Obesity Increases Risk of Ischemic Stroke in Young Adults
Abstract
Background and Purpose—
Body mass index has been associated with ischemic stroke in older populations, but its association with stroke in younger populations is not known. In light of the current obesity epidemic in the United States, the potential impact of obesity on stroke risk in young adults deserves attention.
Methods—
A population-based case–control study design with 1201 cases and 1154 controls was used to investigate the relationship of obesity and young onset ischemic stroke. Stroke cases were between the ages of 15 and 49 years. Logistic regression analysis was used to evaluate the association between body mass index and ischemic stroke with and without adjustment for comorbid conditions associated with stroke.
Results—
In analyses adjusted for age, sex, and ethnicity, obesity (body mass index >30 kg/m2) was associated with an increased stroke risk (odds ratio, 1.57; 95% confidence interval, 1.28–1.94) although this increased risk was highly attenuated and not statistically significant after adjustment for smoking, hypertension, and diabetes mellitus.
Conclusions—
These results indicate that obesity is a risk factor for young onset ischemic stroke and suggest that this association may be partially mediated through hypertension, diabetes mellitus, or other variables associated with these conditions.
Introduction
See related article, p 1435.
Obesity rates in United States have been steadily increasing throughout the past several decades. In 2011 to 2012, the prevalence of obesity in the United States was 16.9% in youth and 34.9% in adults.1 Although obesity is a well-recognized risk factor for stroke in older adults2 and there is evidence for increasing ischemic hospitalization rates for young adults with concurrent increases in obesity,3 few studies have directly examined the association between obesity and early onset stroke. To evaluate this issue, we used data from a case–control study in the Baltimore–Washington area.
Methods
The Stroke Prevention in Young Adults Study was designed as a population-based case–control study of young onset ischemic stroke. During 3 study periods between 1992 and 2008, cases with a first-ever ischemic stroke ages 15 to 49 years were identified by discharge surveillance from 59 hospitals in the greater Baltimore/Washington, DC, area and by direct referral from regional neurologists. Controls were matched to cases by age, sex, region of residence, and, except for the initial study phase, were additionally matched for ethnicity. Details of the study design and case adjudication have been previously described.4
A standardized interview was used to obtain information about stroke risk factors, including age at stroke (or age at interview for controls), ethnicity, smoking status, hypertension, and diabetes mellitus. Height and weight were obtained via self-report during the interview and used to compute body mass index (BMI), calculated as weight (in kg) divided by height (in m) squared. BMI was classified into weight categories according to federal guidelines5 with participants categorized as underweight (BMI<18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obese (BMI>30 kg/m2).
We compared stroke risk factors between stroke cases and controls by t tests and χ2 tests. Odds ratios and confidence intervals were calculated using logistic regression for 3 models: a reduced model adjusted only for age, sex, and race, an intermediate model adjusted for prior covariates and current smoking, and a full model adjusted for these previous covariates plus hypertension and diabetes mellitus. Sequential adjustment was chosen because cigarette smoking is a behavior, whereas hypertension, diabetes mellitus, and obesity cluster together physiologically as a part of the metabolic syndrome.
Results
The study population included a total of 1201 cases and 1154 controls. Table 1 shows that, compared with controls, cases were slightly older, had higher BMI, and had a higher prevalence of current smoking, hypertension, and diabetes mellitus (all P<0.01). Table 2 shows odds ratios for the overweight and obese categories compared with the normal BMI category using the reduced, intermediate, and full models. Table 2 also shows analyses stratified by sex and race and is based on 1168 cases and 1123 controls. For this analysis, the 27 cases and 28 controls in the underweight category were excluded because of our desire to compare overweight and obese to the normal weight category. In addition, to allow comparisons across the 3 models using the same sample, 3 controls and 6 cases were excluded because of missing information on hypertension or diabetes mellitus. Participants in the obese category had an excess risk of stroke under the reduced and intermediate models, but the association was attenuated and no longer statistically significant after additional adjustment for hypertension and diabetes mellitus in the full model. There is a suggestion that BMI is more strongly associated with stroke among men and blacks although the interactions of BMI categories with sex and race were not statistically significant.
