Journal of Gerontology: BIOLOGICAL SCIENCES
2005, Vol. 60A, No. 12, 1518–1524
Copyright 2005 by The Gerontological Society of America
Reference Body Composition in Adult Rhesus Monkeys:
Glucoregulatory and Anthropometric Indices
Aarthi Raman,1 Ricki J. Colman,2 Yu Cheng,1 Joseph W. Kemnitz,2,3
Scott T. Baum,2 Richard Weindruch,2,4,5 and Dale A. Schoeller1
1
Department of Nutritional Sciences, 2Wisconsin National Primate Research Center, 3Department of Physiology,
4
Department of Medicine, and 5Veterans Administration Hospital, Geriatric Research,
Education and Clinical Center, University of Wisconsin–Madison.
Rhesus monkeys have been used as models to study obesity and disease. The aim of this study
was to define body mass indices for underweight and obesity in rhesus monkeys. Longitudinal
data collected over 8–14 years from 40 male and 26 female rhesus monkeys were analyzed. Body
weight, insulin sensitivity index, and disposition index were regressed against percent body fat
(%BF). A minimal %BF beyond which further loss of body weight resulted in loss of lean mass
was determined to be 11.5% in older males, 8% in adult females, and 9% in younger adult males.
Insulin sensitivity index and disposition index reached minimum values at 23% fat in older
males, 18% in adult females, and 21% in younger adult males, indicating obesity. The estimated
reference range for %BF was 9%–23% in male and 8%–18% in female monkeys, corresponding
to body mass indices of 32–44 kg/m2 for male and 27–35 kg/m2 for female monkeys.
A
DVANCEMENTS in gerontological research have
been promoted through the use of numerous animal
models to identify possible mechanisms of aging and agerelated diseases. Research using nonhuman primates has
provided some valuable information for elucidating the
nature and causes of aging processes observed in humans as
well as evaluating potential interventions. Because rhesus
monkeys can develop diet-dependent obesity and diabetes,
they have been highly useful models for discovering antiobesity and antidiabetic treatments.
Monkeys of both sexes with excess body weight (BW)
due to increased fat mass have been shown to have fasting
hyperinsulinemia (1), elevated insulin response to intravenous glucose or marginally impaired glucose tolerance (2),
and elevated fasting serum triglycerides (3). These glucoregulatory and liporegulatory abnormalities are similar to
those of obese humans; nevertheless, there are no uniform
definitions for overweight and obesity in rhesus monkeys.
Similarly, large losses of lean body mass can have deleterious consequences such as damage to organs and disturbances in cardiac function due to attrition in the myocardial
mass (4); however, there are also no uniform definitions of
underweight in rhesus monkeys. This creates an ambiguity
in the interpretation of results based on the non-uniform
definition of underweight, overweight, or obese animals
when used as models for human disease.
In humans, obesity is generally defined as a body mass
index (BMI) . 30 kg/m2 based on the morbidity risks of
cardiovascular diseases, hypertension, diabetes, and associated symptoms (5–7), and underweight is defined as BMI ,
19 kg/m2 (8). In contrast, obesity and underweight in rhesus
monkeys has been characterized using morphometric
parameters such as BW, BMI, and abdominal circumference
(AC), which are reliable predictors of body fat (3,9). For
1518
example, obesity in rhesus monkeys has been characterized
using a BW greater than 2 standard deviations (SD) above
the mean for their sex (3) and break-points for percentage
body fat (%BF), such as 25% BF (10) and 30% BF (11).
The most important variable that addresses the majority
of the gluco- and liporegulatory abnormalities in an individual is body fat mass (3). Hyperinsulinemia, hypertriglyceridemia, decreased glucose clearance rate, and
glucose disposal can be seen with elevated %BF (12). Too
low a %BF, however, may also be detrimental. Higher allcause mortality rates have been observed in individuals with
low BMI (13,14). The increase in mortality rate due to lower
BMI is not fully understood, but factors such as osteoporosisinduced fractures (15), decreased vitamin A status [leading
to decreased survival rates for acute illnesses (16)], and
deficient levels of body fat (16) have been suggested as
possible mechanisms. In addition, a systematic analysis of
the composition of weight loss has shown that mortality
decreases when the weight loss is due to loss of fat, but
increases when it is due to loss of fat-free mass (FFM) (17).
