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Leukocyte count is an independent predictor for risk of acute myocardial infarction in middle-aged Japanese men
Atherosclerosis 195 (2007) 147–152
Leukocyte count is an independent predictor for risk of acute myocardial infarction in middle-aged Japanese men Hironori Imano a,∗ , Shinichi Sato a , Akihiko Kitamura a , Masahiko Kiyama a , Tetsuya Ohira a,c , Takashi Shimamoto a , Hiroyasu Iso b a
c
Osaka Medical Center for Health Science and Promotion, 1-3-2 Nakamichi, Higashinari-ku, Osaka-shi, Osaka 537-0025, Japan b Public Health, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita-shi, Osaka 565-0871, Japan Division of Epidemiology and Community Health, University of Minnesota, Suite 300, 1300 S 2nd Street, Minneapolis, MN 55454-1015, USA Received 8 February 2006; received in revised form 25 August 2006; accepted 2 September 2006 Available online 2 October 2006
Abstract Background: Leukocyte count is recognized as an inflammatory marker and a predictor of cardiovascular events. However, it is uncertain whether the contribution of leukocyte count to the risk of cardiovascular disease is independent of smoking. Methods: The subjects were 4492 male employees aged 40–59 years who worked for nine companies in Osaka. Results: After 9-year follow-up, 40 acute myocardial infarction and 26 ischemic stroke events occurred. Age-adjusted relative risk of acute myocardial infarction in the highest versus lowest quartiles of leukocyte count was 6.0 (95% CI, 1.8–20.5, P for trend <0.001) and the multivariable relative risk adjusted for smoking and other conventional cardiovascular risk factors was 3.7 (1.0–13.4, P for trend = 0.01). The association between leukocyte count and the risk of acute myocardial infarction was also observed among both current smokers and nonsmokers. The positive association between leukocyte count and the risk of ischemic stroke was weak and did not reach statistical significance. Conclusions: Leukocyte count is a predictor of acute myocardial infarction among Japanese middle-aged men, both in smokers and nonsmokers. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Leukocyte count; Acute myocardial infarction; Stroke; Smoking; Prospective studies; Incidence; Men
1. Introduction Leukocyte count is recognized as a marker of inflammation and a predictor of cardiovascular disease. Previous population-based prospective studies showed that leukocyte count was associated with the risk of coronary heart disease [1–3] and stroke [2–5]. Smoking is a major risk factor for cardiovascular disease and raises leukocyte count [6], but few studies have examined the association between leukocyte count and the risk of cardiovascular disease for smokers and nonsmokers separately. Some studies showed high leukocyte count as a predictor for coronary heart disease only for nonsmokers [2,7–9] while the ARIC Study found high leuko∗
Corresponding author. Tel.: +81 6 6973 3535; fax: +81 6 6973 3574. E-mail address: [email protected] (H. Imano).
0021-9150/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2006.09.002
cyte count as a predictor for ischemic stroke only for current smokers [2]. Therefore, it is not clear whether high leukocyte count is a predictor for cardiovascular disease independent of smoking. The aim of the present study was to examine the contribution of leukocyte count as a risk factor for acute myocardial infarction and ischemic stroke independent of smoking among middle-aged Japanese men.
2. Methods 2.1. Study participants The participants included 4492 male employees aged 40–59 years who underwent medical checkups in the Department of Epidemiology and Mass Examination, Osaka
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H. Imano et al. / Atherosclerosis 195 (2007) 147–152
Medical Center for Cancer and Cardiovascular Diseases (presently the Osaka Medical Center for Health Science and Promotion) between 1975 and 1986. The participants worked for nine companies in Osaka, one of the largest metropolitan cities in which Westernized lifestyle is more common. Our previous studies showed in male employees of companies in Osaka, the incidence of coronary heart disease was inversely related to high-density lipoprotein cholesterol [10] and that the incidence of coronary heart disease increased and that of stroke declined [11]. The companies in this study consisted of a broadcasting company, a bank, a textile-processing company, two trading companies, and four manufacturers (chains, chemicals, aluminum cans and pans, and air conditioners). The study was approved by the Ethics Committee in the Osaka Medical Center for Health Science and Promotion. 2.2. Data collection We interviewed subjects at baseline surveys for medical history, smoking and ethanol intake habits, and medication use for hypertension and diabetes. Men who reported smoking at least one cigarette per day were defined as current smokers, and men who reported consuming ethanol of ≥7 g per week were regarded as current drinkers. Both exsmokers and ex-drinkers were defined as abstainers for at least 3 months. Height in stocking feet and weight in light clothing were measured. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. Systolic and fifth-phase diastolic blood pressures in the right arm were measured by trained technicians using standard mercury sphygmomanometers in seated participants who had rested for 5 min. Hypertension was defined as a systolic blood pressure (SBP) ≥140 mmHg, diastolic blood pressure (DBP) ≥90 mmHg, and/or the use of an antihypertensive medication. The blood sample for leukocyte count was collected in a tube containing EDTA-2K, and leukocyte count was measured using Coulter counters. Serum glucose was measured by the cupric-neocuproine method between 1975 and September 1986 and by the hexokinase method thereafter. Glucose values (mmol/L) obtained using the first method were adjusted using the formula: 0.047 × (glucose concentration in mg/dL) − 0.541, as we reported previously [12]. Glucose values were subsequently divided into three categories (normal, borderline diabetes, and diabetes). Borderline diabetes was defined as a fasting glucose level of 6.1–6.9 mmol/L or a non-fasting glucose level of 7.8–11.0 mmol/L without the use of medication for diabetes. Diabetes was defined as a fasting glucose level of ≥7.0 mmol/L, a non-fasting glucose level of ≥11.1 mmol/L, or the use of medication for diabetes. Serum total cholesterol was measured by the LiebermannBurchard direct method using Autoanalyzer II (Technicon, Tarrytown, NY) at the laboratory of the Department of Epidemiology and Mass Examination, Osaka Medical Center for Cancer and Cardiovascular Diseases, an international member of the US National Cholesterol Reference Method
