 |
 |

Body Mass Index, Waist Circumference, and Waist-Hip Ratio on the Risk of Total and Type-Specific Stroke
Gang Hu, MD, PhD;
Jaakko Tuomilehto, MD, PhD;
Karri Silventoinen, PhD;
Cinzia Sarti, MD, PhD;
Satu Männistö, PhD;
Pekka Jousilahti, MD, PhD
Arch Intern Med. 2007;167(13):1420-1427.
ABSTRACT
 |  |
Background Adiposity is an established risk factor for cardiovascular disease, but the relationship of adiposity with the risk of cerebrovascular disease is still to some extent unclear.
Methods We prospectively investigated the association of different indicators of adiposity (body mass index [BMI] [calculated as weight in kilograms divided by height in meters squared], waist circumference, and waist-hip ratio) with total and type-specific stroke incidence among 49 996 Finnish participants who were aged 25 to 74 years and free of coronary heart disease and stroke at baseline.
Results During a 19.5-year follow-up, 3228 people developed an incident stroke event (674 hemorrhagic and 2554 ischemic). Compared with normal-weight men (BMI, 18.5-24.9), the multivariate-adjusted (age, study year, smoking, physical activity, educational level, family history of stroke, and alcohol drinking) hazard ratios among lean (BMI, < 18.5), overweight (BMI, 25.0-29.9), and obese (BMI, 30.0) men were 0.74 (95% confidence interval [CI], 0.18-2.96), 1.23 (95% CI, 1.10-1.37), and 1.59 (95% CI, 1.37-1.83) for total stroke, and 0.49 (95% CI, 0.07-3.50), 1.27 (95% CI, 1.12-1.44), and 1.70 (95% CI, 1.45-2.00) for ischemic stroke, respectively. Among women, the corresponding hazard ratios were 1.87 (95% CI, 1.12-3.14), 1.08 (95% CI, 0.95-1.22), and 1.30 (95% CI, 1.14-1.50) for total stroke, and 1.81 (95% CI, 0.97-3.41), 1.11 (95% CI, 0.96-1.28), and 1.41 (95% CI, 1.21-1.64) for ischemic stroke. Abdominal adiposity, defined as the highest quartile of waist circumference or waist-hip ratio, was associated with a greater risk of total and ischemic stroke in men but not in women.
Conclusions Body mass index was a risk factor for total and ischemic stroke in men and women. Abdominal adiposity was a risk factor for total and ischemic stroke only in men.
INTRODUCTION
Adiposity is an established risk factor for cardiovascular disease,1-2 but the association between adiposity and cerebrovascular disease is still to some extent unclear. Some prospective studies3-9 have found that a high body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) may increase the risk of total stroke, especially ischemic stroke. However, this association disappeared after adjustment for other risk factors, indicating that the effect of BMI on the risk of stroke is mediated through other factors, especially hypertension.3-5,9 Other studies have found no association10-11 or a low BMI associated with a higher risk of stroke.12 In addition, the association between BMI and hemorrhagic stroke remains unclear. Some studies have shown an increased risk of hemorrhagic stroke among lean persons,5, 9, 12 but other studies have found a J-shaped association,8 no association,7 or an increased risk with increasing BMI.6
Several studies13-15 have also suggested that indicators of abdominal adiposity, such as waist-hip ratio, may be a stronger predictor of stroke than general adiposity, measured by BMI. Limited data exist on the association between different indicators of adiposity and the risk of stroke subtypes in men and women. The aim of this study was to examine the association of 3 indicators of adiposity (BMI, waist circumference, and waist-hip ratio) with the risk of total and type-specific stroke incidence.