Unfortunately, most of these definitions were not based on
systematic analysis of any metabolic parameters or variables
in rhesus monkeys in a manner similar to that which has
been used to define underweight, overweight, and obesity in
humans making it difficult to compare outcomes between
rhesus monkeys and humans.
From the above findings it becomes clear that the
relationships between %BF, gluco- and liporegulatory
parameters, and composition of weight loss should be considered to better define obesity and underweight in rhesus
monkeys. We, therefore, investigated whether various
parameters of the metabolic syndrome are associated with
%BF and indicate a %BF at which an adult monkey can be
defined as overweight and/or obese. Also, we investigated
REFERENCE BODY COMPOSITION
the relationship between BW and %BF to identify the point
at which additional loss of weight causes increasing loss of
FFM. This %BF point can indicate the minimum %BF an
animal should have and hence define underweight. Because
not all primate research institutions may have ready access
to body fat measuring equipment, reference ranges of BMI
will be ascertained using the highly correlated relationship
of %BF and BMI. AC is highly correlated with visceral
adiposity in humans as well as nonhuman primates (9,18).
Studies done on humans have shown that increased abdominal obesity is associated with increased risk of type 2
diabetes, cardiovascular diseases, hypertension, and hypercholesterolemia (19,20). Abdominal adiposity is also associated with hyperinsulinemia, higher plasma glucose and
insulin levels, and eventually glucose intolerance which will
be reflected in the insulin sensitivity. Similar to those of
BMI, reference ranges of AC will be ascertained using the
highly correlated relationship of %BF and AC.
SUBJECTS
Longitudinal data from 40 male and 26 female rhesus
monkeys which are part of Wisconsin National Primate
Research Center (WNPRC) were used in this analysis.
These monkeys are part of an ongoing dietary restriction and
aging study the protocol for which was reviewed and
approved by the Institutional Animal Care and Use Committee of the Graduate School at the University of Wisconsin
(21). Data consisted of 639 values from 66 animals (34
calorie restricted and 32 control) over a span of 14 years in
older animals and 8 years in adult animals. Monkeys were
caged individually in standard stainless steel cages with
food containers attached to the cages and provision for
drinking water in each cage. The cages had inside dimensions of 89 cm width, 86 cm depth, and 86 cm height. Room
temperature was maintained at 218C, and the animals were
maintained on a 12-h light/dark cycle with lights on between
6 AM and 6 PM. Animals were fed a semipurified diet
(Teklad, Madison, WI) containing 15% lactalbumin, 10%
corn oil, and ;65% carbohydrate. Additional details about
the study have been published elsewhere (21,22).
METHODS
Body Composition
Whole body composition was measured semiannually
using dual energy x-ray absorptiometry (DXA, Model DPXL; GE/Lunar Corp., Madison, WI). Briefly, animals were
sedated with a mixture of ketamine–HCl (10 mg/kg BW,
IM) and xylazine (0.6 mg/kg BW, IM) for additional
muscular relaxation (18).
%BF ¼ ðFat mass; kgÞ=ðBW; kg ½DXAÞ100
BMI of rhesus monkeys was calculated by dividing BW by
the square of the crown-rump length (CRL) of the animal.
Crown-rump length was measured with the monkey supine
on a calibrated rule with a fixed headrest.
1519
2
BMICRL ¼ ðBW; kgÞ=ðCrown-rump length; mÞ
AC was measured with a non-elastic tape measure to the
nearest 0.1 cm when the animal was in lateral recumbency
(9,18).
Glucose and Insulin Analysis
Glucose and insulin concentrations were measured annually in all the monkeys using frequently sampled intravenous
glucose tolerance tests (FSIGT), the methods of which are
detailed elsewhere (23). Briefly, a central venous catheter is
positioned for administration of the glucose (300 mg/kg BW)
and for blood sample collection. To augment insulin response
to the bolus of glucose, animals were dosed with tolbutamide
(5 mg/kg) after the first-phase insulin response. Plasma
samples collected over a period of 180 minutes were used for
measurement of glucose and insulin levels. Plasma glucose
concentrations were measured using the glucose oxidase
method (Model 23A; YSI, Yellow Springs, OH). Plasma
insulin was measured by double antibody radioimmunoassay
(Linco Research, St. Louis, MO).
