Modifiable risk factors for carotid atherosclerosis: a meta-analysis and systematic review

Introduction

Carotid atherosclerosis is a major cause of ischemic stroke, which remains clinically silent for a long time before an outbreak of acute events. As a global public health problem, stroke is the second leading cause for death worldwide (1), which leads to a huge burden on individuals and society because of the high rate of residual disability (2). Therefore, the prevention of the disease in a subclinical phase is important (3). Among the different stages of carotid atherosclerosis, we selected increased carotid intima media thickness (CIMT) and the presence of carotid plaque because these two were the most commonly used parameters (4).

Recently, it was indicated that healthy lifestyles might contribute to a decline in the prevalence of carotid atherosclerosis in the long term (5,6). In addition, a considerable amount of studies suggested that carotid atherosclerosis could be prevented by medications targeting several comorbidities, such as hypertension, diabetes, and dyslipidemia (7). Nonetheless, the conclusions concerning these potentially modifiable risk factors are still in dispute (8,9). As yet no article has been published on the detail of the risk factors for carotid atherosclerosis. Therefore, we performed a meta-analysis and systematic review to explore the modifiable risk factors for carotid atherosclerosis identified in previous reports, which is expected to throw light on the prevention of carotid atherosclerosis.

Methods

Search strategy

We adhered to the meta-analysis in the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines (10). We searched PubMed for studies that reported risk factors for carotid atherosclerosis from January 1962 to October 2018. Search terms were “carotid”, “risk”, and “risk factor” (the detailed retrieval strategy was shown in Supplementary Material). The reference lists of relevant reviews, meta-analyses and systematic reviews were hand-searched for further supplement.

Inclusion and exclusion criteria

Longitudinal and cross-sectional studies were included if they fulfilled the following criteria simultaneously: (I) the study included community-based population, (II) the exposures considered to be risk or protective factors for carotid atherosclerosis were potentially modifiable, (III) the control group were people without carotid atherosclerosis, and (IV) the outcome of carotid atherosclerosis was measured by increased carotid intima-media thickness (CIMT) or carotid plaque burden which included both non-stenotic and stenotic plaques (4). Increased CIMT was defined as CIMT ≥1.0 mm whether in the distal wall of the common carotid artery or in the bulb where there is no plaque and the presence of carotid plaque was defined as CIMT >1.5 mm or focal structures encroaching into the arterial lumen of at least 0.5 mm or 50% of the surrounding CIMT value (2). We restricted our search to those published in English. The detailed exclusion criteria were shown in Figure 1. If there was any disagreement between authors, the articles would be discussed until an agreement was reached.

Figure 1 Flow chart of identified studies.

Data extraction and quality assessment

General characteristics of studies were extracted, including authors, publication year, baseline characteristics (total sample size, recruitment period, mean age and sex distribution), study design (prospective or cross-sectional), follow-up information (mean or maximum follow-up and the number of lost to follow-up), and outcomes (increased CIMT or the presence of carotid plaque). All data were extracted using an electronic spreadsheet. We preferred multivariate-adjusted OR/RR/HR rather than crude results.

Agency for Healthcare Research and Quality (AHRQ) (11) was used to assess the quality of cross-sectional observational studies (Table S1). Newcastle-Ottawa Scale (NOS) was employed to assess the quality of longitudinal studies (Table S2).

Table S1 The quality evaluation of cross-sectional studies by agency for healthcare research and quality (AHRQ)
Full table

Table S2 The quality evaluation of cohort studies by the Newcastle Ottawa scale (NOS)
Full table

Statistical analyses

Heterogeneity among studies was assessed using the I² statistic and values <75%, P>0.05 were considered as possibly low heterogeneity (12). A random effects model was used to quantitatively synthesize data. When the heterogeneity was high, the source would be explored further (13,14). First, sensitivity analyses were performed to examine whether the pooled effect was influenced by omitting any single study. Second, subgroup analyses were conducted according to the characteristics of studies (e.g., different outcomes). Funnel plot and trim-and-fill method were used to evaluate whether the asymmetry of funnel plot was related to publication bias (15). All statistical analyses were performed with R 3.2.0 software.

