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68 Zhou et al.

Methods

Study design and subjectswo population-based epidemiological studies wereconducted in an urban area of Guangzhou, China,including a cross-sectional survey including 1818subjects aged ≥40 years that was conducted in 2002and a subsequent 4-year follow-up survey (from2003 through 2007) of 759 subjects who did not haveCOPD at the baseline test. In both surveys, multistagecluster sampling strategies were used, and spirom-etry testing and questionnaires interviews were con-ducted.

Te detailed study protocols have been describedin previous publications (6, 7). Ethical approval of thestudy protocols was obtained from the Medical EthicsCommittee of the Guangzhou Institute of RespiratoryDiseases, and informed consent was obtained from allparticipants. Te studies adhered to the principles of theHelsinki Declaration.

Spirometry In both surveys, spirometry testing was performed usingportable spirometers (Micro Medical Ltd., Chatham,Kent, UK) by professional staff. Te spirometry test-ing procedure recommended by American ToracicSociety (8) and Enright PL et al. (9) was applied to alleligible subjects. Subjects with a pre-bronchodilatorFEV

1/FVC <0.7 underwent post-bronchodilator testing;

i.e., spirometry carried out within 15 to 20 minutes aftertaking a dose of 200 µg (in the cross-sectional study) or400 µg (in the 4-year follow-up survey) of Salbutamol(Ventolin; GlaxoSmithKline, Middlesex, UK) inhaled

through a 500-ml spacer.Te use of short- and long-acting bronchodilatorswithin 12 or 24 hours prior to the test, respectively,was prohibited. We determined a quality grade (A–F)based on acceptable maneuvers and repeatability of theFEV

1 and FVC (10). At baseline, spirometry results with

Grades A, B or C (at least two acceptable maneuvers,with FEV

1 values matching within 0.2 L) was considered

acceptable for analysis.In our follow-up, spirometry testing was performed

annually at the same time, and a stricter standardwas required for analysis: at least three acceptableand two reproducible measurements (i.e., the highest

and second highest values of the forced vital capac-ity (FVC) and FEV

1 were within 150 ml or 5%) were

required for analysis. According to the current criteriaof the global initiative for chronic obstructive lung dis-ease (GOLD) (11), subjects with post-bronchodilatorFEV

1/FVC <0.7 were diagnosed with COPD, and

the stage (I-IV) of COPD was determined in eachdiagnosed patient. Predicted normative values ofFEV

1 in Chinese population were derived from ECSC

93

(European Coal and Steel Community in 1993) equa-tions and adjusted using the appropriate conversionfactors (12).

Questionnaire Te questionnaires used in the two studies have been pub-lished elsewhere (6, 7) and include questions about demo-graphic variables, respiratory symptoms/disease history,co-morbidities, health care utilization, activity limitation,nutritional status, smoking and other potential risk factorsfor COPD. Body weight was measured in light clothing tothe nearest 0.1 kg with a calibrated balance beam scale;

height without shoes on was measured to the nearest 0.5 cmusing a vertical ruler; and BMI (kg/m2) was computed asthe ratio of body weight (kg) to height squared (m2).

BMI status was classified as “low (<18.5 kg/m2),”“normal (18.5–23.9 kg/m2),” “overweight (24.0–27.9 kg/m2)” or “obese (≥ 28.0 kg/m2)” (13). Smoking status wasrecorded as “currently smokes,” “has never smoked,” or“previously smoked” at each visit. Subjects who hadsmoked for at least six months or had smoked at least100 cigarettes in their lifetime were defined as “eversmokers”(14), otherwise, they were categorized as neversmokers. “Former smokers” were defined as subjectswho had quit smoking for at least 6 months.

Current smokers included continual smokers andthose who had quit but restarted or relapsed or hadquit for less than 6 months (7). Te following factorswere measured at baseline and coded as dichotomous variables: occupational exposure (yes or no, classifiedwith a cut-off point of occupational exposure to dusts/fumes/gases for one year), co-morbidity (any physician-confirmed COPD-related disease), and family history ofrespiratory disease (any parent or sibling diagnosed withchronic bronchitis, emphysema, asthma or COPD).

