2026 年 33 巻 2 号 p. 181-194
Aims: This study examined whether or not the coexistence of smoking and metabolic syndrome synergistically increases the risk of cardiovascular disease (CVD) beyond their individual effects.
Methods: This prospective cohort study included 68,743 workers from the Japan Epidemiology Collaboration on Occupational Health Study. The participants were categorized into four groups based on their smoking status and metabolic syndrome. Biological interactions were evaluated using relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S).
Results: During a mean follow-up of 7.2 (range: 0.1–10.9) years, 346 participants developed CVD. Current smokers with metabolic syndrome had the highest CVD risk (hazard ratio: 6.45, 95% confidence interval [CI]: 4.73–8.80). Approximately 35% of CVD cases among individuals exposed to both factors were attributed to their biological interactions (RERI: 2.27, 95% CI: 0.56–3.98; AP: 0.35, 95% CI: 0.15–0.55; S: 1.71, 95% CI: 1.16–2.52). An analysis of CVD subtypes revealed a significant biological interaction for myocardial infarction (RERI: 5.14, 95% CI: 0.65–9.62; AP: 0.52, 95% CI: 0.26–0.78; S: 2.38, 95% CI: 1.22–4.62) but not for stroke (RERI: 1.34, 95% CI: -0.46–3.13; AP: 0.25, 95% CI: -0.03–0.53; S: 1.44, 95% CI: 0.89–2.34).
Conclusion: Smoking and metabolic syndrome interact synergistically to elevate CVD risk, particularly for myocardial infarction. Targeting both factors is essential for CVD prevention.
Cardiovascular disease (CVD) remains the leading cause of global mortality, with deaths rising from 12.4 million in 1990 to 19.8 million in 20221). In Japan, CVD mortality has declined since the late 20th century, largely owing to reductions in stroke incidence and mortality2-4). Nonetheless, it remains a major cause of death among the working population, significantly affecting productivity and imposing substantial economic and societal burden. In 2022, CVD accounted for over 20% of the deaths in the working-age population5).
Smoking and metabolic syndrome are well-established modifiable risk factors for CVD; however, most studies have examined these factors independently6, 7). Tobacco use introduces harmful chemicals that contribute to oxidative stress, inflammation, and insulin resistance, which are also central to the pathogenesis of metabolic syndrome8, 9). Furthermore, studies suggest that smoking combined with components of metabolic syndrome, such as abdominal obesity, hypertension, and hyperglycemia, may increase the risk of CVD10-12). This potential interaction highlights the need for deeper understanding of their joint effects.
Despite the importance of this issue, there is limited evidence regarding the biological interaction between smoking and metabolic syndrome. Such evidence could be pivotal for identifying individuals at increased risk of CVD and developing targeted prevention strategies. In Japan, two community-based cohort studies found that current smokers with metabolic syndrome had the highest risk of CVD; however, neither assessed the presence of a biological interaction between these factors13, 14). A community-based cohort study in China identified a biological interaction between smoking and metabolic syndrome, resulting in a synergistic increase in CVD risk15); however, the small number of CVD events (n = 82) limited its ability to assess their joint effects on specific CVD subtypes such as coronary heart disease and stroke. To our knowledge, no similar studies have been conducted in working populations, where the prevalence of smoking and metabolic syndrome is high16, 17).
AimTo address these gaps, this cohort study evaluated the biological interaction between smoking and metabolic syndrome on CVD risk among Japanese workers.
This cohort study utilized data from the ongoing Japan Epidemiology Collaboration on Occupational Health (J-ECOH) Study, which includes workers from over 10 companies spanning various industries such as electric machinery, steel, chemicals, and healthcare. Companies were recruited through convenience sampling via an occupational physician network in the Kanto and Tokai regions of Japan. Data from annual company-organized health checkups were collected between January 2008 and March 2023. A CVD registry was established in the J-ECOH Study in April 2012. Further details regarding the J-ECOH Study and its CVD registration process have been previously published18).
Prior to data collection, the J-ECOH Study was announced within participating companies through posters, allowing participants to opt out without the need for verbal or written consent. The study protocol, including the consent procedure, was approved by the Ethics Committee of the National Center for Global Health and Medicine, Japan (NCGM-G-001140).
Analytic CohortHealth checkup data were obtained from 10 companies, all of which provided records from 2011 onward. Of these, seven companies continued to provide annual data through fiscal year 2022, while the remaining three provided data through fiscal years 2015, 2016, and 2017. Participants ≥ 20 years old were eligible if they had attended a health checkup in 2011. If the 2011 data were unavailable, the 2010 data were used. From 98,937 eligible participants, exclusions were made for those with a history of CVD at baseline (n = 2,324); missing data on smoking status, metabolic syndrome status, or covariates (n = 20,174); or lack of follow-up information on CVD, mortality, or long-term sick leave (n = 7,696). The final analytical cohort included 68,743 participants (58,888 men and 9,855 women).
