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Associations of hip and thigh circumferences independent of waist circumference with the incidence of type 2 diabetes: The Hoorn Study

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  • Amsterdam University Medical Centers - Vrije Universiteit

Abstract and Figures

The higher risk of type 2 diabetes in persons with a high waist-to-hip ratio (WHR) or waist-to-thigh ratio (WTR) has mostly been attributed to increased visceral fat accumulation. However, smaller hip or thigh circumference may also explain the predictive value of the WHR or WTR for type 2 diabetes. This study considered prospectively the association of hip and thigh circumferences, independent of waist circumference, with the incidence of type 2 diabetes. The Hoorn Study is a population-based cohort study of diabetes. A total of 1357 men and women aged 50-75 y and nondiabetic at baseline participated in the 6-y follow-up examination. Glucose tolerance was assessed by use of a 75-g oral-glucose-tolerance test. Baseline anthropometric measurements included body mass index (BMI) and waist, hip, and thigh circumferences. Logistic regression analyses showed that a 1-SD larger hip circumference gave an odds ratio (OR) for developing diabetes of 0.55 (95% CI: 0.36, 0.85) in men and 0.63 (0.42, 0.94) in women, after adjustment for age, BMI, and waist circumference. The adjusted ORs for a 1-SD larger thigh circumference were 0.79 (0.53, 1.19) in men and 0.64 (0.46, 0.93) in women. In contrast with hip and thigh circumferences, waist circumference was positively associated with the incidence of type 2 diabetes in these models (ORs ranging from 1.60 to 2.66). Large hip and thigh circumferences are associated with a lower risk of type 2 diabetes, independently of BMI, age, and waist circumference, whereas a larger waist circumference is associated with a higher risk.
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1192 Am J Clin Nutr 2003;77:1192–7. Printed in USA. © 2003 American Society for Clinical Nutrition
Associations of hip and thigh circumferences independent of waist
circumference with the incidence of type 2 diabetes: the Hoorn Study
1–3
Marieke B Snijder, Jacqueline M Dekker, Marjolein Visser, Lex M Bouter, Coen DA Stehouwer, Piet J Kostense, John S Yudkin,
Robert J Heine, Giel Nijpels, and Jacob C Seidell
ABSTRACT
Background: The higher risk of type 2 diabetes in persons with
a high waist-to-hip ratio (WHR) or waist-to-thigh ratio (WTR) has
mostly been attributed to increased visceral fat accumulation.
However, smaller hip or thigh circumference may also explain the
predictive value of the WHR or WTR for type 2 diabetes.
Objective: This study considered prospectively the association of
hip and thigh circumferences, independent of waist circumference,
with the incidence of type 2 diabetes.
Design: The Hoorn Study is a population-based cohort study of
diabetes. A total of 1357 men and women aged 50–75 y and non-
diabetic at baseline participated in the 6-y follow-up examination.
Glucose tolerance was assessed by use of a 75-g oral-glucose-
tolerance test. Baseline anthropometric measurements included
body mass index (BMI) and waist, hip, and thigh circumferences.
Results: Logistic regression analyses showed that a 1-SD larger
hip circumference gave an odds ratio (OR) for developing diabetes
of 0.55 (95% CI: 0.36, 0.85) in men and 0.63 (0.42, 0.94) in
women, after adjustment for age, BMI, and waist circumference.
The adjusted ORs for a 1-SD larger thigh circumference were 0.79
(0.53, 1.19) in men and 0.64 (0.46, 0.93) in women. In contrast
with hip and thigh circumferences, waist circumference was pos-
itively associated with the incidence of type 2 diabetes in these
models (ORs ranging from 1.60 to 2.66).
Conclusion: Large hip and thigh circumferences are associated
with a lower risk of type 2 diabetes, independently of BMI, age,
and waist circumference, whereas a larger waist circumference is
associated with a higher risk. Am J Clin Nutr 2003;77:1192–7.
KEY WORDS Hip circumference, thigh circumference,
waist-to-hip ratio, waist circumference, BMI, body composition,
fat distribution, type 2 diabetes, insulin resistance, the Hoorn
Study
INTRODUCTION
Although the dramatic worldwide increase in the incidence of
obesity, and consequently in the incidence of type 2 diabetes, has
been recognized, the exact etiologic link between these remains
unclear. It was observed in the Hoorn Study that the waist-to-hip
ratio (WHR) and not body mass index (BMI) is an important inde-
pendent predictor of incident diabetes in 50–75-y-olds (1). This
result indicates that fat distribution may be a better predictor for
progression to type 2 diabetes than is BMI, which is also sug-
gested by studies that examined the WHR or the waist-to-thigh
1
From the Institute for Research in Extramural Medicine, VU University
Medical Center, Amsterdam (MBS, JMD, MV, LMB, CDAS, PJK, JSY, RJH,
GN, and JCS); the Department of Medicine, Diabetes and Cardiovascular Dis-
ease Academic Unit, University College London Medical School, London
(JSY); and the Department of Nutrition and Health, Faculty of Earth and Life
Sciences, Vrije Universiteit, Amsterdam (JCS).
2
Supported by the Dutch Diabetes Research Foundation, project number
96.111.
3
Reprints not available. Address correspondence to MB Snijder, Institute
for Research in Extramural Medicine, VU University Medical Center, Van der
Boechorststraat 7, 1081 BT Amsterdam, Netherlands. E-mail: mb.snijder.
emgo@med.vu.nl.
Received July 29, 2002.
Accepted for publication November 4, 2002.
ratio (WTR) (2–6). In particular, the accumulation of visceral fat
is assumed to play an important role in the etiology of diabetes by
overexposing the liver to free fatty acids, resulting in insulin
resistance and hyperinsulinemia (7–9).
Evidence, however, that the strong predictive value of the WHR
or WTR for type 2 diabetes is not solely due to abdominal fat
accumulation (as indicated by waist circumference) is growing.