Ethics approval

It was not required, because the study type of our article is meta-analysis and systematic review.

Results

A total of 14,700 articles were identified, of which 76 with 27 factors met the inclusion criteria. Finally, eleven factors had data eligible for the meta-analysis and all relevant studies were cross-sectional (Figure 2). The general characteristics of the articles included in the meta-analysis were presented in Table 1. A total of 48,847 subjects were included in the meta-analysis, 92.6% studies were published from 2005 onwards and 72.8% samples were recruited from Asia and North America. The age range of all recruited subjects was from 35 to 100. Where reported, the proportion of females in the samples ranged from 18% to 67.2%. More baseline characteristics of the included population were presented in Table S3.

Figure 2 Forest plot shows the risk factors for carotid atherosclerosis in the meta-analysis. OR, odds ratio; 95% CI, 95% confidence interval. Quality Score*, mean quality score of included studies; ^ presence of carotid plaque; # increased carotid intima-media thickness.

Table 1 General characteristics of studies included in the meta-analysis
Full table

Table S3 Baseline characteristics of the included population
Full table

Cigarette smokers and people with metabolic syndrome (including its components of hypertension, dyslipidemia, and diabetes mellitus), hyperuricemia, hyperhomocysteinemia, negative emotion, socioeconomic strain, obstructive sleep apnea syndrome (OSAS), alcohol, air pollution, and childhood sexual abuse are more likely to have carotid atherosclerosis. Furthermore, interventions against risk factors may prevent atherosclerosis.

Modifiable risk factors

Blood pressure

Data from eight studies (16-23) including 12,474 individuals were pooled in the meta-analysis (Figure 2), which showed that hypertension could increase the risk of carotid plaque by 81% (OR =1.81, 95% CI: 1.55–2.13, I²=19%, P=0.28) (Figure S1). Three studies (17,19,23) with 2,732 subjects exhibited hypertension has higher risk of increased CIMT (OR =2.60, 95% CI: 1.33–5.08, I²=84%, P<0.01) (Figure S2).

Figure S1 The forest plot shows the relationship between hypertension and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.81 (95% CI: 1.55–2.13, P=0.28) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with hypertension. CI indicates confidence interval; OR, odds ratio.

Figure S2 The forest plot shows the relationship between hypertension and the increased carotid intima media thickness. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 2.60 (95% CI: 1.33–5.08, P<0.01) in the random effects model. Values more than 1 denote an increased risk for the increased carotid intima media thickness with hypertension. CI, confidence interval; OR, odds ratio.

Additionally, it was indicated that the risk of plaque was significantly greater in people with increased systolic blood pressure (SBP) variability (every 10 mmHg increase) and diastolic blood pressure (DBP) variability (1,24,25). Pulse pressure (PP) variability (every 10 mmHg increase) raises the risk of carotid plaque for both community-based subjects and stroke patients (26,27).

Diabetes mellitus

Seven studies (16,21-24,28,29) with 16,752 patients were included in the meta-analysis (Figure 2). The results showed that diabetics might have carotid plaque than non-diabetics (OR =1.31, 95% CI: 1.13–1.53, I²=0%, P=0.74) (Figure S3).

Figure S3 The forest plot shows the relationship between diabetes mellitus and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.31 (95% CI: 1.13–1.53, P=0.74) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with diabetes mellitus. CI, confidence interval; OR, odds ratio.