Health CheckupIn accordance with Japan’s Industrial Safety and Health Act, employers are required to conduct health checkups for their employees. These included anthropometric measurements, physical examinations, laboratory tests, and self-reported questionnaires on the medical history and lifestyle factors. Body height and weight were measured with participants wearing light clothing and no shoes, and the body mass index (BMI) was calculated as weight (kg) divided by height squared (m²). Waist circumference (WC) was measured at the umbilical level with the participants standing, using a measuring tape. Blood pressure was recorded in a seated position using either an automatic or a mercury sphygmomanometer. Plasma glucose levels were measured using an enzymatic method or glucose oxidase peroxidative electrode method. Glycated hemoglobin (HbA1c) levels were assessed via latex agglutination immunoassay, high-performance liquid chromatography, or enzymatic methods. Serum triglycerides, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were measured using enzymatic methods. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or receiving medical treatment for hypertension19). Diabetes was defined as fasting plasma glucose level ≥ 126 mg/dL, HbA1c level ≥ 6.5%, or receiving medical treatment for diabetes20). Dyslipidemia was defined as a triglyceride level ≥ 150 mg/dL, LDL-C level ≥ 140 mg/dL, HDL-C level ＜40 mg/dL, or receiving medical treatment for dyslipidemia21). All laboratories conducting health checkups for the participating companies received satisfactory ratings (rank A or ＞95 out of 100) from external quality control agencies.
ExposureSmoking status (never, former, or current) was determined using a self-administered questionnaire at baseline. Based on prior research14), never-smokers and former smokers were grouped as non-current smokers, given their comparable CVD risk (Supplementary Table 1).
| Case/No. | HR (95%CI) | |
|---|---|---|
| Never smokers without metabolic syndrome | 69/26,254 | Ref |
| Never smokers with metabolic syndrome | 37/4,228 | 3.10 (2.06, 4.68) |
| Past smokers without metabolic syndrome | 30/11,721 | 0.89 (0.59, 1.32) |
| Past smokers with metabolic syndrome | 31/3,198 | 2.51 (1.59, 3.95) |
| Current smokers without metabolic syndrome | 101/18,695 | 1.87 (1.35, 2.60) |
| Current smokers with metabolic syndrome | 78/4,647 | 5.82 (4.11, 8.24) |
Adjusted for age and sex; worksite was treated as a cluster variable.
Metabolic syndrome was defined according to the Joint Interim Statement22), requiring the presence of three or more of the following components: elevated blood glucose (fasting plasma glucose level of ≥ 100 mg/dL or the use of antidiabetic medication), central obesity (WC ≥ 90 cm for men or ≥ 80 cm for women), elevated triglycerides ( ≥ 150 mg/dL or the use of lipid-lowering medication), elevated blood pressure (systolic blood pressure ≥ 130 mmHg, diastolic blood pressure ≥ 85 mmHg, or the use of antihypertensive medication), and reduced HDL-C levels (levels of ＜40 mg/dL for men or ＜50 mg/dL for women).
Participants were classified into four groups based on smoking status and presence of metabolic syndrome: (1) non-current smokers without metabolic syndrome, (2) non-current smokers with metabolic syndrome, (3) current smokers without metabolic syndrome, and (4) current smokers with metabolic syndrome.
CovariatesThe covariates included in the analysis were age ( years), sex, and worksite, as these variables were consistently available across all participating companies.
OutcomeThe incidence of CVD events between April 2012 and March 2023 was ascertained. The primary outcome was total CVD, defined as the first occurrence of fatal or nonfatal myocardial infarction or stroke. Secondary outcomes were analyzed separately for myocardial infarction and stroke. For participants who experienced multiple events, such as myocardial infarction and stroke, or a nonfatal event followed by death, only the first event was recorded to ensure consistent classification.
In fatal cases, the cause of death was determined using reports from collaborating occupational physicians. These reports were based on death certificates provided by bereaved families (55.2%), information from family members or colleagues (16.4%), previously submitted medical certificates (20.9%), other or unspecified sources (3.0%), or missing in some cases (4.5%). For nonfatal cases, diagnoses were primarily based on medical certificates issued by treating physicians and submitted by workers (87.8%). A smaller proportion was verified directly by the treating physicians (1.4%), derived from self-reports (6.1%), or categorized as missing (4.7%). Details of all the case classifications, including those with incomplete data, are provided in Supplementary Table 2.