Laboratory Network (CRMLN). This laboratory has been standardized since 1975 by the CDC-NHLBI Lipid Standardized Program provided by the Centers for Disease Control and Prevention (Atlanta, GA) and successfully met the criteria for both precision and accuracy of cholesterol measurements [13]. 2.3. Follow-up and ascertainment of cases The participants were followed-up to determine the first incident of coronary heart disease or stroke, the retirement date, or the date of last medical checkups by the end of 2000. Annual follow-up surveys were undertaken to obtain histories of incident coronary heart disease and stroke. The other methods of case ascertainment were inquiry of death certificate diagnosis, absentee reports due to sickness, and insurance claims [14]. To confirm the diagnosis, study physicians obtained medical histories and resting electrocardiograms (ECGs) for all living patients. If the subject had died, the medical history was obtained from the family, relative, or colleagues. Medical record at company clinics and local hospitals were also reviewed. The criteria for coronary heart disease were modified from those of the World Health Organization Expert Committee [15]. Definite acute myocardial infarction was diagnosed by typical severe chest pain (lasting at least 30 min and with no definite non-ischemic cause) accompanied by new abnormal and persistent Q or QS waves, consistent change in cardiac enzyme levels, or both. If the ECG and enzyme levels were not available, but the patient had typical chest pain, a diagnosis of probable acute myocardial infarction was made. Stroke was defined as a focal neurological disorder with rapid onset, persisting for at least 24 h or until death. Using the clinical criteria, incident strokes were identified by a panel of three to four study physicians who were blinded to the data from the risk factor survey. Stroke events were classified as ischemic strokes (thrombotic or embolic) and others (intraparenchymal hemorrhages, subarachnoid hemorrhages, or strokes of undetermined type), primarily based on computerized tomography (CT) and/or magnetic resonance imaging (MRI) [16]. The CT and/or MRI were available for 85% of ischemic strokes. 2.4. Statistical analysis Analysis of covariance was used to test differences in ageadjusted means and proportions of baseline characteristics among quartiles of leukocyte count. Person-years of followup for each participant was calculated from enrollment to the date of cardiovascular disease event or dates of job quitting or retirement. The average follow-up period for the cohort was 9.3 years. Relative risks and 95% confidence intervals (CI) for acute myocardial infarction and ischemic stroke were calculated according to Cox proportional hazards regression models. The initial model was adjusted only for age. The multivariable adjustment included baseline hypertension (slight: SBP 140–159 mmHg and/or DBP 90–99 mmHg,
H. Imano et al. / Atherosclerosis 195 (2007) 147–152
moderate to severe: SBP ≥ 160 mmHg or DBP ≥ 100 mmHg and/or the use of an antihypertensive medication), hyperglycemia (borderline diabetes, diabetes), serum cholesterol levels (mmol/L), smoking status (ex-smokers, current smokers of cigarettes <20 per day, and ≥20 per day), BMI (category <18.5, 18.5–24.9, and ≥25.0 kg/m2 ), usual ethanol intake (never drinker, ex-drinker, current drinker of ethanol <69 g/day, and ≥69 g/day). Trends across leukocyte count quartiles were assessed by using a variable that equaled the median of the leukocyte count within the pertinent quartile, and the corresponding Pvalues were reported. The analyses using Cox proportional hazard models were repeated, stratified by smoking status. The test for interaction with smoking status was made using a cross-product term of smoking status (current versus nonsmokers) × continuous variable of leukocyte count. All statistical analyses were performed using the SAS System for Windows (Version 9.1; SAS Inc., Cary, NC). All P-values for statistical tests were two tailed, and values of <0.05 were regarded as statistically significant.
3. Results Table 1 shows the baseline characteristics according to quartiles of leukocyte count. There was a striking increase in the proportion of current smokers across quartiles of leukocyte count with smokers in the fourth quartile about two-fold higher than smokers in the first quartile. BMI and serum cholesterol levels were also positively associated with leukocyte count. Table 2 shows relative risks of acute myocardial infarction and ischemic stroke according to quartiles of leukocyte count. We documented 40 events of acute myocardial infarction and 26 events of ischemic stroke. There was a strong dose–response relationship between leukocyte count and age-adjusted risk of acute myocardial infarction. After
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adjustment for other cardiovascular risk factors including smoking, the association was somewhat weakened but remained statistically significant. There was a positive trend between leukocyte count and age-adjusted risk of ischemic stroke, albeit there were only a small numbers of cases. The relative risks were reduced substantially in the multivariable model. The reduction in the relative risks was primarily observed when adjusting for smoking status; the relative risk of ischemic stroke for the highest versus lowest quartiles of leukocyte count was 1.5 (0.4–5.8) and that for 1 S.D. change of leukocyte count was 1.0 (0.7–1.5) (not shown in the table). Table 3 shows relative risks of acute myocardial infarction, stratified by smoking status. The association between leukocyte count and the risk of acute myocardial infarction was similarly observed among both current smokers and nonsmokers (P for interaction = 0.96).
