Background:
The risk factors for cardiovascular and cerebrovascular diseases in young and middle-aged people have not yet been determined. We conducted a meta-analysis to find the risk factors for cardiovascular and cerebrovascular diseases, in order to provide guidance for the prevention of diseases in the young and middle-aged population.
Methods:
We searched PubMed, Embase, Cochrane Library from the establishment of the database to Mar 2022. We included case-control or cohort studies reporting risk factors for cardiovascular and cerebrovascular disease in young and middle-aged adults. We excluded repeated publication, research without full text, incomplete information or inability to conduct data extraction and animal experiments, reviews and systematic reviews. STATA 15.1 was used to analyze the data.
Results:
The pooled results indicated that increased systolic blood pressure was significantly associated with increased risk of any stroke, ischemic stroke and hemorrhagic stroke. Body Mass Index (BMI), current smoking, hypertension, and diabetes were significantly associated with increased risk of any stroke and ischemic stroke. Atrial fibrillation was only significantly associated with increased risk of any stroke. Increased total cholesterol was significantly associated with an increased risk of ischemic stroke, whereas increased triglycerides were significantly associated with a decreased risk of ischemic stroke. In addition, increased hypertension was also significantly associated with an increased risk of acute coronary syndrome.
Conclusion:
Our pooled results show that BMI, current smoking, atrial fibrillation, hypertension, systolic blood pressure, and total cholesterol can be used as risk factors for cardiovascular and cerebrovascular diseases in young people, while triglycerides can be used as protective factors for cardiovascular and cerebrovascular diseases in young and middle-aged adults.
Keywords: cardiovascular, cerebrovascular, meta-analysis, risk factors, young and middle-aged
1. Introduction
Cardiovascular and cerebrovascular disease is characterized by ischemic or hemorrhagic lesions in the brain, heart and systemic tissues.[1] Common cardiovascular and cerebrovascular diseases in the modern population include ischemic stroke, hemorrhagic stroke, coronary heart disease, myocardial infarction, etc.[2] Cardiovascular and cerebrovascular diseases are one of the diseases that seriously threaten human life and health, and have become the first and second causes of death in most countries in the world.[3] From 2007 to 2017, the number of deaths from cardiovascular and cerebrovascular diseases worldwide increased by 21.1%. About 630,000 people died of heart disease in the U.S. in 2015, accounting for a quarter of all deaths.[4]
With the development of social economy, the incidence of cardiovascular and cerebrovascular diseases in young and middle-aged people is getting higher and higher.[5–7] Younger patients have a greater socioeconomic burden among patients in all age groups.[8] Therefore, looking for risk factors for cardiovascular and cerebrovascular diseases in young and middle-aged people can help prevent the occurrence of diseases and reduce the economic burden on society. However, the risk factors for cardiovascular and cerebrovascular diseases in young and middle-aged people have not yet been determined. This study focused on the risk factors of ischemic stroke, hemorrhagic stroke, acute myocardial infarction, acute coronary syndrome and other diseases. Evidence-based medicine is defined as the judicious use of the current evidence in making decisions about the healthcare of individual patients.[9] Research has shown that utilizing an evidence-based strategy to treat patients reduces medical errors, increases individualized patient care, and supports the application of best practices in the clinical setting.[10,11] We used evidence-based medicine to conduct a meta-analysis by summarizing relevant studies to find the risk factors of the above-mentioned major cardiovascular and cerebrovascular diseases, in order to provide guidance for the prevention of diseases in the population.
2. Methods
2.1. Literature inclusion and exclusion criteria
The inclusion criteria were as follows: the study design was a case control or cohort study; patients with cardiovascular and cerebrovascular disease; the patient is young and middle-aged; the language is limited to English.
Exclusion criteria: studies that have not reported relevant risk factors; the subjects of the study were the elderly; duplicate publication; research without full text, incomplete information or inability to conduct data extraction; animal experiments; case report; reviews and systematic reviews.
2.2. Search strategy
In this meta-analysis, we searched PubMed, Embase, Cochrane Library from establishment of the database to Mar 2022. The search terms are as follows: “Acute Coronary Syndrome” “ST Elevation Myocardial Infarction” “Sudden Cardiac Death” “Stroke” “Hemorrhagic Stroke” “Brain Infarction” AND “young people” “young adults” “middle aged” AND “risk factor” “risk factors.”
