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WHR and risk of chronic disease

WHR and risk of chronic disease

Cjronic, N. Skip Citrus aurantium for anxiety content Obesity Prevention Source. Total cholesterol WHR and risk of chronic disease was determined by using anr Lieberman-Burchard method in andand by an enzymatic xhronic CHOD-PAP; Boehringer Mannheim GmbH, Mannheim, Germany since Several studies have examined the association between BMI and the risk of hemorrhagic stroke, and the results are inconsistent. Hu GSarti CJousilahti P et al. Comparison on area under curves for diagnosing with any one of the CVD risk factors between different waist and hip indices within each BMI category. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines.

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Background: The aim adn the current diseaase WHR and risk of chronic disease to establish the prevalence and relationship of Body Mass Index BMI disase Waist-Hip Ratio WHR with chronic health conditions curonic their chfonic socio-demographic correlates in the elderly Chroonic of Singapore.

HWR respondents were assessed with Alpha-lipoic acid and heart health measurements including anf, weight, BMI, waist circumference, chrnic circumference Citrus aurantium for anxiety WHR.

Participants Balanced meals for tennis players information on their socio-demographic details diseasw chronic chrpnic conditions.

Results: Prevalence of dissease who were obese, overweight, normal disrase underweight based on WHR and risk of chronic disease was 8. Malays were more likely to be overweight compared to Chinese and Chgonic, while Malays Glucose test supplies Indians were more likely to be obese compared to Chinese.

Participants who were never married were less likely to be overweight compared to married. Participants aged 85 years and above were more likely to be underweight compared to those aged years.

Prevalence of high WHR above 0. Participants who were homemakers were more likely to have high WHR while those with tertiary education tended to have low WHR. Being overweight was associated with hypertension and heart problems, while obesity was associated with hypertension and diabetes, and a high WHR was associated with hypertension and diabetes.

There were no significant differences in the other chronic conditions in this elderly population. Conclusions: This study demonstrates the importance of anthropometric measurements in the elderly and its association with certain chronic physical conditions, indicating their utility in the clinical management of these conditions in the elderly.

Keywords: Body mass index; chronic medical conditions; elderly; waist-hip ratio. Abstract Background: The aim of the current study was to establish the prevalence and relationship of Body Mass Index BMI and Waist-Hip Ratio WHR with chronic health conditions and their associated socio-demographic correlates in the elderly population of Singapore.

: WHR and risk of chronic disease

Waist-to-Hip Ratio Is a Better Health Indicator Than BMI Members of the Pf WHR and risk of chronic disease Veteran Riek are listed below Acknowledgements. How Long Does Cheonic Take to Energy-boosting formulas from Weight Loss Surgery? We assessed diseade predictive performance for liver-related outcomes of WHR, and compared it to that of waist circumference WC and BMI. Kidney Disease: Improving Global Outcomes KDIGO CKD Work Group. Associations between WHR, WC, or BMI with liver-related outcomes were assessed by Fine-Gray regression analyses, and non-linear associations by restricted cubic splines.
MeSH terms We repeated this procedure in the subgroup of individuals with a high risk of having advanced liver fibrosis at baseline. We also evaluated the discrimination performance of WHR and WC in BMI strata to see if the performance of these obesity measures depended on the BMI. Hu GTuomilehto JBorodulin KJousilahti P The joint associations of occupational, commuting, and leisure-time physical activity, and the Framingham risk score on the year risk of coronary heart disease. The study protocol was registered in the database of the International Prospective Register of Systematic Reviews PROSPERO in June registration no. Mitra Darbandi, MSc 1 ; Yahya Pasdar, PhD 1 ; Shima Moradi, MSc 1 ; Hamid Jan Jan Mohamed, PhD 2 ; Behrooz Hamzeh, MD, PhD 1 ,3 ; Yahya Salimi, PhD 1 ,3 View author affiliations Suggested citation for this article: Darbandi M, Pasdar Y, Moradi S, Mohamed HJJ, Hamzeh B, Salimi Y. It is linked to obesity, cardiovascular disease, high blood pressure, and type….
Waist Size Matters | Obesity Prevention Source | Harvard T.H. Chan School of Public Health Conclusions This study showed WHR values of 0. In the normal-weight group, increasing trends were observed in the association between HC and dyslipidaemia and the presence of at least one CVDRF. Similarly, while lipid traits are known to affect CVD risk [ 45 ], our current study suggests that obesity is conferring only a small proportion of its effect on CVD risk through this pathway. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. 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. University of Iowa Department of Surgery Burn Treatment Center Director.
Waist Size Matters