4. Discussion The present prospective cohort study showed that leukocyte count was a significant predictor for acute myocardial infarction among middle-aged Japanese male employees after adjustment for other cardiovascular risk factors, including smoking and after stratification of smoking status. A previous meta-analysis [1] of 19 population-based prospective studies indicated that the relative risk of coronary heart disease for highest versus lowest tertiles of leukocyte count was 1.4 (95% CI, 1.3–1.5). In the ARIC Study [2], the relative risk of coronary heart disease in the highest versus lowest quartiles of leukocyte count was 1.9 (95% CI, 1.2–3.1) among African Americans and 1.7 (95% CI, 1.1–2.5) among Whites. In the Women’s Health Initiative Observational Study [3], the relative risk of nonfatal myocardial infarction was 1.4 (95% CI, 1.1–1.8). A previous Japanese study [17] showed a significant age-adjusted relative risk of coro-
Table 1 Baseline characteristics of Japanese male employees, aged 40–59 years free of coronary heart disease or stroke at baseline, according to quartiles of leukocyte count Quartiles of leukocyte count (×102 cells/mm3 )
P-value
Q1
Q2
Q3
Q4
Range of leukocyte count Median leukocyte count
25–49 44
50–59 55
60–70 64
71–178 81
No. of subjects Age (years) Body mass index (kg/m2 ) Current smoker (%) Usual ethanol intake (g/day) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Hypertension (%) Serum cholesterol (mmol/L) Impaired glucose tolerance (%) Diabetes (%)
1080 45.8 (0.2) 22.2 (0.1) 43 (1.4) 30.0 (0.7) 124 (0.5) 82 (0.4) 25 (1.4) 4.95 (0.03) 5 (0.7) 0.9 (0.4)
1213 46.2 (0.2) 22.6 (0.1) 57 (1.3) 29.7 (0.7) 125 (0.5) 83 (0.3) 29 (1.3) 5.09 (0.02) 4 (0.6) 1.6 (0.4)
1090 46.5 (0.2) 22.8 (0.1) 68 (1.4) 30.1 (0.8) 125 (0.5) 82 (0.4) 28 (1.3) 5.14 (0.03) 6 (0.7) 1.4 (0.4)
1109 46.4 (0.2) 22.9 (0.1) 85 (1.4) 31.6 (0.8) 126 (0.5) 82 (0.4) 28 (1.3) 5.17 (0.03) 5 (0.6) 2.3 (0.4)
Data are age-adjusted mean or percentage values. Numbers in parentheses indicate standard errors.
0.006 <0.0001 <0.0001 0.27 0.05 0.14 0.14 <0.0001 0.53 0.05
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Table 2 Age-adjusted and multivariable relative risk (RR) of acute myocardial infarction and ischemic stroke according to quartiles of leukocyte count Leukocyte count quartile
Person-years
No. of events
Age-adjusted incidence per 1000 person-year
Age-adjusted RR (95% CI)
Multivariable RR (95% CI)
Acute myocardial infarction Q1 Q2 Q3 Q4
10,376 11,917 10,251 10,143
3 7 12 18
0.3 0.6 1.2 1.8
1.0 (Referent) 2.1 (0.5–8.1) 4.0 (1.1–14) 6.0 (1.8–21)
1.0 (Referent) 1.5 (0.4–5.9) 2.6 (0.7–9.6) 3.7 (1.0–13)
<0.001
0.01
P for trend 1 S.D. change
41,967
40
1.0
1.7 (1.4–2.1)
1.6 (1.2–2.0)
Ischemic stroke Q1 Q2 Q3 Q4
10,376 11,917 10,251 10,143
3 7 8 8
0.3 0.6 0.8 0.8
1.0 (Referent) 2.1 (0.5–8.0) 2.5 (0.7–9.6) 2.6 (0.7–9.9)
1.0 (Referent) 1.4 (0.4–5.6) 1.6 (0.4–6.0) 1.2 (0.3–4.7)
0.18
0.97
1.2 (0.8–1.7)
0.9 (0.6–1.4)
P for trend 1 S.D. change
41,967
26
0.6
1730 cells/mm3
RRs of 1 S.D. change were assessed per increment of leukocyte count. Multivariable adjustment for age, body mass index, smoking status, ethanol intake, blood pressure category, serum cholesterol level, blood glucose category.
with the findings from two previous studies [4,5]. In those studies, the elevated leukocyte count was positively associated with the age-adjusted risk of ischemic stroke, but the association was no longer statistically significant after adjustment for smoking status. However, the ARIC Study [2] and the Women’s Health Initiative Observational Study [3] found a significant association between leukocyte count and the risk of ischemic or total stroke even after adjustment for smoking. The multivariable relative risk of stroke in the highest versus lowest quartiles of leukocyte count was 2.0 (95% CI, 1.3–3.0) for the ARIC Study and 1.5 (1.2–1.8) for the Women’s Health Initiative Observational Study. What are the underlying mechanisms of the association between leukocytosis and the risk of acute myocardial infarction? First, leukocytosis is a marker of inflammation in the process of atherosclerosis [19]. Second, a high leukocyte count promotes atherosclerosis via their migration into the arterial vessel wall or through the release of chemical factors from proliferating endothelial cells [20,21]. Leukocytes may stimulate platelets and promote thrombus formation [22].
