Reduced lung function and risk of atrial fibrillation in The Copenhagen City Heart Study

Study population

This study was based on data from the Copenhagen City Heart Study (CCHS). The original cohort of CCHS comprised a random age-stratified sample of 19,329 males and females aged ≥20 yrs from an area of Copenhagen, Denmark. A total of 14,223 persons participated in the first examination between 1976–1978. Re-examination took place after 5 yrs (1981–1983). The overall response rates were of 74% and 70%, respectively. At each examination, cardiovascular and respiratory risk factors were obtained by a detailed self-administered questionnaire and several laboratory tests. Details of the examination procedure have been described previously 9. Since the aim of this study was to investigate lung function asa predictor of AF, only baseline data from the first examination were used. Subjects with pre-existing AF (n=87) were excluded from further analyses. To diminish contribution of pre-existing IHD, an additional 386 subjects with prior myocardial infarction (MI) were excluded. Among the remaining participants, 25 subjects with extreme values of forced expiratory volume in one second (FEV₁) % predicted lower than 10% or higher than 140%, and subjects with missing FEV₁ % pred or electrocardiograms (ECGs; n=295) were excluded. Thus, a total of 13,430 subjects (6,084 males and 7,346 females) were included at baseline.

At 5-yr follow-up, 10,670 subjects (79%) were re-examined and were eligible for analyses of new AF detected at examination. Cox regression analyses of hospitalisations with AF were restricted to 13,181 subjects because of lack of one or more covariates at baseline (n=249). Between the first and second examination, 756 subjects died. Of those who were eligible for hospitalisation analyses a total of 2,956 subjects had died at the end of follow-up (December 31, 1990). Compared with responders at re-examination, nonresponders had lower FEV₁ % pred, higher systolic blood pressure, higher nonfasting blood sugar, more frequent diabetes and were more often current smokers, all measured at baseline. There was no difference in age and body mass index (BMI). Thus, nonresponders in general had a poorer cardiopulmonary risk profile than responders.

New cases of atrial fibrillation

Two outcomes of occurrence of AF were used: 1) presence of AF after 5-yr follow-up at re-examination; and 2) hospital admission with a diagnosis of AF until December 31, 1990. A 12-lead resting ECG was recorded using a Mingograf 34 (Elema-Siemens, Solna, Sweden) at both health examinations. All ECGs were coded independently by two laboratory technicians according to the Minnesota coding system and in case of disagreement a third coder settled the disagreement 10. No distinction was made between AF and atrial flutter. A random sample of 10% of the population >65 yrs of age was selected and ECGs were reviewed by a physician who also made reviews of all ECGs originally coded as AF. The random sample revealed two subjects (1.0%) at baseline who were misclassified as not having AF. No misclassifications were found at 5-yr follow-up. At review, all ECGs originally coded as AF were found to be consistent at baseline, whereas three subjects (2.7%) at 5-yr follow-up did not have AF.

Hospital discharge diagnoses were obtained from the National Hospital Discharge Register and International Classification of Diseases (ICD) codes for new AF or atrial flutter in any coding position were identified (ICD-8 codes 427.93 or 427.94). As AF in subjects with, for example, COPD or IHD leading to hospital admission is more likely to be diagnosed than in subjects with lone AF, this might cause bias 11. Separate analyses using only hospital admission with AF as the main diagnosis (first code) were therefore performed. Furthermore, the primary cause (main diagnosis) for hospital admission for those subjects who had AF diagnosed in the second or higher coding position, according to the National Hospital Discharge Register, was obtained. All analyses were based on the first ever hospitalisation with AF for participants without AF or IHD at baseline. Follow-up was limited to 13 yrs (December 31, 1990), since it was assumed that exposure measured at baseline would be too imprecise compared with the end-point if a longer follow-up period was chosen.

Pulmonary function tests

FEV₁ and forced vital capacity (FVC) were measured at baseline using an electronic spirometer (Monaghan N 403; Monaghan, Littleton, CO, USA), which had measurement accuracy within 5% of volume. The spirometer was calibrated daily with a 1-L syringe and weekly against a water-sealed Godard spirometer (Sensormedics, Bilthoven, the Netherlands). Specially trained technicians performed all measurements. Three forced expiratory manoeuvres were obtained and, as a criterion for correct performance of the procedure, at least two measurements differing <5% had to be produced. The highest value of FEV₁ and FVC were used in the analyses. FEV₁ % pred was calculated separately for males and females using coefficients obtained from linear regressions, based on a subgroup of healthy never-smokers 12. Thefollowing formulae for males (Equation 1) and females (Equation 2) were used: FEV₁ % pred was categorised into three subgroups: <60%, 60–80% and ≥80%.