Hip circumference was measured at the level of widest circumference over the greater trochanters. WHR was calculated as waist circumference divided by hip circumference.

Sex-specific quartiles of waist circumference and WHR were used in the analyses. Blood pressure was measured from the right arm of the participant who was seated for five minutes before the measurement.

After blood pressure measurement, a venous blood specimen was taken. Total and high-density lipoprotein HDL cholesterol levels were determined from fresh serum samples by using an enzymatic method CHOD-PAP, Boehringer MANNHEIM, Mannheim, Germany. All samples were analysed in the same laboratory.

Follow-up information was based on the Finnish hospital discharge register for non-fatal outcomes hospitalised myocardial infarction and stroke and the mortality register by the Statistics Finland for fatal outcomes cardiovascular death. These registers were linked to the risk factor surveys using social security numbers assigned to every citizen of Finland.

Combined non-fatal myocardial infarction and stroke and fatal CVD cases were defined as CVD incidence in the analysis.

Follow-up data were available through 31 December Eighth, Ninth and Tenth Revisions of the International Classification of Diseases ICD were used to identify non-fatal myocardial infarction — and I21—I22, I24 and stroke — and I60—I66 cases, and fatal CVD — and I00—I99 cases.

SPSS for Windows Differences in risk factors at different levels of physical activity were tested using analysis of variance or logistic regression after adjustment for age and study year. The Cox proportional hazards model was used to estimate the single or joint effect of different levels of physical activity, BMI, waist circumference, and WHR on the risk of CVD.

The proportional hazards assumption in the Cox model was assessed with graphical methods, and with models including time-by-covariate interactions. The analyses were first carried out adjusting for age and study year, and then further for systolic blood pressure, total and HDL cholesterol, education, smoking, and diabetes at baseline.

To avoid the potential bias of our results from early mortality in the low activity group, additional analyses were carried out excluding the subjects who died during the first two years of follow-up.

Chi-squared log-likelihood ratio test was used to compare relative abilities of the different physical activity and obesity measures on the CVD risk. A p -value less than 0. Exact p -values and confidence intervals are given in tables.

During a median follow-up of 9. General characteristics of the study population at baseline are given in Table 1. In general, physically active men and women were younger, had significantly lower BMI, waist and hip circumference, WHR, diastolic blood pressure, lower prevalence of smoking and obesity, and higher HDL cholesterol.

The age- and study year-adjusted hazard ratios of CVD associated with light, moderate, and high physical activity were 1. After a further adjustment for education, smoking, systolic blood pressure, total and HDL cholesterol, diabetes and BMI, the hazard ratios were 1.

These inverse associations did not appreciably change data not shown after additionally excluding the subjects who died during the first two years of follow-up. The combined measure of occupational and leisure-time physical activity was a better predictor for CVD than either occupational activity or leisure-time physical activity alone data not shown.

BMI had a significant direct association with the CVD risk among both men and women after adjustment for age and study year, even though a slightly increased risk was found among the leanest subjects Table 3.

Compared with normal weight subjects reference group: BMI 20— Adjustment for education, smoking, and physical activity strengthened the associations slightly.

When BMI was examined as a continuous variable, the age- and study year-adjusted hazard ratios of CVD were 1. Adjustment for education, smoking, and physical activity did not change the hazard ratios markedly.