nary heart disease associated with leukocyte count, but after adjustment for smoking status, the association was no longer statistically significant. In the present study, the association between leukocyte count and the risk of acute myocardial infarction was observed among both smokers and nonsmokers. In previous population-based cohort studies stratified by smoking status, i.e. the Framingham Study [7], the British Regional Heart Study [8], the Zutphen Study [9], and the ARIC Study [2], the significant association was observed only for nonsmokers, while among dyslipidemic men of the Helsinki Heart Study [18], the significant association was observed only for smokers. To our knowledge, this is the first population-based cohort study to show positive associations between leukocyte count and the risk of coronary heart disease for both in smokers and nonsmokers, with no significant statistical interaction. The positive association between leukocyte count and the risk of ischemic stroke was weak and did not reach statistical significance in the present study. This result was consistent
Table 3 Age-adjusted and multivariable relative risk of acute myocardial infarction according to quartiles of leukocyte stratified by smoking status Leukocyte count category
Person-years
No. of events
Age-adjusted incidence per 1000 person-year
Age-adjusted RR (95% CI)
Multivariable RR (95% CI)
Current smokers Q1 and Q2 Q3 and Q4
10,453 15,531
6 24
0.6 1.6
1.0 (Referent) 2.7 (1.1–6.6)
1.0 (Referent) 2.6 (1.0–6.9)
1 S.D. change
25,985
30
1.2
1.6 (1.3–2.1)
1.6 (1.2–2.0)
10,982 4,808
4 6
0.4 1.3
1.0 (Referent) 3.4 (0.9–12)
1.0 (Referent) 3.5 (1.0–12)
15,791
10
0.7
1.8 (0.9–3.7)
1.7 (0.8–3.6)
Nonsmokers Q1 and Q2 Q3 and Q4 1 S.D. change
1730 cells/mm3
RRs of 1 S.D. change were assessed per increment of leukocyte count. Multivariable adjustment for age, body mass index, ethanol intake, blood pressure category, serum cholesterol level, blood glucose category.
H. Imano et al. / Atherosclerosis 195 (2007) 147–152
Third, leukocytosis could be an intermediate factor for smoking. However, this possibility is less likely because we found a similar association between leukocyte count and the risk of acute myocardial infarction among nonsmokers as did among smokers. It is uncertain what subtypes of leukocyte were associated with the risk of acute myocardial infarction because we did not have the data on the leukocyte subtypes in the present study. However, in our later cohort at baseline between 1990 and 1996, we found mononuclear leukocytes but not neutrophils or lymphocytes were associated with the risk of ischemic cardiovascular disease [coronary heart diseases (n = 15) plus ischemic stroke (n = 9)]; the multivariable relative risk in 1 S.D. change of mononuclear leukocyte count was 1.8 (1.1–2.9). Our result is in agreement with the pathological finding that the monocytes, the precursor of macrophages, are present in every phase of atherogenesis [23]. However, a recent prospective study showed that the neutrophil count was more strongly associated with the risk for incident or mortality of myocardial infarction compared with the monocyte count among patients undergoing coronary arteriography [24]. Neutrophil count may be a marker of systematic inflammation and be a predictor for the incident and mortality of coronary heart disease among patients with advanced atherosclerosis. The limitations of the present study warrant discussion. First, we did not measure other inflammation markers, such as C-reactive protein and fibrinogen, which are recognized predictors of cardiovascular disease [1]. The Women’s Health Initiative Observational Study [3] showed that the leukocyte count was an independent predictor for coronary heart disease risk in the multivariable models adjusting for C-reactive protein, and the magnitude of contribution of these inflammation markers was similar to that of leukocyte count [1,3,25]. In the present study, serum albumin, another inflammation marker [1], was measured in 48% (2146/4492) of the participants, but it was not associated with the risk of acute myocardial infarction or ischemic stroke; the multivariable relative risk with 1 S.D. decrease of serum albumin (0.3 mg/dL) was 1.2 (95% CI, 0.8–1.8) for acute myocardial infarction and 0.8 (0.5–1.3) for ischemic stroke. Second, the variability of measurement of leukocyte count may weaken the association with the risk of cardiovascular disease. However, the Spearman’s correlation coefficient for leukocyte count measured at baseline and at 1-year later (69% followed) was high (r = 0.73, P < 0.001). Third, we did not identify cardiovascular disease events after retirement. However, there were no apparent differences in age-specific or age-adjusted mean values of baseline coronary risk factors, including leukocyte count, between men who left employment and men who did not. Thus, the withdrawal of these men is unlikely to affect the results substantially. In summary, we found that leukocyte count was positively associated with the risk of acute myocardial infarction among Japanese middle-aged men, both in smokers and nonsmokers. Leukocytosis may increase the risk of acute myocardial
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infarction by enhancing atherosclerosis and thrombus formation through arterial wall inflammation, or it may reflect systemic inflammation that increases such risk.
Acknowledgements The authors thank Prof. Minoru Iida (Kansai University of Welfare Sciences), Prof. Yoshihiko Naito (Mukogawa Women’s University), Dr. Tomonori Okamura (Shiga University of Medical Science), and Dr. Yuko Nakagawa (Neyagawa Public Health Center) for their valuable comments. We also thank the clinical laboratory technologists, public health nurses, engineers of the computer processing unit, nurses, and nutritionists in the Department of Epidemiology and Mass Examination, Osaka Medical Center for Cancer and Cardiovascular Diseases for their expert help.