| Type of CVD event | Source of information | Number of cases | % within category |
|---|---|---|---|
| Fatal (n = 67) | Death certificates | 37 | 55.2% |
| CVD registries | 14 | 20.9% | |
| Information from family members or colleagues | 11 | 16.4% | |
| other or unspecified sources | 2 | 3.0% | |
| Missing | 3 | 4.5% | |
| Non-fatal (n = 279) | Medical certificates | 245 | 87.8% |
| Treating physicians | 4 | 1.4% | |
| Self-reports | 17 | 6.1% | |
| Missing | 13 | 4.7% | |
| Total (n = 346) | Lacked a source of diagnostic information | 16 (fatal)+ 30 (non-fatal) = 46 | 13.3% of the total |
Occupational physicians affiliated with the participating companies reported all cardiovascular events, including fatal and non-fatal cases. They completed structured case report forms that included the type of event (e.g., myocardial infarction or stroke) and the source of diagnostic information, such as medical certificates, death certificates, reports from family or colleagues, or self-reports. In a subset of cases, the source of diagnostic information was missing; however, the event type was explicitly stated by the occupational physician (e.g., clearly labelled as “stroke” or “myocardial infarction”). In such cases, we classified the event based on the physician’s diagnosis, even in the absence of a documented source.
The baseline characteristics of the study participants were summarized as means for continuous variables and percentages for categorical variables, grouped by smoking status and metabolic syndrome status. Differences in baseline characteristics between groups were evaluated using Chi-squared tests for categorical variables and analyses of variance for continuous variables.
Person-time was calculated starting from March 31, 2012, one day before CVD registration began for baseline examinations in the fiscal year 2011. Follow-up continued until the earliest of the following events: the first CVD event, individual censoring based on available data (including information from annual health checkups, sick leave, retirement, or death), or the end of the follow-up period, typically March 31, 2023, for most companies.
The Cox proportional hazards regression model was employed to estimate the hazard ratio (HR) for CVD and the corresponding 95% confidence interval (CI) using non-current smokers without metabolic syndrome as the reference group. Adjustments were made for age and sex, with the worksite treated as a cluster variable. The proportional hazard assumption was evaluated using Schoenfeld residuals, and no violations were detected. The population attributable fraction (PAF) was calculated using the following formula: PAF = pd[(HR − 1) / HR], where pd represents the proportion of cases exposed to the risk factor and HR is the adjusted HR. To assess the robustness of the findings, a sensitivity analysis was conducted excluding all CVD cases not confirmed by medical or death certificates.
Biological interaction, which assesses a departure from the additivity of effects, was analyzed because it is more causally informative than statistical interactions. In contrast, statistical interactions are scale-dependent (additive or multiplicative) and are not necessarily linked to a biological mechanism23). To evaluate whether or not smoking and metabolic syndrome produced greater-than-additive effects on CVD risk, biological interaction was assessed by calculating the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S)24). RERI values greater than 0, AP greater than 0, and S greater than 1 are considered indicative of biological interactions.
To explore potential effect modifications, interaction terms between the joint smoking/metabolic syndrome categories and sex or age were tested. In addition, stratified analyses by sex and age group (aged ＜45 and ≥ 45 years) were performed to assess the consistency of the associations across subgroups. All statistical analyses were performed using the SAS software program, version 9.4 (SAS Institute, Cary, NC, USA). Statistical significance was defined as a two-sided P-value ＜0.05.
Among the 68,743 participants included in the analysis, 85.7% were men, and the mean age at baseline was 44.5 (10.3) years old. The baseline characteristics of the study participants, stratified by smoking status and the presence of metabolic syndrome, are presented in Table 1. Participants who were current smokers with metabolic syndrome tended to be older and predominantly male and had a higher BMI and worse cardiometabolic profiles than non-current smokers without metabolic syndrome. Over a mean follow-up period of 7.2 (range: 0.1–10.9) years, 346 participants (32 women) developed CVD, comprising 250 cases of stroke and 96 cases of myocardial infarction. The overall incidence rate of CVD was 0.7 per 1,000 person-years. Detailed incidence rates stratified by age, sex, smoking status, metabolic syndrome status, and joint categories are presented in Supplementary Table 3.