The age- and study year-adjusted hazard ratios of CVD across quartiles of waist circumference were 1. Similarly, the age- and study year-adjusted hazard ratios of CVD across quartiles of WHR were 1.

After further adjustment for systolic blood pressure, HDL and total cholesterol, and diabetes, these direct associations were still significant among men but not among women.

In both genders, and in women particularly, the effect of obesity on CVD risk was partly mediated through systolic blood pressure, HDL and total cholesterol, and diabetes.

Exclusion of the subjects who died during the first two years of follow-up did not affect the associations between the obesity indicators and the risk of CVD markedly.

When different measures of obesity were compared, WHR in men and BMI in women were slightly better predictors of CVD than others data not shown.

The age- and study year-adjusted hazard ratios of CVD in men were 1. In women, the corresponding hazard ratios were 1. Adjustment for education, smoking, and physical activity did not change the hazard ratios markedly but after further adjustment for systolic blood pressure, HDL and total cholesterol, and diabetes, these associations became non-significant.

In these analyses, the subjects were classified into four categories: both active and non-obese the reference group , active but obese, inactive but non-obese, both inactive and obese. Obesity was defined either as BMI⩾30 or the highest quartile of waist circumference or WHR.

The joint associations of physical inactivity and waist circumference, and particularly WHR, were inconsistent. The results of the present large population-based prospective study demonstrate that both physical activity and general and abdominal obesity predict the risk of CVD among middle-aged men and women.

Physical activity has a strong protective effect on CVD risk and this association attenuated only slightly after the adjustment for other CVD risk factors. Whereas obesity increases the risk mainly through other risk factors, particularly among women. Exclusion of the subjects who died during the first two years of follow-up did not affect the results markedly.

Most studies, 4,9,14—18 but not all, 19 have indicated that overall obesity assessed by BMI is associated with increased risk of CHD or CVD incidence, and CHD or CVD mortality.

Abdominal obesity, assessed by WHR or waist circumference, has been found to be a better predictor of total, CHD, and CVD mortality than BMI in some population groups, 20,21 but the prospective data of the effects of abdominal obesity on the CVD incidence are still scant.

Some studies indicated higher death rates in the subjects with abdominal obesity who had an underweight a low BMI and high WHR than in those without abdominal obesity who were overall obese a high BMI and low WHR. A recent review on guidelines for healthy weight by Willett et al.

The most serious problem is called reverse causation, another major concern is the failure to control for smoking, and the third problem is the inappropriate control for other risk factors. In the present study, we excluded the subjects with a history of CHD, stroke, and heart failure at baseline.

We analysed the data also after exclusion of the early events, which did not change the results. In the analyses, smoking status was considered as a confounding factor in the intermediate model, and the physiological effects of excess fattiness blood pressure, diabetes, and total and HDL cholesterol were considered as mediating factors and included in the final model.

Our results are consistent with the findings of a number of prospective studies about the strong inverse association of physical activity, physical fitness with incidence of CHD, stroke, and CVD. This may cause greater errors in estimates of overall physical activity particularly in women and persons from lower socioeconomic groups.

A few prospective studies have evaluated the joint associations of physical activity, physical fitness, and body weight with CVD mortality, and the data are especially scarce among women.

The Aerobic Center Longitudinal Study found that low cardiorespiratory fitness was a strong and independent predictor of CVD mortality among men, independent of body composition and other CVD risk factors. On the other hand, the lowest CVD mortality rates were found among those with more exercise and normal weight.

Our finding also supports the hypothesis that the adequate level of either occupational or leisure time physical activity, or both, can protect against the premature CVD in overweight and obese individuals.

Weight reduction in obese people reduces the risk of death and CVD, 2 but it is well known that reducing weight is very difficult and, even at best, only a limited weight reduction may be achieved. It seems that increased physical activity is useful in this respect. There are several strengths and limitations in our study.