Dyslipidemia

The meta-analysis of ten studies (16,21-24,28,30-33) including 12,568 patients showed that patients with hyperlipidemia (OR =1.92, 95% CI: 1.39–2.65, I²=0, P=0.56), hypertriglyceridemia (triglyceride ≥1.7 mmol/L) (OR =1.33, 95% CI: 1.14–1.55, I²=0%, P=0.85), and higher low density lipoprotein (low density lipoprotein ≥3.4 mmol/L) (OR =1.11, 95% CI: 1.08–1.13, I²=0%, P=0.46) were more likely to have carotid plaque (Figures S4,S5,S6). Moreover, there was strong likelihood of positive relationship between lower high density lipoprotein (high density lipoprotein ≤1.0 mmol/L) (OR =1.28, 95% CI: 0.99–1.67, I²=32%, P=0.22) or hypercholesterolemia (total cholesterol ≥5.2 mmol/L) (OR =1.20, 95% CI: 0.80–1.82, I²=6%, P=0.34) with carotid plaque (Figures S7,S8). One cohort study (34) indicated that hypercholesterolemia, hypertriglyceridemia, and higher low density lipoprotein were risk factors for CIMT. Nevertheless, one cross-sectional study (33) failed to prove the relationship of total cholesterol (every 1 mmol/L increase) or triglyceride (every 1 mmol/L increase) with carotid plaque.

Figure S4 The forest plot shows the relationship between hyperlipidemia and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.92 (95% CI: 1.39–2.65, P=0.56) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with hyperlipidemia. CI, confidence interval; OR, odds ratio.

Figure S5 The forest plot shows the relationship between hypertriglyceridemia and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.33 (95% CI: 1.14–1.55, P=0.85) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with hyperlipidemia. CI, confidence interval; OR, odds ratio.

Figure S6 The forest plot shows the relationship between higher low density lipoprotein and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.11 (95% CI: 1.08–1.13, P=0.46) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with higher low-density lipoprotein. CI, confidence interval; OR, odds ratio.

Figure S7 The forest plot shows the relationship between hypercholesterolemia and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.20 (95% CI: 0.80–1.82, P=0.34) in the random effects model. Values across 1 means there are no relationship between hypercholesterolemia and the presence of carotid plaque. CI, confidence interval; OR, odds ratio.

Figure S8 The forest plot shows the relationship between lower high density lipoprotein and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.28 (95% CI: 0.99–1.67, P=0.22) in the random effects model. Values across 1 means there are no relationship between lower high-density lipoprotein and the presence of carotid plaque. CI, confidence interval; OR, odds ratio.

Metabolic syndrome (MetS)

MetS was defined according to the criteria of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP-III) (35). Six studies (21,22,36-39) including 18,058 individuals explored the association between MetS and carotid atherosclerosis, which showed that people with MetS might have more carotid plaque than non- MetS (OR =1.39, 95% CI: 1.23–1.57, I²=8%, P=0.36) (Figure S9). Notably, there was a dose-response relationship between the presence of carotid plaque and an increasing number of components of MetS (OR =1.71, 95% CI: 1.10–2.66, I²=0%, P=0.64 for MetS-1; OR =2.17, 95% CI: 1.39–3.37, I²=0%, P=0.48 for MetS-2; OR =2.21, 95% CI: 1.42–3.46, I²=0%, P=0.56 for MetS-3; OR =2.65, 95% CI: 1.57–4.47, I²=8%, P=0.30 for MetS-4; OR =4.78, 95% CI: 2.60–8.81, I²=0%, P=0.36 for MetS-5) (Figures S10,S11,S12,S13,S14). Consistently, the association was confirmed by one cohort study (40) showing that individuals with MetS had higher risk of carotid plaque (HR =1.92, 95% CI: 1.06–3.47).

Figure S9 The forest plot shows the relationship between metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.39 (95% CI: 1.23–1.57, P=0.36) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with metabolic syndrome. CI, confidence interval; OR, odds ratio.

Figure S10 The forest plot shows the relationship between one component of metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.71 (95% CI: 1.10–2.66, P=0.64) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with one component of metabolic syndrome. CI, confidence interval; OR, odds ratio; MetS-1, one component of metabolic syndrome.

Figure S11 The forest plot shows the relationship between two components of metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 2.17 (95% CI: 1.39–3.37, P=0.48) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with two components of metabolic syndrome. CI, confidence interval; OR, odds ratio; MetS-2, two components of metabolic syndrome.