2.3. Literature screening and data extraction
The literature search, screening, and information extraction were all independently completed by 2 researchers. When there is a dispute over the availability of data and the selection of data, the decision was made after discussion or consultation with a third party. The data extraction included the author, year, study design, country, sample size, sex, age, BMI, number of people with hypertension, diabetes and hyperlipidemia, disease types and the odds ratio (OR) (95%CI) of related risk factors.
2.4. Literature quality assessment
Two researchers independently conducted literature quality evaluations using the Newcastle-Ottawa Scale[12] for cohort and case-control studies. When the opinions are inconsistent, it is decided through discussion or consultation with the third person. The meta-analysis was performed based on the related items of the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement.[13]
2.5. Data synthesis and statistical analysis
STATA 15.1[14] was used to analyze the data. OR (95% Cl) was used to analyze the risk factors of subtype of cardiovascular and cerebrovascular disease. I2 was used to evaluate heterogeneity. If the heterogeneity test was P ≥ .1 and I2 ≤ 50%, it indicated that there is homogeneity between studies, and the fixed effects model was used for combined analysis; if P < .1, I2 > 50%, it indicated that the study is heterogeneous, and sensitivity analysis was used to find the source of heterogeneity. If the heterogeneity was still large, the random effects model was used or we gave up the combination of results and used descriptive analysis. Since there were no more than 5 articles in the study for each indicator, no publication bias detection was carried out in this study.
2.6. Sensitivity analysis
Sensitivity analysis eliminated each included study one by one, and a summary analysis was performed on the remaining studies to assess whether a single included study had an excessive impact on the results of the entire meta-analysis (see Fig. S1–13, http://links.lww.com/MD/I22, Supplemental Content, which demonstrates results of sensitivity analysis). The sensitivity analysis graph shows the change in effect size after the deletion of a study. The circle “○” in the figure represents deleted after the study of the effect measure to change, and “|” represents the confidence interval.
3. Results
3.1. The results of literature search
In this study, a total of 9785 studies were retrieved from the database. After eliminating duplicate studies, 7943 were obtained. After browsing titles and abstracts, we excluded studies that were animal experiments, case reports, reviews and systematic reviews and the subjects of the study were the elderly and 7278 studies were obtained. After browsing full-text, we excluded studies that did not report the outcomes of interest and had no available data. Finally, 18 articles were included in the meta-analysis (Fig. 1).
Figure 1.
Flow diagram for selection of studies.
3.2. Baseline characteristics and quality assessment of the included studies
A total of 14 case-control and 4 cohort studies were included in this meta-analysis. The sample size of patients was 23071 in total. Patients in 10 studies were from Asia, and the patients in the other 8 studies were all Europe and America. The Newcastle-Ottawa Scale score used for quality assessment is equal to or above 6. (Table 1).
Table 1.
Baseline characteristics and quality assessment of the included studies.
| Study | Study design | Coutry | Sample size | Sex (male/female) | Age | BMI (kg/m2) | Hypertension | Diabetes mellitus | Hyperlipidemia | Disease | NOS score |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Wiberg 2006[15] | Cohort study | China | 421 | 421/0 | / | 25.2 ± 3.1 | / | / | / | Any stroke | 9 |
| 308 | 308/0 | / | 25.2 ± 3.0 | / | / | / | Ischemic stroke | ||||
| 86 | 86/0 | / | 24.6 ± 2.6 | / | / | / | Hemorrhagic stroke | ||||
| Harmsen 2006[16] | Cohort study | USA | 7457 | 7457/0 | / | / | / | / | / | Any stroke | 7 |