METHODS
SUBJECTS
Six independent cross-sectional population surveys were carried out in 5 geographic areas of Finland in 1972, 1977, 1982, 1987, 1992, and 1997.16 In 1972 and 1977, a randomly selected sample making up 6.6% of the population born between 1913 and 1947 was drawn. Since 1982, the sample was stratified by area, sex, and 10-year age group according to the World Health Organization (WHO) MONICA (MONItoring trends and determinants of CArdiovascular disease) Project.17 The participation rate varied by year from 74% to 88%.16 The subjects included in the 6 surveys were aged 25 to 64 years, and the 1997 survey also included subjects aged 65 to 74 years. Subjects who participated in more than 1 survey were included only in the first survey cohort. The total sample size of the 6 surveys was 53 166. The final sample comprised 23 967 men and 26 029 women, after excluding the participants with a history of coronary heart disease (n = 1298) or stroke (n = 768) at baseline and the participants with incomplete data on any variables required for this analysis (n = 1104). The participants gave informed consent (verbal in 1972-1992 and signed in 1997). These surveys were conducted according to the ethical rules of the National Public Health Institute, and the investigations were performed in accordance with the Declaration of Helsinki.
BASELINE MEASUREMENTS
A self-administered questionnaire was sent to the participants to be completed at home. The questionnaire included questions on medical history, socioeconomic factors, physical activity, smoking habits, and alcohol consumption. Educational level, measured as the total number of school years, was divided into birth cohort–specific tertiles. Physical activity included occupational, commuting, and leisure-time physical activity, and was merged and regrouped into 3 categories: low, moderate, and high.18-19 Based on the responses, the participants were classified as never smokers, ex-smokers, and current smokers. Current smokers were categorized into those participants who smoked less than 20 or 20 or more cigarettes per day. Because questions on alcohol consumption were different between the first 2 surveys (1972 and 1977) and the latter surveys, the participants were categorized into abstainers and alcohol users. Family history of stroke was defined as a history of those whose mothers or fathers were once diagnosed as having stroke. Subjects who reported having diabetes mellitus diagnosed by a physician were classified as having a history of diabetes mellitus at baseline.
At the study center, specially trained nurses measured height, weight, and blood pressure using the standardized protocol according to the WHO MONICA Project.17 Height and weight were measured without shoes and with light clothing. The measurements of height were rounded to the nearest centimeter, and weight to the nearest 100 g. Blood pressure was measured from the right arm after 5 minutes of sitting using a mercury sphygmomanometer for each survey. After blood pressure measurement, a venous blood specimen was taken. Total cholesterol level was determined by using the Lieberman-Burchard method in 1972 and 1977, and by an enzymatic method (CHOD-PAP; Boehringer Mannheim GmbH, Mannheim, Germany) since 1982. Because the enzymatic method gave 2.4% lower values than the Lieberman-Burchard method, the values measured in 1972 and 1977 were corrected by this percentage. All samples were analyzed in the same central laboratory at the National Public Health Institute.
SUBGROUP MEASUREMENTS
More detailed data on diet and alcohol consumption, and measurement of waist and hip circumferences, were included in the surveys of 1987, 1992, and 1997 (men, n = 9186; and women, n = 10 163). The participants were asked, "How many slices of bread do you eat daily?" The major proportion of fiber (55%) consumption in Finland comes from bread. The frequency of consumption of vegetables and fruits during the past week (< 1 time per week, 1-2, 3-5, and 6-7 times per week) and the frequency of consumption of sausages during the past 12 months (< 1 time per month, 1-2 times per month, 1 time per week, 2 times per week, almost daily, and > 1 time per day) were obtained. Ethanol consumption was categorized into 4 groups (0, 1-34, 35-209, and 210 g/wk in men; and 0, 1-34, 35-139, and 140 g/wk in women).
Waist circumference was measured midway between the lower rib margin and iliac crest. Hip circumference was measured at the level of the widest circumference over the greater trochanters. The measurements of waist and hip were rounded to the nearest half centimeter. Waist-hip ratio was calculated as waist circumference divided by hip circumference.