Insulin Sensitivity Index
Glucose and insulin data were analyzed using the minimal
model method (24). This model yields a measure of insulin
sensitivity reflecting the ability of insulin to augment the
effect of hyperglycemia in promoting glucose uptake and
inhibiting hepatic glucose output by insulin (24,25). Basal
insulin (Ib) and glucose (Gb) levels, glucose disappearance
rate (KG), first-phase (acute) insulin response (AIR), secondphase insulin response, and tolbutamide-induced insulin
response are calculated by this model and are then used to
deduce the insulin sensitivity index (SI). Disposition index
(DI) was calculated as the product of first-phase AIR and SI,
and indicated the compensatory adaptation to insulin resistance which is a measure of b-cell function.
Cholesterol and Triglycerides
Fasting triglycerides (TGb) were measured using the
enzymatic colorimetric method with glycerol oxidase and
4-aminophenazone (COBAS INTEGRA; Roche Diagnostics, Indianapolis, IN) with a between-day coefficient of
variation (CV) of 1.9%. Fasting total cholesterol levels were
measured using the enzymatic colorimetric method with
cholesterol esterase and 4-aminoantipyrine at an absorbance
of 512 nm (COBAS INTEGRA; Roche Diagnostics) with a
between-day CV of 1.9%.
Statistical Analysis
Because age had a significant univariate relationship with
%BF (2% increase with age; p , .0001), monkeys were
categorized based on sex and age range. The males were
divided into younger adult males (AM; mean current age:
18.5 6 3 years; range: 15–22 years) and older males (OM;
mean current age: 23.2 6 2 years; range: 22–28 years); the
adult females (AF; mean current age: 19.5 6 2 years; range:
17–23 years) were similar in age to AM. Animals were
studied based on the groups of the main study of calorie
restriction. Data consisted of 639 values from 66 animals over a span of 14 years in OM [(n ¼ 24; N ¼ 297),
RAMAN ET AL.
1520
Table 1. Group Characteristics (Mean 6 SD)
Variable
Weight
Body fat
Body fat
Body mass index
Abdominal
circumference
Basal glucose level
Basal insulin level
Glucose
disappearance rate
Insulin sensitivity
index
Disposition index
Fasting triglycerides
Plasma cholesterol
Units
OM
6
6
6
6
3a
2a
10
9a
AF
6
6
6
6
AM
2b
1b
11
7b
6
6
6
6
2a
2a
9
7a
kg
kg
%
kg/m2
11.9
2.9
21.5
42.0
cm
mmol/L
pmol/L
51.0 6 11a 45.6 6 9b
50.1 6 10a
3.4 6 0.4a 3.4 6 0.4a 3.6 6 1.2b
285 6 289 254 6 274 205 6 195
8.3
1.9
19.9
34.6
11.9
2.4
17.9
41
%
6.4 6 3a
10.2 6 5y
7.3 6 4c
105/min1/
(pmol/L) 4.6 6 4a
7.1 6 6b
5.7 6 5a
1
a
b
min
377 6 282 760 6 491 526 6 360c
mmol/L
1.5 6 1.4ay 1.1 6 0.8a 2.0 6 5b
mmol/L
4.7 6 0.9a 4.9 6 0.9ab 5.1 6 2.4b
Notes: a,b,cGroups with different letters are significantly different ( p , .05).
SD ¼ standard deviation; OM ¼ older males; AF ¼ adult females; AM ¼
adult males.
n ¼ number of animals; N ¼ number of values from ‘n’
animals] and 8 years in AF (n ¼ 26; N ¼ 219) and AM (n ¼
14; N ¼ 123). Data are presented as mean 6 SD with
a significance level of p , .05.
To define the %BF values that correspond to obese, we
regressed %BF onto each of SI, DI, Ib, TGb, and cholesterol
levels and sought to identify a break-point in the curvilinear
relationships. Similarly, the minimum %BF was ascertained
by regressing %BF onto BW and trying to identify the breakpoint in the curvilinear relationship. Break-point analysis was
performed using the statistical software ‘R’ (version 2.0.0;
Free Software Foundation, GNU project), which identified
the point at which the relationships between variables
became insignificant (i.e., slope not different from zero).
