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Logo of ijmedsciSubmission informationAbout this journalmedsci.orgInternational Journal of Medical Science
Int J Med Sci. 2013; 10(1): 1–7.
Published online 2012 December 5. doi:  10.7150/ijms.5003
PMCID: PMC3534871

Retrospective Analysis of the Relationship between Decline in FEV1 and Abdominal Circumference in Male Smokers: the Takahata Study


Background:Metabolic syndrome (Mets) is reportedly associated with chronic obstructive pulmonary disease (COPD). However, the relationship between abdominal circumference (AC) and decline in FEV1 has not been elucidated. We aimed to investigate this relationship among male current smokers.

Methods:Spirometry was performed on subjects (n = 3,257) ≥ 40 years of age, who participated in a community-based annual health check in Takahata, Japan, from 2004 through 2006 (visit 1). Spirometry was re-evaluated, and AC was assessed in 147 of the male current smokers in 2009 (visit 2). The diagnosis of Mets was based on the criteria used in the Hisayama Study.

Results:No significant relationships were observed between AC and spirometric parameters such as % predicted forced vital capacity (FVC), % predicted forced expiratory volume in 1 s (FEV1) and FEV1/FVC. However, decline in FEV1 was significantly correlated with AC. Multivariate logistic regression analysis showed that AC was a significant discriminating factor for decline in FEV1, independently of age, Brinkman index and change in body mass index from visit 1 to visit 2. At visit 2, there was a greater prevalence of decline in FEV1 among subjects with Mets (n=17) than among those without Mets. Although there were no differences in % predicted FVC, % predicted FEV1 or FEV1/FVC between subjects with or without Mets, the rate of decline in FEV1 was significantly greater in subjects with Mets than in those without.

Conclusions:This retrospective analysis suggested that measuring AC may be useful for discriminating male smokers who show a decline in FEV1.

Keywords: decline in FEV1, abdominal circumference, smoker, health check.


Long-term cigarette smoking is most important cause of chronic obstructive pulmonary disease (COPD) 1. In patients with COPD, forced expiratory volume in 1 s (FEV1) is progressively reduced as the disease develops. In addition, patients with COPD have various systemic comorbidities, including atherosclerosis, cachexia, diabetes mellitus, and osteoporosis 2-7. These comorbidities are thought to be associated with systemic inflammation due to leakage of mediators from sites of local inflammation in the lung, and this is an important determinant of the morbidity associated with the disease 8. Recently, metabolic syndrome (Mets) has received attention as a comorbidity of COPD 9-12.

Mets is also thought to be a disease of systemic inflammation that is derived from visceral fat 13. Patients with Mets have higher risks of cardiovascular disease, stroke, and death, compared to subjects without Mets 14. Since Mets and COPD both involve states of systemic inflammation, it is conceivable that these diseases share common inflammatory pathways.

The results of recent cross-sectional investigations from China and France suggested that the central obesity component of Mets was associated with impairment of pulmonary function 10,15. However, it was not clear whether Mets is a risk factor for decline in pulmonary function parameters such as FEV1, among healthy smokers. We hypothesized that excess abdominal circumference (AC), one of the major signs of Mets, is associated with a decline in FEV1 among smokers. To examine this hypothesis, we retrospectively investigated the relationship between AC and the rate of decline in FEV1.


Study population

This study formed part of the Molecular Epidemiological Study of the Regional Characteristics of 21st Century Centers of Excellence (COE) Program and the Global Centers of Excellence Program in Japan 16. The study was approved by the institutional ethics committee and all participants gave written informed consent.

The study was based on an annual community health check, in which all residents of Takahata town in northern Japan, who were aged 40 years or older, were invited to participate. We have previously reported cross-sectional analyses of spirometry data for subjects who were included in the database from 2004 through 2005 (n = 3,165: 1,380 males; 1735 females) 16-20. We continued to enroll subjects from Takahata in 2006, and recently the additional 2006 database became available for analysis. From 2004 through 2006 (visit 1), 1,579 males and 1,941 females (a total of 3,520 subjects) were enrolled in the study, and performed initial spirometry. Two-hundred and sixty-three subjects were excluded from the analysis because their spirometry data did not meet the specified criteria. The data for a total of 3,257 subjects (1,502 males, 1,755 females) was entered into the final statistical analysis. Subjects used a self-report questionnaire to document their medical histories, smoking habits, current use of medications, and clinical symptoms. The lifetime consumption of cigarettes was expressed as the Brinkman index (number of cigarettes per day x years of smoking). One-hundred and forty-seven of the 523 male current smokers (visit 1) performed subsequent follow-up spirometry in 2009 (visit 2). Body mass index (BMI), Brinkman index, mean blood pressure (BP), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-c), fasting blood sugar (FBS), % predicted forced vital capacity [FVC (%predicted)], and % predicted forced expiratory volume in 1 s [FEV1 (% predicted)] were not significantly different between these 147 male current smokers and the remaining 376 male smoker who did not participate in follow-up spirometry in 2009 (data not shown). However, the mean age of these 147 participants was significantly lower than that of the 376 non-participants assessed in 2004-2006 [mean age (years): 56.40 ± 9.06 vs. 61.09 ± 10.59, P < 0.0001].