| Non-current smokers | Current smokers | |||
|---|---|---|---|---|
|
No metabolic syndrome |
Metabolic syndrome |
No metabolic syndrome |
Metabolic syndrome |
|
| N | 37,975 | 7,426 | 18,695 | 4,647 |
| Men, % | 79.1 | 88.5 | 95.0 | 97.2 |
| Age (years) | 43.8±10.4 | 50.0±8.7 | 43.1±10.4 | 47.8±8.5 |
| Body mass index (kg/m2) | 22.6±2.9 | 27.0±3.7 | 22.9±3.0 | 27.0±3.8 |
| Waist circumference (cm) | 79.1±11.1 | 92.0±9.2 | 79.3±14.0 | 92.3±10.1 |
| Triglycerides (mg/dL) | 98.8±62.8 | 191.5±129.2 | 118.9±80.8 | 225.9±156.3 |
| Low-density lipoprotein cholesterol (mg/dL) | 118.6±29.6 | 128.5±30.7 | 118.1±30.9 | 128.0±32.0 |
| High-density lipoprotein cholesterol (mg/dL) | 62.8±15.2 | 50.8±12.7 | 56.8±13.7 | 46.5±11.3 |
| Dyslipidemia, % | 33.9 | 86.4 | 40.5 | 91.2 |
| Systolic blood pressure (mmHg) | 119.0±14.2 | 133.6±14.2 | 118.7±13.9 | 131.4±14.7 |
| Diastolic blood pressure (mmHg) | 74.7±10.4 | 85.0±9.5 | 73.9±10.0 | 83.2±9.9 |
| Hypertension, % | 13.7 | 56.9 | 12.1 | 48.8 |
| Fasting blood glucose (mg/dL) | 95.7±13.9 | 114.4±27.8 | 96.9±17.4 | 115.5±30.8 |
| HbA1c (%) | 5.4±0.5 | 6.0±1.0 | 5.5±0.6 | 6.1±1.1 |
| Diabetes, % | 3.1 | 23.7 | 4.4 | 26.2 |
| N |
CVD cases |
Person-years |
Incidence rate (per 1,000 person-years) |
|
|---|---|---|---|---|
| Sex | ||||
| Men | 58,888 | 314 | 429,035 | 0.73 |
| Women | 9,823 | 32 | 68,830 | 0.46 |
| Age (years) | ||||
| ＜40 | 21,407 | 39 | 173,461 | 0.22 |
| 40-49 | 24,409 | 147 | 196,736 | 0.75 |
| 50-59 | 18,549 | 146 | 111,692 | 1.30 |
| ≥ 60 | 4,378 | 14 | 15,975 | 0.87 |
| Smoking status | ||||
| Non-current smokers | 45,401 | 167 | 325,385 | 0.51 |
| Current smokers | 23,342 | 179 | 172,479 | 1.04 |
| Metabolic syndrome status | ||||
| No metabolic syndrome | 56,670 | 200 | 416,160 | 0.48 |
| With metabolic syndrome | 12,073 | 146 | 81,704 | 1.79 |
| Joint categories | ||||
| Non-current smokers without metabolic syndrome | 37,975 | 99 | 276,230 | 0.36 |
| Non-current smokers with metabolic syndrome | 7,426 | 68 | 49,156 | 1.38 |
| Current smokers without metabolic syndrome | 18,695 | 101 | 139,931 | 0.72 |
| Current smokers with metabolic syndrome | 4,647 | 78 | 32,549 | 2.40 |
As shown in Fig.1 and Supplementary Table 4, the highest risk of CVD was observed among current smokers with metabolic syndrome (HR: 6.45, 95% CI: 4.73–8.80), followed by non-current smokers with metabolic syndrome (HR: 3.11, 95% CI: 2.26–4.28) and current smokers without metabolic syndrome (HR: 2.07, 95% CI: 1.55–2.77), in comparison with non-current smokers without metabolic syndrome. The results remained consistent in the sensitivity analysis (Supplementary Table 5), which excluded all CVD cases that were not confirmed by medical or death certificates (n = 46). A significant biological interaction between smoking and metabolic syndrome was identified in relation to the total CVD. The RERI was 2.27 (95% CI: 0.56–3.98), indicating that the 2.27 units of excess risk were attributable to their joint effect. The AP was 0.35 (95% CI: 0.15–0.55), signifying that 35% of CVD cases among individuals exposed to both factors were due to the interaction. The S was 1.71 (95% CI: 1.16–2.52), suggesting that the joint risk was 1.71 times greater than the sum of individual risks. The results remained robust in separate analyses of fatal and nonfatal CVD (Supplementary Tables 4 and 6).
RERI, relative excess risk due to interaction; AP, attributable proportion due to interaction; S, synergy index
| Non-current smokers | Current smokers | |||
|---|---|---|---|---|
|
No metabolic syndrome |
Metabolic syndrome |
No metabolic syndrome |
Metabolic syndrome |
|
| Total CVD | ||||
| Person years | 276,230 | 49,156 | 139,931 | 32,549 |
| Cases | 99 | 68 | 101 | 78 |
| Adjusted HR (95% CI) | 1 | 3.11 (2.26, 4.28) | 2.07 (1.55, 2.77) | 6.45 (4.73, 8.80) |
| PAF | 13.3% | 15.1% | 19.1% | |
| Non-fatal CVD | ||||
| Cases | 79 | 57 | 80 | 63 |
| Adjusted HR (95% CI) | 1 | 3.17 (2.23, 4.50) | 1.95 (1.41, 2.70) | 6.22 (4.40, 8.78) |
| PAF | 14.0% | 14.0% | 19.0% | |
| Fatal CVD | ||||
| Cases | 20 | 11 | 21 | 15 |
| Adjusted HR (95% CI) | 1 | 2.80 (1.29, 6.05) | 2.69 (1.41, 5.15) | 7.58 (3.70, 15.53) |
| PAF | 10.6% | 19.7% | 19.4% | |
Adjusted for age and sex; worksite was treated as a cluster variable.