| Lipska 2007[17] | Case control | India | 214 | 141/73 | 35.0 ± 7.0 | / | 77 | 30 | / | Ischemic stroke | 9 |
| Towfighi 2008[18] | Cohort study | USA | 1061 | 1061/0 | 45.0–54.0 | 28.6 | 310 | 82 | / | Any stroke | 6 |
| Bhat 2008[19] | Case control | USA | 466 | 0/466 | 15.0–49.0 | / | 160 | 66 | 89 | Ischemic stroke | 7 |
| Prugger 2012[20] | Case control | France | 80 | / | 55.5 ± 2.9 | 27.0 ± 4.0 | / | 6 | / | Ischemic stroke | 8 |
| Wang 2014[21] | Case control | China | 86 | 76/10 | 40.0 (23.0–44.0) | 28.0 ± 2.8 | 41 | 18 | / | Acute myocardial infarction | 7 |
| Bergman 2015[22] | Case control | Sweden | 2599 | 1511/1088 | 37.2 ± 6.6 | / | / | / | / | Any stroke | 7 |
| Aigner 2017[23] | Case control | Germany | 2125 | 1317/808 | 44.8 ± 8.2 | / | 950 | 213 | 624 | Any stroke | 7 |
| 2009 | 1247/762 | 44.8 ± 8.2 | / | 879 | 206 | 596 | Ischemic stroke | ||||
| 116 | 70/46 | 45.8 ± 8.2 | / | 71 | 7 | 28 | Hemorrhagic stroke | ||||
| Prestgaard 2017[24] | Cohort study | Norway | 316 | 316/0 | 51.7 ± 5.5 | 25.0 ± 2.8 | / | / | / | Any stroke | 6 |
| 287 | 287/0 | 51.8 ± 5.2 | 24.9 ± 2.8 | / | / | / | Ischemic stroke | ||||
| 29 | 29/0 | 51.0 ± 5.1 | 25.3 ± 2.3 | / | / | / | Hemorrhagic stroke | ||||
| Ge 2018[25] | Case control | China | 104 | 104/0 | 42.0 (40.0–45.0) | 27.8 ± 3.6 | 75 | 0 | 3 | Acute coronary syndrome | 7 |
| Kivioja 2018[26] | Case control | Finland | 961 | 603/358 | / | / | 371 | 81 | / | Ischemic stroke | 8 |
| Fan 2018[27] | Case control | China | 58 | 38/20 | 44.2 ± 7.4 | 24.8 ± 3.5 | 34 | 16 | 41 | Ischemic stroke | 6 |
| Zhang 2020[28] | Case control | China | 60 | 51/9 | 44.4 ± 4.7 | 25.9 ± 2.6 | / | / | / | Ischemic stroke | 7 |
| Sun 2021[29] | Case control | China | 828 | 795/33 | 33.0 (30.0–34.0) | 28.5 ± 4.6 | 402 | 162 | / | Acute coronary syndrome | 8 |
| Xu 2021[30] | Case control | China | 110 | 74/36 | 48.3 ± 6.4 | / | 60 | 39 | 54 | Ischemic stroke | 8 |
| Zhang 2021[31] | Case control | China | 2739 | 2739/0 | / | / | 1113 | 407 | / | Acute myocardial infarction | 7 |
| Chen 2021[32] | Case control | China | 292 | 194/98 | 38.5 ± 6.5 | / | 116 | 55 | 112 | Ischemic stroke | 8 |
| 259 | 183/76 | 36.4 ± 7.4 | / | 113 | 24 | 24 | Hemorrhagic stroke | 7 |
Age (mean ± SD/median with interquartile range/range).
BMI = body mass index, NOS = Newcastle-Ottawa scale.
3.3. Results of meta-analysis
3.3.1. Age.
There were 4 studies reported the association between age and the risk of ischemic stroke. Since there was significant heterogeneity (I2 = 95.3%, P = .000), and sensitivity analyses did not identify studies that had an excessive impact on the results, a meta-analysis was conducted through a random effects model. Pooled results show that there was no significant association between age and the risk of ischemic stroke (OR = 1.29, 95%CI: 0.99–1.68, P = .057; Fig. 2).
Figure 2.
Association between age and the risk of ischemic stroke or hemorrhagic stroke in young and middle-aged adults.
Additionally, there were 2 studies, reported the association between age and the risk of hemorrhagic stroke. Since there was significant heterogeneity (I2 = 71.3%, P = .062), and sensitivity analyses did not identify studies that had an excessive impact on the results, a meta-analysis was conducted through a random effects model. Pooled results show that there was no significant association between age and the risk of hemorrhagic stroke (OR = 1.25, 95%CI: 0.63–2.49, P = .529; Fig. 2).
3.3..2. Sex (Male).
There were 3 studies reported the association between age and the risk of ischemic stroke. Since there was no significant heterogeneity (I2 = 0.0%, P = .454), a meta-analysis was conducted through a fixed effects model. Pooled results show that there was no significant association between sex and the risk of ischemic stroke (OR = 1.22, 95%CI: 0.88–1.71, P = .238; Fig. 3).
Figure 3.
Association between sex (male) and the risk of ischemic stroke in young and middle-aged adults.
3.3..3. BMI.