PROSPECTIVE FOLLOW-UP
The survey cohorts were followed up until the end of 2004 through computerized register linkage by a unique personal identification number. Mortality data were obtained from Statistics Finland, and data on nonfatal events were obtained from the National Hospital Discharge Register. The 8th, 9th, and 10th revisions of the International Classification of Diseases were used to identify subarachnoid (codes 430 and I60) and intracerebral (codes 431 and I61-I62) hemorrhage, intracerebral infarction (codes 432-438 and I63-I66), and any stroke events (codes 430-438 and I60-I66). International Classification of Diseases, Ninth Revision (ICD-9) code 432 was classified as an intracerebral hemorrhage. In the data analyses, we combined all hemorrhagic strokes because the number of cases with subarachnoid hemorrhage was small. The stroke events that occurred before the baseline survey were identified from the Hospital Discharge Register retrospectively and excluded from the analyses. The validity of the diagnosis of acute stroke in Finland is good for hospital discharge register (agreement in 90% for all strokes, 82% for hemorrhage, and 90% for cerebral infarction) and death register (agreement in 97% for all strokes, 95% for hemorrhage, and 92% for cerebral infarction).20 End points during follow-up were incident stroke events, defined as either the first nonfatal stroke event or stroke-related death without a preceding nonfatal event.
STATISTICAL ANALYSES
Differences in risk factors at different levels of BMI were tested using analysis of variance or logistic regression after adjustment for age and study year (Table 1). The Cox proportional hazards model was used to estimate the association of BMI, waist circumference, and waist-hip ratio on the risk of stroke incidence. Body mass index was evaluated in the following 2 ways: (1) as the 4 WHO weight categories (underweight, < 18.5; normal weight, 18.5-24.9 [reference]; overweight, 25.0-29.9; and obese, 30.0) and (2) as a continuous variable. Waist circumference and waist-hip ratio were evaluated in 2 ways: (1) as sex-specific quartiles and (2) as a continuous variable. Different levels of BMI, waist circumference, and waist-hip ratio were included in the models as dummy and categorical variables, and the significance of the trend over different categories of BMI, waist circumference, and waist-hip ratio was tested in the same models by giving an ordinal numeric value for each dummy variable. The proportional hazards assumption in the Cox model was assessed with graphical methods, and with models including time x covariate interactions.21 In general, all proportionality assumptions were appropriate. The analyses were first carried out adjusting for age and study year, and then further for smoking, physical activity, educational level, family history of stroke, and alcohol consumption (fruit, vegetable, sausage, and bread consumption in subgroup analyses) (multivariate model 1), and for systolic blood pressure, total cholesterol level, and history of diabetes mellitus (multivariate model 2). To avoid the potential bias due to possible early weight loss in the year before death, additional analyses were carried out excluding the subjects who died during the first 1 year of follow-up (n = 140). All statistical analyses were performed with a commercially available software program (SPSS for Windows, version 14.0; SPSS Inc, Chicago, Illinois).
|
|
|
|
Table 1. Baseline Characteristics Among the Study Population by Body Mass Index Categories a
|
|
|
RESULTS
During an average 19.5 years of follow-up, 1673 men and 1555 women developed an incident stroke event (674 hemorrhagic and 2554 ischemic). General characteristics of the study population at baseline are presented in Table 1.
When we used WHO categories for BMI, men who were underweight (BMI, < 18.5), overweight (BMI, 25.0-29.9), and obese (BMI, 30.0) had multivariate-adjusted (age, study year, smoking status, physical activity, educational level, family history of stroke, and alcohol drinking [multivariate model 1]) hazard ratios (HRs) of 0.74, 1.23, and 1.59 for total stroke and 0.49, 1.27, and 1.70 for ischemic stroke, respectively, compared with men with a normal weight (BMI, 18.5-24.9) (Table 2). Among women, the corresponding HRs were 1.87, 1.08, and 1.30 for total stroke and 1.81, 1.11, and 1.41 for ischemic stroke. Additional adjustment for systolic blood pressure, total cholesterol level, and history of diabetes mellitus attenuated these associations, particularly in women, but the association remained statistically significant in both sexes. Body mass index did not associate with the risk of hemorrhagic stroke in men and women if we used WHO categories, but a statistically significant U-shaped association was found in women if we divided BMI into 7 categories (< 18.5, 18.5-22.9, 23.0-24.9 [reference group], 25.0-26.9, 27.0-29.9, 30.0-34.9, and 35.0) (P = .004 for trend). In multivariate analyses (model 1), an increased risk of hemorrhagic stroke was found in women with a low BMI (BMI of < 18.5: HR, 2.90 [95% confidence interval (CI), 1.14-7.40]; and BMI of 20.0-22.9: HR, 1.91 [95% CI, 1.30-2.79]) and a high BMI (BMI of 27.0-29.9: HR, 1.60 [95% CI, 1.08-2.36]; and BMI of 35: HR, 1.94 [95% CI, 1.16-3.25]) compared with women with a BMI of 23.0 to 24.9 (data not shown). Further adjustment for systolic blood pressure, total cholesterol level, and diabetes mellitus affected the results only slightly.
