The prevalence of coronary artery disease (CAD) in China is on the rise, causing great threat to society and families (1). The risk factors of CAD include hypertension, type 2 diabetes (T2DM), hyperlipidemia, smoking, obesity and other risk factors. Although hypertension, T2DM and other risk factors have been managed, the current situation of CAD prevention and control is still not optimistic. Therefore, in addition to these traditional cardiovascular risk factors, other risk factors in CAD are worth valuing (2). Discovering new potential risk factors for CAD can benefit the management of CAD and improve the prognosis of CAD patients.

Due to the powerful and attractive advantages of smartphones, many people overuse smartphones, leading to similar addiction symptoms. The definition of smartphone addiction (SA) is psychological dependence on smartphones, referring to long-term dependence on playing with them (3). Just like the essence of the Internet addiction, SA habit is more widespread and hidden, not only among teenagers, but also among adults. Researchers have suggested that excessive use of smartphones may be associated with increased body mass index (BMI), poorer sleep quality and higher hypertension prevalence (4). In addition, patients with SA habit, especially those who prefer to use smartphones before bedtime, often experience changes in sleep habits, are more prone to staying up late, and have various poor sleep quality problems such as short sleep maintenance time, which may be detrimental to physical health (5, 6).

In a quantitative study on SA habit with sleep quality and academic performance in 323 students conducted by Rathakrishnan B et al., it was confirmed that the higher the SA level of college students, the lower their academic performance appeared to be (5). It was also demonstrated that students with poor sleep quality might exhibit lower academic performance. Going to bed late can reduce the short sleep time and lead to poorer sleep quality. Short sleep time or poor sleep quality often lead to insulin resistance and metabolic syndrome by affecting glucose metabolism and blood pressure, thereby increasing the risk of cardiovascular disease (6). Antza C et al. observed the correlation between sleep quality and T2DM, confirming that sleep quality is related to T2DM and obesity (7). Consistent with the above research results, the other two research results also showed that short sleep time would increase the incidence of obesity and metabolic syndrome (8, 9). Ogilvie RP et al. pointed out that short sleep duration and other aspects of sleep deprivation were associated with obesity in both cross-sectional and longitudinal studies. There is a potential causal relationship between sleep deprivation and weight gain, which may be related to the impact of sleep on dietary intake or physical activity (8). By contrast, improving sleep quality contributes to weight control (10). Patients with short sleep time and self-reported sleep problems or sleep disorders have a higher risk of developing hypertension (11). Late sleep duration and high sleep variability are mostly associated with adverse health outcomes in adults (12). In addition, the circadian rhythm disorder caused by late sleep will increase the risk of hypertension, T2DM and obesity. Among people who sleep at night, the incidence rate of T2DM increased 2.5 times, and the incidence rate of hypertension increased 1.3 times (13–15). The decreased secretion of melatonin, changes in sleep structure, or increased sympathetic nervous system activity are considered pathophysiological reasons for the relationship between late sleep and hypertension (13). Late night sleepers are more likely to experience health problems, such as unhealthy eating and sedentary behavior (16, 17). The association between short sleep time and obesity, hypertension, T2DM, and cardiovascular disease may be mediated by changes in dietary intake (16). Patients with SA habit, especially those who prefer to use smartphones before bedtime, are more likely to be exposed to nighttime light, which is associated with cardiovascular disease risk factors including BMI, systolic blood pressure, and low density lipoprotein (LDL) (18). A cohort study confirmed that artificial light while sleeping at night was significantly associated with the risk of increased weight and obesity (19). The mechanisms of light exposure affecting sleep have been confirmed by previous research. Firstly, exposure to light will change the circadian rhythm of sleep (20–22). Secondly, light can directly affect sleep and wakefulness (23). Finally, nighttime lighting can delay some activities that were originally scheduled during the day to nighttime (24). For patients with SA habit who prefer to use their phones before bedtime, excessive exposure to artificial lighting may lead to poorer sleep quality, which increases the risk of developing CAD (25, 26).

In summary, although SA habit may have an impact on CAD related risks such as hypertension, obesity, poor sleep quality, and decreased exercise, there have been no reports on the association between SA habit and CAD patients so far. Therefore, it is necessary to explore the role of SA habit in CAD. This study aims to explore the relationship between SA habit and CAD and its severity in Chinese adults using a case-control study.