Figure S12 The forest plot shows the relationship between three components of metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 2.21 (95% CI: 1.42–3.46, P=0.56) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with three components of metabolic syndrome. CI, confidence interval; OR, odds ratio; MetS-3, three components of metabolic syndrome.

Figure S13 The forest plot shows the relationship between four components of metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 2.65 (95% CI: 1.57–4.47, P=0.30) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with four components of metabolic syndrome. CI, confidence interval; OR, odds ratio; MetS-4, four components of metabolic syndrome.

Figure S14 The forest plot shows the relationship between five components of metabolic syndrome and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 4.78 (95% CI: 2.60–8.81, P=0.36) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with five components of metabolic syndrome. CI, confidence interval; OR, odds ratio; MetS-5, five components of metabolic syndrome.

Hyperuricemia

The association between hyperuricemia (uric acid ≥420 µmol/L in man or uric acid ≥360 µmol/L in woman) and carotid plaque was reported in four studies (25,39,41,42) including 17,113 participants. Pooled results indicated that hyperuricemia might increase the presence of plaque (OR =1.57, 95% CI: 1.11–2.22, I²=84%, P<0.01) (Figure S15). Similarly, the increased CIMT was presented in those with higher uric acid level (OR =1.24, 95% CI: 1.04–1.47) (43). Further, people with carotid plaque or stenosis were reported to have higher uric acid level. But another cross-sectional study (44) failed to find the relationship between uric acid and plaque.

Figure S15 The forest plot shows the relationship between hyperuricemia and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.57 (95% CI: 1.11–2.22, P<0.01) in the random effects model. Values more than 1 denote an increased risk for the presence of carotid plaque with hyperuricemia. CI, confidence interval; OR, odds ratio.

Hyperhomocysteinemia

Four studies (17,45-47) with 5,623 individuals were included and a significant positive relationship between hyperhomocysteinemia (homocysteine ≥15 µmol/L) and carotid plaque was found (OR =1.88, 95% CI: 1.19–2.95, I²=78%, P<0.01) (Figure S16). Additionally, one cross-sectional study (48) found CIMT increased 0.06mm as the level of homocysteine elevated per 1 µmol/L.

Figure S16 The forest plot shows the relationship between hyperhomocysteinemia and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.88 (95% CI: 1.19–2.95, P<0.01) in the random effects model. Values more than an increased risk for the presence of carotid plaque with hyperhomocysteinemia. CI, confidence interval; OR, odds ratio.

Smoking

A pooled analysis of six studies (16,23,24,30,49,50) including 7,995 participants indicated that smoking had a significant association with the risk of carotid plaque. Subgroup analyses showed that current smoking (current smokers vs. non-smokers, OR =1.52, 95% CI: 1.14–2.03, I²=59%, P=0.03) conferred greater risk than former smoking (former smokers vs. non-smokers, OR =1.42, 95% CI: 1.08–1.87, I²=9%, P=0.33) for the presence of carotid plaque (Figures S17,S18). Similarly, tobacco smoking is associated with increased CIMT, especially current smokers (51).

Figure S17 The forest plot shows the relationship between current smoking and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.52 (95% CI: 1.14–2.03, P=0.03) in the random effects model. Values more than an increased risk for the presence of carotid plaque with current smoking. CI, confidence interval; OR, odds ratio.

Figure S18 The forest plot shows the relationship between former smoking and the presence of carotid plaque. Each comparison is presented by the name of the first author and the year of publication. The contrast has an OR of 1.42 (95% CI: 1.08–1.87, P=0.33) in the random effects model. Values more than an increased risk for the presence of carotid plaque with former smoking. CI, confidence interval; OR, odds ratio.

Sensitivity analyses

In sensitivity analyses (Table S4), the results were robust for hypertension, hyperhomocysteinemia, MetS, and hypercholesterolemia. For current smoking, the heterogeneity was reduced after omitting one study (30) without changing the significance of the results. For hyperuricemia, the pooled effect became non-significant (OR=1.50, 95% CI: 0.95–2.38) after omitting one study (41) with different races.