There were 2 studies reported the association between Body Mass Index (BMI) and the risk of any stroke and 3 studies reported the association between BMI and the risk of ischemic stroke. The results of the heterogeneity test suggest that there is no heterogeneity in the results of the above 2 studies (I2 = 0.0%, P = .734; I2 = 0.0%, P = .426). The pooled results show that an increase in BMI was significantly associated with an increased risk of either any stroke (OR = 1.12, 95%CI: 1.04–1.21, P = .003; Fig. 4) or ischemic stroke (OR = 1.09, 95%CI: 1.02–1.17, P = .009; Fig. 4). In addition, there were 3 studies, reported the association between BMI and the risk of hemorrhagic stroke. Since there was significant heterogeneity (I2 = 53.5%, P = .142), a meta-analysis was conducted through a random effects model. Pooled results show that there was no significant association between BMI and the risk of hemorrhagic stroke (OR = 1.04, 95%CI: 0.76–1.42, P = .818; Fig. 4).
Figure 4.
Association of BMI and with the risk of any stroke, ischemic stroke and hemorrhagic stroke in young and middle-aged adults. BMI = body mass index.
3.3..4. Current smoking.
There were 3 studies reported the association between current smoking and the risk of any stroke. Since there was no significant heterogeneity (I2 = 0.0%, P = .472), a meta-analysis was conducted through a fixed effects model. Pooled results indicated that current smoking was significantly associated with increased risk of any stroke (OR = 1.31, 95%CI: 1.20–1.43, P = .000; Fig. 5).
Figure 5.
Association of current smoking with the risk of any stroke, ischemic stroke and hemorrhagic stroke in young and middle-aged adults.
Additionally, there were 5 studies reported the association between current smoking and the risk of ischemic stroke. Since there was significant heterogeneity (I2 = 76.6%, P = .002), a meta-analysis was conducted through a random effects model. Pooled results indicated that current smoking was also significantly associated with increased risk of ischemic stroke (OR = 1.72, 95%CI: 1.38–2.14, P = .000; Fig. 5).
Furthermore, there were 2 studies reported the association between current smoking and the risk of hemorrhagic stroke. Since there was no significant heterogeneity (I2 = 0.0%, P = .539), a meta-analysis was conducted through a fixed effects model. Pooled results showed that there was no significant association between current smoking and the risk of hemorrhagic stroke (OR = 0.68, 95%CI: 0.41–1.13, P = .138; Fig. 5).
3.4. Family history of coronary heart disease (CHD)
There were 2 studies reported the association between family history of CHD and the risk of acute myocardial infarction. Since there was significant heterogeneity (I2 = 90.1%, P = .001), a meta-analysis was conducted through a random effects model. Pooled results showed that there was no significant association between family history of CHD and the risk of acute myocardial infarction (OR = 1.52, 95%CI: 0.40–5.82, P = .537; Fig. 6).
Figure 6.
Association between family history of CHD and the risk of acute myocardial infarction in young and middle-aged adults. CHD = coronary heart disease.
3.5. Atrial fibrillation
There were 2 studies reported the association between atrial fibrillation and the risk of any stroke. Since there was no significant heterogeneity (I2 = 0.0%, P = .788), a meta-analysis was conducted through a fixed effects model. Pooled results indicated that atrial fibrillation was significantly associated with increased risk of any stroke (OR = 4.12, 95%CI: 2.70–6.29, P = .000; Fig. 7).
Figure 7.
Association of atrial fibrillation with the risk of any stroke and ischemic stroke in young and middle-aged adults.
Additionally, there were 2 studies reported the association between atrial fibrillation and the risk of ischemic stroke. Since there was significant heterogeneity (I2 = 85.7%, P = .008), a meta-analysis was conducted through a random effects model. Pooled results showed that there was no significant association between atrial fibrillation and the risk of ischemic stroke (OR = 4.35, 95% CI: 0.30–63.82, P = .284; Fig. 7).