|
|
|
|
Table 2. Adjusted Data for Total, Ischemic, and Hemorrhagic Stroke by Body Mass Index Category
|
|
|
When BMI was examined as a continuous variable, multivariate-adjusted HRs for each 1-U increase in BMI were 1.04 (95% CI, 1.03-1.06) for total stroke, 1.05 (95% CI, 1.04-1.07) for ischemic stroke, and 1.01 (95% CI, 0.98-1.04) for hemorrhagic stroke in men. Among women, the HRs were 1.03 (95% CI, 1.02-1.04), 1.04 (95% CI, 1.02-1.05), and 1.00 (95% CI, 0.98-1.03), respectively.
When the analysis was restricted to surveys from 1987 to 1997 (men, n = 9186; and women, n = 10 163), the multivariate-adjusted positive associations of total and ischemic stroke across quartiles of waist circumference or waist-hip ratio were found among men but not among women (Table 3 and Table 4). Men with the highest quartile of waist circumference had multivariate-adjusted HRs (model 1) of 1.83 for total stroke and 2.07 for ischemic stroke, compared with men with the lowest quartile of waist circumference (P < .01 for trend for both) (Table 3). Similarly, men with the highest quartile of waist-hip ratio had multivariate-adjusted HRs (model 1) of 1.81 for total stroke and 2.26 for ischemic stroke, compared with men with the lowest quartile of waist-hip ratio (P < .001 for trend for both) (Table 4). After additional adjustment for systolic blood pressure, total cholesterol level, and history of diabetes mellitus, these associations remained statistically significant in men (P < .05 for trend for all). The relative risk of stroke showed almost no change in the multivariate adjustment (model 1), including a dichotomized measure of alcohol consumption compared with another multivariate adjustment, including 4 categories of alcohol consumption plus other dietary variables (fruit, vegetable, sausage, and bread consumption) (data not shown).
|
|
|
|
Table 3. Adjusted Data for Total, Ischemic, and Hemorrhagic Stroke by Quartile of Waist Circumference a
|
|
|
|
|
|
|
Table 4. Adjusted Data for Total, Ischemic, and Hemorrhagic Stroke by Quartile of Waist-Hip Ratio a
|
|
|
The multivariate-adjusted HRs of total stroke in men were 1.02 (95% CI, 1.01-1.03) for each 1-cm increase in waist circumference (as a continuous variable), and 1.40 (95% CI, 1.21-1.63) for each 0.1-U increase in waist-hip ratio (as a continuous variable). In men, the corresponding HRs of ischemic stroke were 1.02 (95% CI, 1.01-1.04) and 1.48 (95% CI, 1.25-1.75). Neither waist circumference nor waist-hip ratio as a continuous variable predicted the risk of total or ischemic stroke in women, or hemorrhagic stroke in men and women. No significant (P > .01) interactions between sex and any 1 of BMI, waist circumference, and waist-hip ratio on total, ischemic, and hemorrhagic stroke were identified. The exclusion of the subjects who died during the first 1 year of follow-up did not affect the associations between the adiposity indicators and the risk of stroke (data not shown). We also found a positive association between BMI and ischemic stroke risk in nonsmokers and smokers (Table 5).
|
|
|
|
Table 5. Adjusted Data for Ischemic Stroke by Body Mass Index Category, Stratified by Smoking Status
|
|
|
COMMENT
General adiposity, measured by BMI, was associated with an increased risk of total and ischemic stroke in both sexes. Body mass index had a U-shaped association with the risk of hemorrhagic stroke in women. Abdominal adiposity, measured by waist circumference or waist-hip ratio, was associated with an increased risk of total and ischemic stroke in men, but not in women.