CVD, cardiovascular disease; PAF, population attributable fraction.
| Non-current smokers | Current smokers | |||
|---|---|---|---|---|
|
No metabolic syndrome |
Metabolic syndrome |
No metabolic syndrome |
Metabolic syndrome |
|
| Total CVD | ||||
| Person years | 276,049 | 49,099 | 139,799 | 32,456 |
| Cases | 85 | 63 | 83 | 69 |
| Adjusted HR (95% CI) | 1 | 3.41 (2.43, 4.78) | 1.95 (1.42, 2.67) | 6.64 (4.76, 9.26) |
| PAF | 14.8% | 13.5% | 19.5% | |
| Non-fatal CVD | ||||
| Cases | 68 | 53 | 69 | 59 |
| Adjusted HR (95% CI) | 1 | 3.34 (2.31, 4.85) | 1.86 (1.31, 2.63) | 6.58 (4.58, 9.45) |
| PAF | 14.9% | 12.8% | 20.1% | |
| Fatal CVD | ||||
| Cases | 17 | 10 | 14 | 10 |
| Adjusted HR (95% CI) | 1 | 4.03 (1.73, 9.40) | 2.41 (1.12, 5.22) | 7.08 (2.99, 16.74) |
| PAF | 14.7% | 16.1% | 16.8% | |
Adjusted for age and sex with the worksite treated as a cluster variable.
CVD, cardiovascular disease; PAF, population attributable fraction.
| Measures of biological interaction | |||
|---|---|---|---|
| RERI | AP | S | |
| Total CVD | 2.27 (0.56, 3.98) | 0.35 (0.15, 0.55) | 1.71 (1.16, 2.52) |
| Non-fatal CVD | 2.10 (0.26, 3.94) | 0.34 (0.11, 0.56) | 1.67 (1.08, 2.58) |
| Fatal CVD | 3.09 (-1.46, 7.64) | 0.41 (-0.01, 0.82) | 1.89 (0.81. 4.41) |
CVD, cardiovascular disease; RERI, relative excess risk due to interaction; AP, the attributable
proportion due to interaction; S, synergy index.
Smoking and metabolic syndrome accounted for nearly half (47.5%) of all the CVD cases. PAF was highest among current smokers with metabolic syndrome (19.1%), followed by current smokers without metabolic syndrome (15.1%), and non-current smokers with metabolic syndrome (13.3%) (Supplementary Table 4).
As shown in Fig.2 and Supplementary Table 7, current smokers with metabolic syndrome had the highest risk of stroke (HR: 5.34, 95% CI: 3.67–7.78) and myocardial infarction (HR: 9.87, 95% CI: 5.60–17.40). A significant biological interaction between smoking and metabolic syndrome was observed for myocardial infarction (RERI: 5.14, 95% CI: 0.65–9.62; AP: 0.52, 95% CI: 0.26–0.78; S: 2.38, 95% CI: 1.22–4.62) but not for stroke (either hemorrhagic or ischemic) (Fig.2 and Supplementary Table 8). A weaker interaction was observed for atherosclerotic cardiovascular diseases (comprising myocardial infarction and ischemic stroke) compared to that observed for myocardial infarction alone.