3.6. Hypertension
There are 3 and 4 studies reported the relationship of hypertension with the risk of any stroke and ischemic stroke, respectively. Heterogeneity analysis results show significant heterogeneity among studies targeting any stroke (I2 = 95.2%, P = .000) and ischemic stroke (I2 = 61.6%, P = .050) (Fig. 8). Sensitivity analysis found that Aigner et al’s study had a significant impact on the association between hypertension and the risk of any stroke. Sensitivity analysis found that Aigner et al’s study had a major impact on the association of hypertension with the risk of any stroke and ischemic stroke. Heterogeneity analysis was performed again after excluding the literature. Since there was no significant heterogeneity (I2 = 0.0%, P = .317), a meta-analysis was conducted through a fixed effects model. Pooled results showed that hypertension was significantly associated with increased risk of any stroke (OR = 10.92, 95%CI: 7.07–16.86, P = .000; Fig. 9). Additionally, since there was no significant heterogeneity (I2 = 47.3%, P = .150), a meta-analysis was conducted through a fixed effects model. Pooled results showed that hypertension was significantly associated with increased risk of ischemic stroke (OR = 1.86, 95%CI: 1.58–2.19, P = .000; Fig. 9).
Figure 8.
Association of hypertension with the risk of any stroke, ischemic stroke, and acute coronary syndrome in young and middle-aged adults (Before sensitivity analysis).
Figure 9.
Association of hypertension with the risk of any stroke, ischemic stroke, and acute coronary syndrome in young and middle-aged adults (After sensitivity analysis).
There were also 2 studies reported the association between hypertension and acute coronary syndrome. Since there was significant heterogeneity (I2 = 85.1%, P = .009), a meta-analysis was conducted through a random effects model. Pooled results showed that hypertension was significantly associated with increased risk of acute coronary syndrome (OR = 2.57, 95%CI: 1.07–6.16, P = .035; Fig. 9).
3.7. Diabetes
There were 3 studies reported the association between diabetes and the risk of any stroke. Heterogeneity analysis showed there was significant heterogeneity (I2 = 94.3%, P = .000) (Fig. 10), and sensitivity analyses found Aigner et al’ study had an excessive impact on the results. After excluding this literature, it was found that the heterogeneity was significantly reduced (I2 = 51.2%, P = .152), a meta-analysis was conducted through a random effects model. Pooled results showed that diabetes was significantly associated with increased risk of any stroke (OR = 4.93, 95%CI: 2.41–10.11, P = .000; Fig. 11).
Figure 10.
Association of diabetes with any stroke and the risk of ischemic stroke in young and middle-aged adults (Before sensitivity analysis).
Figure 11.
Association of diabetes with any stroke and the risk of ischemic stroke in young and middle-aged adults (After sensitivity analysis).
There were also 3 studies reported the association between diabetes and the risk of ischemic stroke. Since there was significant heterogeneity (I2 = 57.4%, P = .096) (Fig. 10), and sensitivity analyses did not identify studies that had an excessive impact on the results, a meta-analysis was conducted through a random effects model. Pooled results showed that diabetes was significantly associated with increased risk of ischemic stroke (OR = 1.89, 95%CI: 1.27–2.79, P = .002; Fig. 11).
3.8. Hyperlipidemia
There were 2 studies reported the association between hyperlipidemia and the risk of any stroke. Since there was significant heterogeneity (I2 = 95.3%, P = .000), a meta-analysis was conducted through a random effects model. Pooled results showed there was no significant association between hyperlipidemia and the risk of any stroke (OR = 3.03, 95%CI: 0.25–36.53, P = .383; Fig. 12). In addition, the pooled results also showed there was no significant association between hyperlipidemia and the risk of ischemic stroke (I2 = 55.1%, P = .136; OR = 1.05, 95%CI: 0.66–1.69, P = .830; enrolling 2 studies; Fig. 12).
Figure 12.
Association of hyperlipidemia with the risk of any stroke and ischemic stroke in young and middle-aged adults.
3.9. Systolic blood pressure
Pooled results showed that increased systolic blood pressure was significantly associated with increased risk of any stroke (I2 = 12.8%, P = .284; OR = 1.30, 95%CI: 1.20–1.40, P = .000; enrolling 2 studies; Fig. 13).
Figure 13.
Association of systolic blood pressure with the risk of any stroke, ischemic stroke and hemorrhagic stroke in young and middle-aged adults (After sensitivity analysis).
There were 5 studies reported the association between systolic blood pressure and the risk of ischemic stroke. Heterogeneity analysis showed there was significant heterogeneity (I2 = 77.6%, P = .001) (Fig. 14), and sensitivity analyses found Zhang et al’ study had an excessive impact on the results. After excluding this literature, it was found that the heterogeneity was significantly reduced (I2 = 0.0%, P = .432), a meta-analysis was conducted through a fixed effects model. Pooled results showed that increased systolic blood pressure was significantly associated with increased risk of ischemic stroke (OR = 1.27, 95%CI: 1.17–1.38, P = .000; Fig. 13).