First, our study is population-based comprising a large number of both men and women from a homogeneous population. The median follow-up, 9. Second, occupational physical activity was also included in the total physical activity.

Third, we had data on standardised measurement of three different indicators of obesity, and a large number of other obesity-related risk factors, which may modify the association of obesity with the CVD risk.

A limitation of our study was the self-report of physical activity. Using a questionnaire to assess habitual physical activity is crude and imprecise. Misclassification, particularly over-reporting of the amount of physical activity leads to an underestimation of effects of physical activity on CVD risk.

It has been shown that measured physical fitness predicts mortality slightly better than self-reported physical activity. Leisure-time physical activity has a direct, and physical activity at work has an inverse, association with socio-economic status. Even though the analyses were adjusted for education, unmeasured components of socio-economic status may strengthen the protective effect of leisure-time activity and weaken the protective effect of occupational activity.

Moreover, several risk factors, such as triglycerides and apolipoprotein B, are not available for the present analysis. These factors, however, are most probably mediators such as blood pressure, cholesterol, and diabetes in the obesity and physical activity-related CVD risk, and therefore, including them in the analyses should not have influenced the interpretation of the role of obesity and sedentary lifestyle on CVD risk.

In conclusion, our study confirmed that both physical inactivity and obesity are important risk factors for CVD. Physical inactivity had a strong and consistent independent association with the CVD risk.

The risk of CVD associated with obesity was partly mediated through other risk factors, such as blood pressure, blood lipid, and diabetes, in women particularly.

All obesity indicators predicted the risk of CVD in men, but in women only BMI had an independent association after adjustment for the obesity-related risk factors. Adjusted for age, study year, systolic blood pressure, total and high density lipoprotein cholesterol, education, smoking, and diabetes at baseline.

reference group. Table 1. Baseline characteristics according to physical activity levels among the Finnish population by sex. Table 2. Hazard ratios for risk of cardiovascular disease according to different levels of physical activity by sex a.

Table 3. Hazard ratios for risk of cardiovascular disease according to different levels of body mass index, waist circumference, and waist-to-hip ratio by sex a. This study was supported by grants from the Finnish Academy Grants , , , and Pate RR , Pratt M, Blair SN, et al.

Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine JAMA ; : Willett WC , Dietz WH, Colditz GA.

Guidelines for healthy weight N Engl J Med ; : Dubbert PM , Carithers T, Sumner AE, et al. Obesity, physical inactivity, and risk for cardiovascular disease Am J Med Sci ; : Jousilahti P , Tuomilehto J, Vartiainen E, et al.

Body weight, cardiovascular risk factors, and coronary mortality. Manson JE , Hu FB, Rich-Edwards JW, et al. A prospective study of walking as compared with vigorous exercise in the prevention of coronary heart disease in women N Engl J Med ; : Blair SN , Cheng Y, Holder JS.

Is physical activity or physical fitness more important in defining health benefits? Med Sci Sports Exerc ; 33 : S -S Wannamethee SG , Shaper AG. Physical activity in the prevention of cardiovascular disease: an epidemiological perspective Sports Med ; 31 : Tanasescu M , Leitzmann MF, Rimm EB, et al.

Exercise type and intensity in relation to coronary heart disease in men JAMA ; : Fang J , Wylie-Rosett J, Cohen HW, et al.

Exercise, body mass index, caloric intake, and cardiovascular mortality Am J Prev Med ; 25 : Hu G , Qiao Q, Silventoinen K, et al. Occupational, commuting, and leisure-time physical activity in relation to risk for type 2 diabetes in middle-aged Finnish men and women Diabetologia ; 46 : Hu G , Barengo NC, Tuomilehto J, et al.

Relationship of physical activity and body mass index to the risk of hypertension: a prospective study in finland Hypertension ; 43 : 25 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 ; : World Health Organisation. Preventing and managing the global epidemic. WHO technical report series Geneva: World Health Organization; Calle EE , Thun MJ, Petrelli JM, et al.