Cross-sectional studies showed that a larger hip circumference is
associated with a lower prevalence of self-reported type 2 diabetes
and lower fasting glucose concentrations, independently of BMI
and waist circumference (10, 11). We obtained similar results in
the Hoorn Study for both hip and thigh circumferences (12).
In one prospective study of Chinese men and women, hip cir-
cumference was positively associated with the incidence of
type 2 diabetes (13). In that study, however, neither waist cir-
cumference nor BMI was taken into account. To our knowledge,
only one prospective study of the specific association of hip cir-
cumference with the incidence of diabetes has been carried out
in whites. That study found a larger hip circumference to be
associated with a lower incidence of several cardiovascular end-
points and diabetes, independently of waist circumference (14).
However, the latter study was limited to women and in both
prospective studies the presence of diabetes was not examined
on the basis of an oral-glucose-tolerance test (OGTT).
In the Hoorn Study, a population-based cohort study of glucose
tolerance, both men and women were included and a 75-g OGTT
was performed. The aim of the present study was to investigate
the associations of hip and thigh circumferences independent of
waist circumference with the incidence of type 2 diabetes and with
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HIP AND THIGH CIRCUMFERENCES AND TYPE 2 DIABETES 1193
TABLE 1
Baseline characteristics of the men and women
1
Men (n = 619) Women (n = 738)
Age (y) 60.2 ± 6.9 60.4 ± 6.9
BMI (kg/m
2
) 25.9 ± 2.7
2
26.5 ± 3.5
WHR 0.94 ± 0.06
2
0.83 ± 0.07
WTR 1.68 ± 0.15
2
1.46 ± 0.16
Waist circumference (cm) 94.2 ± 8.4
2
85.8 ± 9.9
Hip circumference (cm) 100.2 ± 5.1
2
102.9 ± 6.9
Thigh circumference (cm) 56.6 ± 4.6
2
59.6 ± 5.2
Fasting glucose (mmol/L) 5.46 ± 0.49
2
5.31 ± 0.53
Postload glucose (mmol/L) 5.22 ± 1.65
2
5.54 ± 1.59
1
x
± SD. WHR, waist-to-hip ratio; WTR, waist-to-thigh ratio.
2
Significantly different from women, P < 0.05 (Student’s t test).
changes in fasting and postload glucose concentrations during
6 y of follow-up.
SUBJECTS AND METHODS
Subjects
The Hoorn Study is a population-based cohort study of glucose
tolerance among 2484 white men and women aged 50–75 y that
started in 1989 and has been described elsewhere (15). In
1996–1998 a follow-up examination was carried out. Of the 2484
subjects, 150 subjects had died and 108 subjects had moved out of
Hoorn. Another 140 subjects were not invited because of logistic
reasons. Of the remaining 2086 subjects who were invited to the
follow-up examination, 1513 subjects (72.5%) participated. After
the exclusion of subjects with type 2 diabetes at baseline (49 men
and 44 women) and subjects with missing anthropometric data,
prospective analyses were performed in 1357 subjects (619 men
and 738 women). Informed consent was obtained from all partic-
ipants, and ethical approval for the study was obtained from the
local ethics committee.
Measurements
Fasting glucose concentrations and postload glucose concentra-
tions 2 h after a 75-g OGTT were measured in plasma (mmol/L)
with the glucose dehydrogenase method (Merck, Darmstadt, Ger-
many) at baseline (15) and with the hexokinase method (Boehringer
Mannheim, Mannheim, Germany) at follow-up, except in subjects
who were already known to have diabetes. Fasting and postload
glucose concentrations were used to classify subjects according to
the 1999 World Health Organization criteria (16).
Weight and height were measured while subjects were barefoot
and wearing light clothes only, and BMI was calculated as weight
divided by height squared (kg/m
2
). Waist circumference was
measured at the level midway between the lowest rib margin and
the iliac crest, and hip circumference was measured at the widest
level over the greater trochanters. Thigh circumference was meas-
ured on the left leg directly below the gluteal fold. The mean value
of 2 measurements was used in the analyses. Waist-to-hip ratio
(WHR) was calculated as waist circumference divided by hip cir-
cumference, and waist-to-thigh ratio (WTR) was calculated as
waist circumference divided by thigh circumference.
Information on lifestyle factors was obtained by questionnaire.
Smoking was expressed in cigarette-years (number of cigarettes
smoked per day times the number of years smoked) for smokers
or former smokers. Alcohol intake was categorized in 4 groups:
nondrinkers and drinkers of 10, 10–30, and > 30 g/d. Habitual
physical activity was expressed as hours per day. The activities
included sports, bicycling, gardening, walking, odd jobs, and
housekeeping.
Statistical analysis
Differences in baseline characteristics between men and women
were tested by Student’s t test for normally distributed variables
and by Mann-Whitney’s test for variables with a skewed distribu-
tion. Differences in proportions were tested by the chi-square test.
Logistic regression analyses were performed to study the asso-
ciation of baseline anthropometric measures (BMI, WHR, WTR,
and waist, hip, and thigh circumferences) with the incidence of
type 2 diabetes. Associations are expressed as odds ratios (ORs)
with their 95% CIs per (sex-specific) 1-SD increase in the anthro-
pometric variable involved. An OR can be interpreted as a relative
risk. All models were adjusted for age and then additionally for
baseline glucose concentrations. The influence of possible con-
founding by lifestyle factors was studied by adding these factors
to the regression model. Possible interaction (effect modification)
by sex, age, and anthropometric characteristics was studied by
adding product terms to the model. Because the follow-up dura-
tion was not the same for each individual, we repeated the analy-
ses with additional adjustment for follow-up duration.
