Study population

The AICOS is a currently ongoing prospective cohort study designed to clarify risk and protective factors for various health problems that was initiated in 2015^17,18. The baseline AICOS survey was conducted in Yawatahama City in 2015, Uchiko Town in 2016, and in Seiyo City and Ainan Town in 2017, with total approximate populations of 36000, 17000, 38000, and 22000, respectively. These municipalities are among 20 municipalities in Ehime Prefecture on Shikoku Island, located south of the main island of Japan. The baseline study enrolled 798, 347, 524, and 755 participants in Yawatahama City, Uchiko Town, Seiyo City, and Ainan Town, respectively, and the participants were recruited from individuals who had undergone health checkups conducted by their municipality of residence or through alternative recruitment procedures. A total of 2424 participants, aged 33–89 years (including 894 men aged 35–89 years and 1530 women aged 33–85 years), completed the baseline questionnaire after providing written informed consent. For the present analyses, a total of 2024 study participants (727 men aged 35–88 years and 1297 women aged 34–85 years) were included after excluding 258 participants who had missing or questionable data for the study variables and 142 participants who self-reported a history of cardiovascular disease. The Ehime University Graduate School of Medicine ethics committee approved the AICOS study.

Measurements

An automatic on-screen carotid ultrasound system (GM - 72P00A , The CardioHealth Station; Panasonic Healthcare Co., Ltd., Ehime, Japan) was used by one of two trained laboratory technicians and two medical doctors to measure left and right CIMT of the common carotid artery within a specified time limit. The UK Biobank reported high face validity and reproducibility of this automated device¹⁹. Moreover, it has been validated for accurate measurements even by novice operators²⁰. Participants were placed in a supine position on a 180° examination bed with their head rotated against a gauge angled to 45°. All images were taken from the far wall of the distal common carotid artery, 1 cm proximally from the bifurcation. When the region of interest was correctly identified and software image criteria were met, an image was automatically frozen at end-diastole, and CIMT was calculated over a 10 mm length using automated boundary detection. The maximum CIMT was determined as the greatest CIMT observed in the left or right common carotid artery. According to the guidelines of the Japan Academy of Neurosonology and the Japan Society of Ultrasonics in Medicine, carotid wall thickening is defined as a maximum CIMT greater than 1.0 mm^21,22.

A self-administered questionnaire was used to collect data on age, sex, smoking status, SHS exposure at home and at work, alcohol consumption, physical activity, medication use for hypertension, hypercholesterolemia, and diabetes, employment, and education. Research technicians conducted phone interviews to clarify any missing or implausible responses. Never smoking was defined as having smoked <100 cigarettes over one’s lifetime. Former smoking was defined as having smoked ≥100 cigarettes over one’s lifetime, but having quit smoking by the time of the survey. Current smoking was defined as having smoked ≥100 cigarettes over one’s lifetime and still smoking at the time of the survey. Cumulative exposure to cigarette smoking (pack-years of smoking) was calculated by multiplying the average number of packs smoked per day (cigarettes smoked per day/20) by the number of years smoked, regardless of whether smoking status was former or current. SHS exposure at home and at work was assessed, respectively, by the following questions: ‘Have you ever lived in the same house with a regular smoker for not less than one year?’ and ‘Have you ever worked in the same office with a regular smoker for not less than one year?’. Pack-years of SHS exposure at home were estimated by multiplying the average number of packs exposed to SHS at home per day by the number of years exposed to SHS at home. Leisure time physical activity was determined based on whether the participants engaged in any moderate to vigorous physical activity; for example, playing golf, walking briskly, jogging, gardening, or playing tennis for at least 30 min once a week. After the participant had rested for at least 5 min in a seated position, blood pressure measurements were recorded twice using an automated sphygmomanometer, and the latter value was used in this study. The presence of hypertension was determined based on systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or current use of antihypertensive medication²³. Following an overnight fast, blood was drawn from the antecubital vein, and serum levels of low-density and high-density lipoprotein cholesterol, triglycerides, plasma glucose, and hemoglobin A1c were determined by a third-party laboratory (Shikoku Chuken, Ehime, Japan). Dyslipidemia was diagnosed when serum low-density lipoprotein cholesterol levels were ≥140 mg/dL, high-density lipoprotein cholesterol levels were below 40 mg/dL, triglyceride levels were ≥150 mg/dL, or the participant was currently taking medication to lower cholesterol²⁴. Diabetes mellitus was diagnosed when a fasting plasma glucose level was ≥126 mg/dL, hemoglobin A1c levels were ≥6.5%, or the participant was currently taking medication for diabetes²⁵. Body height and weight were recorded while the study participant was wearing light clothing and without shoes, and body mass index (BMI, kg/m²) was calculated. Waist circumference was measured at the level of the navel with the participant standing.