Table S4 Sensitivity analysis of the meta-analysis
Full table

Assessment of publication bias

For studies reporting the association between hypertension, diabetes mellitus, MetS, current smoking and the presence of carotid plaque, there was evidence of publication bias. After using the trim and fill method, the result barely changed for hypertension, diabetes mellitus, and MetS, but not for current smoking (Figure S19,S20,S21,S22,S23,S24,S25,S26).

Figure S19 Funnel plot for publication bias in studies on hypertension and the presence of carotid plaque. The asymmetry of the funnel plot suggests that publication bias may exist.

Figure S20 Funnel plot for publication bias in studies on diabetes mellitus and the presence of carotid plaque. The asymmetry of the funnel plot suggests that publication bias may exist.

Figure S21 Funnel plot for publication bias in studies on metabolic syndrome and the presence of carotid plaque. The asymmetry of the funnel plot suggests that publication bias may exist.

Figure S22 Funnel plot for publication bias in studies on current smoking and the presence of carotid plaque. The asymmetry of the funnel plot suggests that publication bias may exist.

Figure S23 After using the trim and filling method, the change of the merger effect was not obvious. The results were moderate, which means hypertension is a risk factor for the presence of carotid plaque.

Figure S24 After using the trim and filling method, the change of the merger effect was not obvious. The results were moderate, which means diabetes mellitus is a risk factor for the presence of carotid plaque.

Figure S25 After using the trim and filling method, the change of the merger effect was not obvious. The results were moderate, which means metabolic syndrome is a risk factor for the presence of carotid plaque.

Figure S26 After using the trim and filling method, the merger effect became non-significant. The results were not moderate, which means the caution is needed in drawing conclusion.

Others

Some modifiable factors could not be included in the meta-analysis due to insufficient data, consisting of sexual abuse in early life (52), air pollution (53,54), socioeconomic strain (55-57), negative emotion (58-60), lifestyles (drinking, physical activity, and sleep duration) (5,61-64), diet (vitamin supplementation, egg consumption, vegetable intake and fish consumption) (65-72), medications (antihypertensive drugs, lipid-lowering drugs, and glucose-lowering drugs) (73-82), and pre-existing disease (OSAS) (apnea-hypopnea index >15 events/h) (83,84) in mid-to-late life (Figure 3 and Table S5).

Figure 3 Factors showing significant positive and negative association with carotid atherosclerosis. DM, diabetes mellitus; MetS, metabolic syndrome; Hcy, homocysteine; HDL, how density lipoprotein; LDL, low density lipoprotein; TC, total cholesterol; TG, Triglyceride; OSAS, obstructive sleep apnea syndrome; CPAP, continuous positive airway pressure. Risk factors of meta-analysis are above the dotted line; Risk factors of systematic review are below the dotted line; The dots with four different filled ratios below risk factors represent different total sample size ranges; Different colors represent different quality score ranges.

Table S5 General characteristics of studies included in the systematic reviews
Full table

Discussion

There were 27 studies included in the meta-analysis and 49 studies included in the systematic review. The meta-analysis suggested that dyslipidemia, hyperhomocysteinemia, hypertension, hyperuricemia, smoking, MetS, and diabetes mellitus could increase the risk of carotid plaque. Some low- and medium-quality references were included in the meta-analysis and systematic review; therefore, more high-quality and large-scale prospective studies were needed to obtain more reliable results.

It is known that atherosclerosis affects other vascular beds before it causes significant carotid disease. The prevalence of carotid atherosclerosis and carotid plaque was 27.22% and 20.15% of Chinese people aged 30–79 years in 2010 (85). Among patients with diagnosed coronary artery disease, 56.3% patients had raised CIMT, 74.8% patients had carotid plaques, and 8.4% patients had stenosis in carotid arteries (86). Patients with coronary artery disease more often had multiple plaques (86.7% versus 13.8%, P<0.001) (87). This suggests that coronary artery disease may be an early marker of carotid atherosclerosis.