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Leukocyte count is an independent predictor for risk of acute myocardial infarction in middle-aged Japanese men Hironori Imano a,∗ , Shinichi Sato a , Akihiko Kitamura a , Masahiko Kiyama a , Tetsuya Ohira a,c , Takashi Shimamoto a , Hiroyasu Iso b a
c
Osaka Medical Center for Health Science and Promotion, 1-3-2 Nakamichi, Higashinari-ku, Osaka-shi, Osaka 537-0025, Japan b Public Health, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita-shi, Osaka 565-0871, Japan Division of Epidemiology and Community Health, University of Minnesota, Suite 300, 1300 S 2nd Street, Minneapolis, MN 55454-1015, USA Received 8 February 2006; received in revised form 25 August 2006; accepted 2 September 2006 Available online 2 October 2006
Abstract Background: Leukocyte count is recognized as an inflammatory marker and a predictor of cardiovascular events. However, it is uncertain whether the contribution of leukocyte count to the risk of cardiovascular disease is independent of smoking. Methods: The subjects were 4492 male employees aged 40–59 years who worked for nine companies in Osaka. Results: After 9-year follow-up, 40 acute myocardial infarction and 26 ischemic stroke events occurred. Age-adjusted relative risk of acute myocardial infarction in the highest versus lowest quartiles of leukocyte count was 6.0 (95% CI, 1.8–20.5, P for trend <0.001) and the multivariable relative risk adjusted for smoking and other conventional cardiovascular risk factors was 3.7 (1.0–13.4, P for trend = 0.01). The association between leukocyte count and the risk of acute myocardial infarction was also observed among both current smokers and nonsmokers. The positive association between leukocyte count and the risk of ischemic stroke was weak and did not reach statistical significance. Conclusions: Leukocyte count is a predictor of acute myocardial infarction among Japanese middle-aged men, both in smokers and nonsmokers. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Leukocyte count; Acute myocardial infarction; Stroke; Smoking; Prospective studies; Incidence; Men
1. Introduction Leukocyte count is recognized as a marker of inflammation and a predictor of cardiovascular disease. Previous population-based prospective studies showed that leukocyte count was associated with the risk of coronary heart disease [1–3] and stroke [2–5]. Smoking is a major risk factor for cardiovascular disease and raises leukocyte count [6], but few studies have examined the association between leukocyte count and the risk of cardiovascular disease for smokers and nonsmokers separately. Some studies showed high leukocyte count as a predictor for coronary heart disease only for nonsmokers [2,7–9] while the ARIC Study found high leuko∗
Corresponding author. Tel.: +81 6 6973 3535; fax: +81 6 6973 3574. E-mail address: [email protected] (H. Imano).
0021-9150/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2006.09.002
cyte count as a predictor for ischemic stroke only for current smokers [2]. Therefore, it is not clear whether high leukocyte count is a predictor for cardiovascular disease independent of smoking. The aim of the present study was to examine the contribution of leukocyte count as a risk factor for acute myocardial infarction and ischemic stroke independent of smoking among middle-aged Japanese men.
2. Methods 2.1. Study participants The participants included 4492 male employees aged 40–59 years who underwent medical checkups in the Department of Epidemiology and Mass Examination, Osaka
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Medical Center for Cancer and Cardiovascular Diseases (presently the Osaka Medical Center for Health Science and Promotion) between 1975 and 1986. The participants worked for nine companies in Osaka, one of the largest metropolitan cities in which Westernized lifestyle is more common. Our previous studies showed in male employees of companies in Osaka, the incidence of coronary heart disease was inversely related to high-density lipoprotein cholesterol [10] and that the incidence of coronary heart disease increased and that of stroke declined [11]. The companies in this study consisted of a broadcasting company, a bank, a textile-processing company, two trading companies, and four manufacturers (chains, chemicals, aluminum cans and pans, and air conditioners). The study was approved by the Ethics Committee in the Osaka Medical Center for Health Science and Promotion. 2.2. Data collection We interviewed subjects at baseline surveys for medical history, smoking and ethanol intake habits, and medication use for hypertension and diabetes. Men who reported smoking at least one cigarette per day were defined as current smokers, and men who reported consuming ethanol of ≥7 g per week were regarded as current drinkers. Both exsmokers and ex-drinkers were defined as abstainers for at least 3 months. Height in stocking feet and weight in light clothing were measured. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. Systolic and fifth-phase diastolic blood pressures in the right arm were measured by trained technicians using standard mercury sphygmomanometers in seated participants who had rested for 5 min. Hypertension was defined as a systolic blood pressure (SBP) ≥140 mmHg, diastolic blood pressure (DBP) ≥90 mmHg, and/or the use of an antihypertensive medication. The blood sample for leukocyte count was collected in a tube containing EDTA-2K, and leukocyte count was measured using Coulter counters. Serum glucose was measured by the cupric-neocuproine method between 1975 and September 1986 and by the hexokinase method thereafter. Glucose values (mmol/L) obtained using the first method were adjusted using the formula: 0.047 × (glucose concentration in mg/dL) − 0.541, as we reported previously [12]. Glucose values were subsequently divided into three categories (normal, borderline diabetes, and diabetes). Borderline diabetes was defined as a fasting glucose level of 6.1–6.9 mmol/L or a non-fasting glucose level of 7.8–11.0 mmol/L without the use of medication for diabetes. Diabetes was defined as a fasting glucose level of ≥7.0 mmol/L, a non-fasting glucose level of ≥11.1 mmol/L, or the use of medication for diabetes. Serum total cholesterol was measured by the LiebermannBurchard direct method using Autoanalyzer II (Technicon, Tarrytown, NY) at the laboratory of the Department of Epidemiology and Mass Examination, Osaka Medical Center for Cancer and Cardiovascular Diseases, an international member of the US National Cholesterol Reference Method