Statistical analysis

Statistical analyses were performed with Stata software(Version 7.0, Stata Corporation, College Station, X,USA) and SAS version 9.1 software (SAS Institute, Cary,NC). Te association between BMI and COPD was eval-uated using dichotomous logistic regression, and oddsratios (ORs) and relative risk ratios (RRs) for COPDwere calculated after adjustment for clusters, gender,education level, smoking status, family history of respi-ratory disease, history of exposure to occupational dust/fume/gases, and age. No interaction was added to thefinal logistic regression model. A p-value of <0.05 wasconsidered statistically significant.

Results

Baseline characteristics of the two study populationsTe mean age of the population in the cross-sectionalstudy was 59.11 (the standard deviation (SD), 11.82) yrs;40.2% were male; the mean FEV

1 was 2.06 (SD, 0.64) L;

the mean FVC was 2.58 (SD, 0.75) L; the mean FEV 1/

FVC was 80.00 (SD, 9.31) %; the mean BMI was 22.88(SD, 3.50); and 35.1% of population had ever smoked cig-arettes. Te baseline characteristics of the cohort studyand the cross-sectional study populations were similar,except for occupational exposure ( p < 0.05) (able 1).



Association between BMI and COPD in Guangzhou, China

www.copdjournal.com

BMI and COPD As the cross-sectional study has shown, patients withlow BMI had a higher prevalence of COPD than thosewith normal BMI (21.1% vs. 7.5%), with an adjusted ORof 2.75 (95% CI, 1.69 to 4.47) (able 2). In addition, itappeared that the subjects with higher BMI had a lowerlikelihood of COPD ( P

trend < 0.001). Tis association

was further identified in the follow-up cohort study, as

shown in able 3.Non-COPD subjects with low BMI at baseline were

more prone to developing COPD than were those with-out low BMI, with an RR of 2.88 (95% CI, 1.06 to 7.85).In addition, as shown in able 2, males, elderly subjects,smokers and subjects with a family history of respiratorydisease were more likely to develop COPD. Non-COPDsubjects with low FEV

1/FVC at baseline and those with

a higher smoking index were also more likely to developCOPD (able 3). Finally, we found that patients withCOPD had lower BMIs than those without COPD,and patients with stage IV COPD had the lowest BMIs(Figure 1). Te baseline survey showed that both low

BMI and obese subjects with or without COPD hadlower FEV

1 after adjustment for covariates (Figure 2).

Discussion

Te major finding of this study was that low BMI wasassociated with an increased incidence of COPD, andthat this association was not merely observed at a laterstage of COPD. A major strength of the present studycompared to previous studies is that it provides com-prehensive data about COPD and BMI in the generalpopulation using both cross-sectional and prospective

approaches. With regard to the association betweenCOPD and low BMI, researchers have previously sug-gested that low BMI was secondary to COPD (15)and could be attributed to the systemic inflammation,imbalance of oxidative status and tissue hypoxia presentin COPD patients (16–18).

In contrast to this hypothesis, we observed that subjects with low BMI were at a substantially elevated riskof COPD even after adjusting for other potential riskfactors. Our results were consistent with the reports ofHarik-Khan and Higgins. Harik-Khan (5) has indicatedthat men with a low BMI are at increased risk of devel-oping COPD, and Higgins (19) has demonstrated that

the incidence of obstructive airway disease, defined as apredicted FEV

1 < 65%, is highest in lean men and lowest

in overweight men.Te association between low BMI and an excessive

incidence of COPD may be explained by several factors.First, poor nutritional status at birth or during earlyinfancy is associated with impaired lung function or thedevelopment of COPD in adulthood (20, 21). Althoughwe assessed low adulthood BMI rather than low birthweight, both of these observations suggest that malnutri-tion reduces respiratory muscle and is likely to increasethe likelihood of chronic lung infections (22, 23). Second,