MetS and its components were associated with both the presence and the progression of carotid atherosclerosis via multiple pathways. The association of hypertension with carotid atherosclerosis might be explained by hemodynamic changes which were related to the severity of CIMT (88). High plasma glucose levels could induce carotid structural changes by promoting endothelial dysfunction and vascular smooth muscle cell proliferation (8). Dyslipidemia might play an important role through the influx of lipids into the sites of vascular lesions. Interestingly, it was showed that higher high-density lipoprotein could reverse the transport of cholesterol and return it to the liver to protect against carotid atherosclerosis (89). The effect of triglyceride on carotid atherosclerosis was controversial because the criteria of hypertriglyceridemia were inconsistent. Recently, a large number of studies have been conducted to investigate whether drugs targeting comorbidities could reduce the incidence of carotid atherosclerosis. Some cohort studies showed that medications including antihypertensive drugs, lipid-lowering drugs and glucose-lowering drugs were protective against CIMT progression. The protective role of these drugs in atherosclerosis relies not only on their therapeutic effects on the pre-existing disease, but also on their direct protective effects on the arterial wall (75). A number of longitudinal studies showed that long-term use of lipid-lowering drugs for prevention of atherosclerosis might be more effective than short-term use (78,90). Moreover, the results in our analysis were supportive of the roles of glucose-lowering drugs in preventing CIMT progression (81,82,91). However, one cohort study showed no relationship between glucose-lowering drugs and the progression of CIMT, which could be explained either by insufficient follow-up or by the different inclusion criteria for people free from diabetes (80).

In addition, it was indicated that hyperuricemia could increase the occurrence of carotid plaque and accelerate CIMT progression through the production of reactive oxygen species, which could lead to oxidative stress and endothelial dysfunction (92). Besides, OSAS was reported to have a similar impact on carotid atherosclerosis (83), especially in rapid eye movement sleep (93), which may be attributed to nocturnal hypoxemia that could augment local inflammatory responses and exacerbate vessel damage in carotid arteries (94). Therefore, continuous positive airway pressure (CPAP) was considered the treatment for OSAS by ameliorating inflammation to protect against carotid atherosclerosis (95).

Negative emotion including depression, anger, and anxiety was identified as a risk factor for the progression of carotid atherosclerosis by many cohort studies (58,96), which might be accounted for by sympathetic nervous system hyperreactivity, abnormalities in platelet function, hypercortisolemia, endothelial dysfunction, and heart rate variability (97). One cohort study (59) failed to prove that depression symptoms could increase the risk of CIMT, but the inconsistencies could be explained by threshold effect (depression vs. depression symptoms). The relationship between anger and CIMT was controversial according to different socioeconomic status (SES). People with low SES would have a greater likelihood of increased CIMT (52,55,98). Business workers are considered to have higher CIMT when compare with factory workers (99). More evidence is required to explore the relationship between social, psychological condition and carotid atherosclerosis. Moreover, psychosocial interventions may play an important role in the prevention of carotid atherosclerosis.

Healthy lifestyles (e.g., no smoking, little drink and exercise) could protect against atherosclerosis through increasing endothelial dilatory factors and blood volume in the carotid artery. The mechanism for the influence of smoking on carotid atherosclerosis might be attributed to chronic inflammation which could damage endothelial cells exposed to circulating thrombogenic factors. These factors might increase macrophage infiltration and plaque thrombogenicity (49). One longitudinal study identified current smoking is related with extracranial carotid atherosclerosis but not with intracranial artery (100). Interestingly, if mothers smoked in pregnancy, children had thicker CIMT, and the impact was stronger if both parents smoked during pregnancy (101). Drinking could increase low density lipoprotein oxidation and oxidative stress to accelerate the progression of atherosclerosis when a man consumes alcohol over 40 g/d, and the CIMT progression had a dose-response relationship with alcohol intake, no matter what he drinks: beer, wine or spirits (102). Moderate exercise could increase antioxidant stress and anti-inflammatory processes, which could protect against the progression of carotid atherosclerosis (5). Shorter sleep duration may have higher CIMT in Western populations rather than Asian populations (103). More evidence is needed to confirm the association between sleep duration and carotid atherosclerosis.