AC around the navel was determined at visit 2 using a tape measure. Systolic and diastolic BP were measured using a mercury sphygmomanometer, which was placed on the right arm of seated subjects, who had rested in a sitting position for at least 5 min before the measurement. Measurements were performed twice. Blood samples were taken from the antecubital vein of subjects who had been fasting, and the samples were immediately transferred to chilled tubes.

The diagnosis of Mets was based on the criteria used in the Hisayama Study, a Japanese cohort study in a general population: abdominal obesity with abdominal circumference >90 cm in men; elevated blood pressure with average systolic/diastolic blood pressures ≥130/85 mm Hg; hypertriglyceridemia, defined as a serum TG level ≥150 mg/dL; a low HDL-c level, defined as <40 mg/dL in men; elevated blood glucose with a FBS level ≥110 mg/dL. Metabolic syndrome was defined as the presence of three or more of these factors 21.

Spirometric parameters (FVC and FEV1) were measured using standard techniques, with subjects performing FVC maneuvers on a CHESTAC-25 part II EX instrument (Chest Corp., Tokyo, Japan), according to the guidelines of the Japanese Respiratory Society (JRS) 22. Bronchodilator was not administered prior to spirometry. The highest value from at least three FVC maneuvers by each subject was used for the analysis. The results were assessed by two pulmonary physicians, who visually inspected the flow-volume curves and excluded subjects with inadequate data, as defined by the JRS criteria 22. The rate of decline in spirometric measures [ΔFEV1 (% predicted)/year (%/year) and ΔFVC (% predicted)/year (%/year)] were calculated as [(% predicted value at visit 2 - %predicted value at visit 1)/% predicted value at visit 1] × 100/ time between observations (years).

Statistical analyses

The student's t-test for parametric data or the Mann-Whitney U test for non-parametric data were used to analyze the differences between two groups of subjects. The chi-square test was used to evaluate differences in proportions. All statistical analyses, including linear regression and logistic regression analyses were performed using JMP version 8 software (SAS Institute Inc., Cary, NC, USA). Data are presented in the Figures and Tables as means (SD) or medians (interquartile range). Significance was inferred for differences with P values < 0.05.


Characteristics of the subjects

The characteristics of the male smoking subjects who participated in this study and performed spirometry at both visit 1 and visit 2 are summarized in Table Table1.1. Mean BMI did not differ between visit 1 and visit 2. Mean FVC (% predicted) at visit 2 was significantly higher than that at visit 1, although FEV1 (% predicted) at visit 2 did not differ from that at visit 1. FEV1/FVC was significantly lower at visit 2 than at visit 1, and the prevalence of airflow limitation was significantly greater at visit 2 than at visit 1 (Table (Table1).1). There was a strong correlation between BMI and AC at visit 2 (r = 0.89, P <0.0001).

Table 1
Characteristics of the study subjects at visit 1 and visit 2.