Table 1. Baseline characteristics of the participants in the cross-sectionalstudy and subsequent cohort study

Cross-sectionalstudy Cohort study

Subjects 1818 (100.0) 759 (100.0)

Age (years) 59.11 (11.82) * 59.27 (11.31) *

40-49 yrs 517 (28.4) 198 (26.1)

50-59 yrs 384 (21.1) 176 (23.2)

60-69 yrs 521 (28.7) 231 (30.4)

70 yrs or over 396 (21.8) 154 (20.3)

Gender

Male 730 (40.2) 316 (41.6)

Female 1088 (59.8) 443 (58.4)

Education, yrs

0 yrs 175 (9.6) 70 (9.2)

1-5 yrs 585 (32.2) 269 (35.4)

6-8 yrs 455 (25.0) 184 (24.2)

9-11 yrs 485 (26.7) 196 (25.8)

≥12 yrs 118 (6.5) 40 (5.3)

Family history of respiratorydisease

Yes 354 (19.5) 144 (19.0)

No 1464 (80.5) 615 (81.0)

BMI, kg/m2 22.88 (3.50) * 23.09 (3.50) *

Low (<18.5) 166 (9.1) 57 (7.5)

Normal (18.5-23.9) 1008 (55.4) 414 (54.5)

Preobese (24.0-27.9) 524 (28.8) 235 (31.0)

Obese (≥28.0) 120 (6.6) 53 (7.0)

Occupational exposureξ

Yes 384 (21.1) 354 (46.6)

No 1434 (78.9) 405 (53.4)

Smoking index, pack-yrs 10.01 (19.27) * 11.90 (20.36) *

<15pack-yrs 1370 (75.4) 529 (69.7)

15-29 pack-yrs 196 (10.8) 97 (12.8)

30-44 pack-yrs 124 (6.8) 72 (9.5)

≥45 pack-yrs 128 (7.0) 61 (8.0)

Smoking status

Never smoked 1179 (64.9) 446 (58.8)

Former smoker 227 (12.5) 106 (14.0)

Current smoker 412 (22.7) 207 (27.3)

Pre-bronchodilator FEV1, L 2.06 (0.64) * 2.11 (0.58) *

Pre-bronchodilator FVC, L 2.58 (0.75) * 2.60 (0.70) *

Pre-bronchodilator FEV1 /FVC, % 80.00 (9.31) * 81.44 (6.92) *

Post-bronchodilator FEV1†, L 1.32 (0.60) * -

Post-bronchodilator FVC†, L 2.15 (0.81) * -

Post-bronchodilator FEV1 /FVC†, % 59.99 (11.17) * -

All data are shown as n (%), unless otherwise specified.*Data are shown as the mean (SD).†Only data for patients with COPD were shown because subjects without COPD did notreceive post-bronchodilator spirometry testing.ξp < 0.05 between cross-sectional study and cohort study.




70 Zhou et al.

Table 3. Association between BMI and COPD in popula tion-based cohort study

Subjects(n)

COPD(n, %)

Crude Adjusted*

RR (95% C.I.) p RR (95% C. I.) p

BMI (kg/m2) † 0.019 0.039

Low (<18.5) 57 6 (10.5) 3.06 (1.20-7.77) 2.88 (1.06-7.85)

Normal or over (≥18.5) 702 26 (3.7) 1.00 (Reference) 1.00 (Reference)

Age (years) 0.185 0.852

40-49 yrs 198 4 (2.0) 1.00 (Reference) 1.00 (Reference)

50-59 yrs 176 6 (3.4) 1.71 (0.48-6.17) 0.411 1.21 (0.32-4.66) 0.781

60-69 yrs 231 12 (5.2) 2.66 (0.84-8.38) 0.095 1.54 (0.46-5.20) 0.485

70 yrs or over 154 10 (6.5) 3.37 (1.04-10.95) 0.044 1.68 (0.46-6.15) 0.433

Smoking index <0.001 0.036*

<15pack-yrs 529 11 (2.1) 1.00 (Reference) 1.00 (Reference)