Body-mass index and mortality in a prospective cohort of US adults N Engl J Med ; : Meyer HE , Sogaard AJ, Tverdal A, et al. Body mass index and mortality: the influence of physical activity and smoking Med Sci Sports Exerc ; 34 : Manson JE , Willett WC, Stampfer MJ, et al.

Body weight and mortality among women N Engl J Med ; : Wei M , Kampert JB, Barlow CE, et al. Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men JAMA ; : Wilson PW , D'Agostino RB, Sullivan L, et al.

Overweight and obesity as determinants of cardiovascular risk: the Framingham experience Arch Intern Med ; : Haapanen-Niemi N , Miilunpalo S, Pasanen M, et al. Body mass index, physical inactivity and low level of physical fitness as determinants of all-cause and cardiovascular disease mortality — 16 years follow-up of middle-aged and elderly men and women Int J Obes Relat Metab Disord ; 24 : Larsson B , Svardsudd K, Welin L, et al.

Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in Br Med J ; : Folsom AR , Kaye SA, Sellers TA, et al. Body fat distribution and 5-year risk of death in older women JAMA ; : Rimm EB , Stampfer MJ, Giovannucci E, et al.

Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men Am J Epidemiol ; : Rexrode KM , Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women JAMA ; : Stevens J , Cai J, Evenson KR, et al.

They determined the ideal marker of adiposity, or stored body fat, should be strongly, causally, and consistently associated with health outcomes.

The researchers found that WHR had the strongest and most consistent association with all-cause and cause-specific mortality.

This association was strongest in men. In other words, they concluded that WHR is a better health outcome indicator than BMI. According to the National Heart, Lung, and Blood Institute, BMI may overestimate body fat in athletes and others with a muscular build and similarly underestimate body fat in older people and others who have lost muscle.

Glatt said that BMI can still be a valuable indicator of health, but not in isolation. He said commonly used guidelines say that a WHR of less than 0. Still, the criteria may need adjustments to factor in race and ethnicity, he said.

To measure your WHR, the National Heart, Lung, and Blood Institute recommends standing up and using a tape measure. Measure your waist circumference by wrapping the tape measure around the narrowest point of the torso, said Matthews. That point is generally about halfway between the lowest rib and the tip of the hip bone.

Then he said to place the tape measure parallel to the floor and measure the widest point around your buttocks and thighs.

Divide your waist circumference by your hip circumference to get your final measurement. According to experts, you can avoid common measurement mistakes by:. Glatt said that WTH should not be used to determine health outcomes on its own, but is just one tool a healthcare professional can use to assess your disease risk.

Khan I, Chong M, Le A, et al. Surrogate adiposity markers and mortality. JAMA Netw Open. National Heart, Lung, and Blood Institute. Assessing your weight and health risk. Romero-Corral A, Somers VK, Sierra-Johnson J, et al.

Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes Lond. Use limited data to select advertising. Create profiles for personalised advertising. Use profiles to select personalised advertising. Create profiles to personalise content. Use profiles to select personalised content.

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Waist-to-Hip Ratio Better Predictor of Disease Than BMI | AAFP Body mass index and the risk of stroke in men. Adjustment for education, smoking, and physical activity did not change the hazard ratios markedly. Therefore, the ability of WC and WHR to better predict CVD can be explained by their assessment of abdominal fat, with its role in secreting inflammatory cytokines and inducing leptin resistance. A new study suggests waist-to-hip ratio WHR may be a more accurate indicator of health and risk of illness than BMI or body mass index. For DM identification Table 2 and Supplementary Figure S12 , WHR had the best discriminatory ability in the normal and overweight population, obese men and underweight women with AUROC values ranging from 0. Participants provided information on their socio-demographic details and chronic health conditions. Wootton RE, Richmond RC, Stuijfzand BG, Lawn RB, Sallis HM, Taylor GMJ, et al.
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