The results of the previous studies were contradictory because in some studies BMI has been found as a strong risk factor for stroke,6-8 but not in others.10-11,14 The Honolulu Heart Program did not find an association between BMI and the risk of stroke among relatively lean US men with Japanese origin.11 In a Swedish study7 including 7402 apparently healthy men, BMI had a positive association with the risk of total and ischemic stroke, which is in accordance with our results. However, the researchers did not find any association between BMI and the risk of hemorrhagic stroke.7 In the Nurses' Health Study5 and the Women's Health Study,9 BMI was a risk factor for total and ischemic stroke, but this association was highly mediated by hypertension, diabetes mellitus, and elevated serum cholesterol level. In a recent study12 of 104 928 Japanese men and women, subjects with a BMI of less than 18.5 had a higher risk of total stroke and intraparenchymal hemorrhage compared with those with a BMI of 23.0 to 24.9. Some studies3, 13-15 have also suggested that abdominal adiposity, in particular, would be associated with the increased risk of stroke. A previous international comparison22 provided evidence that high BMI was more highly correlated with high waist-hip ratio in Finland than in other European populations. In the present study, BMI predicted total and ischemic stroke risk among men and women; however, waist circumference or waist-hip ratio predicted total and ischemic stroke risk only in men, but not in women, although there were no significant interactions between sex and waist circumference or waist-hip ratio on stroke risk.
Several studies have examined the association between BMI and the risk of hemorrhagic stroke, and the results are inconsistent. Most studies5, 9, 12 have found an increased risk of hemorrhagic stroke among lean persons. Other studies, however, found a J-shaped association,8 no association,7 or an increased risk with increasing BMI.6 The few hemorrhagic strokes in most of the studies5-7,9, 12 may explain in part the inconsistent results between BMI and hemorrhagic stroke. Only 1 Korean study8 and our study ascertained more than 600 cases of hemorrhagic stroke during follow-up. In the Korean study,8 including 234 864 men, a J-shaped association of BMI with hemorrhagic stroke risk was shown. In the present study, a significant U-shaped association between BMI and the risk of hemorrhagic stroke was found among women, but not among men, if we used 7 categories of BMI. The reason behind this difference in our study is not known. High levels of blood pressure and total cholesterol level may explain at least part of the observed association between high BMI and an increased risk of hemorrhagic stroke, and expanded investigation is required.
Adiposity has been found as a strong risk factor for hypertension,23 diabetes mellitus,24 and high serum cholesterol level,25 and has been the key or an important component of the metabolic syndrome.26 All these factors were associated with an increased risk of stroke or cardiovascular disease,26-30 and were considered as mediating factors for the physiologic effects of adiposity on stroke risk. In the present study, the adjustment for systolic blood pressure, total cholesterol level, and history of diabetes mellitus attenuated the association between BMI and stroke, but BMI remained a statistically significant predictor of total and ischemic stroke in the multivariate model. The failure to control for smoking may also distort the association between adiposity and stroke risk. In the present study, smoking status was considered a confounding factor in the multivariate model and the positive association between BMI and the risk of ischemic stroke was found in nonsmokers and smokers.