To use cutoffs for fasting and postload glucose concentrations
and combine them for the definition of type 2 diabetes (16) impli-
cates a loss of quantitative information. To examine whether the
results of the logistic regression analyses for hip, thigh, and waist
circumferences were influenced by the use of these criteria, linear
regression analyses were performed with continuous fasting and
continuous postload glucose concentrations at follow-up as the
outcome variables. These regression models were adjusted for age
and BMI and then additionally for baseline fasting or postload glu-
cose concentrations. Standardized coefficients are reported to
make the regression coefficients directly comparable between the
different anthropometric measures. A standardized of 0.1 indi-
cates that if the independent variable changes 1 SD, the depend-
ent variable changes 0.1 SD. The stability of the models was con-
sidered to be disturbed by multicolinearity if tolerance was < 0.1.
Tolerance is a statistic used to determine how much the inde-
pendent variables are linearly related to one another. It is calcu-
lated as 1 R
2
for an independent variable when it is predicted by
the other independent variables already included in the analyses.
All analyses were performed by using SPSS for WINDOWS (ver-
sion 10.1.0; SPSS Inc, Chicago).
RESULTS
Baseline characteristics by sex are shown in Table 1. The men
and women were of the same age, but differed significantly in all
anthropometric measures: the women had higher BMI and thigh
and hip circumferences, but lower waist circumference, WHR, and
WTR. The men had higher fasting glucose concentrations,
whereas the women had higher postload glucose concentrations,
although the differences in glucose concentrations were relatively
small. Follow-up duration did not differ significantly between the
men and women (6.4 ± 0.5 y in both sexes), and ranged from 4.4
to 8.1 y in men and from 4.5 to 7.9 y in women. The women were
more physically active, smoked less, and had a lower alcohol
intake than did the men (data not shown).
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1194 SNIJDER ET AL
FIGURE 1. Odds ratios (ORs) for developing type 2 diabetes per
1-SD larger waist () and hip () circumferences. Waist circumference
was adjusted for hip circumference, BMI, and age; hip circumference was
adjusted for waist circumference, BMI, and age.
During follow-up, 64 men (10.3%) and 68 women (9.2%)
developed type 2 diabetes. Type 2 diabetes was diagnosed by a
general practitioner in only 6 men and 12 women before the fol-
low-up examination took place; the remaining patients were diag-
nosed at this examination. Because sex was a significant effect
modifier in the relation between anthropometry and incident dia-
betes, we performed all analyses for men and women separately.
The results in Table 2 show that after adjustment for age, WHR
was a strong predictor for type 2 diabetes in both sexes (model
2), whereas BMI was a significant predictor in women only
(model 1). After mutual adjustment (model 3), only WHR seemed
to be important in predicting diabetes. Waist circumference
(model 4) was less strongly associated with incident diabetes after
adjustment for age than was the WHR, suggesting a predictive role
for hip circumference.
To examine whether the association of WHR was largely due
to waist circumference or to hip circumference, we added these
variables separately into one regression model (model 6). After
adjustment for BMI also, both circumferences appeared to be
significantly associated in opposite directions with the risk of dia-
betes in both sexes (Figure 1). BMI was not significantly associ-
ated with the incidence of type 2 diabetes in this model. No inter-
actions were observed between anthropometric variables or
between age and anthropometric variables. Similar analyses were
performed for the WTR and thigh circumference (Table 3 ). The
results were similar, except that in men, thigh circumference was
not significantly associated with a lower risk of diabetes (model
6). Adjustment for BMI did not change this result (Figure 2).
Adjustment for lifestyle factors (smoking, alcohol intake, and
physical activity) also did not change the results (data not shown).
TABLE 3
Relative risk [odds ratio (OR)] for the development of type 2 diabetes per
1-SD increase in risk factor: logistic regression analyses
1
Men (n = 619) Women (n = 738)
Risk factors in model
2
OR (95% CI) OR (95% CI)
Model 1: BMI 1.03 (0.79, 1.34) 1.53 (1.21, 1.95)
3
Model 2: WTR 1.41 (1.05, 1.89)
4
2.08 (1.59, 2.72)
3
Model 3: BMI 0.97 (0.73, 1.27) 1.31 (1.02, 1.69)
4
WTR 1.42 (1.05, 1.92)
4
1.92 (1.45, 2.54)
3
Model 4: Waist circumference 1.23 (0.95, 2.64) 1.98 (1.54, 2.55)
3
Model 5: Thigh circumference 0.90 (0.68, 1.19) 1.00 (0.79, 1.28)
Model 6: Waist circumference 1.44 (1.05, 1.96)
4
2.37 (1.78, 3.17)
3
Thigh circumference 0.73 (0.52, 1.04) 0.68 (0.50, 0.92)
4
1
WTR, waist-to-thigh ratio.
2
All models were adjusted for age.
3
P < 0.01.
4
P < 0.05.
TABLE 2
Relative risk [odds ratio (OR)] for the development of type 2 diabetes per
1-SD increase in risk factor: logistic regression analyses
1
Men (n = 619) Women (n = 738)
Risk factors in model
2
OR (95% CI) OR (95% CI)
Model 1: BMI 1.03 (0.79, 1.34) 1.53 (1.21, 1.95)
3
Model 2: WHR 1.55 (1.17, 2.06)
3
2.15 (1.63, 2.83)
3
Model 3: BMI 0.79 (0.57, 1.08) 1.20 (0.91, 1.58)
WHR 1.75 (1.27, 2.41)
3
1.98 (1.47, 2.67)
3
Model 4: Waist circumference 1.23 (0.95, 2.64) 1.98 (1.54, 2.55)
3
Model 5: Hip circumference 0.87 (0.66, 1.14) 1.27 (1.00, 1.62)
4
Model 6: Waist circumference 1.94 (1.31, 2.88)
3
2.75 (1.90, 3.97)
3
Hip circumference 0.54 (0.36, 0.79)
3
0.65 (0.45, 0.92)
4
1
WHR, waist-to-hip ratio.
2
All models were adjusted for age.
3
P < 0.01.