Relationship between abdominal circumference and spirometric measures

The relationship between AC and spirometric measures, and that between BMI and spirometric measures was investigated. No significant correlations between AC and unadjusted spirometric measures, and between BMI and unadjusted spirometric measures were detected (data not shown). In addition, there were no significant correlations between AC and adjusted spirometric measures for Brinkman index and status of Mets (Table (Table2A),2A), and nor was BMI correlated with adjusted spirometric measures (Table (Table2B).2B). The relationships between AC and changes in spirometric values were also evaluated. As shown in Figure Figure1,1, AC was inversely correlated with changes in FEV1 (% predicted) (r = -0.19, P = 0.024; Figure Figure1B),1B), but not with changes in FVC (% predicted) (Figure (Figure1A).1A). However, there were no correlations between BMI and the changes in FVC (% predicted) or FEV1 (% predicted) (Figures (Figures1C1C & 1D). In addition, the relationship between changes in spirometric values and change in BMI (ΔBMI = BMIvisit2 - BMIvisit1) were investigated, since weight gain may reduce spirometric values 23. Both ΔFVC (% predicted)/year and ΔFEV1 (% predicted)/year did not correlated with ΔBMI [ΔFVC (% predicted)/year: r = -0.06, P = 0.44; ΔFEV1 (% predicted)/year: r = -0.11, P = 0.16]. We set the cut-off value for decline in FEV1 (% predicted) as a reduction from baseline of ≥1.6%, because this was the lowest quintile of ΔFEV1 (% predicted)/year. Multiple logistic regression analysis revealed that AC significantly discriminated subjects who showed a decline in FEV1, independently of age, cigarette consumption (Brinkman index), and ΔBMI (Table (Table33).

Figure 1
Abdominal circumference was inversely correlated with decline in FEV1 in this study population. Graphs show the relationships between decline in spirometric parameters [A and C, ΔFVC (% predicted)/year; B and D, ΔFEV1 (% predicted)/year] ...
Table 2
Relationship of abdominal circumference and body mass index with spirometric measures at visit 2.
Table 3
Multivariate logistic regression analysis for discrimination of subjects showing a decline in FEV1.

Metabolic syndrome and decline in FEV1

A diagnosis of Mets could not be made for 10 of the 147 subjects due to the lack of necessary information (AC for 9; FBS level for 1). The differences in subject characteristics according to whether or not they had Mets are shown in Table Table4.4. Subjects with Mets were younger, and had a greater BMI, ΔBMI, AC, systolic BP, diastolic BP, and higher TG levels (Table (Table4).4). HDL-c levels were significantly lower in subjects with Mets than in those without Mets; however FBS levels and Brinkman index did not differ between subjects with or without Mets (Table (Table4).4). A decline in FEV1 (% predicted) was more prevalent among subjects with Mets compared to those without Mets (Table (Table5).5). In addition, the median decline in FEV1 (% predicted) was significantly greater in subjects with Mets than it was in those without Mets (Table (Table6).6). Spirometric measures at visit 2 did not differ significantly between subjects with or without Mets (Table (Table6).6). Even after adjustment of FEV1/FVC for age, there was no difference in FEV1/FVC between the two groups (P = 0.91).

Table 4
Differences in subject characteristics according to presence or absence of metabolic syndrome (Mets).
Table 5
Prevalence of decline in FEV1 (% predicted) according to the presence or absence of metabolic syndrome (Mets).
Table 6
Decline in FEV1 and spirometric measures at visit 2 according to the presence or absence of metabolic syndrome (Mets).


In this longitudinal study, spirometric values were measured twice in male smokers, who participated in an annual health check. At visit 2, AC was evaluated in these subjects, and a significant correlation between rate of decline in FEV1 and AC was retrospectively demonstrated. Furthermore, multivariate logistic regression analysis revealed that a decline in FEV1 was associated with AC, independently of age, cigarette consumption (Brinkman index) and ΔBMI. In addition, a decline in FEV1 was more prevalent among subjects with Mets, and the rate of decline in FEV1 in these subjects was significantly greater than that in subjects without Mets.

Mets is a common disease that is characterized by abdominal obesity, high blood pressure, hypertriglyceridemia, low HDL-c levels, and high fasting glucose levels 24. Data from the Third National Health and Nutrition Examination Survey indicates that this syndrome is present in almost a quarter of US residents aged 20 years or older 25. Although Mets is less prevalent in Asian compared with Western populations, a survey of the incidence of acute myocardial infarction suggested that the prevalence of Mets is also increasing in Japan, resulting in an increased incidence of myocardial infarction among men 26. Mets is associated with an increased risk of diabetes mellitus and cardiovascular disease, leading to increased cardiovascular and all-cause mortality 14. Recent studies have demonstrated that systemic inflammation, derived from visceral fat, is an important mechanism in the pathogenesis of Mets 13. Because both Mets and COPD are associated with the same comorbidities, including atherosclerosis and diabetes, and involve a state of chronic systemic inflammation, the pathogenesis of the two diseases is thought to share a common inflammatory pathway. A recent study showed that the prevalence of Mets is greater in subjects with COPD compared to those without COPD 11,27.