Cases (n=1201) | Controls (n=1154) | P Value* | |
---|---|---|---|
Age, y, mean±SD | 40.8±7.1 | 38.6±7.4 | <0.01 |
Men, % | 52.0 | 46.5 | 0.01 |
White, %† | 50.1 | 56.9 | <0.01 |
Hypertension, % | 42.3 | 18.1 | <0.01 |
Diabetes mellitus, % | 16.9 | 4.6 | <0.01 |
Current smoker, % | 44.8 | 29.4 | <0.01 |
BMI, kg/m2, mean±SD | 29.7±7.6 | 27.6±6.1 | <0.01 |
BMI categories, % | <0.0001 | ||
<18.5 | 2.3 | 2.4 | |
18.5–24.9 | 27.0 | 35.6 | |
25.0–29.9 | 31.3 | 33.0 | |
≥30.0 | 39.5 | 29.0 |
BMI indicates body mass index.
*
P value for association with case–control status computed by t test or χ2.
†
Non-whites include: black (44.8% cases vs 38.3% controls) and other ethnicity (5.1% cases vs 4.8% controls).
Reduced Model (Age, Sex, and Race) | Intermediate Model (Age, Sex, Race, and Smoking) | Full Model (Age, Sex, Race, Smoking, HTN, and DM) | |
---|---|---|---|
All (n=2291) | |||
Overweight | 1.12 (0.91–1.38) | 1.13 (0.92–1.40) | 1.02 (0.82–1.27) |
Obese | 1.57 (1.28–1.94) | 1.65 (1.33–2.04) | 1.21 (0.96–1.51) |
Men (n=1147) | |||
Overweight | 1.13 (0.84–1.53) | 1.22 (0.90–1.66) | 1.04 (0.76–1.43) |
Obese | 1.73 (1.27–2.40) | 1.92 (1.40–2.65) | 1.34 (0.96–1.88) |
Women (n=1144) | |||
Overweight | 1.13 (0.84–1.52) | 1.06 (0.78–1.44) | 0.99 (0.72–1.36) |
Obese | 1.46 (1.10–1.95) | 1.42 (1.06–1.91) | 1.07 (0.79–1.46) |
Whites (n=1221) | |||
Overweight | 1.05 (0.80–1.40) | 1.07 (0.80–1.42) | 0.99 (0.74–1.33) |
Obese | 1.37 (1.02–1.82) | 1.40 (1.04–1.88) | 1.04 (0.76–1.43) |
Blacks (n=958) | |||
Overweight | 1.08 (0.76–1.53) | 1.09 (0.76–1.54) | 0.96 (0.67–1.38) |
Obese | 1.62 (1.16–2.25) | 1.71 (1.22–2.39) | 1.26 (0.89–1.79) |
DM indicates diabetes mellitus; and HTN, hypertension.
*
Reference category is normal body mass index.
Discussion
Our results show an association between increased BMI and early onset stroke, which is consistent with studies conducted in older adults.2 The association between BMI and stroke was attenuated after adjustment for hypertension and diabetes mellitus, and no longer achieved statistical significance. From the public health perspective, the unadjusted association is more meaningful because hypertension and diabetes mellitus are at least partially caused by obesity.
Limitations of our report include the use of self-reported height and weight. Although the use of self-reported data to calculate BMI has been found to be valid for identifying relationships in epidemiological studies,6 it is likely that the use of such data will underestimate the association between BMI and stroke risk because obese participants are more likely to underestimate their weight. Furthermore, obesity indices other than BMI, such as waist:hip ratio, have shown stronger associations with stroke risk.7 Additional limitations include potential selection bias in ascertainment of cases and controls, and inability to examine all possible confounders, mediators, and effect modifiers of the association between BMI and stroke risk. Further research in young adults is needed to replicate our findings and to examine potential differences by sex and race. In addition, additional studies should evaluate the association of obesity with ischemic stroke subtypes, which was not possible in this report because of small sample size among stroke subtypes.
Recent reports have shown that the incidence of stroke is decreasing in the overall population and have attributed the decline to reductions in stroke risk factors such as smoking and hypertension.8 Available evidence suggests that young adults may not be sharing in this decline of stroke incidence.9 This report adds to the concern that younger individuals may be experiencing an increased stroke risk resulting from increasing levels of obesity and accompanying comorbidities and supports the need for vigorous public health initiatives to reverse this trend.
References
1.
Ogden CL, Carroll MD, Kit BK, Flegal KM Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311:806–814. doi: 10.1001/jama.2014.732.
2.
Meschia JF, Bushnell C, Boden-Albala B, Braun LT, Bravata DM, Chaturvedi S, et al.; American Heart Association Stroke Council; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; Council on Functional Genomics and Translational Biology; Council on Hypertension. Guidelines for the primary prevention of stroke: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45:3754–3832. doi: 10.1161/STR.0000000000000046.
3.
George MG, Tong X, Kuklina EV, Labarthe DR Trends in stroke hospitalizations and associated risk factors among children and young adults, 1995-2008. Ann Neurol. 2011;70:713–721. doi: 10.1002/ana.22539.