4
P < 0.05.
FIGURE 2. Odds ratios (ORs) for developing type 2 diabetes per
1-SD larger waist () and thigh () circumferences. Waist circumference
was adjusted for thigh circumference, BMI, and age; thigh circumference
was adjusted for waist circumference, BMI, and age.
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HIP AND THIGH CIRCUMFERENCES AND TYPE 2 DIABETES 1195
TABLE 5
Associations (standardized coefficients) of baseline body
circumferences with continuous postload glucose concentrations at
follow-up: multiple linear regression analyses
Men (n = 619) Women (n = 738)
Independent variables P P
Model 1
1
Waist circumference 0.203 0.003 0.253 0.000
Hip circumference 0.180 0.005 0.203 0.000
Model 2
1
Waist circumference 0.137 0.036 0.182 0.003
Thigh circumference 0.037 0.517 0.148 0.002
Model 3
2
Waist circumference 0.083 0.162 0.119 0.021
Hip circumference 0.074 0.180 0.057 0.240
Model 4
2
Waist circumference 0.056 0.322 0.093 0.072
Thigh circumference 0.007 0.889 0.066 0.097
1
Adjusted for age and BMI.
2
Adjusted for age, BMI, and baseline postload glucose concentration.
The ORs for a 1-SD larger hip circumference after adjustment
for waist circumference and all lifestyle factors were 0.52 (95%
CI: 0.33, 0.80) for men and 0.65 (95% CI: 0.43, 0.98) for women.
A 1-SD larger thigh circumference after adjustment for waist cir-
cumference and all lifestyle factors resulted in ORs of 0.80 (95%
CI: 0.53, 1.20) for men and 0.64 (95% CI: 0.44, 0.93) for women.
Adjustment for follow-up duration did not change any of the
observed associations (data not shown). After adjustment for base-
line fasting and postload glucose concentrations, only waist cir-
cumference in women remained significantly associated with the
incidence of type 2 diabetes (data not shown).
The results of the multiple linear regression models for the asso-
ciations of baseline body circumferences with follow-up fasting and
postload glucose concentrations are shown in Tables 4 and 5, respec-
tively. We adjusted for age and BMI (models 1 and 2) and then addi-
tionally for baseline fasting or postload glucose concentrations
(model 3 and 4). In accordance with the results of the logistic regres-
sion analyses, glucose concentrations (fasting and postload) were
positively associated with baseline waist circumference and nega-
tively associated with baseline hip or thigh circumference, although
the results were not significant for thigh circumference in men
(models 1 and 2). After adjustment for baseline glucose concentra-
tions (models 3 and 4), most associations became nonsignificant: in
men, waist circumference was still significantly and positively asso-
ciated with fasting glucose, whereas in women only thigh circum-
ference was significantly associated (negatively). None of the cir-
cumferences was significantly associated with postload glucose
concentrations in men, whereas in women waist circumference was
positively associated and thigh circumference was negatively asso-
ciated after adjustment for baseline postload glucose concentrations.
The correlation between waist and hip circumferences was 0.71
in men and 0.69 in women, and the correlation between waist and
thigh circumferences was 0.46 in men and 0.42 in women. The
regression models were not disturbed by multicolinearity.
DISCUSSION
In the present study, we showed that the body circumference
ratios (WHR and WTR) are better predictors of future type 2
diabetes than is overall obesity measured by BMI. Both waist and
hip circumference have important, but opposite, associations with
the risk of diabetes after adjustment for age and BMI. A larger waist
circumference is associated with a higher risk of diabetes, whereas
a larger hip circumference is associated with a lower risk of dia-
betes. A larger thigh circumference was also associated with a lower
risk of diabetes, although the protective effect was statistically signi-
ficant only in women. The measurements of continuous glucose con-
centrations showed that fasting and postload concentrations were
positively associated with baseline waist circumference and nega-
tively associated with baseline hip and thigh circumferences.
Of the 2086 persons who were invited for the follow-up exam-
ination, 72.5% participated. These participants were healthier at
baseline than were the nonparticipants (1). Therefore, it is possi-
ble that we underestimated the true incidence of diabetes and con-
sequently underestimated the associations with waist, hip, and
thigh circumferences.
When incident diabetes or continuous glucose concentrations
after follow-up are used as the study outcome, there is often dis-
cussion of whether to adjust for baseline glucose concentrations.
Adjustment for baseline glucose answers the question of whether
knowledge about the thigh or hip circumference contributes to the
prediction of incident diabetes once baseline glucose is taken into
account. In our study, thigh or hip circumference did not inde-
pendently contribute to incident diabetes or continuous glucose
concentrations after adjustment for baseline glucose. However, if
baseline glucose concentrations and baseline thigh or hip circum-
ferences result from the same etiologic process, adjustment for
glucose concentrations would be inappropriate. Alternatively, if
we assume that there is a causal association of thigh or hip cir-
cumference with impaired glucose metabolism, it is possible that
persons with narrow hips or small thighs had increased glucose
concentrations already at baseline. If we then adjust for these
baseline glucose concentrations, the effects of thigh or hip cir-
cumference disappear. The observed cross-sectional association
between body circumferences and glucose concentrations (12)
reinforce these suggestions. Waist circumference is more likely to
remain a significant predictor of type 2 diabetes after adjustment
for baseline glucose concentrations.
TABLE 4
Associations (standardized coefficients) of baseline body
circumferences with continuous fasting glucose concentrations at follow-
up: multiple linear regression analyses
Men (n = 619) Women (n = 738)
Independent variables P P
Model 1
1
Waist circumference 0.284 0.000 0.216 0.000
Hip circumference 0.178 0.005 0.154 0.008
Model 2
1
Waist circumference 0.219 0.001 0.157 0.011
Thigh circumference 0.036 0.528 0.134 0.005
Model 3
2
Waist circumference 0.159 0.008 0.094 0.082
Hip circumference 0.102 0.064 0.076 0.134
Model 4
2
Waist circumference 0.120 0.036 0.060 0.267
Thigh circumference 0.024 0.633 0.084 0.043
1
Adjusted for age and BMI.