RESULTS
The data used for this analysis are from an ongoing study,
and each animal has multiple representations in this data set
with the OM measured for 14 years and the AF and AM
measured for 8 years. The characteristics of the animals are
summarized in Table 1. Within males, the OM and AM
differed in KG, Gb, DI, plasma cholesterol, and TGb. Female
monkeys were significantly different from males (OM and
AM; p , .0001) in their BW, BF (kg), BMI, AC, and SI.
Basal glucose concentrations (Gb) were significantly higher
in the AM compared to the OM and AF ( p , .0007), but
basal insulin levels were not different among the three
groups. TGb was lower in AF than in AM but was not
different from the OM monkeys, whereas cholesterol levels
were higher in AM than in OM. These findings prompted us
to stratify the analysis according to age range and gender for
the analyses that follow.
Break-points in the relationships between %BF and SI and
DI were at a point of change in slope between the dependent
and independent variables. When %BF was regressed with
SI, an exponential relationship was observed in male (OM,
%BF¼ 28.216 * e(0.091 * SI), p , .001; AM, %BF¼ 23.694 *
e(0.08 * SI), p , .0001) and female monkeys (%BF ¼ 26.12 *
e(0.067 * SI), p , .001) (Figure 1). Using the R software, the
Figure 1. Relationship between % body fat (%BF) and insulin sensitivity
index (SI) in old male (OM) (A), adult male (AM) (B), and adult female (AF)
(C) monkeys. Symbols represent data from individual animal collected over an
8-year (AF and AM) or 14-year (OM) period. The exponential regression lines
of animals which were significant ( p , .05) are shown in the insets.
break-points for maximum attainable %BF before its SI
becomes minimal were 23.2% in OM, 20.8% in AM,
and 17.5% in AF monkeys. DI also showed an
exponential relationship with %BF in male (AM, %BF
¼ 26.67 * e(0.001 * DI), p , .001; OM, %BF ¼ 26.025 *
e(0.001 * DI), p , .001) and female (%BF ¼ 22.819 *
e(0.0004 * DI), p , .001) monkeys. Accordingly, the %BF
break-points for DI were 23.2% in OM, 22% in AM, and
16.4% in AF monkeys. In a regression plot of %BF
against SI, AM and OM showed a similar increase in SI
with decreasing %BF compared to AF. The mean
difference in %BF among all three groups was significantly different at any given SI (OM and AM ¼ 3.5%, AF
and AM ¼ 2.1%, and OM and AF ¼ 1.5%; p , .05).
However, for a given %BF, females had higher absolute SI
values than males. At a mean value of 5.7 SI units, the
average %BF was 20% in OM and 18% in AM versus
REFERENCE BODY COMPOSITION
1521
Table 2. Correlation of Systemic Metabolic Indices
% Fat
KG
Gb,
Ib,
AIR, Cholesterol,
mmol/L pmol/L pmol/L mmol/L
OM
KG
0.49
Gb, mmol/L
0.36 0.19
Ib, pmol/L
0.37 0.21
AIR, pmol/L
0.35 0.09
Cholesterol, mmol/L 0.04 0.05
TGb, mmol/L
0.39 0.31
0.25
0.05
0.06
0.11
0.51
0.01 0.21
0.59
0.46
0.18
KG
0.61
Gb, mmol/L
0.24 0.24
Ib, pmol/L
0.49 0.35
0.14
AIR, pmol/L
0.27 0.01 0.26
Cholesterol, mmol/L 0.03 0.15
0.38
TGb, mmol/L
0.18 0.23
0.48
0.43
0.09 0.19
0.24 0.14
0.87
0.40
KG
Gb, mmol/L
0.24 0.21
Ib, pmol/L
0.28 0.17
0.36
AIR, pmol/L
0.37 0.02 0.18
Cholesterol, mmol/L 0.07 0.11
0.06
TGb, mmol/L
0.44 0.27
0.07
0.41
0.16 0.23
0.27
0.36
0.00
AM
AF
Note: SD ¼ standard deviation; KG ¼ glucose disappearance rate; Gb ¼ basal
glucose level; Ib ¼ basal insulin level; AIR ¼ acute insulin response; TGb ¼
fasting triglycerides.