4.
Hamedani AG, Cole JW, Cheng Y, Sparks MJ, O’Connell JR, Stine OC, et al. Factor V Leiden and ischemic stroke risk: the Genetics of Early Onset Stroke (GEOS) study. J Stroke Cerebrovasc Dis. 2013;22:419–423. doi: 10.1016/j.jstrokecerebrovasdis.2011.10.007.
5.
Flegal KM, Graubard BI, Williamson DF, Gail MH Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005;293:1861–1867. doi: 10.1001/jama.293.15.1861.
6.
Spencer EA, Appleby PN, Davey GK, Key TJ Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5:561–565. doi: 10.1079/PHN2001322.
7.
Walker SP, Rimm EB, Ascherio A, Kawachi I, Stampfer MJ, Willett WC Body size and fat distribution as predictors of stroke among US men. Am J Epidemiol. 1996;144:1143–1150.
8.
Koton S, Schneider AL, Rosamond WD, Shahar E, Sang Y, Gottesman RF, et al. Stroke incidence and mortality trends in US communities, 1987 to 2011. JAMA. 2014;312:259–268. doi: 10.1001/jama.2014.7692.
9.
Kissela BM, Khoury JC, Alwell K, Moomaw CJ, Woo D, Adeoye O, et al. Age at stroke: temporal trends in stroke incidence in a large, biracial population. Neurology. 2012;79:1781–1787. doi: 10.1212/WNL.0b013e318270401d.
Information & Authors
Information
Published In
Copyright
© 2015 American Heart Association, Inc.
Versions
You are viewing the most recent version of this article.
History
Received: 26 January 2015
Revision received: 3 March 2015
Accepted: 5 March 2015
Published online: 5 May 2015
Published in print: June 2015
Keywords
Subjects
Authors
Disclosures
None.
Sources of Funding
This work was supported by the Department of Veterans Affairs, the Centers for Disease Control and Prevention, and the National Institutes of Health (R01 NS45012).
Metrics & Citations
Metrics
Citations
Download Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.
- Trends in stroke-related mortality in atrial fibrillation patients in the United States: Insights from the CDC WONDER database, American Heart Journal Plus: Cardiology Research and Practice, 49, (100491), (2025).https://doi.org/10.1016/j.ahjo.2024.100491
- Obesity Medications and Their Impact on Cardiovascular Health: A Narrative Review, Cureus, (2024).https://doi.org/10.7759/cureus.71875
- A Narrative Review of the Best Anesthesia Care for Endovascular Thrombectomy: Early Diagnosis of the Ischemic Stroke and Evaluation of Risk Factors in Female Population, Surgeries, 5, 4, (1056-1071), (2024).https://doi.org/10.3390/surgeries5040085
- Silymarin administration after cerebral ischemia improves survival of obese mice by increasing cortical BDNF and IGF1 levels, Frontiers in Aging Neuroscience, 16, (2024).https://doi.org/10.3389/fnagi.2024.1484946
- White Matter Lesions, Risk Factors, and Etiological Classification in Young versus Old Cerebral Infarction Patients: A Retrospective Study, Clinical Interventions in Aging, Volume 19, (1723-1730), (2024).https://doi.org/10.2147/CIA.S485511
- Association Between TCBI (Triglycerides, Total Cholesterol, and Body Weight Index) and Stroke-Associated Pneumonia in Acute Ischemic Stroke Patients, Clinical Interventions in Aging, Volume 19, (1091-1101), (2024).https://doi.org/10.2147/CIA.S467577
- Ischemic stroke in men 18—50 years of age, Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova, 124, 3, (5), (2024).https://doi.org/10.17116/jnevro20241240325
- Construction of Plasma Sphingosine 1-Phosphate Expression Level and Risk Nomogram in Patients with Ischemic Stroke, Advances in Clinical Medicine, 14, 05, (901-910), (2024).https://doi.org/10.12677/acm.2024.1451505
- Global burden of stroke in adolescents and young adults (aged 15–39 years) from 1990 to 2019: a comprehensive trend analysis based on the global burden of disease study 2019, BMC Public Health, 24, 1, (2024).https://doi.org/10.1186/s12889-024-19551-1
- Temporal Trends of Obesity Among Nebraska Adults: EMR Data Shows a More Rapid Increase Than Projected, Journal of Primary Care & Community Health, 15, (2024).https://doi.org/10.1177/21501319241301236
- See more
Loading...
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Personal login Institutional LoginPurchase Options
Purchase this article to access the full text.
eLetters(0)
eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.
Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.