Laboratory Network (CRMLN). This laboratory has been standardized since 1975 by the CDC-NHLBI Lipid Standardized Program provided by the Centers for Disease Control and Prevention (Atlanta, GA) and successfully met the criteria for both precision and accuracy of cholesterol measurements [13]. 2.3. Follow-up and ascertainment of cases The participants were followed-up to determine the first incident of coronary heart disease or stroke, the retirement date, or the date of last medical checkups by the end of 2000. Annual follow-up surveys were undertaken to obtain histories of incident coronary heart disease and stroke. The other methods of case ascertainment were inquiry of death certificate diagnosis, absentee reports due to sickness, and insurance claims [14]. To confirm the diagnosis, study physicians obtained medical histories and resting electrocardiograms (ECGs) for all living patients. If the subject had died, the medical history was obtained from the family, relative, or colleagues. Medical record at company clinics and local hospitals were also reviewed. The criteria for coronary heart disease were modified from those of the World Health Organization Expert Committee [15]. Definite acute myocardial infarction was diagnosed by typical severe chest pain (lasting at least 30 min and with no definite non-ischemic cause) accompanied by new abnormal and persistent Q or QS waves, consistent change in cardiac enzyme levels, or both. If the ECG and enzyme levels were not available, but the patient had typical chest pain, a diagnosis of probable acute myocardial infarction was made. Stroke was defined as a focal neurological disorder with rapid onset, persisting for at least 24 h or until death. Using the clinical criteria, incident strokes were identified by a panel of three to four study physicians who were blinded to the data from the risk factor survey. Stroke events were classified as ischemic strokes (thrombotic or embolic) and others (intraparenchymal hemorrhages, subarachnoid hemorrhages, or strokes of undetermined type), primarily based on computerized tomography (CT) and/or magnetic resonance imaging (MRI) [16]. The CT and/or MRI were available for 85% of ischemic strokes. 2.4. Statistical analysis Analysis of covariance was used to test differences in ageadjusted means and proportions of baseline characteristics among quartiles of leukocyte count. Person-years of followup for each participant was calculated from enrollment to the date of cardiovascular disease event or dates of job quitting or retirement. The average follow-up period for the cohort was 9.3 years. Relative risks and 95% confidence intervals (CI) for acute myocardial infarction and ischemic stroke were calculated according to Cox proportional hazards regression models. The initial model was adjusted only for age. The multivariable adjustment included baseline hypertension (slight: SBP 140–159 mmHg and/or DBP 90–99 mmHg,
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moderate to severe: SBP ≥ 160 mmHg or DBP ≥ 100 mmHg and/or the use of an antihypertensive medication), hyperglycemia (borderline diabetes, diabetes), serum cholesterol levels (mmol/L), smoking status (ex-smokers, current smokers of cigarettes <20 per day, and ≥20 per day), BMI (category <18.5, 18.5–24.9, and ≥25.0 kg/m2 ), usual ethanol intake (never drinker, ex-drinker, current drinker of ethanol <69 g/day, and ≥69 g/day). Trends across leukocyte count quartiles were assessed by using a variable that equaled the median of the leukocyte count within the pertinent quartile, and the corresponding Pvalues were reported. The analyses using Cox proportional hazard models were repeated, stratified by smoking status. The test for interaction with smoking status was made using a cross-product term of smoking status (current versus nonsmokers) × continuous variable of leukocyte count. All statistical analyses were performed using the SAS System for Windows (Version 9.1; SAS Inc., Cary, NC). All P-values for statistical tests were two tailed, and values of <0.05 were regarded as statistically significant.
3. Results Table 1 shows the baseline characteristics according to quartiles of leukocyte count. There was a striking increase in the proportion of current smokers across quartiles of leukocyte count with smokers in the fourth quartile about two-fold higher than smokers in the first quartile. BMI and serum cholesterol levels were also positively associated with leukocyte count. Table 2 shows relative risks of acute myocardial infarction and ischemic stroke according to quartiles of leukocyte count. We documented 40 events of acute myocardial infarction and 26 events of ischemic stroke. There was a strong dose–response relationship between leukocyte count and age-adjusted risk of acute myocardial infarction. After
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adjustment for other cardiovascular risk factors including smoking, the association was somewhat weakened but remained statistically significant. There was a positive trend between leukocyte count and age-adjusted risk of ischemic stroke, albeit there were only a small numbers of cases. The relative risks were reduced substantially in the multivariable model. The reduction in the relative risks was primarily observed when adjusting for smoking status; the relative risk of ischemic stroke for the highest versus lowest quartiles of leukocyte count was 1.5 (0.4–5.8) and that for 1 S.D. change of leukocyte count was 1.0 (0.7–1.5) (not shown in the table). Table 3 shows relative risks of acute myocardial infarction, stratified by smoking status. The association between leukocyte count and the risk of acute myocardial infarction was similarly observed among both current smokers and nonsmokers (P for interaction = 0.96).