2
Adjusted for age, BMI, and baseline fasting glucose concentration.
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1196 SNIJDER ET AL
Our observation that central obesity, independent of overall
obesity, is an important determinant of type 2 diabetes is not new
(3–6). The abdominal visceral fat is considered to be possibly eti-
ologically important through increased fatty acid release into the
portal system (7–9). Our results extend these findings by showing
an independent association of waist and hip circumferences with
the development of diabetes. Our results agree with the results of
the scarce cross-sectional studies (10, 11). One previous prospec-
tive study, showing an independent protective effect of hip cir-
cumference on the development of diabetes, was limited to women
(14). Furthermore, the presence of diabetes was examined on the
basis of an OGTT. In the present prospective study, an OGTT was
performed in both men and women. In addition, we included
measurements of thigh as well as hip circumference.
The negative association of hip circumference with glucose
metabolism was proposed to be caused by a greater muscle mass
at the gluteal region (10). Muscle mass is one of the sites of insulin
resistance as well as the main target of insulin. WHR has been
related to both larger visceral fat and smaller leg muscle areas in
men (17). Also, the higher prevalence of glucose tolerance in
Indian men than in Swedish men was related to lower muscle mass
(18). Thigh circumference might better reflect muscle mass than
hip circumference, because it is less likely to be influenced by
frame size (pelvic width). Our results, however, show that hip cir-
cumference has a stronger negative association with glucose con-
centrations than does thigh circumference, especially in men.
Larger thigh and hip circumferences could also reflect
increased femoral and gluteal subcutaneous fat mass. Particu-
larly in women, these depots have relatively high lipoprotein
lipase activity and relatively low rates of basal and stimulated
lipolysis (19). These depots may protect the liver and muscle
from high exposure to free fatty acids through uptake and stor-
age. Recently, Van Pelt et al (20) showed that larger leg fat mass
measured by dual-energy X-ray absorptiometry was associated
with better insulin sensitivity and a better lipid profile after
adjustment for trunk fat.
Regional differences in adipocyte metabolism (lipoprotein
lipase activity and lipolysis) are more pronounced in women than
in men (19). This may explain why the observed protective role
of larger thighs was stronger in the women than in the men in the
present study. Furthermore, the interpretation of hip circumfer-
ence may differ between men and women. Gluteal fat mass and
pelvic width may be the main determinants of hip circumference
in women, whereas pelvic width and muscle mass may be the
main determinants in men.
Adrenal and sex steroid concentrations and growth hormone
concentrations may influence visceral fat accumulation as well as
the development of insulin resistance (21–24). For example,
hyperandrogenicity in women and hypoandrogenicity in men has
been associated with insulin sensitivity and the development of
type 2 diabetes (25, 26) and with fat distribution (27–29). These
steroids may influence adipose tissue by changing lipoprotein
lipase activity (7, 22, 25, 30). In the present study, no information
on hormones was available.
Although the exact mechanisms need to be further explored,
the results of the present study show that body tissue distribution
is an important factor in the development of type 2 diabetes in
older persons, even more than is BMI. Therefore, lifestyle inter-
ventions aimed at the prevention of type 2 diabetes not only should
focus on weight loss but should preferably combine
approaches that decrease waist circumference and increase hip
or thigh circumference. Increased physical activity, less heavy
drinking, and smoking cessation have been shown to do both (31).
Energy restriction tends to decrease both waist and hip or thigh
circumference. Increased physical activity results in a better body
composition, by an increase of the muscle mass in the legs and a
decrease in visceral fat accumulation. The better body composi-
tion achieved by smoking cessation and less heavy drinking is sug-
gested to be caused by the influence these have on hormones, as
discussed above. Further research on prevention strategies, how-
ever, is needed.
In summary, larger hip or thigh circumference is associated
with a lower risk of type 2 diabetes in both men and women, inde-
pendently of BMI, age, and waist circumference, whereas larger
waist circumference is associated with higher risk. Further
research should be aimed at determining the underlying etiologic
mechanisms of this association and whether our results can be
extrapolated to other ethnic groups.
MBS performed the data analyses and wrote the drafts and the final article;
JMD, MV, LMB, CDAS, JSY, RJH, GN, and JCS provided advice in the pres-
entation or interpretation of the results; JMD, LMB, CDAS, RJH, and GN were
responsible for the design and data collection of the Hoorn Study; and PJK pro-
vided statistical advice. All authors declare that they had no duality or conflicts
of interest.
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... In the present study, we found that HC was negatively associated with cognitive impairment using logistic regression analysis, a result that supports the idea that HC contributes to reducing the risk of cognitive impairment in older people. This phenomenon may be explained by the protective effect that larger HC has against high blood glucose levels, thus slowing cognitive decline in older people [40,77,78]. In addition, we found no significant differences in cognitive impairment between older people with higher WHR (Q3) and highest WHR (Q4) compared to the lowest WHR (Q1), while older people with lower WHR (Q2) showed better cognitive functioning. ...