RERI, relative excess risk due to interaction; AP, attributable proportion due to interaction; S, synergy index
| Non-current smokers | Current smokers | |||
|---|---|---|---|---|
|
No metabolic syndrome |
Metabolic syndrome |
No metabolic syndrome |
Metabolic syndrome |
|
| Stroke | ||||
| Person years | 276,230 | 49,156 | 139,931 | 32,549 |
| Cases | 76 | 49 | 76 | 49 |
| Adjusted HR (95% CI) | 1 | 2.96 (2.04, 4.29) | 2.05 (1.47, 2.86) | 5.34 (3.67, 7.78) |
| PAF | 13.0% | 15.6% | 15.9% | |
| Ischemic stroke | ||||
| Cases | 37 | 30 | 37 | 27 |
| Adjusted HR (95% CI) | 1 | 3.59 (2.18, 5.90) | 1.99 (1.23, 3.20) | 5.93 (3.53, 9.96) |
| PAF | 16.5% | 14.1% | 17.1% | |
| Haemorrhagic stroke | ||||
| Cases | 26 | 14 | 29 | 17 |
| Adjusted HR (95% CI) | 1 | 2.38 (1.21, 4.66) | 2.29 (1.32, 3.98) | 5.09 (2.69, 9.65) |
| PAF | 9.4% | 19.0% | 15.9% | |
| Myocardial infarction | ||||
| Cases | 23 | 19 | 25 | 29 |
| Adjusted HR (95% CI) | 1 | 3.58 (1.92, 6.70) | 2.15 (1.20, 3.86) | 9.87 (5.60, 17.40) |
| PAF | 14.3% | 13.9% | 27.2% | |
| ASCVD (myocardial infarction and ischemic stroke) | ||||
| Cases | 60 | 49 | 62 | 56 |
| Adjusted HR (95% CI) | 1 | 3.58 (2.42, 5.29) | 2.04 (1.41, 2.96) | 7.47 (5.11, 10.93) |
| PAF | 15.6% | 13.9% | 21.4% | |
Adjusted for age and sex; worksite was treated as a cluster variable.
ASCVD, atherosclerotic cardiovascular disease; PAF, population attributable fraction.
| Measures of biological interaction | |||
|---|---|---|---|
| RERI | AP | S | |
| Stroke | 1.34 (-0.46, 3.13) | 0.25 (-0.03, 0.53) | 1.44 (0.89, 2.34) |
| Ischemic stroke | 1.35 (-1.34, 4.04) | 0.23 (-0.16, 0.61) | 1.38 (0.74, 2.57) |
| Haemorrhagic stroke | 1.42 (-1.46, 4.31) | 0.28 (-0.18, 0.74) | 1.53 (0.66, 3.57) |
| Myocardial infarction | 5.14 (0.65, 9.62) | 0.52 (0.26, 0.78) | 2.38 (1.22, 4.62) |
| ASCVD | 2.84 (0.49, 5.20) | 0.38 (0.15, 0.61) | 1.78 (1.14, 2.80) |
ASCVD, atherosclerotic cardiovascular disease (myocardial infarction and ischemic stroke); RERI, relative excess risk due to interaction; AP, the attributable proportion due to interaction; S, synergy index.
Smoking and metabolic syndrome accounted for 44.5% of stroke cases and 55.4% of myocardial infarction cases, respectively. For stroke, PAFs were similar across the groups: current smokers with metabolic syndrome (15.9%), current smokers without metabolic syndrome (15.6%), and non-current smokers with metabolic syndrome (13.0%). For myocardial infarction, the highest PAF was observed in current smokers with metabolic syndrome (27.2%), followed by non-current smokers with metabolic syndrome (14.3%) and current smokers without metabolic syndrome (13.9%) (Supplementary Table 7).
The interaction terms between the joint smoking/metabolic syndrome categories and sex or age were not statistically significant, indicating no evidence of an effect modification. Despite this, stratified analyses by sex and age group (Supplementary Tables 9 and 10) revealed patterns consistent with the main analysis. A significant biological interaction between smoking and metabolic syndrome was observed for myocardial infarction in men and in participants aged ≥ 45 years, but not for stroke. Although the results for women and younger participants (aged ＜45 years) suggested a possible synergistic effect, especially for myocardial infarction, the small number of events led to wide confidence intervals and reduced the reliability of the estimates.