4. Discussion The present prospective cohort study showed that leukocyte count was a significant predictor for acute myocardial infarction among middle-aged Japanese male employees after adjustment for other cardiovascular risk factors, including smoking and after stratification of smoking status. A previous meta-analysis [1] of 19 population-based prospective studies indicated that the relative risk of coronary heart disease for highest versus lowest tertiles of leukocyte count was 1.4 (95% CI, 1.3–1.5). In the ARIC Study [2], the relative risk of coronary heart disease in the highest versus lowest quartiles of leukocyte count was 1.9 (95% CI, 1.2–3.1) among African Americans and 1.7 (95% CI, 1.1–2.5) among Whites. In the Women’s Health Initiative Observational Study [3], the relative risk of nonfatal myocardial infarction was 1.4 (95% CI, 1.1–1.8). A previous Japanese study [17] showed a significant age-adjusted relative risk of coro-
Table 1 Baseline characteristics of Japanese male employees, aged 40–59 years free of coronary heart disease or stroke at baseline, according to quartiles of leukocyte count Quartiles of leukocyte count (×102 cells/mm3 )
P-value
Q1
Q2
Q3
Q4
Range of leukocyte count Median leukocyte count
25–49 44
50–59 55
60–70 64
71–178 81
No. of subjects Age (years) Body mass index (kg/m2 ) Current smoker (%) Usual ethanol intake (g/day) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Hypertension (%) Serum cholesterol (mmol/L) Impaired glucose tolerance (%) Diabetes (%)
1080 45.8 (0.2) 22.2 (0.1) 43 (1.4) 30.0 (0.7) 124 (0.5) 82 (0.4) 25 (1.4) 4.95 (0.03) 5 (0.7) 0.9 (0.4)
1213 46.2 (0.2) 22.6 (0.1) 57 (1.3) 29.7 (0.7) 125 (0.5) 83 (0.3) 29 (1.3) 5.09 (0.02) 4 (0.6) 1.6 (0.4)
1090 46.5 (0.2) 22.8 (0.1) 68 (1.4) 30.1 (0.8) 125 (0.5) 82 (0.4) 28 (1.3) 5.14 (0.03) 6 (0.7) 1.4 (0.4)
1109 46.4 (0.2) 22.9 (0.1) 85 (1.4) 31.6 (0.8) 126 (0.5) 82 (0.4) 28 (1.3) 5.17 (0.03) 5 (0.6) 2.3 (0.4)
Data are age-adjusted mean or percentage values. Numbers in parentheses indicate standard errors.
0.006 <0.0001 <0.0001 0.27 0.05 0.14 0.14 <0.0001 0.53 0.05
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Table 2 Age-adjusted and multivariable relative risk (RR) of acute myocardial infarction and ischemic stroke according to quartiles of leukocyte count Leukocyte count quartile
Person-years
No. of events
Age-adjusted incidence per 1000 person-year
Age-adjusted RR (95% CI)
Multivariable RR (95% CI)
Acute myocardial infarction Q1 Q2 Q3 Q4
10,376 11,917 10,251 10,143
3 7 12 18
0.3 0.6 1.2 1.8
1.0 (Referent) 2.1 (0.5–8.1) 4.0 (1.1–14) 6.0 (1.8–21)
1.0 (Referent) 1.5 (0.4–5.9) 2.6 (0.7–9.6) 3.7 (1.0–13)
<0.001
0.01
P for trend 1 S.D. change
41,967
40
1.0
1.7 (1.4–2.1)
1.6 (1.2–2.0)
Ischemic stroke Q1 Q2 Q3 Q4
10,376 11,917 10,251 10,143
3 7 8 8
0.3 0.6 0.8 0.8
1.0 (Referent) 2.1 (0.5–8.0) 2.5 (0.7–9.6) 2.6 (0.7–9.9)
1.0 (Referent) 1.4 (0.4–5.6) 1.6 (0.4–6.0) 1.2 (0.3–4.7)
0.18
0.97
1.2 (0.8–1.7)
0.9 (0.6–1.4)
P for trend 1 S.D. change
41,967
26
0.6
1730 cells/mm3
RRs of 1 S.D. change were assessed per increment of leukocyte count. Multivariable adjustment for age, body mass index, smoking status, ethanol intake, blood pressure category, serum cholesterol level, blood glucose category.
with the findings from two previous studies [4,5]. In those studies, the elevated leukocyte count was positively associated with the age-adjusted risk of ischemic stroke, but the association was no longer statistically significant after adjustment for smoking status. However, the ARIC Study [2] and the Women’s Health Initiative Observational Study [3] found a significant association between leukocyte count and the risk of ischemic or total stroke even after adjustment for smoking. The multivariable relative risk of stroke in the highest versus lowest quartiles of leukocyte count was 2.0 (95% CI, 1.3–3.0) for the ARIC Study and 1.5 (1.2–1.8) for the Women’s Health Initiative Observational Study. What are the underlying mechanisms of the association between leukocytosis and the risk of acute myocardial infarction? First, leukocytosis is a marker of inflammation in the process of atherosclerosis [19]. Second, a high leukocyte count promotes atherosclerosis via their migration into the arterial vessel wall or through the release of chemical factors from proliferating endothelial cells [20,21]. Leukocytes may stimulate platelets and promote thrombus formation [22].