21.3% in the AF monkeys. Using the interaction between SI and
group, this difference proved to be significant ( p , .0001).
However, there was no significant effect of age on the
relationship of SI and %BF (interaction of SI 3 Age) when
animals in individual groups were analyzed. Also, when the
males were grouped together there was no significant interaction
between SI and age on %BF indicating that age in this group of
animals does not affect the relationship between SI and %BF.
Besides SI and DI, TGb and cholesterol levels and
additional indices of glucoregulation, KG, AIR, Ib, and Gb
levels were examined for any associations with %BF (Table
2). Though Gb, Ib, TGb, and cholesterol levels showed
similar relationships with %BF, a break-point analysis using
these variables did not reach significance due to a high
variability in the data. Hence these variables did not
contribute to the determination of the maximal body fat level.
The lower end of the range for %BF was ascertained
using the relationship between BW and %BF. The %BF
of male monkeys showed an exponential relationship with
their BW (OM, %BF ¼ 2.49 * e(0.168 * BW), p , .001;
AM, %BF ¼ 1.03 * e(0.225 * BW), p , .001) and female
(%BF ¼ 1.02 * e(0.335 * BW), p , .001). Percent BF was
regressed with BW sequentially to identify the break-point
where the relationship indicates most of the weight loss as FFM
(Figure 2). The minimum %BF an animal should have before
increasing loss of lean body mass occurs was ascertained to be
8.5% in OM, 6% in AM, and 5% in AF monkeys.
The above break-point analysis does not provide a measure
of statistical range around the break-point values. The
values, therefore, have limitations. There may be individual
variation among animals, and the measurement of %BF may
not be exact. In either case, animals at the lower end of the
reference body fat spectrum could be at a greater risk for
Figure 2. Relationship between % body fat (%BF) and body weight (BW) in
old male (OM) (A), adult male (AM) (B), and adult female (AF) (C) monkeys.
Symbols represent data from individual animal collected over an 8-year (AF and
AM) or 14-year (OM) period. The exponential regression lines of animals which
were significant (p , .05) are shown in the insets.
negative health-related outcomes even with slight decreases
in body fat. It is therefore prudent to add a safety factor to the
low-end break-point. Based on a comparison of %BF
measurement between DXA and total body water, we calculated a mean difference of 3% for the determination of
%BF and used this as the safety level needed on the lower
end of reference %BF. In so doing, the minimal %BF
below which animals can be classified as underweight were
11.5% in OM, 9% in AM, and 8% in AF monkeys.
The %BF values can also be translated to BMICRL.
Percent BF showed significant correlations with BMI in all
three groups of monkeys (%BF ¼19.3 þ 0.97 * BMI; r2 ¼
0.7, p , .0001 in OM; %BF ¼29.2 þ 1.4 * BMI; r2 ¼ 0.8,
p , .0001 in AF, and %BF ¼30.7 þ 1.2 * %BF; r2 ¼ 0.8,
p , .0001 in AM; Figure 3) with the mean %BF (mean 6
SD) at 21.5 6 10% in OM, 19.9 6 11% in AM, and 17.9 6
9% in AF monkeys. Hence a reference BMI of 32–44 kg/m2
1522
RAMAN ET AL.
Figure 3. Relationship between % body fat and body mass index (BMI) in
older male (OM, closed triangles), adult female (AF, open squares), and adult
male (AM, plus symbols) monkeys. Percent body fat showed significant correlations with BMI in all three groups of monkeys (% body fat ¼19.3 þ 0.97 *
BMI, r2 ¼ 0.7, p , .0001 in OM; % body fat ¼29.2 þ 1.4 * BMI, r2 ¼ 0.8, p ,
.0001 in AF; % body fat ¼ 30.7 þ 1.2 * %BF, r2 ¼ 0.8, p , .0001 in AM).
in the AM, 34–44 kg/m2 in OM, and 26–38 kg/m2 in AF
monkeys was deduced.
Similarly, these break-points can be translated to AC values.