| Non-current smokers | Current smokers | |||
|---|---|---|---|---|
| No metabolic syndrome | Metabolic syndrome | No metabolic syndrome | Metabolic syndrome | |
| Men | ||||
| Total CVD | ||||
| Cases/No. | 76/30,032 | 65/6,571 | 98/17,767 | 75/4,518 |
| Adjusted HR (95% CI) | 1 | 3.44 (2.45, 4.83) | 2.22 (1.63, 3.01) | 6.65 (4.80, 9.22) |
| PAF | 14.7% | 17.2% | 20.3% | |
| Stroke | ||||
| Cases/No. | 54/30,032 | 46/6,571 | 74/17,767 | 47/4,518 |
| Adjusted HR (95% CI) | 1 | 3.37 (2.25, 5.03) | 2.30 (1.61, 3.30) | 5.72 (3.84, 8.53) |
| PAF | ||||
| Myocardial infarction | 14.6% | 18.9% | 17.6% | |
| Cases/No. | 22/30,032 | 19/6,571 | 24/17,767 | 28/4,518 |
| Adjusted HR (95% CI) | 1 | 3.62 (1.93, 6.79) | 1.99 (1.10, 3.58) | 9.07 (5.12, 16.05) |
| PAF | 14.8% | 12.8% | 26.8% | |
| Women | ||||
| Total CVD | ||||
| Cases/No. | 23/7,943 | 3/855 | 3/928 | 3/129 |
| Adjusted HR (95% CI) | 1 | 1.48 (0.42, 5.21) | 1.23 (0.36, 4.22) | 9.61 (2.75, 33.66) |
| PAF | - | - | - | |
| Stroke | ||||
| Cases/No. | 22/7,943 | 3/855 | 2/928 | 2/129 |
| Adjusted HR (95% CI) | 1 | 1.42 (0.40, 5.01) | 0.77 (0.18, 3.35) | 6.21 (1.40, 27.53) |
| PAF | - | - | - | |
| Myocardial infarction | ||||
| Cases/No. | 1/7,943 | 0/855 | 1/928 | 1/129 |
| Adjusted HR (95% CI) | - | - | - | - |
| PAF | - | - | - | - |
| Age ＜45 years | ||||
| Total CVD | ||||
| Cases/No. | 34/20,187 | 17/2,018 | 37/10,443 | 20/1,690 |
| Adjusted HR (95% CI) | 1 | 4.86 (2.66, 8.86) | 1.78 (1.07, 2.95) | 6.92 (3.86, 12.41) |
| PAF | 12.5% | 15.0% | 15.8% | |
| Stroke | ||||
| Cases/No. | 26/20187 | 13/2018 | 31/10443 | 13/1690 |
| Adjusted HR (95% CI) | 1 | 4.70 (2.37, 9.32) | 2.00 (1.14, 3.52) | 5.84 (2.90, 11.76) |
| PAF | 12.3% | 18.7% | 13.0% | |
| Myocardial infarction | ||||
| Cases/No. | 8/20,187 | 4/2,018 | 6/10,443 | 7/1,690 |
| Adjusted HR (95% CI) | 1 | 5.43 (1.54, 19.12) | 1.14 (0.36, 3.65) | 10.69 (3.60, 31.70) |
| PAF | 13.1% | 3.0% | 25.3% | |
| Age ≥ 45 years | ||||
| Total CVD | ||||
| Cases/No. | 65/17,788 | 51/5,408 | 64/8,252 | 58/2,957 |
| Adjusted HR (95% CI) | 1 | 2.81 (1.93, 4.08) | 2.20 (1.54, 3.14) | 6.03 (4.17, 8.71) |
| PAF | 13.8% | 14.7% | 20.3% | |
| Stroke | ||||
| Cases/No. | 50/17,788 | 36/5,408 | 45/8,252 | 36/2,957 |
| Adjusted HR (95% CI) | 1 | 2.56 (1.65, 3.98) | 2.02 (1.33, 3.07) | 4.87 (3.11, 7.60) |
| PAF | 13.1% | 13.6% | 17.1% | |
| Myocardial infarction | ||||
| Cases/No. | 15/17,788 | 15/5,408 | 19/8,252 | 22/2,957 |
| Adjusted HR (95% CI) | 1 | 3.60 (1.74, 7.46) | 2.76 (1.39, 5.48) | 9.77 (4.98, 19.17) |
| PAF | 15.3% | 17.1% | 27.8% | |
Adjusted for age and sex; in sex-specific analyses, adjusted for age only. Worksite was treated as a
cluster variable. CVD, cardiovascular disease; PAF, population attributable fraction.
| Measures of biological interaction | |||
|---|---|---|---|
| RERI | AP | S | |
| Men | |||
| Total CVD | 2.00 (0.18, 3.81) | 0.30 (0.08, 0.52) | 1.55 (1.05, 2.27) |
| Stroke | 1.13 (-0.82, 3.08) | 0.20 (-0.10, 0.51) | 1.33 (0.82, 2.15) |
| Myocardial infarction | 4.51 (0.01, 9.02) | 0.46 (0.16, 0.75) | 2.04 (1.07, 3.92) |
| Women | |||
| Total CVD | 7.90 (-3.88, 19.69) | 0.82 (0.51, 1.13) | 12.2 (0.34, >100) |
| Stroke | 5.17 (-4.20, 14.54) | 0.81 (0.40, 1.22) | 27.22 (0.00, >100) |
| Myocardial infarction | 3.98 (-4.37, 4.37) | 0.98 (0.84, 1.13) | 69.08 (0.00, >100) |
| Age ＜45 years | |||
| Total CVD | 1.29 (-2.60, 5.18) | 0.19 (-0.31, 0.69) | 1.27 (0.61, 2.66) |
| Stroke | 0.25 (-3.80, 4.30) | 0.04 (-0.65, 0.74) | 1.06 (0.43, 2.57) |
| Myocardial infarction | 5.38 (-5.71, 16.46) | 0.46 (-0.18, 1.12) | 2.02 (0.50, 8.25) |
| Age ≥ 45 years | |||
| Total CVD | 2.02 (0.17, 3.88) | 0.34 (0.10, 0.57) | 1.67 (1.06, 2.65) |
| Stroke | 1.34 (-0.54, 3.22) | 0.28 (-0.04, 0.60) | 1.54 (0.84, 2.83) |
| Myocardial infarction | 4.46 (-0.92, 9.84) | 0.43 (0.09, 0.77) | 1.90 (0.95, 3.80) |
CVD, cardiovascular disease; RERI, relative excess risk due to interaction; AP, the attributable
proportion due to interaction; S, synergy index.