There are several strengths and limitations in our study. First, many men and women from a homogeneous population participated in the study. Second, the mean follow-up was sufficiently long to ascertain many type-specific stroke end point events. Third, we had data on standardized measurement of 3 different indicators of adiposity, and many other adiposity-related risk factors, which may modify the association of adiposity with the stroke risk. Because our data allowed for only a dichotomized measure of alcohol consumption in the whole sample, we may not be able to fully control for the effect of this variable on the risk of stroke. Also, we did not have detailed dietary variables in the whole sample. To evaluate the impact of this shortcoming, we performed separate subgroup analyses (surveys of 1987, 1992, and 1997) in the multivariate-adjusted model of a dichotomized measure of alcohol consumption compared with another multivariate-adjusted model of 4 categories of alcohol consumption plus fruit, vegetable, sausage, and bread consumption. In general, the relative risk between BMI and total and ischemic stroke was not influenced substantially or systematically. We cannot completely exclude either the effects of residual confounding due to measurement error in the assessment of confounding factors or some unmeasured factors, such as triglycerides, apolipoprotein B, and other dietary factors.
In conclusion, the present study demonstrates that BMI is associated with an increased risk of total and ischemic stroke in men and women. Furthermore, a substantial additional risk is mediated through adiposity-related risk factors, such as blood pressure, total cholesterol level, and history of diabetes mellitus. Body mass index has a U-shaped association with the risk of hemorrhagic stroke in women. Abdominal adiposity is a risk factor for total and ischemic stroke in men only.
AUTHOR INFORMATION
Correspondence: Gang Hu, MD, PhD, Department of Health Promotion and Chronic Diseases Prevention, National Public Health Institute, Mannerheimintie 166, FIN-00300 Helsinki, Finland (hu.gang{at}ktl.fi).
Accepted for Publication: March 18, 2007.
Author Contributions: Study concept and design: Hu, Tuomilehto, Silventoinen, and Jousilahti. Acquisition of data: Hu, Tuomilehto, and Jousilahti. Analysis and interpretation of data: Hu, Sarti, Männistö, and Jousilahti. Drafting of the manuscript: Hu, Sarti, and Jousilahti. Critical revision of the manuscript for important intellectual content: Hu, Tuomilehto, Silventoinen, Sarti, and Männistö. Statistical analysis: Hu and Sarti. Obtained funding: Hu, Tuomilehto, and Jousilahti. Administrative, technical, and material support: Hu, Tuomilehto, and Jousilahti. Study supervision: Tuomilehto and Sarti.
Financial Disclosure: None reported.
Funding/Support: This study was supported by grant 108297 from the Finnish Academy and by the Finnish Foundation for Cardiovascular Research.
Role of the Sponsors: The funding bodies had no role in data extraction and analyses, in the writing of the manuscript, or in the decision to submit the manuscript for publication.
Author Affiliations: Department of Health Promotion and Chronic Diseases Prevention, National Public Health Institute (Drs Hu, Tuomilehto, Sarti, Männistö, and Jousilahti), and Department of Public Health, University of Helsinki (Drs Hu, Tuomilehto, and Silventoinen), Helsinki, Finland; South Ostrobothnia Central Hospital, Seinäjoki, Finland (Dr Tuomilehto); and School of Public Health, University of Tampere, Tampere, Finland (Dr Jousilahti).
REFERENCES
 |  |
1. Hu G, Tuomilehto J, Silventoinen K, Barengo N, Jousilahti P. Joint effects of physical activity, body mass index, waist circumference and waist-to-hip ratio with the risk of cardiovascular disease among middle-aged Finnish men and women. Eur Heart J. 2004;25(24):2212-2219.
FREE FULL TEXT
2. Hu G, Tuomilehto J, Silventoinen K, Barengo NC, Peltonen M, Jousilahti P. The effects of physical activity and body mass index on cardiovascular, cancer and all-cause mortality among 47 212 middle-aged Finnish men and women. Int J Obes (Lond). 2005;29(8):894-902.
FULL TEXT
|
ISI
| PUBMED
3. Folsom AR, Prineas RJ, Kaye SA, Munger RG. Incidence of hypertension and stroke in relation to body fat distribution and other risk factors in older women. Stroke. 1990;21(5):701-706.
FREE FULL TEXT
4. Tuomilehto J, Rastenyte D, Jousilahti P, Sarti C, Vartiainen E. Diabetes mellitus as a risk factor for death from stroke: prospective study of the middle-aged Finnish population. Stroke. 1996;27(2):210-215.