nary heart disease associated with leukocyte count, but after adjustment for smoking status, the association was no longer statistically significant. In the present study, the association between leukocyte count and the risk of acute myocardial infarction was observed among both smokers and nonsmokers. In previous population-based cohort studies stratified by smoking status, i.e. the Framingham Study [7], the British Regional Heart Study [8], the Zutphen Study [9], and the ARIC Study [2], the significant association was observed only for nonsmokers, while among dyslipidemic men of the Helsinki Heart Study [18], the significant association was observed only for smokers. To our knowledge, this is the first population-based cohort study to show positive associations between leukocyte count and the risk of coronary heart disease for both in smokers and nonsmokers, with no significant statistical interaction. The positive association between leukocyte count and the risk of ischemic stroke was weak and did not reach statistical significance in the present study. This result was consistent
Table 3 Age-adjusted and multivariable relative risk of acute myocardial infarction according to quartiles of leukocyte stratified by smoking status Leukocyte count category
Person-years
No. of events
Age-adjusted incidence per 1000 person-year
Age-adjusted RR (95% CI)
Multivariable RR (95% CI)
Current smokers Q1 and Q2 Q3 and Q4
10,453 15,531
6 24
0.6 1.6
1.0 (Referent) 2.7 (1.1–6.6)
1.0 (Referent) 2.6 (1.0–6.9)
1 S.D. change
25,985
30
1.2
1.6 (1.3–2.1)
1.6 (1.2–2.0)
10,982 4,808
4 6
0.4 1.3
1.0 (Referent) 3.4 (0.9–12)
1.0 (Referent) 3.5 (1.0–12)
15,791
10
0.7
1.8 (0.9–3.7)
1.7 (0.8–3.6)
Nonsmokers Q1 and Q2 Q3 and Q4 1 S.D. change
1730 cells/mm3
RRs of 1 S.D. change were assessed per increment of leukocyte count. Multivariable adjustment for age, body mass index, ethanol intake, blood pressure category, serum cholesterol level, blood glucose category.
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Third, leukocytosis could be an intermediate factor for smoking. However, this possibility is less likely because we found a similar association between leukocyte count and the risk of acute myocardial infarction among nonsmokers as did among smokers. It is uncertain what subtypes of leukocyte were associated with the risk of acute myocardial infarction because we did not have the data on the leukocyte subtypes in the present study. However, in our later cohort at baseline between 1990 and 1996, we found mononuclear leukocytes but not neutrophils or lymphocytes were associated with the risk of ischemic cardiovascular disease [coronary heart diseases (n = 15) plus ischemic stroke (n = 9)]; the multivariable relative risk in 1 S.D. change of mononuclear leukocyte count was 1.8 (1.1–2.9). Our result is in agreement with the pathological finding that the monocytes, the precursor of macrophages, are present in every phase of atherogenesis [23]. However, a recent prospective study showed that the neutrophil count was more strongly associated with the risk for incident or mortality of myocardial infarction compared with the monocyte count among patients undergoing coronary arteriography [24]. Neutrophil count may be a marker of systematic inflammation and be a predictor for the incident and mortality of coronary heart disease among patients with advanced atherosclerosis. The limitations of the present study warrant discussion. First, we did not measure other inflammation markers, such as C-reactive protein and fibrinogen, which are recognized predictors of cardiovascular disease [1]. The Women’s Health Initiative Observational Study [3] showed that the leukocyte count was an independent predictor for coronary heart disease risk in the multivariable models adjusting for C-reactive protein, and the magnitude of contribution of these inflammation markers was similar to that of leukocyte count [1,3,25]. In the present study, serum albumin, another inflammation marker [1], was measured in 48% (2146/4492) of the participants, but it was not associated with the risk of acute myocardial infarction or ischemic stroke; the multivariable relative risk with 1 S.D. decrease of serum albumin (0.3 mg/dL) was 1.2 (95% CI, 0.8–1.8) for acute myocardial infarction and 0.8 (0.5–1.3) for ischemic stroke. Second, the variability of measurement of leukocyte count may weaken the association with the risk of cardiovascular disease. However, the Spearman’s correlation coefficient for leukocyte count measured at baseline and at 1-year later (69% followed) was high (r = 0.73, P < 0.001). Third, we did not identify cardiovascular disease events after retirement. However, there were no apparent differences in age-specific or age-adjusted mean values of baseline coronary risk factors, including leukocyte count, between men who left employment and men who did not. Thus, the withdrawal of these men is unlikely to affect the results substantially. In summary, we found that leukocyte count was positively associated with the risk of acute myocardial infarction among Japanese middle-aged men, both in smokers and nonsmokers. Leukocytosis may increase the risk of acute myocardial
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infarction by enhancing atherosclerosis and thrombus formation through arterial wall inflammation, or it may reflect systemic inflammation that increases such risk.
Acknowledgements The authors thank Prof. Minoru Iida (Kansai University of Welfare Sciences), Prof. Yoshihiko Naito (Mukogawa Women’s University), Dr. Tomonori Okamura (Shiga University of Medical Science), and Dr. Yuko Nakagawa (Neyagawa Public Health Center) for their valuable comments. We also thank the clinical laboratory technologists, public health nurses, engineers of the computer processing unit, nurses, and nutritionists in the Department of Epidemiology and Mass Examination, Osaka Medical Center for Cancer and Cardiovascular Diseases for their expert help.
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