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Background Numerous studies have indicated an obesity paradox in observational research on aging health, where being normal weight or underweight adversely affects cognitive function, while moderate obesity may offer protective benefits. This study aims to investigate the association between body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), abdominal volume index (AVI), and the joint effect of BMI and HC on cognitive impairment in older Chinese people. Methods A total of 10,579 participants aged 65 years and older from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) were included in this cross-sectional study. BMI, WC, HC, WHtR, WHR, and AVI were calculated from height, weight, WC, and HC measurements, where weight, WC, and HC were obtained by direct measurement. Mini-Mental State Examination was used to assess cognitive impairment. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using binary logistic regression. Non-linear correlations were investigated using restricted cubic spline curves. Results In multivariate logistic regression models fully adjusted for confounding variables, our analyses showed significant negative associations of WC [OR 0.93 (95%CI 0.88–0.98), P = .012], HC [OR 0.92 (95%CI 0.87–0.97), P = .004], lower WHR (Q2) [OR 0.85 (95%CI 0.72-1.00), P = .044], and AVI [OR 0.93 (95%CI 0.88–0.98), P = .011] with cognitive impairment. Nonlinear curve analysis showed that the risk of cognitive impairment was lowest when the BMI was about 25.5 kg/m², suggesting that the optimal BMI for older Chinese people to maintain good cognitive ability may be in the overweight range. In addition, there was a non-linear “N” shaped relationship between HC and cognitive impairment, with HC having the highest risk of cognitive impairment at about 82 cm and the lowest risk at about 101 cm. The joint effects analysis indicated that the lowest risk was observed among those with normal or higher BMI but higher HC compared with participants with normal BMI levels and lower HC levels. Conclusion In older Chinese people, a low-waisted and high-hip circumference body figure is favorable for cognitive function in older people. It also found a significant association between AVI and cognitive impairment. The joint analysis of BMI and HC suggests that maintaining a normal or higher BMI with a higher HC may be more conducive to maintaining good cognitive function.
... One possible explanation for this protective effect is that adipose tissue in the hip might serve as a "safe" fat storage depot, diverting free fatty acids away from "ectopic" sites such as the liver and muscles, where excess fat can cause insulin resistance. Compared with visceral fat, hip adipose tissue may possess greater insulin sensitivity, enabling it to store excess energy without adverse metabolic effects 4,18,19 . Therefore, not all fat accumulation is cardiovascular or metabolic harmful, which is what we call "good fat." ...
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Objective This study aimed to assess the correlation between hip circumference (HC) and the risk of cardiovascular disease (CVD) and type 2 diabetes mellitus using Mendelian randomization (MR) to overcome observational study limitations. Design MR analysis utilized genetic variation from the MR Base in a two‐sample analysis. Three methods were employed: MR‐Egger regression, weighted median estimator, and inverse variance weighting (IVW). Setting Data was acquired from MR Base, a platform summarizing genome‐wide association study (GWAS) data for MR research. Main Outcome Measures Publicly available summary statistics datasets from GWAS meta‐analyses were used, with HC and HC adjusted for body mass index (BMI) as exposures. Data for CVD and type 2 diabetes mellitus were obtained as outcomes. Results Results indicated a positive causal relationship between HC and CVD (IVW: P = 1.84e‐07, OR: 1.37, 95% CI: 1.22–1.54) as well as type 2 diabetes mellitus (IVW: P = 0.04, OR: 1.62, 95% CI: 1.02–2.56), independent of BMI. However, HC after BMI adjustment showed no significant causal relationship with CVD (IVW: P = 0.05, OR: 1.09, 95% CI: 1.00–1.19) and exhibited a negative association with type 2 diabetes mellitus (IVW: P = 0.00, OR: 0.76, 95% CI: 0.66–0.88), suggesting a protective effect against type 2 diabetes mellitus. Conclusions After adjusting for BMI, adipose tissue concentrated in the hip region showed a protective effect against type 2 diabetes mellitus but not against CVD. These findings offer insights into diabetes prevention and treatment strategies, and may inform plastic surgery procedures. Further research is needed to validate these findings and explore underlying mechanisms.
... It has been reported that waist circumference is associated with the incidence of MAFLD [14]. The waist-to-thigh ratio has been identified as a significant predictor of diabetes and all-cause mortality [15,16]. However, there are few reports indicating that the abdominal circumference to thigh circumference ratio is associated with the incidence of MAFLD. ...
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Background This study aimed to determine whether the waist-to-thigh ratio (WTTR) is associated with the incidence of metabolic-associated fatty liver disease (MAFLD) in health care workers. Methods There were 4517 health care workers with baseline data and results from 2 follow-up examinations. We divided the subjects into 3 groups according to baseline WTTR and used the Cox hazard regression model to estimate MAFLD risk. Results The WTTRs were categorized by tertiles at baseline using the values 1.58 and 1.66. Patients with higher WTTR tended to have significantly greater values for the following factors, body mass index (BMI), fasting blood glucose (FPG), systolic blood pressure, diastolic blood pressure, total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C) and neck circumference. The incidence of MAFLD significantly increased with increasing WTTR tertiles (5.74%, 12.75% and 22.25% for the first, second and third tertiles, respectively, P < 0.05 for trend). Kaplan-Meier(K-M) survival analysis revealed a significant tendency towards increased MAFLD risk with increasing WTTR tertile. In the fully adjusted model, the hazard ratios (95% CIs) for MAFLD in the second, third WTTR tertiles compared with the first quartile were 2.17(1.58,2.98), 3.63(2.70,4.89), respectively, third neck circumference tertiles compared with the first quartile were 2.84(1.89,4.25), 8.95(6.00,13.35), respectively. Compared with those of individuals with a BMI > 23 kg/m2, the associations between WTTR and MAFLD incidence were more pronounced in subjects with a BMI < 23 kg/m2. Similarly, the difference in neck circumference was more pronounced in these patients with a BMI < 23 kg/m2. Conclusions Our results revealed that the WTTR is an independent risk factor for MAFLD, and there was a dose‒response relationship between the WTTR and MAFLD risk. The neck circumference was significantly different in subjects with a BMI < 23 kg/m2. This approach provides a new way to predict the incidence rate of MAFLD.
... Incorporating the right mix for the best effect is currently a knowledge gap worth studying in the future. Higher hip circumference being a surrogate measure of gluteal musculature is understandably inversely associated with sarcopenia [19, [74][75][76]. In addition, our study finds that a higher BMI is also protective of sarcopenia similar to other studies [18,[77][78][79]. ...