FREE FULL TEXT
5. Rexrode KM, Hennekens CH, Willett WC; et al. A prospective study of body mass index, weight change, and risk of stroke in women. JAMA. 1997;277(19):1539-1545.
FREE FULL TEXT
6. Kurth T, Gaziano JM, Berger K; et al. Body mass index and the risk of stroke in men. Arch Intern Med. 2002;162(22):2557-2562.
FREE FULL TEXT
7. Jood K, Jern C, Wilhelmsen L, Rosengren A. Body mass index in mid-life is associated with a first stroke in men: a prospective population study over 28 years. Stroke. 2004;35(12):2764-2769.
FREE FULL TEXT
8. Song YM, Sung J, Davey Smith G, Ebrahim S. Body mass index and ischemic and hemorrhagic stroke: a prospective study in Korean men. Stroke. 2004;35(4):831-836.
FREE FULL TEXT
9. Kurth T, Gaziano JM, Rexrode KM; et al. Prospective study of body mass index and risk of stroke in apparently healthy women. Circulation. 2005;111(15):1992-1998.
FREE FULL TEXT
10. Shaper AG, Wannamethee SG, Walker M. Body weight: implications for the prevention of coronary heart disease, stroke, and diabetes mellitus in a cohort study of middle aged men. BMJ. 1997;314(7090):1311-1317.
FREE FULL TEXT
11. Curb JD, Marcus EB. Body fat, coronary heart disease, and stroke in Japanese men. Am J Clin Nutr. 1991;53(6)(suppl):1612S-1615S.
FREE FULL TEXT
12. Cui R, Iso H, Toyoshima H; et al, JACC Study Group. Body mass index and mortality from cardiovascular disease among Japanese men and women: the JACC study. Stroke. 2005;36(7):1377-1382.
FREE FULL TEXT
13. Lapidus L, Bengtsson C, Larsson B, Pennert K, Rybo E, Sjostrom L. Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed). 1984;289(6454):1257-1261.
FREE FULL TEXT
14. Welin L, Svardsudd K, Wilhelmsen L, Larsson B, Tibblin G. Analysis of risk factors for stroke in a cohort of men born in 1913. N Engl J Med. 1987;317(9):521-526.
ABSTRACT
15. 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(12):1143-1150.
FREE FULL TEXT
16. Vartiainen E, Jousilahti P, Alfthan G, Sundvall J, Pietinen P, Puska P. Cardiovascular risk factor changes in Finland, 1972-1997. Int J Epidemiol. 2000;29(1):49-56.
FREE FULL TEXT
17. Geographical variation in the major risk factors of coronary heart disease in men and women aged 35-64 years: the WHO MONICA Project. World Health Stat Q. 1988;41(3-4):115-140.
PUBMED
18. Hu G, Sarti C, Jousilahti P, Silventoinen K, Barengo NC, Tuomilehto J. Leisure time, occupational, and commuting physical activity and the risk of stroke. Stroke. 2005;36(9):1994-1999.
FREE FULL TEXT
19. Hu G, Tuomilehto J, Borodulin K, Jousilahti P. The joint associations of occupational, commuting, and leisure-time physical activity, and the Framingham risk score on the 10-year risk of coronary heart disease. Eur Heart J. 2007;28(4):492-498.
FREE FULL TEXT
20. Leppälä JM, Virtamo J, Heinonen OP. Validation of stroke diagnosis in the National Hospital Discharge Register and the Register of Causes of Death in Finland. Eur J Epidemiol. 1999;15(2):155-160.
PUBMED
21. Cox DR. Regression models and life tables (with discussion). J R Stat Soc B. 1972;34:187-220.
22. Molarius A, Seidell JC, Sans S, Tuomilehto J, Kuulasmaa K. Waist and hip circumferences, and waist-hip ratio in 19 populations of the WHO MONICA Project. Int J Obes Relat Metab Disord. 1999;23(2):116-125.