Confounders

Among the available data on the CCHS participants, only confounders that were shown to be independent risk factors of AF in earlier studies were chosen 13–17. Thus, corrections were made for hypertension, IHD, BMI, diabetes, age and sex. Valvular heart disease and congestive heart failure havealso been shown to be strong predictors of AF, but no information was available. As a surrogate parameter for congestive heart failure, treatment with diuretics was used. Tobacco smoking and levels of education have not been shown to be predictors but were included since they could influence FEV₁. Arterial blood pressure was measured in a sedentary position after 5-min rest. Systolic blood pressure was divided into three categories: <140, 140–159 and ≥160 mmHg. Previous MI was defined as self-reported MI, verified by hospital records or a personal general practitioner, or as pathological Q-waves detected on ECGs at baseline. Possible angina was defined as self-reported chest pain at activity. BMI was calculated as weight (kg) divided by height squared (m²) and divided into three categories: <25, 25–29 and ≥30 kg·m⁻². Diabetes was considered present if nonfasting blood glucose was ≥11.1 mM (200 mg·dL⁻¹) or the subjects answered “yes” to the question: “Do you have diabetes?” Tobacco smoking was studied in five categories: never-smokers, exsmokers and current smokers of 1–10, 11–24 and ≥25 g tobacco per day. Type of tobacco (cigarette, cheroot, cigar, pipe or mixed) was recorded for current smokers, and tobacco consumption was calculated by equating a cigarette to 1 g, a cheroot to 3 g, and a cigar to 5 g of tobacco. Level ofeducation was divided into three groups: <9, 9–11 and ≥12 yrs of school.

Statistics

One-way variance analysis was used to compare continuous variables between groups. The Chi-squared test was used for categorical variables. Logistic regression was used to identify independent predictors of new AF at re-examination. First, each variable of interest was tested, adjusting only for age (by 10-yr age groups) and sex. The final model was tested for interaction between sex and each covariate.

Association between risk factors and AF detected by hospital discharge diagnosis was analysed using Cox proportional hazards regression models 18 with the first hospitalisation for AF as end-point. Age and delayed entry were used as the underlying time axes with subjects entering analyses at their age of study inclusion. Subjects who experienced an event (AF) only contributed with observation time until the time of this event. Those who died before the end of follow-up contributed with observation time until the time of their death at which time they were censored. Relative risk (RR) for FEV₁ % pred did not differ between males and females and the final analyses were performed on the whole sample stratified by sex. The limit of significance was 5% for all analysis.

Baseline characteristics

Table 1⇓ shows the correlation between level of lung function and selected characteristics of the population at baseline. In general, there was an inverse relationship between FEV₁ % pred and biological, socioeconomical and cardiopulmonary risk factors. Thus, participants with lower levels of lung function were older, had higher systolic and diastolic blood pressure, higher mean blood glucose, higher BMI, lower mean FEV₁/FVC and more frequent chest pain or diabetes. They also more often had <9 yrs of education and were current smokers. There was no difference in BMI or tobacco consumption between the lowest group of FEV₁ and the middle group. When analyses were performed separately for males and females (data not shown), similar trends were seen.

Risk of incident atrial fibrillation at 5-yr follow-up examination

At the re-examination, 62 new cases of AF were registered. Table 2⇓ shows the distribution of cases of AF at baseline, re-examination and at hospital admission. With lower levels of lung function, the prevalence of AF increased. This wasseen both for AF at re-examination and for hospital admissions of AF.

There was an inverse relationship between FEV₁ and risk of AF after 5 yrs in the model, adjusting for age and sex only (table 3⇓). After full adjustment for all confounders the inverse association between FEV₁ and AF was attenuated but remained significant. This association was only seen for FEV₁ between 60–80% of predicted and reduction of FEV₁ below 60% was not associated with AF in any of the models. Only age, sex, systolic blood pressure, diabetes and BMI were significantly associated with AF after multivariate adjustment.

In subanalyses, degrees of obstruction (FEV₁/FVC) and risk of AF were investigated but no association was found in the age- and sex-adjusted model, and therefore this parameter was not included in the following analyses.

Risk of incident atrial fibrillation at hospitalisations

Hospital admissions recorded a total of 290 subjects with new AF. In 93 (32.1%) cases, AF was mentioned as the main cause of hospital admission. In the remaining 187 cases, the most common main diagnoses were IHD (20.6%), followed byMI (14.3%), pneumonia (9.1%), congestive heart failure (5.7%), stroke (3.4%) and COPD/asthma (2.9%).

Figure 1⇓ outlines the RRs of all hospitalisations with new AF for each 10% decline in FEV₁ % pred, adjusted for ageand sex. A trend towards a dose/response relationship between AF and reduced lung function was observed. The RRs were only slightly affected by adjustment for all selected confounders (table 4⇓). The association remained similar, independent of whether AF was recorded as the main or as a contributory cause of admission.

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Fig. 1.—

Forced expiratory volume in one second % predicted (FEV₁ % pred) and relative risk (RR) of hospital admission for new atrial fibrillation. Based on Cox regression model stratified by sex and age. Bars indicate the 95% confidence intervals. —: regression line.