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Background Sarcopenia is common in older adults worldwide, but its prevalence varies widely owing to differences in diagnostic criteria, population sampled, and care setting. We aimed to determine the prevalence and factors associated with sarcopenia in patients aged 65 and above admitted to a post-acute hospital in Singapore. Methods This was a cross-sectional study of 400 patients recruited from a community hospital in Singapore. Data including socio-demographics, physical activity, nutritional status, cognition, clinical and functional status, as well as anthropometric measurements were collected. Sarcopenia was defined using the Asian Working Group for Sarcopenia 2019 criteria [AWGS2019]. Results Of the 383 patients with complete datasets, overall prevalence of sarcopenia was 54% while prevalence of severe sarcopenia was 38.9%. Participants with increased age, male gender and a low physical activity level were more likely to be sarcopenic, while those with higher hip circumference and higher BMI of ≥27.5m/kg2 were less likely to be sarcopenic. Other than the above-mentioned variables, cognitive impairment was also associated with severe sarcopenia. Conclusions More than 1 in 2 older adults admitted to a post-acute hospital in Singapore are sarcopenic. There is an urgent need to address this important clinical syndrome burden and to identify patients at risk of sarcopenia in post-acute settings in Singapore for early intervention.
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Aim: This study aimed to investigate how demographic factors such as race, age, sex and ethnicity can impact hip circumference (HC) and waist circumference (WC) in patients with chronic pain.Materials & methods: We queried the NIH-sponsored All of Us database for patients with documented HC, WC and waist/hip ratio (WHR) data. This cross-sectional study categorized participants into four groups: total cohort, no chronic pain, mild/moderate chronic pain (numeric rating scale < 7) and severe chronic pain (numeric rating scale > 7). Further subgroup analyses were performed based on race, age, sex and ethnicity. We examined the correlation between chronic pain and WC, HC and WHR. ANCOVA analysis was used to determine to investigate demographics.Results: This study included 204,013 participants, with 25.22% having a chronic pain diagnoses. In most subgroups, females had significantly greater HC, while males had greater WC and WHR. WC (p < 0.001 in females, p < 0.01 in males), HC (p < 0.001 in females) and WHR (p < 0.001 in females, p < 0.05 in males) were significantly greater in the severe pain group compared with the mild/moderate pain group.Conclusion: These findings suggest that when assessing HC and WC, demographic variables need to be considered to develop more personalized and comprehensive treatment plans for chronic pain patients.
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Insulin resistance is the cornerstone for the development of non-insulin-dependent diabetes mellitus (NIDDM). Free fatty acids (FFAs) cause insulin resistance in muscle and liver and increase hepatic gluconeogenesis and lipoprotein production and perhaps decrease hepatic clearance of insulin. It is suggested that the depressing effect of insulin on circulating FFA concentration is dependent on the fraction derived from visceral adipocytes, which have a low responsiveness to the antilipolytic effect of insulin. Elevated secretion of cortisol and/or testosterone induces insulin resistance in muscle. This also seems to be the case for low testosterone concentrations in men. In addition, cortisol increases hepatic gluconeogenesis. Cortisol and testosterone have "permissive" effects on adipose lipolysis and therefore amplify lipolytic stimulation; FFA, cortisol, and testosterone thus have powerful combined effects, resulting in insulin resistance and increased hepatic gluconeogenesis. All these factors promoting insulin resistance are active in abdominal visceral obesity, which is closely associated with insulin resistance, NIDDM, and the "metabolic syndrome." In addition, the endocrine aberrations may provide a cause for visceral fat accumulation, probably due to regional differences in steroid-hormone-receptor density. In addition to the increased activity along the adrenocorticosteroid axis, there also seem to be signs of increased activity from the central sympathetic nervous system. These are the established endocrine consequences of hypothalamic arousal in the defeat and defense reactions. There is some evidence that suggests an increased prevalence of psychosocial stress factors is associated with visceral distribution of body fat. Therefore, it is hypothesized that such factors might provide a background not only to a defense reaction and primary hypertension, suggested previously, but also to a defeat reaction, which contributes to an endocrine aberration leading to metabolic aberrations and visceral fat accumulation, which in turn leads to disease.
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Insulin resistance is the cornerstone for the development of non-insulin-dependent diabetes mellitus (NIDDM). Free fatty acids (FFAs) cause insulin resistance in muscle and liver and increase hepatic gluconeogenesis and lipoprotein production and perhaps decrease hepatic clearance of insulin. It is suggested that the depressing effect of insulin on circulating FFA concentration is dependent on the fraction derived from visceral adipocytes, which have a low responsiveness to the antilipolytic effect of insulin. Elevated secretion of cortisol and/or testosterone induces insulin resistance in muscle. This also seems to be the case for low testosterone concentrations in men. In addition, cortisol increases hepatic gluconeogenesis. Cortisol and testosterone have "permissive" effect on adipose lipolysis and therefore amplify lipolytic stimulation; FFA, cortisol, and testosterone thus have powerful combined effects, resulting in insulin resistance and increased hepatic gluconeogenesis. All these factors promoting insulin resistance are active in abdominal visceral obesity, which is closely associated with insulin resistance, NIDDM, and the "metabolic syndrome." In addition, the endocrine aberrations may provide a cause for visceral fat accumulation, probably due to regional differences in steroid-hormone-receptor density. In addition to the increased activity along the adrenocorticosteroid axis, there also seem to be signs of increased activity from the central sympathetic nervous system. These are the established endocrine consequences of hypothalamic arousal in the defeat and defense reactions. There is some evidence that suggests an increased prevalence of psychosocial stress factors is associated with visceral distribution of body fat. Therefore, it is hypothesized that such factors might provide a background not only to a defense reaction and primary hypertension, suggested previously, but also to a defeat reaction, which contributes to an endocrine aberration leading to metabolic aberrations and visceral fat accumulation, which in turn leads to disease.