FULL TEXT
|
ISI
| PUBMED
23. Hu G, Barengo NC, Tuomilehto J, Lakka TA, Nissinen A, Jousilahti P. Relationship of physical activity and body mass index to the risk of hypertension: a prospective study in Finland. Hypertension. 2004;43(1):25-30.
FREE FULL TEXT
24. Hu G, Lindstrom J, Valle TT; et al. Physical activity, body mass index, and risk of type 2 diabetes in patients with normal or impaired glucose regulation. Arch Intern Med. 2004;164(8):892-896.
FREE FULL TEXT
25. Gostynski M, Gutzwiller F, Kuulasmaa K; et al. Analysis of the relationship between total cholesterol, age, body mass index among males and females in the WHO MONICA Project. Int J Obes Relat Metab Disord. 2004;28(8):1082-1090.
FULL TEXT
|
ISI
| PUBMED
26. Grundy SM, Cleeman JI, Daniels SR; et al, American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735-2752.
FREE FULL TEXT
27. Stamler J, Vaccaro O, Neaton JD, Wentworth D. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993;16(2):434-444.
ABSTRACT
28. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet. 2002;360(9349):1903-1913.
FULL TEXT
|
ISI
| PUBMED
29. Hu G, Sarti C, Jousilahti P; et al. The impact of history of hypertension and type 2 diabetes at baseline on the incidence of stroke and stroke mortality. Stroke. 2005;36(12):2538-2543.
FREE FULL TEXT
30. Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K. Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in nondiabetic European men and women. Arch Intern Med. 2004;164(10):1066-1076.
FREE FULL TEXT
CiteULike Connotea Del.icio.us Digg Reddit Technorati Twitter
What's this?
RELATED LETTERS
Waist to Hip Ratio as a Supplement to Body Mass Index
Arthur J. Hartz and Alfred A. Rimm
Arch Intern Med. 2008;168(2):237-238.
EXTRACT
| FULL TEXT
Waist to Hip Ratio as a Supplement to Body Mass Index—Reply
Gang Hu, Jaakko Tuomilehto, Karri Silventoinen, and Pekka Jousilahti
Arch Intern Med. 2008;168(2):238.
EXTRACT
| FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
 |
Influence of Age and Obesity on Serum Estradiol, Estrone, and Sex Hormone Binding Globulin Concentrations following Oral Estrogen Administration in Postmenopausal Women
Karim et al.
J. Clin. Endocrinol. Metab. 2009;94:4136-4143.
ABSTRACT
| FULL TEXT
Initial management of suspected transient cerebral ischaemia and stroke in primary care: implications of recent research
Lasserson
Postgrad. Med. J. 2009;85:422-427.
ABSTRACT
| FULL TEXT
Body mass index and the risk of total and cardiovascular mortality among patients with type 2 diabetes: a large prospective study in Ukraine
Khalangot et al.
Heart 2009;95:454-460.
ABSTRACT
| FULL TEXT
Hyperglycemia and Stroke Mortality: Comparison between fasting and 2-h glucose criteria
Hyvarinen et al.
Diabetes Care 2009;32:348-354.
ABSTRACT
| FULL TEXT
Association of body size and muscle strength with incidence of coronary heart disease and cerebrovascular diseases: a population-based cohort study of one million Swedish men
Silventoinen et al.
Int J Epidemiol 2009;38:110-118.
ABSTRACT
| FULL TEXT
Atherosclerotic Burden Findings in Young Cryptogenic Stroke Patients With and Without a Patent Foramen Ovale
Rodes-Cabau et al.
Stroke 2009;40:419-425.
ABSTRACT
| FULL TEXT
Contribution of Obesity and Abdominal Fat Mass to Risk of Stroke and Transient Ischemic Attacks
Winter et al.
Stroke 2008;39:3145-3151.
ABSTRACT
| FULL TEXT
Waist to Hip Ratio as a Supplement to Body Mass Index--Reply
Hu et al.
Arch Intern Med 2008;168:238-238.
FULL TEXT
Waist to Hip Ratio as a Supplement to Body Mass Index
Hartz and Rimm
Arch Intern Med 2008;168:237-238.
FULL TEXT
|