15-29 pack-yrs 97 6 (6.2) 3.11 (1.12-8.61) 0.029 1.66 (0.52-5.33) 0.396

30-44 pack-yrs 72 8 (11.1) 5.89 (2.28-15.18) <0.001 2.77 (0.91-8.48) 0.073

≥45 pack-yrs 61 7 (11.5) 6.10 (2.27-16.40) <0.001 2.45 (0.76-7.91) 0.133

Sex 0.089

Male 316 24 (7.6) 4.47 (1.98-10.08) <0.001 2.25 (0.88-5.75)

Female 443 8 (1.9) 1.00 (Reference) 1.00 (Reference)

Baseline FEV1 /FVC‡ 0.87 (0.81-0.94) <0.001 0.92 (0.85-0.98) 0.015

*Adjusted for age, sex, education, smoking index, occupational exposure to dust, and family history of respiratory disease.†When BMI was included in the logistic regression model as a continuous variable, the adjusted OR was 1.14 (1.02–1.26),p = 0.017.‡Baseline FEV

1 /FVC was included into the logistic regression model as a continuous variable.

Table 2. Association between BMI and COPD in a popula tion-based cross-sectional study

Subjects(n)

COPD(n, %)

Crude Adjusted*

OR (95% C.I.) p OR (95% C.I.) p

BMI (kg/m2) <0.001 <0.001

Low (<18.5) 166 35 (21.1) 3.28 (2.11-5.08) <0.001 2.75 (1.69-4.47) <0.001

Normal (18.5-23.9) 1008 76 (7.5) 1.00 (Reference) 1.00 (Reference)

Overweight (24.0-27.9) 524 22 (4.2) 0.54 (0.33-0.87) 0.012 0.49 (0.30-0.82) 0.006

Obese (≥28.0) 120 1 (0.8) 0.10 (0.01-0.75) 0.025 0.11 (0.02-0.85) 0.034

Age (years) <0.001 <0.001

40-49 yrs 517 9 (1.7%) 1.00 (Reference) 1.00 (Reference)

50-59 yrs 384 13 (3.4%) 1.98 (0.84-4.68) 0.120 2.21 (0.92-5.31) 0.077

60-69 yrs 521 42 (8.1%) 4.95 (2.38-10.28) <0.001 5.41 (2.56-11.44) <0.001

70 yrs or over 396 70 (17.7%) 12.12 (5.97-24.60) <0.001 12.11 (5.75-25.49) <0.001

Sex <0.001 <0.001

Male 730 101 (13.8%) 5.13 (3.42-7.70) 3.04 (1.85-5.00)

Female 1088 33 (3.0%) 1.00 (Reference) 1.00 (Reference)

Family history of respiratory disease 0.376 0.046

Yes 354 30 (8.5%) 1.21 (0.79-1.85) 1.61 (1.01-2.58)

No 1464 104 (7.1%) 1.00 (Reference) 1.00 (Reference)

Smoking status <0.001 0.047

Never smoked 1179 44 (3.7%) 1.00 (Reference) 1.00 (Reference)

Current smoker 412 51 (12.4%) 3.64 (2.39-5.55) <0.001 1.76 (1.05-2.95) 0.031

Former smoker 227 39 (17.2%) 5.35 (3.39-8.46) <0.001 1.83 (1.06-3.16) 0.029

Smoking index 0.002 0.027

<15 pack-yrs 1370 60 (4.4%) 1.00 (Reference) 1.00 (Reference)

15-29 pack-yrs 196 19 (9.7%) 2.34 (1.37-4.02) <0.001 1.12 (0.61-2.06) 0.716

30-44 pack-yrs 124 21 (16.9%) 4.45 (2.61-7.61) <0.001 1.94 (1.05-3.57) 0.033

≥45 pack-yrs 128 34 (26.6%) 7.90 (4.94-12.63) <0.001 2.10 (1.21-3.67) 0.009

*Adjusted for age, sex, education, smoking status and index, occupational exposure to dust, and family history of respiratory disease.