Because %BF and AC have a linear relationship (%BF ¼
11.9 þ 0.66 * AC; r2 ¼ 0.6, p , .0001 in OM; %BF ¼
29.5 þ 1.08 * AC; r2 ¼ 0.8, p , .0001 in AF, and
%BF ¼ 24.9 þ 0.9 * AC; r2 ¼ 0.9, p , .0001 in AM),
we estimated a reference AC of 40–54 cm in AM, 35–53 cm
in OM, and 35–44 cm in AF monkeys using the reference
range of body fat (Figure 4).
DISCUSSION
Using glucoregulatory indices and changes in body
composition, we developed a reference range of %BF
a monkey can have before being classified as underweight
or overweight and obese. Insulin-sensitivity measures and
changes in FFM during weight change have been used to
identify the reference range for %BF; hence, these data
promise to be a good index to define health using a group of
metabolic predictors in young and old rhesus monkeys. This
is an effort in classifying rhesus monkeys into underweight,
reference, and obese based on their %BF and will make it
easier to compare health outcomes with humans.
The linear relationship between BMI and body fat can be
used effectively to ascertain the %BF of an individual based
on their BMI. However, this relationship needs to be analyzed
with caution, because a higher BW can be due to a higher lean
body mass, in which instance using BMI may lead to
misclassification of the individual as overweight or obese.
Nonetheless, BMI has been used effectively to assess obesity
and underweight in numerous human studies (26–28).
Overweight and Obesity
The literature is replete with evidence of body fat being
strongly associated with most of the glucoregulatory pro-
Figure 4. Relationship between % body fat and abdominal circumference
(AC) in older male (OM, closed triangles), adult female (AF, open squares), and
adult male (AM, plus symbols) monkeys. Percent body fat showed significant
correlations with AC in all three groups of monkeys (% body fat ¼11.9 þ 0.66 *
AC, r2 ¼ 0.6, p , .0001 in OM; % body fat ¼29.5 þ 1.08 * AC, r2 ¼ 0.8, p ,
.0001 in AF; % body fat ¼ 24.9 þ 0.9 * AC, r2 ¼ 0.9, p , .0001 in AM).
cesses in the body. A lower %BF has been associated with
better glucose regulation and better insulin sensitivity (29).
Significant correlations between basal and stimulated insulin
levels with various indices of obesity have been noted in
monkeys (2,9) and humans (30,31). Hyperinsulinemia has
been shown to occur as one of the initial consequences of
increased BW or body fat (32). In fact, this relationship has
been best reported in monkeys with body fat greater than
30% of their BW (33,34). Conversely, a reduction in BW
or body fat has been shown to decrease insulin dosage or
eliminate the need for supplemental insulin in type 2 diabetics
(35,36). Hence, we used insulin sensitivity and disposition
indices to identify the upper end of reference %BF.
Hypertriglyceridemia and hypercholesterolemia have
been observed in obese humans (37) and nonhuman primates with higher %BF (3,9), but we were unable to find
a break-point associated with these variables. Perhaps this is
because there is a strong genetic component to the elevated
plasma triglycerides (32,38). This genetic component may
have obscured the break-points, wherein the fasting triglyceride and total cholesterol levels were higher in animals
with higher body fat but were highly variable (CV was 0.3
for plasma cholesterol and 1.9 for TGb). Nonetheless, the
mean TGb levels in the male and female monkeys with
a reference %BF was 1.1 6 0.9 mmol/L and 0.7 6 0.4
mmol/L, respectively, compared to 2.7 6 5 mmol/L and
1.4 6 0.9 mmol/L in obese animals (p , .001). The levels
seen in reference %BF animals were within the ranges defined for humans (39).
Overweight Versus Obese
The relationship between %BF and glucoregulatory
indices was exponential and could not be used to
differentiate between overweight and obese monkeys.