Compared with a low-fat diet, a long-term use of the Mediterranean diet prevented the progression of carotid atherosclerosis in patients who were newly diagnosed with type 2 diabetes. Because Mediterranean diet is rich in vegetables and fish, which have beneficial effects on carotid via inhibition of oxidative stress (71). A number of cohort studies showed that vitamin supplementation (including vitamin C, vitamin B, or vitamin E) could protect from CIMT progression, and it was speculated that the potential mechanism was the improved endothelial vasodilator function, but the effect might depend on dose (68). Vitamin B12 deficiency may increase the risk of carotid atherosclerosis by elevating total homocysteine (104), and vitamin B supplementation may slow the progression of carotid plaque burden by reducing homocysteine (105). Further longitudinal studies should be conducted to clarify the association between diet and carotid atherosclerosis.

Strength and limitations

As far as we know, this is the first meta-analysis and systematic review exploring the modifiable risk factors for carotid atherosclerosis. We tried to search all available studies and synthesise all suitable data.

Our study had a few limitations. First, our meta-analysis was based on cross-sectional studies, which could not reflect causal links between risk factors and carotid atherosclerosis. Hence, we carried out a systematic review based on the longitudinal studies. Second, as the analysis included observational studies, some unmeasured confounding factors and biases might exist. Therefore, the quality assessment of individual studies was carried out. Third, the number of population was relatively small for some risk factors, which should be clarified with caution. Fourth, there was publication bias when exploring the association between current smoking and the presence of carotid plaque, but the result was robust after sensitivity analyses. Therefore, the conclusion should be drawn with caution.

Conclusions

The current meta-analysis and systematic review indicated that pre-existing disease, negative emotion, lifestyle, and diet could increase the risk of carotid atherosclerosis, suggesting that these factors may serve as prevention targets. More investigation is needed to clarify the association of mood, lifestyle, and medication with carotid atherosclerosis. Further good-quality prospective studies are warranted.

Supplementary

Retrieval strategy

[PubMed]

((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((risk) OR risk factor) OR hypertension) OR hypertensive disease) OR blood pressure) OR BP) OR systolic blood pressure) OR SBP) OR diastolic blood pressure) OR DBP) OR diabetes) OR diabetes mellitus) OR DM) OR hyperglycemia) OR hyperlipidemia) OR hyperlipaemia) OR dyslipidemia) OR triglyceride) OR TG) OR high density lipoprotein) OR HDL) OR low density lipoprotein) OR LDL) OR cholesterin) OR cholesterol) OR hypercholesterolemia) OR apolipoprotein) OR Apo) OR BMI) OR body mass index) OR overweight) OR overload) OR obesity) OR high weight circumference) OR fat) OR adiposis) OR corpulence) OR metabolic syndrome) OR Mets) OR metabolic dysfunction) OR metabolic disorder) OR metabolic disturbance) OR smoking) OR smoke) OR smoker) OR tabacco) OR nicotine addiction) OR uric acid) OR UA) OR hyperuricemia) OR hyperuricaemia) OR homocysteine) OR HCY) OR homocystinemia) OR diet) OR food) OR wine) OR alcohol) OR drinking) OR drink) OR drinker) OR vitamin) OR niacin) OR nicotinic acid) OR folic acid) OR folate) OR folacin) OR cobalamin) OR sport) OR exercise) OR movement) OR activity)) AND (carotid)) AND (((((prospective) OR cohort) OR follow) OR longitudinal) OR nested case-control)

Acknowledgments

Funding: This work was supported by grants from Taishan Scholars Program of Shandong Province (ts201511109 and tsqn20161079) and Qingdao Key Health Discipline Development Fund.

Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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