Figure 14.
Association of systolic blood pressure with the risk of any stroke, ischemic stroke and hemorrhagic stroke in young and middle-aged adults (Before sensitivity analysis).
Furthermore, the pooled results showed that increased systolic blood pressure was significantly associated with increased risk of hemorrhagic stroke (I2 = 0.0%, P = .734; OR = 1.27, 95%CI: 1.03–1.56, P = .023; enrolling 2 studies; Fig. 13).
3.10. Diastolic blood pressure
There were 2 studies reported the association between diastolic blood pressure and the risk of ischemic stroke. Since there was significant heterogeneity (I2 = 73.2%, P = .054), a meta-analysis was conducted through a random effects model. Pooled results showed there was no significant association between diastolic blood pressure and the increased risk of ischemic stroke (OR = 1.12, 95%CI: 0.98–1.29, P = .090; Fig. 15).
Figure 15.
Association between diastolic blood pressure and the risk of ischemic stroke in young and middle-aged adults.
3.11. Fasting blood glucose
There were also 3 studies reported the association between fasting plasma glucose and the risk of ischemic stroke. Since there was no significant heterogeneity (I2 = 0.0%, P = .427), and sensitivity analyses did not identify studies that had an excessive impact on the results, a meta-analysis was conducted through a fixed effects model. Pooled results showed there was no significant association between fasting blood glucose and the risk of ischemic stroke (OR = 1.08, 95%CI: 0.97–1.20, P = .172; Fig. 16).
Figure 16.
Association between fasting blood glucose and ischemic stroke in young and middle-aged adults.
3.12. Total cholesterol
There were also 3 studies reported the association between total cholesterol and the risk of ischemic stroke. Since there was no significant heterogeneity (I2 = 0.3%, P = .367), and sensitivity analyses did not identify studies that had an excessive impact on the results, a meta-analysis was conducted through a fixed effects model. Pooled results showed increased total cholesterol was significantly associated with the increased risk of ischemic stroke (OR = 1.49, 95%CI: 1.13–1.96, P = .005; Fig. 17).
Figure 17.
Association between total cholesterol and the risk of ischemic stroke in young and middle-aged adults.
3.13. Triglyceride
There were 4 studies reported the association between triglyceride and the risk of ischemic stroke. Heterogeneity analysis showed there was significant heterogeneity (I2 = 86.0%, P = .000) (Fig. 18), and sensitivity analyses found Wiberg et al’ study had an excessive impact on the results. After excluding this literature, it was found that the heterogeneity was significantly reduced (I2 = 16.8%, P = .301), a meta-analysis was conducted through a fixed effects model. Pooled results showed that increased triglyceride was significantly associated with a reduced risk of ischemic stroke (OR = 0.55, 95%CI: 0.42–0.72, P = .000; Fig. 19).
Figure 18.
Association between triglyceride and the risk of ischemic stroke in young and middle-aged adults (Before sensitivity analysis).
Figure 19.
Association between triglyceride and the risk of ischemic stroke in young and middle-aged adults (After sensitivity analysis).
4. Discussion
Cardiovascular and cerebrovascular diseases generally refer to heart, cerebral ischemia or hemorrhagic diseases caused by various factors such as diabetes, dyslipidemia, hypertension, overweight or obesity.[33] The 2017 Global Burden of Disease Study shows that cardiovascular and cerebrovascular diseases are still the leading cause of death.[3] Taking stroke as an example, in recent decades, the incidence of stroke in young and middle-aged people has been increasing, accounting for about 10% to 15% of all stroke cases. The increase in young patients has caused more and more economic burdens.[34] In this meta-analysis, we pooled 18 articles enrolling 23071 patients reporting risk factors for cardiovascular and cerebrovascular diseases including ischemic stroke, hemorrhagic stroke, acute myocardial infarction, and acute coronary syndrome, aiming to identify risk factors for cardiovascular and cerebrovascular diseases in young and middle-aged adults (Table 2), so as to provide guidelines for the prevention of the population.
Table 2.