Statistical analysis

Smoking status was classified into three categories (never, former, and current), pack-years of smoking into three categories (none, 0.05 to <30, and ≥30 in men and none, 0.015 to <10, and ≥10 in women), SHS exposure at home into three categories (never, former, and current), pack-years of SHS exposure at home into three categories (none, 0 to <10, and ≥10 in men and none, 0 to <15, and ≥15 in women), SHS exposure at work into three categories (never, former, and current), and years of SHS exposure at work into three categories (none, 1 to <23, and ≥23 in men and none, 1 to <11, and ≥11 in women). Pack-years of smoking among former or current smokers, pack-years of SHS exposure at home among those who had been exposed to SHS at home, and years of SHS exposure at work among those who had been exposed to SHS at work were classified at approximately the median point with the sexes separated.

A priori, possible confounding factors examined in this study were age, alcohol consumption, leisure time physical activity, hypertension, dyslipidemia, diabetes mellitus, BMI, waist circumference, employment, and education level. Age, BMI, and waist circumference were continuous variables. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the relationships between active smoking or SHS exposure and carotid wall thickening, were estimated using multiple logistic regression analysis. Analysis of covariance was used to calculate the adjusted mean of the maximum CIMT according to active smoking or SHS exposure, with adjustment for confounding factors. A trend in an association was assessed using a multiple logistic regression model or multiple linear regression analysis, assigning consecutive integers to the categories of the exposure variables. A two-sided p-value of less than 0.05 was regarded as statistically significant. Since the maximum CIMT distribution was skewed to the right, the natural logarithms of the values were used. Thus, the mean maximum CIMT values and their 95% CIs were expressed as geometric means. All statistical analyses were carried out utilizing SAS software version 9.4 (SAS Institute, Inc., Cary, NC, USA).

Strengths and limitations

A number of methodological advantages were identified in the present study: participants had similar regions of residence, an automatic on-screen carotid ultrasound system was used, and several confounders were controlled for.

The present results should be interpreted in the context of its limitations. The cross-sectional nature of the current study precludes its use for proving causality. With regard to selection bias, study subjects were recruited from health checkup participants or through alternative recruitment procedures. The percentage participation was likely very low, although it could not be calculated because an accurate total of eligible study participants was not available. Thus, the current study population did not represent the general population of Japan, and our findings may not be generalized. For instance, the participants in the current study were more educated compared with the general population. According to the 2010 population census in Ehime Prefecture, the percentage of individuals between 60 and 69 years with a low, middle, high, or undisclosed educational level were 28.2%, 48.6%, 19.0%, and 4.2% in men, and 26.7%, 56.4%, 12.9%, and 4.0% in women, respectively³⁰. The corresponding percentages for study participants in the same age range were 13.2%, 52.7%, 34.1%, and 0.0% in men, and 16.4%, 51.8%, 31.9%, and 0.0% in women, respectively. We were not able to assess differences between participants in the AICOS and non-participants because information on personal characteristics of non-participants was not available.

In the current study, smoking and SHS exposure were evaluated on the basis of participants’ questionnaire responses; no information on objective measures such as cotinine levels in saliva, serum, or hair was available. Participants may have intentionally underreported smoking activities to provide answers they deemed socially acceptable. Also, the number of cigarettes smoked in relation to SHS exposure at work were not available. Participants likely had the same probability of being misclassified in relation to their smoking and SHS exposure regardless of whether they had carotid wall thickening, and this type of non-differential exposure misclassification would lead to an underestimation of the strength of the association between exposure and outcome. That is to say, it would dilute the effect of the exposure.

An inherent weakness of the carotid ultrasound system employed here is that it cannot be used to quantify the amount of plaque shown in images. Although CIMT and plaque are distinct in phenotype and both denote elevated vascular risk, CIMT, even in the absence of plaque, is an important indicator of heightened risk for vascular incidents and reliably signals the likelihood of plaque formation³¹. In addition, while the accuracy of CIMT measurement using an automated onscreen carotid ultrasonography device has been validated in previous studies^19,20, we did not verify the inter- and intra-observer measurement accuracy for CIMT within our study. Furthermore, in the present study, the maximum CIMT was defined solely based on the common carotid artery. Typically, the maximum CIMT also encompasses evaluations of the internal carotid artery and carotid bulb. However, the reproducibility of measuring CIMT in the internal carotid artery, carotid bulb, and common carotid artery is lower compared to measuring only the common carotid artery site³². One reason is that in Japanese individuals, compared to Western populations, the carotid bifurcation often lies higher than the angle of the mandible³³, making evaluations of the internal carotid artery and carotid bulb more challenging. Therefore, considering the potential issues with reproducibility, we decided to assess IMT based only on the common carotid artery. The observed null associations of active smoking and SHS exposure with the outcomes under study might be ascribed to insufficient statistical power. In particular, the associations with SHS exposure in men were assessed among only 222 participants. Residual confounding effects could not be ruled out although we adjusted for multiple confounders.