistical software (SPSS version 10.0; SPSS; Chicago, IL).
| Results |
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Adjustment for Confounders
To further understand the role that smoking might play in these associations, we adjusted for smoking status at both baseline and resurvey in our analyses in addition to the age and sex adjustment. The results showed that ex-smokers at resurvey had a significantly lower QOL (total QOL score and score for the independence domain). Ex-smokers at baseline and current smokers at baseline or resurvey did not exhibit this association (data not shown). On the whole, adding smoking status to the model reduced the regression coefficient of FEV1% with QOL independence domain score by 5.6% and reduced the coefficient with total QOL score by 7.3% (Table 4
). The corresponding values for the general, physical, and psychological domains were 12.7%, 8.3%, and 8.3%, respectively (data not shown). Using the same strategy of analysis, we tested whether the associations between baseline pulmonary function and future QOL was independent of respiratory symptoms. The results showed that there were still significant associations between baseline FEV1% and later QOL scores after adjustment for respiratory symptoms at both baseline and resurvey (Table 4, Appendix 2). However, adding respiratory symptoms into the model reduced the size of the association of FEV1% with total QOL score by 50% and reduced the association with QOL score for independent domains by 34% (Table 4). The corresponding values for the general, physical, psychological domains were 43.0%, 73.8%, and 60%, respectively (data not shown).
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| Discussion |
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In this study, all participants came from a community-based population cohort, while previous reported studies456789101112131415 have been done in patients with COPD, asthma, or nonspecific lung disease. Since the association between pulmonary function and QOL in patients cannot be directly applied to a general normal population, our results demonstrating that impaired pulmonary function predicts lower future QOL in the general population and even in asymptomatic never-smokers are important. We found that this association is not linear but curvilinear. The changes of pulmonary function in the normal range had little effect on future QOL. But when pulmonary function is lower than a threshold value (FEV1 < 80% of predicted value in our analysis), further decreases in pulmonary function would affect significantly QOL scores. This is consistent with previous studies4567 in which considerable effects on QOL have been demonstrated in severe pulmonary disease but not in the early milder stages of the disease in Western populations.
It is clear that impaired pulmonary function leads to difficulties in performing physical activities, such as items in the independence domain which include running, walking, lifting, shopping, doing homework, bathing, and dressing. Noteworthy were the effects on the physical domain, which include pain, sleep, eating, and fatigue. The effects on the psychological domain, which include self-confidence, living pleasure, nervousness, negative feeling (downhearted, despaired, anxiety, melancholy), memory, and attention span, were relatively small but still significant. These indicate almost every aspect of functional status would be affected at lower levels of pulmonary function at baseline.
One striking finding was that men had lower age- and height-adjusted lung function and higher QOL. This is in accordance with the results of studies by Osborne et al21 and Wijnhoven et al,4 who found that men with asthma or COPD and lower lung function reported a better QOL than women. However, men and women had similar regression coefficients for lung function with QOL after adjustment for potential confounders (data not shown). This suggests that the association between lung function and QOL is similar in men and women. The higher QOL in men might be partly attributed to physical fitness, muscle strength, and emotional well-being.
The precise mechanisms by which impaired pulmonary function causes reduced QOL are not clear.22 However, our data may provide some suggestive evidence for the possible mechanisms linking pulmonary function to QOL. After controlling for the confounding effects of age, sex, and height, adding smoking status into the model could only explain approximately 10% of the association between pulmonary function and QOL, but adding respiratory symptoms could explain about half of the association. Nevertheless, it was ex-smokers but not current smokers who had a significant lower QOL in comparison to nonsmokers (data not shown), suggesting that quitting smoking reflected concomitantly poorer health status. In fact, adding respiratory symptoms into the model removed the significance of smoking status (data not shown). Considering the abundance of evidence,31923 including our own results for a causal relationship between smoking and poor pulmonary function and for a causal relation between impaired pulmonary function and respiratory disease, our results do not imply that smoking is not associated to QOL or is associated less stronger than respiratory symptoms. The findings actually support that impaired pulmonary function is caused by smoking, inflammation, or other factors. Impaired pulmonary function further causes poor QOL either by causing respiratory symptoms (as an intermediate, accounting for approximately half of the effect in our study) or by some other mechanisms that we do not understand (accounting for the other half of the effect in our study). Thus, our findings suggest that smoking cessation and other measures that may prevent impairment of pulmonary function should also be effective in preventing poor QOL later in life. This is of importance from the preventive medicine point of view, because better QOL is becoming an important subjective indicator of therapeutic or preventive management with prolonged human longevity.24 Physical exercise, quitting smoking, decreasing air pollution, and preventing airway infection should be helpful for improving long-term QOL.
In addition, our findings in the relationship between baseline pulmonary function and later QOL were established on group data and hence should not be used for individual prediction, giving the relative small correlation coefficients (Table 3) and the relative large spread of the QOL scores (Table 2, Fig 1). This means that an individual with low pulmonary function has a greater but not definite chance of having worse QOL later in life.
Although we are not able to predict an individuals QOL in the future, our findings do have a clear message for clinicians. The comparison of QOL between groups of normal, impaired pulmonary function only, respiratory symptoms only, and impaired pulmonary function plus respiratory symptoms showed that only participants with both impaired pulmonary function and chronic respiratory symptoms were at high risk for having poor QOL in the future. However, the participants with either impaired pulmonary function only or respiratory symptoms only had a very mild risk of poor QOL in the future. Thus, the clinical use of spirometric testing and questions about chronic respiratory symptoms will help in identifying those who need early intervention. In terms of effective interventions, findings from the recent large clinical trails232526 were quite disappointing: smoking cessation was the only effective measure found to result in a deceleration of pulmonary function decline.323 However, interventional treatments that are not effective in preventing impaired pulmonary function may be helpful in maintaining higher QOL by relieving chronic respiratory symptoms. Our findings are in agreement with those of Boom et al25 and Grunsven et al,26 who found that early treatment with fluticasone propionate was not effective in treatment of pulmonary function decline but was effective in increasing QOL (by reducing dyspnea).25
Our study has some limitations. First, there were dropouts and nonresponders. The results showed that the nonresponders and dropouts were older, were more frequently smokers, had worse pulmonary function, and had more respiratory symptoms. Thus, the responders were healthier than the original study population. Using only the responders would be expected to dilute the association between baseline pulmonary function and future QOL because the subgroup with lower baseline pulmonary function (dropouts and nonresponders) would have had an even lower QOL than the responders. Thus, a stronger association would be expected if there had been full participation.
We did not have QOL measured at baseline and pulmonary function measured at resurvey. This prevented us from being able to better separate the independent effect of baseline pulmonary function and changes of pulmonary function from confounders and inter-mediates.
Despite these limitations, our data provide strong support for the conclusion that baseline impaired pulmonary function is associated with decreased future QOL. These effects are dependent on the extent of impaired pulmonary function but are independent of other potential confounders. These results help us to understand the long-term effects of impaired pulmonary function and its modifiable risk factor (tobacco consumption) on QOL. More interventional programs on smoking and other risk factors should be carried out in general population, as well as in those with impaired pulmonary function and chronic respiratory symptoms.
| Appendix |
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| Acknowledgements |
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| Footnotes |
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Supported by the Peoples Republic of China National Tenth Five-Year Plan Project (grant No. 2001BA703B01).
Received for publication August 6, 2004. Accepted for publication March 21, 2005.
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