Risk factors associated with different types of disease analyzed (stroke, cute myocardial infarction and acute coronary syndrome).
| Any stroke | |||||
|---|---|---|---|---|---|
| Variables | Heterogeneity | OR | 95%CI (LCI, UCI) | P value | |
| BMI | I 2 = 0.0%, P = .734 | 1.12 | 1.04 | 1.21 | .003 |
| Current smoking | I 2 = 0.0%, P = .472 | 1.31 | 1.20 | 1.43 | .000 |
| Atrial fibrillation | I 2 = 0.0%, P = .788 | 4.12 | 2.70 | 6.29 | .000 |
| Hypertension | I 2 = 0.0%, P = .317 | 10.92 | 7.07 | 16.86 | .000 |
| Diabetes | I 2 = 51.2%, P = .152 | 4.93 | 2.41 | 10.11 | .000 |
| Systolic blood pressure | I 2 = 12.8%, P = .284 | 1.30 | 1.20 | 1.40 | .000 |
| Ischemic stroke | |||||
| Age | I 2 = 95.3%, P = .000 | 1.29 | 0.99 | 1.68 | .057 |
| Sex | I 2 = 0.0%, P = .454 | 1.22 | 0.88 | 1.71 | .238 |
| BMI | I 2 = 0.0%, P = .426 | 1.09 | 1.02 | 1.17 | .009 |
| Current smoking | I 2 = 76.6%, P = .002 | 1.72 | 1.38 | 2.14 | .000 |
| Atrial fibrillation | I 2 = 85.7%, P = .008 | 4.35 | 0.30 | 63.82 | .284 |
| Hypertension | I 2 = 47.3%, P = .150 | 1.86 | 1.58 | 2.19 | .000 |
| Diabetes | I 2 = 57.4%, P = .096 | 1.89 | 1.27 | 2.79 | .002 |
| Hyperlipidemia | I 2 = 95.3%, P = .000 | 3.03 | 0.25 | 36.53 | .383 |
| Systolic blood pressure | I 2 = 0.0%, P = .432 | 1.27 | 1.17 | 1.38 | .000 |
| Diastolic blood pressure | I 2 = 73.2%, P = .054 | 1.12 | 0.98 | 1.29 | .090 |
| Fasting blood glucose | I 2 = 0.0%, P = .427 | 1.08 | 0.97 | 1.20 | .172 |
| Total cholesterol | I 2 = 0.3%, P = .367 | 1.49 | 1.13 | 1.96 | .005 |
| Triglyceride | I 2 = 16.8%, P = .301 | 0.55 | 0.42 | 0.72 | .000 |
| Hemorrhagic stroke | |||||
| Age | I 2 = 71.3%, P = .062 | 1.25 | 0.63 | 2.49 | .529 |
| BMI | I 2 = 53.5%, P = .142 | 1.04 | 0.76 | 1.42 | .818 |
| Current smoking | I 2 = 0.0%, P = .539 | 0.68 | 0.41 | 1.13 | .138 |
| Hyperlipidemia | I 2 = 55.1%, P = .136 | 1.05 | 0.66 | 1.69 | .830 |
| Systolic blood pressure | I 2 = 0.0%, P = .734 | 1.27 | 1.03 | 1.56 | .023 |
| Acute myocardial infarction | |||||
| CHD | I 2 = 90.1%, P = .001 | 1.52 | 0.40 | 5.82 | .537 |
| Acute coronary syndrome | |||||
| Hypertension | I 2 = 85.1%, P = .009 | 2.57 | 1.07 | 6.16 | .035 |
BMI = body mass index, CHD = coronary heart disease, OR = odds ratio.
In analyzing risk factors for stroke, the pooled results first showed that an increase in BMI was significantly associated with an increased risk of any stroke and ischemic stroke, while there was no significant association between BMI and the risk of hemorrhagic stroke. This suggests that obese people are more prone to ischemic stroke. Cerebral thrombosis is the most common type of ischemic stroke, accounting for about 60% of all cerebral infarction, and the etiological basis of cerebral thrombosis is mainly atherosclerosis.[35] Obesity is recognized as an important factor leading to atherosclerosis.[36] Additionally, pooled results indicated that current smoking was significantly associated with increased risk of any stroke and ischemic stroke. Young and middle-aged individuals are the main population of smoking. Given that smoking is a modifiable risk factor, it appears essential to further support tobacco abstinence to prevent ischemic strokes among young adults. Notably, pooled results indicated that atrial fibrillation was significantly associated with increased risk of any stroke but not ischemic stroke, which suggests that atrial fibrillation may be associated with findings in strokes other than ischemic stroke. As a traditional risk factor for cardiovascular and cerebrovascular diseases,[37] hypertension was reported to be significantly associated with increased risk of any stroke and ischemic stroke in our study. Our further study found that systolic blood pressure can be used as a predictor of stroke in young and middle-aged people, and screening the population for systolic blood pressure can prevent any stroke including ischemic stroke and hemorrhagic stroke in young and middle-aged adults. However, according to our pooled results, diastolic blood pressure does not have this predictive role. We continued to explore the association of diabetes with stroke risk and found that diabetes was significantly associated with an increased risk of any stroke and ischemic stroke. Since the current article cannot support us to further explore the relationship between the specific type of diabetes and the risk of stroke, future research needs to carry out more clinical studies to analyze the differences between different types of diabetes. However, pooled results showed there was no significant association between fasting blood glucose and the risk of ischemic stroke, indicating that fasting glucose cannot be used as a laboratory marker for predicting ischemic stroke, and other glucose markers may need to be considered. Interestingly, the pooled results also suggest that an increase in total cholesterol predicts an increased risk of ischemic stroke, while an increase in triglycerides predicts a decreased risk of ischemic stroke.