In this large working population-based cohort study, we found that current smokers with metabolic syndrome had the highest risk of CVD among all groups. A significant biological interaction between smoking and metabolic syndrome was observed, further amplifying the risk of myocardial infarction, although no such interaction was noted in stroke. To our knowledge, this is the first prospective cohort study to evaluate the biological interaction between smoking and metabolic syndrome on CVD in a Japanese population.
Smoking and metabolic syndrome, whether independent or concurrent, accounted for nearly half of the CVD cases in our working population. This underscores the critical importance of addressing these risk factors in prevention efforts, as supported by previous studies6, 7, 13-15). Notably, our study showed that a significant biological interaction between smoking and metabolic syndrome contributed to 35% of CVD cases among individuals exposed to both factors. This finding aligns with a previous study conducted in a Chinese population, which reported that 42% of CVD cases among those exposed to both factors were attributable to biological interactions15). These results emphasize the necessity of jointly targeting smoking and metabolic syndrome in future preventive strategies to effectively mitigate CVD risk.
The mechanisms underlying the biological interaction between smoking and metabolic syndrome on CVD risk remain unclear. One plausible explanation for this is that the interaction reflects shared biological pathways. Both smoking and metabolic syndrome are known to increase oxidative stress, exacerbate insulin resistance, and activate the sympathetic nervous system, all of which contribute to CVD development8, 9, 25). In addition, smoking has been reported to increase the risk of metabolic syndrome by worsening insulin resistance, promoting central obesity, intensifying oxidative stress, and further increasing the risk of cardiovascular complications9, 26).
Our findings revealed differences in CVD subtypes, with a significant biological interaction observed for myocardial infarction but not for stroke. One possible explanation is that smoking and metabolic syndrome are more strongly associated with myocardial infarction than with stroke27-29). For instance, a meta-analysis of 141 cohort studies reported that men who smoke approximately 1 cigarette per day have a 48% higher risk of heart disease than never smokers, whereas the corresponding risk for stroke is 25%27). With regard to metabolic syndrome, evidence has been inconsistent. While a previous meta-analysis suggested a similar association between metabolic syndrome and both myocardial infarction and stroke7), more recent studies have reported conflicting findings28-30). In our nested case-control study of a working Japanese population, the association between metabolic syndrome and myocardial infarction was twice as strong as that for stroke28). Further research is needed to determine whether or not a biological interaction exists between smoking and metabolic syndrome in stroke or its subtypes.
Strengths and LimitationsThis study has several strengths, including its large cohort size, relatively long follow-up period (up to 11 years), and detailed analysis of the CVD subtypes. However, the study also had some limitations. First, the CVD registry relied on reports from collaborating occupational physicians and predominantly captured severe cases, which may have limited the applicability of our findings to milder CVD cases. Second, variations in lifestyle and work environment questionnaires across the participating companies restricted the covariates included in the analysis to age and sex. Residual and unmeasured confounding factors, such as secondhand smoke exposure and dietary habits, may have influenced the results. Third, the small number of current smokers among women (1,057 individuals, approximately 10.7% of all women), along with the limited number of CVD cases observed in women (n = 32), limits the ability to conduct sex-specific analyses. Finally, as this study was conducted in a Japanese occupational cohort, caution should be exercised when generalizing our findings to other populations.
This cohort study showed that nearly half of all CVD cases are attributable to smoking, metabolic syndrome, or both. A significant biological interaction between smoking and metabolic syndrome was also observed, increasing the risk of myocardial infarction among Japanese workers. These findings underscore the importance of addressing both factors in reducing CVD risk in the working population.
This work was supported by the Industrial Health Foundation, Industrial Disease Clinical Research Grants (140202-01, 150903-01, 170301-01), JSPS KAKENHI Grants (JP25293146, JP25702006, JP16H05251, JP20H03952, and JP23K09757), NCGM Intramural Research Fund (28-Shi-1206, 30-Shi-2003, 19A1006, 21A1020, 22A1008), and JIHS Intramural Research Fund (25A1005).
The authors declare that they have no conflicts of interest to disclose.