The main findings of this study were that risk factors for CAD in Chinese adults include age, male gender, hypertension, T2DM, TC, decreased exercise, poor sleep quality, and SA habit. Further analysis also found that SA habit might be related to smoking history, reduced exercise, poor sleep quality, and hyperlipidemia. Therefore, SA habit might be an independent and important predictor of CAD and its related cardiovascular risk factors.

Zou Y et al. conducted a cross-sectional survey using a random cluster sampling method. A total of 2,639 middle school students (1,218 boys and 1,421 girls) aged 12–15 were included, and a significant correlation was observed between SA habit and adolescent hypertension and obesity (4). There were significant differences in SA habit rates among students of different grades, and the SA rate also showed an upward trend with increased weight, which was crucial for hypertension. We observed that patients with SA habit were more likely to experience decreased exercise and hypertension. However, we did not find that SA habit was associated with increased BMI. Overuse of electronic devices, including smartphones, before bedtime can contribute to exposure to blue rich substances at night, which can lead to delayed circadian rhythms and poor physical condition in the morning. The activity of the autonomic nervous system in the heart can significantly increase the users’ heart rate after prolonged use (34). In addition, a study also observed that excessive use of electronic devices such as smartphones in adolescents might lead to a significant circadian rhythm change (35). The mechanisms involved may be severe inhibition of melatonin and delayed circadian rhythm (36).

Compared to patients who were not addicted to smartphones, patients with SA habit were more likely to skip meals, eat unhealthy foods, gain weight, and suffer from sleep disorders (37). Zou Y et al. also observed a correlation between SA habit and poor sleep quality. We used PSQI to evaluate sleep quality and observed a close relationship between SA habit and poor sleep quality. Poor sleep quality and difficulty falling asleep or maintaining a short sleep duration were considered to be negative consequences of SA habit (38, 39). A study has observed the prevalence of SA habit is 42.4% among nurses (40). In the above study, the SA habit is associated with poorer sleep quality and excessive daytime drowsiness among nurses (40). A study on young people found that 75% of youngsters (aged <30 years old) used smartphones before going to bed, which might increase the likelihood of poor sleep quality (41). Being unable to control their smartphone usage even when in bed and worrying about missing information may be the reasons for leaving their smartphones in bed, as they did not want to miss any notifications (42, 43). Al Battashi N et al. also observed that SA habit was associated with sleep problems in adolescents (44). As for the influence of smart phones on sleep quality, in addition to the delay in sleep, there is another possible reason that blue light from smart phones may have a negative impact on the circadian rhythm, leading to negative sleep consequences, such as sleeping later than expected, thus shortening the overall sleep time (45). In conclusion, SA habit was related to poor sleep quality, which was associated with CAD and its related risks such as hypertension, BMI, LDL. Zhang H et al. analyzed the association of PSQI score with blood pressure and hypertension in rural China (33). They enrolled 27,112 individuals aged 18–79 and divided the PSQI score into four parts: <3, 3 -, 6 -, and ≥9. They used a multivariable logistic regression model with hypertension as the dependent variable to analyze, and also completed a meta-analysis to verify the results of the cross-sectional study. The results showed that poor sleep quality was associated with higher hypertension in the general population, which was visible in both males and females. In addition, the risk of hypertension in patients increased with the increase of PSQI score, and the meta-analysis ultimately confirmed that patients with poor sleep quality had significantly higher overall concomitant OR for hypertension. Nedeltcheva AV et al. further explored the relationship between sleep disorders and CAD, and found a connection between sleep disorders and CAD (46). Laugsand LE et al. also confirmed that sleep disorders such as insomnia were closely related to acute myocardial infarction (AMI) (47). In their study, they observed that compared with those who have never experienced such sleep difficulties, people who struggle to fall asleep almost every night had a multiple adjusted risk ratio of 1.45 for AMI, and those who struggle to maintain sleep almost every night had a multiple adjusted risk ratio of 1.30 for AMI. Patients with poor sleep quality were accompanied by circadian rhythm disorders. On the one hand, cardiovascular diseases are often accompanied with regulation of heart rate, blood pressure, and adrenaline (48, 49). Compared with the morning sleep type, the night sleep type was associated with higher resting heart rate, blood pressure, and adrenaline (15, 50). On the other hand, people who go to bed late at night were more likely to lack physical activity and become obese, which were closely related to cardiovascular disease (17). SA users often have the habit of watching their phones at night and prefer to use them before going to bed, which requires the help of screen lighting. Cross-sectional and comparative studies support the impact of artificial light on sleep. People living in electrified communities often sleep later than those without electricity, and in some cases, their sleep time can also be reduced (20, 51). Light patterns affect sleep quality and physical and mental health (52). Exposure to bright light in the day and evening can severely decrease melatonin and somnolence levels, and delay the circadian rhythm (36). Night light intensity is associated with cardiovascular disease risk factors such as BMI, systolic blood pressure, and LDL (18). From a cohort study, artificial light during sleep at night was significantly associated with the risk of weight gain and obesity, especially among women who sleep with a light or television on in their room (19).