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Anthropometry and dual-photon absorptiometry (DPA) were used to examine associations of regional adiposity with plasma lipid, lipoprotein, and lipoprotein subfraction mass concentrations in moderately overweight men and women. Among 130 women, waist to thigh girth ratio (WTR) correlated with triglycerides (TG) (r = .33, P less than .0001) and negatively with high-density lipoprotein (HDL)-cholesterol (HDL-C) (r = -.37, P less than .0001) concentration, as expected. While WTR did not correlate with low-density lipoprotein (LDL)-cholesterol (LDL-C) it correlated positively with the mass subfraction of small (Sfo, 0 to 7) LDL (r = .38, P less than .0001), and negatively with large (Sfo, 7 to 12) LDL (r = -.31, P less than .01). Among 133 men, similar though weaker relationships were found. Thigh girth correlated positively with HDL and HDL2-C and mass, and with LDL particle size among women. Multivariate analysis suggests that association of WTR with lipoprotein values known to carry risk of coronary heart disease (CHD) are due at least as much to effects of thigh girth as to deleterious effects of waist girth. Estimates of fat weight in thigh and abdominal regions by DPA support thigh fat as contributing to these effects of thigh girth. Thigh fat may contribute to lipoprotein profiles that predict lower risk of cardiovascular disease.
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Twenty-three healthy men (age 25 to 50 years), covering a wide range of fatness and body fat distribution, were studied. An oral glucose tolerance test was performed and adipose tissue areas were calculated from computed tomography (CT) scans made at the level of L4/L5. Visceral fat area was associated with elevated concentrations of insulin and C-peptide and with glucose intolerance before and after the oral glucose load. Concentrations of sex-hormone-binding globulin (SHBG), as well as total and free testosterone, were negatively correlated with waist/hip circumference ratio and visceral fat area and also negatively associated with increased glucose, insulin, and C-peptide concentrations. In multiple linear regression, adjusting for age, body mass index, and visceral fat area, serum concentrations of free testosterone were still negatively correlated with glucose, insulin, and C-peptide levels. Without claiming any causality in the observed associations, we conclude that, unlike in women, abdominal fat distribution, insulin, glucose, and C-peptide levels are negatively associated with serum testosterone levels in men.
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We studied 24 healthy men (25-50 years old) covering a wide range of fatness (body mass index range: 21-34 kg/m2) and fat distribution (waist/hip range: 0.75-1.06). Computed tomography scans were taken at five levels (thigh, hip, waist, arm, and liver) from which fat, muscle and bone areas were calculated. Both waist/hip and BMI were correlated with fat areas in the thigh, arm and waist scans. BMI showed stronger correlations with peripheral fat areas, whereas waist/hip showed stronger correlations with fat areas in the waist scan (particularly with visceral fat area: r = 0.88, P less than 0.001). BMI was correlated with muscle and bone areas in the thigh scan. In multiple regression BMI was, independently of waist/hip and age, positively correlated with fat areas in the arm, thigh, and waist (not with visceral fat) and muscle and bone areas in the thigh. Waist/hip was independently of BMI and age correlated with fat areas in the arm and waist, including visceral fat area (but not with fat areas in the thigh). Moreover, waist/hip showed an independent negative correlation with muscle area in the thigh, muscle endurance and physical activity. Serum triglycerides, plasma insulin, glucose, uric acid and diastolic and systolic blood pressure were associated with visceral fat area but also to anthropometric indicators of abdominal fat distribution (especially waist/hip ratio). Liver attenuation, but not the liver/spleen attenuation ratio, was associated with some liver enzymes and BMI but not with waist/hip or metabolic parameters. We conclude that a higher BMI is associated with increased central and peripheral fat stores (but not visceral fat) and increased thigh muscle whereas waist/hip is primarily associated with increased central fat stores (noteably with visceral fat), decreased thigh muscle and reduced physical fitness. It is suggested that physical training might be an important element in the treatment of abdominal obesity in men.
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The results refer to a 12-year longitudinal population study of women in Gothenburg, Sweden. Correlations were studied between initial adipose tissue amount and adipose tissue distribution on the one hand and incidence of diabetes and change in serum blood glucose concentration on the other. Body mass index, sum of two skinfolds and waist-to-hip circumference ratio were significantly associated with incidence of diabetes. The waist-to-hip ratio was also positively associated with an increase of serum glucose concentration in the fasting state during the followup period. The significant correlations remained in multivariate analysis and were independent of age, initial smoking habits, systolic blood pressure, intake of antihypertensive drugs and serum cholesterol, triglyceride and glucose concentrations. The correlations between the separate anthropometric variables and incidence of diabetes remained when the other anthropometric variables were considered as background factors. The distribution of fat to the abdominal region as well as the total amount of fat per se seem to be important risk factors for diabetes and the effect of one of these factors seems to add to the other.
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Adipose tissue lipolysis and lipoprotein lipase (LPL) activity were studied in biopsies from the femoral and abdominal depots in healthy women during early or late menstrual cycle, pregnancy, and the lactation period. When the differences in cell size were taken into account, basal lipolysis was similar in both regions in nonpregnant women. During lactation, however, lipolysis was significantly higher in the femoral region. The lipolytic effect of noradrenaline (10(-6) M) was significantly less in the femoral region in the nonpregnant women and during early pregnancy. However, the lipolytic response was the same in both regions in lactating women. LPL activity was higher in the femoral than in the abdominal region except during lactation when a marked decrease in the LPL activity was seen in the femoral region. The LPL activity in the abdominal region remained unchanged in all patient groups. The results imply that in both nonpregnant and pregnant women lipid assimilation is favored in the femoral depot. During lactation, however, the metabolic pattern changes; the LPL activity decreases and lipid mobilization increases in this depot. These changes are much less pronounced in the abdominal region. Thus, fat cells from different regions show a differential response during pregnancy and lactation. These results suggest that the adipose tissue in different regions may have specialized functions.