Association between BMI and COPD in Guangzhou, China

www.copdjournal.com

increases in BMI over time provoked greater decreasesin FVC than in FEV

1; therefore, the ratios of FEV

1/FVC

increased as BMI increased because both FVC and FEV 1decreased (24).Tird, the lower caloric intake by cigarette smokers

may contribute to the finding that low BMI subjects weremore susceptible to COPD. However, smoking-inducedlow caloric intake cannot completely account for lowBMI because the association of leanness with a higherrisk of respiratory mortality was also observed in non-smokers (never smokers) (25, 26). Hence, weight loss inCOPD is unlikely to be due to simple malnutrition. Inaddition, deficits in cell-mediated immunity and circu-lating -lymphocyte numbers caused by protein-energymalnutrition can lead to an increased susceptibility to

infection (27), which exacerbate declines in pulmonaryfunction and are considered important risk factors forCOPD (23).

A somewhat surprising result of this study is ourfinding that subjects with high baseline BMI had a lowerrisk of developing COPD, despite their lower FEV

1. We

had initially suspected that the predominantly restric-tive effects of central obesity would eventually lead to areduction in both FVC and FEV

1.

However, this study has several limitations thatmust be acknowledged. First, there were insuffi cientsubjects with low BMI and newly developed COPD for

an independent analysis of the female subgroup in thecohort study. Second, like many other prospective stud-ies, this study has an inevitable survivor bias. However,the influence of this effect should be minor becauseCOPD is typically not a fatal condition.

In addition, the assessment of nutritional status basedon BMI has several inherent limitations, in that the lossof skeletal muscle mass is the main cause of weight loss

in patients with COPD, and this commonly occurs at anearlier stage of COPD than does the decrease in BMI.Recent data have suggested that fat-free mass index(FFMI) and mid-arm muscle area (MAMA) can provideinformation beyond that provided by BMI (28–30).

In summary, we have found that low BMI is an impor-tant risk factor for development of COPD, independentof patient age, smoking status, and other potential riskfactors. Te source of this relationship is unclear, but itraises the possibility that early intervention in patientswith low BMI may reduce the occurrence of COPD.

AcknowledgementsWe are grateful to Prof. Shiliang Liu (Health Surveil-lance and Epidemiology Division, Health Promotionand Chronic Disease Prevention Branch, Public HealthAgency of Canada, Ministry of Health, Ottawa) for theirassistance in English.

Declaration of Interest Statement

Supported by Chinese Central Government keyresearch projects of the 10th national 5-year develop-ment plan grants 2001BA703B03(A) (P.R.) and Te

National Key echnology R&D Program of the 12thNational Five-year Development Plan 2012BAI05B01(P.R.).

Te researchers were also independent from funders.Te study funders were independent from the study indesign, collection, analysis, interpretation of data, writ-ing of the report, and in the decision to submit the articlefor publication. Te study protocol was approved by theMedical Ethics Committee of Guangzhou Institute ofRespiratory Diseases on 20 May 2002.

Yumin Zhou collected the data and monitored datacollection, planned the statistical analysis, analysedthe data, and drafted the manuscript. Dali Wang,

Shengming Liu, and Jiachun Lu implemented the trial.Jingping Zheng and Nanshan Zhong conducted andmonitored data collection. Pixin Ran initiated anddesigned the project, monitored data, and drafted thepaper. Yumin Zhou and Pixin Ran are guarantors.

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Figure 1. BMI stratified by non-COPD and COPD stages in the population-basedcross-sectional study, after adjustment for age, sex, education, co-morbidity,smoking, occupational exposure to dust, and family history of respiratory disease.

Figure 2. Estimated FEV1 for each BMI stage in the population-based cross-

sectional study, after adjustment for age, sex, education, co-morbidity, smokingindex, occupational exposure to dust, and family history of respiratory disease.




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