Our research results also found an association between SA habit and hyperlipidemia. The correlation between SA and hyperlipidemia was mainly related to TC and LDL levels rather than TG level. In our study, patients with SA were also found to have poor sleep quality in our study, which has been proven to be closely related to hyperlipidemia in some studies (53, 54). Wang D et al. found that compared with participants with good sleep quality, participants with poor sleep quality had significantly higher risk of hyperlipidemia. Poor sleep quality was therefore related to the incidence rate of hyperlipidemia (53). Lemke MK et al. observed that hypercholesterolemia played an important role in the cardiovascular health of truck drivers, and also collected the demography characteristics and sleep variables of the group (54). The results showed that poor sleep quality was closely related to LDL and TC levels in the drivers. Therefore, they suggested that targeted improvement of drivers' sleep quality could curb the risk of arterial atherosclerosis.

Based on the above research confirming the correlation between SA habit and CAD risk factors such as hypertension, BMI, decreased exercise, poor sleep quality, and hyperlipidemia, we conducted a case-control study to investigate the relationship between SA habit and CAD risk in Chinese adults. Our study showed that SA habit was closely related to CAD and its severity. We further conducted subgroup analysis of CAD based on hypertension, age, and sex, and found that there were distribution differences in the hypertension subgroup, ≤55 years old and female subgroups, while this was not the case in the non-hypertension, >55 years old, and male subgroups. The correlation between SA and hypertension has been confirmed in some studies (4), which involved possible mechanisms such as reduced exercise and poor sleep quality. Our study also confirmed that patients with SA may experience decreased exercise and poor sleep quality. Lo K et al. evaluated the correlation between subjective sleep quality and blood pressure or hypertension (55). They conducted a meta-analysis that included 22 studies, and the results showed a significant correlation between poor sleep quality and the likelihood of developing hypertension. People with poor sleep quality had higher average systolic and diastolic blood pressure than normal people. Among middle-aged women in the climacteric period, poor sleep quality and shorter sleep time were related to higher subclinical carotid atherosclerosis (56). Sleep time disorder was considered a modifiable cardiovascular risk factor (57).

To investigate the correlation between SA habit and the severity of CAD in Chinese adults, we divided CAD patients into single vessel, double vessel, and triple vessel lesions based on the number of lesions. The results showed that there were statistical differences in the distribution of SA habit among CAD populations with different degrees, and SA habit was more pronounced in the three-vessel lesion group. We used the Gensini score to quantify the relationship between the severity of coronary artery stenosis and SA. Our study declared that patients with high Gensini score had a higher prevalence of drinking history, hypertension, T2DM, and SA habit. Our study also observed that SA habit increased the risk of factors such hypertension, T2DM, which were associated with the severity of CAD. Therefore, we speculated that SA habit might ultimately participate in the progression of CAD by affecting the risk of hypertension, T2DM.

This study has several limitations. Firstly, the sample of our study was small and from a single center, thereby reducing the testing effectiveness of statistical model. Larger sample and multicenter studies in the future to further confirm the association between SA habit and CAD are needed. Secondly, we did not collect detailed information on smartphone user usage, which were not conducive to explaining the complex relationship between factors such as SA habit and CAD. Thirdly, there was a possibility of selection bias, since we selected patients without history or symptoms of atherosclerotic vascular diseases from the health examination center as controls. Fourthly, given the case-control study design, we could not draw a causal relationship between SA and CAD. Further prospective studies are warranted.

There was a positive correlation of SA habit with CAD and its severity in Chinese adults. Our findings suggest the important role of SA in the development of CAD. However, these results need further confirmation from prospective studies.