The mechanism underlying the rapid decline in pulmonary function in male smokers with a high AC has not been fully elucidated. One possible mechanism that might explain this phenomenon is endothelial dysfunction in subjects with Mets 28. Accumulating evidence suggests that endothelial dysfunction is one of the important features in the development of COPD 29. In particular, pulmonary endothelial cell apoptosis is thought to play an important role in the loss of pulmonary vasculature 30,31. Systemic inflammation may play a significant role in endothelial dysfunction in COPD patients 32. Mets is characterized by systemic low-grade inflammation, and endothelial dysfunction resulting from this systemic inflammation leads to functional impairment of organ systems 33,34. In addition, long term exposure to cigarette smoke induces systemic inflammation 35. Therefore, in active smokers with Mets, systemic inflammation may be enhanced because it is derived from two sources, namely visceral fat and exposure of the lungs to cigarette smoke. This may result in enhanced endothelial dysfunction and a rapid decline in pulmonary function.

Abdominal obesity may change the compliance of the diaphragm and chest wall. Chen and colleagues reported that a 1-cm increase in AC was associated with a 13-mL reduction in FVC and a 11-mL reduction in FEV1 23. In the present study, there was no difference in mean BMI between visit 1 and visit 2, although AC was not measured at visit 1. In addition, multivariate logistic regression analysis demonstrated that AC was a significant factor for discrimination of decline in FEV1, independently of ΔBMI (Table (Table3).3). It is unlikely that the decline in FEV1 observed in the present study is explained by weight gain during follow-up.

In the present study, the longitudinal decrease in FEV1 was significantly greater in subjects with Mets, and the prevalence of a decline in FEV1 was significantly greater in subjects with Mets than in those without Mets. However, FEV1/FVC did not differ significantly between subjects with or without Mets. Even after adjustment of FEV1/FVC for age, there was no difference in FEV1/FVC between the two groups. This finding was in keeping with those from previous studies, which demonstrated that FEV1/FVC was not reduced in subjects with Mets compared to those without Mets 36,37.

This study had several limitations. First, there may have been sampling bias. Takahata town has a resident population of 15,222 adults aged 40 years or older. For visit 1, data for a total of 3,257 enrolled subjects was entered into the final statistical analysis. Among the 1,502 male subjects, there were 523 active smokers. However, follow-up spirometry in 2009 was only performed for 147 subjects who had continued to smoke; the remaining subjects were lost to follow-up or quit smoking before visit 2. The number of subjects who were followed-up was not large, but the only significant difference between participants and non-participants in 2009 was age (see Method section). Thus, we thought the participants in 2009 were not largely different from non-participants. Differences between participants and non-participants in type of employment, socio-economic status or life style may have influenced the results. However, this information was not available in the present study. Second, pulmonary function testing at visit 2 in 2009 was only performed for male current smokers, not for male non-smokers, ex-smokers or females. This was only because we could not find a sufficient number of testers in 2009. Therefore we needed to focus on the data for the subjects who were assessed in the present study. Because of this limitation, the results from the present study may not be applicable to females or ex-smokers. Third, AC measurements were performed at visit 2, not visit 1. Therefore, the association between decline in FEV1 and AC was retrospectively demonstrated in this study. It should be noted that it could not be concluded that AC is predictive for decline in FEV1 among male smokers. However, despite these limitations we think this study is clinically significant as an initial investigation, and future prospective studies have the potential to confirm AC as a new and simple biomarker for discriminating subjects with a decline in FEV1 among active smokers.

In conclusion, AC was significantly associated with the rate of decline in FEV1 among male smokers in this study population. A decline in FEV1 was more prevalent among subjects with Mets, and the rate of decline in FEV1 was significantly greater in subjects with Mets compared to those without Mets. This retrospective analysis suggested that measurement of AC may be a simple and useful method of discriminating subjects with a decline in FEV1 among male smokers.


We thank Taiko Aita, Emiko Nakamura, and Eiji Tsuchida for their excellent technical assistance. We also thank the additional contributors: Michiko Nishiwaki (Yamagata City Hospital, Saiseikan), Toshihiro Wada (Yamagata City Hospital, Saiseikan), Jun-Ichi Machiya (Nihonkai General Hospital), Noriyuki Hirama (NHO Yamagata National Hospital), Noriaki Takabatake (Tohoku Central Hospital), Makoto Sata (National Cerebral and Cardiovascular Center, Japan).


This study was supported by a grant-in-aid from the Global COE Program of the Japan Society for the Promotion of Science, and grants-in-aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan (19590880, 20590892, and 23390220).

Ethics approval

This study was approved by the institutional ethics committee and all participants gave written informed consent.


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