In exploring the risk factors for cardiovascular diseases, we found that there was no significant association between family history of CHD and the risk of acute myocardial infarction. However, since only 2 studies were included and the findings of Wang et al[21] and Zhang et al[31] were contrary, more studies need to be included in the future to further verify the reliability of the current findings. Furthermore, our pooled results showed that hypertension was significantly associated with increased risk of acute coronary syndrome. With the development of social economy, the incidence of hypertension in young and middle-aged people is gradually increasing,[38] and the incidence of cardiovascular disease is also increasing.[39] Strengthening the prevention of hypertension in young people will help to reduce the incidence of cardiovascular diseases and reduce the social burden.[40]
This meta-analysis also has several limitations. First, we had fewer studies on cardiovascular disease risk factors due to the limited number of articles investigating cardiovascular disease risk factors in young and middle-aged adults. Second, due to the limited number of studies on each indicator, we could not conduct a publication bias analysis, which makes the study potentially publication biased. In the future, we need to continuously include new studies to further verify the current research results. Third, according to the results of the baseline characteristics, there were more men than women, which may be due to gender bias. However, none of the included studies were adjusted for sex, so we could not analyze differences by sex. It is necessary to carry out further epidemiological investigation and analyze the differences between different sexes in future studies.
5. Conclusion
Our pooled results show that BMI, current smoking, atrial fibrillation, hypertension, systolic blood pressure, and total cholesterol can be used as risk factors for cardiovascular and cerebrovascular diseases in young people, while triglycerides can be used as protective factors for cardiovascular and cerebrovascular diseases in young and middle-aged people. The prevention and intervention of the above risk factors will help to prevent the occurrence of diseases and reduce the economic burden on society.
Author contributions
YHW conceived the study, and wrote the manuscript. YX, PW, RL, XLJ and YYK participated in data collection, FFL, CC and XZ participated in data analysis. YZZ conceived the final approval of the version to be submitted and obtaining of funding.
Conceptualization: Yinghua Wu.
Data curation: Yinghua Wu, Yan Xiong, Ping Wang, Rui Liu, Xiaoling Jia, Yuyan Kong, Fangfang Li, Chen Chen, Xia Zhang.
Writing – original draft: Yinghua Wu.
Writing – review & editing: Yuzhen Zheng.
Supplementary Material
Abbreviations:
- BMI =
- body mass index
- CHD =
- coronary heart disease
- OR =
- odds ratio
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
This study was supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region (2019D01A11).
Supplemental Digital Content is available for this article.
The authors have no conflicts of interest to disclose.
How to cite this article: Wu Y, Xiong Y, Wang P, Liu R, Jia X, Kong Y, Li F, Chen C, Zhang X, Zheng Y. Risk factors of cardiovascular and cerebrovascular diseases in young and middle-aged adults: A meta-analysis. Medicine 2022;101:48(e32082).
Contributor Information
Yinghua Wu, Email: 534803539@qq.com.
Yan Xiong, Email: 1728923707@qq.com.
Ping Wang, Email: 652312751@qq.com.
Rui Liu, Email: 304320051@qq.com.
Xiaoling Jia, Email: 1461868600@qq.com.
Yuyan Kong, Email: 1097482135@qq.com.
Fangfang Li, Email: 107923886@qq.com.
Chen Chen, Email: 837338824@qq.com.
Xia Zhang, Email: 417203730@qq.com.
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