Nonetheless, obesity is associated with hyperinsulinemia,
REFERENCE BODY COMPOSITION
Table 3. Characteristics of Monkeys When Assigned to Underweight,
Normal, and Obese Categories (Mean 6 SD)
Variable
Weight,
kg
Body
fat, %
Gb,
mmol/L
I b,
pmol/L
TGb,
mmol/L
Cholesterol,
mmol/L
Males
Underweight 8.8 6 1a 5 6 1a
Normal
10.7 6 2b 16 6 5b
Obese
14 6 2c 29 6 5c
3.1 6 0.3a 90 6 48a 0.6 6 0.3a
3.4 6 0.4b 200 6 144b 1.1 6 1a
3.6 6 1c 372 6 337c 2.8 6 5b
4.6 6 1a
4.7 6 1a
5.2 6 2b
Underweight 5.9 6 1a 4.2 6 0.5a 3.1 6 0.3a 133 6 118a 0.6 6 0.2a
Normal
7.0 6 1b 10 6 3.9b 3.4 6 0.4b 164 6 107a 0.7 6 0.4a
Obese
9.3 6 1c 27 6 6.2c 3.5 6 0.5b 319 6 324b 1.4 6 1b
4.5 6 1a
5.1 6 1b
4.9 6 1b
Females
Notes: a,b,cDifferent letters indicate significant differences between underweight, normal, and obese groups within males and females ( p , 0.05).
SD ¼ standard deviation; Gb ¼ basal glucose level; Ib ¼ basal insulin level;
TGb ¼ fasting triglycerides.
insulin resistance, and glucose intolerance (11). It has been
shown that animals with increasing body fat may gradually
become diabetic after going through a sequence of events
of normoglycemia–normoinsulinemia, normoglycemia–
hyperinsulinemia, and hyperglycemia–hyperinsulinemia. With
regard to this sequence, there are two diabetic monkeys in
the larger study cohort that were not included in this
analysis. The %BF of these two animals was 34.2% and
37.6% at the time of diagnosis. In addition, Gresl and
colleagues (1) reported one additional animal in the larger
study that has since died and was not included in the current
data analysis (this animal became diabetic and had a %BF of
36% at the time of diagnosis). In our analysis, we concluded
that the maximum body fat a male animal could have before
SI became minimal was ;22% of BW. Hence, we
conjecture that male animals with %BF between 22% and
36% can be categorized as overweight, above which we see
more animals with frank diabetes.
The findings of Hotta and colleagues (40) can be
compared with ours. Hotta and colleagues grouped a cohort
of rhesus monkeys according to their fasting plasma insulin
and glucose levels using a priori values to characterize the
animals as lean (normal) hyperinsulinemic or diabetic
(obese). They reported that the ‘‘normal weight’’ monkeys
in their study had a mean %BF of 18.1 6 3.3% and normal
fasting plasma glucose and insulin concentrations. The male
monkeys in our data set with a ‘‘reference’’ %BF (,22%;
mean ¼ 16 6 4.5%) were also normoglycemic (3.4 6 0.4
mmol/L) and normoinsulinemic (200 6 143 pmol/L); these
values are comparable to those of the animals of Hotta and
colleagues (40) (Table 3). The obese group of Hotta and
colleagues had a mean %BF of 32.6 6 2.7% and were
hyperinsulinemic but normoglycemic, thus paralleling our
data in the animals above the upper %BF break-point.
Among the obese group reported by Hotta and colleagues
(40), noninsulin-dependent diabetes mellitus was observed
in a group of monkeys with mean %BF 35.1 6 4%, similar
to the three diabetic animals in our larger study. These data
support our conjecture on classifying overweight rhesus
monkeys as 22–34%BF and obese rhesus monkeys as
35%BF, although further evidence is needed because the
number of animals on which this is based is still small.
1523
Underweight with Minimal Body Fat
On the other end of the spectrum of body fat, we
identified a minimal %BF to define reference or normal
weight of ;10% in male and 8% in female rhesus monkeys.
There are, however, few studies in literature that provide
data against which we can compare these values. One study
by Altmann and colleagues (41), however, reported that
young adult baboons foraging in the wild had %BF as low
as 2% (in adult females) and 1% (in adult males).
Anthropometric data indicated that, despite their lower
%BF, growth among the female baboons continued and that
the animals maintained reproductive function. This might
indicate that our minimal %BF values were too conservative; however, caution should be maintained when comparing our data to animals under free-living conditions, due to
the high fiber content of the diet and the high activity level
of the free-living animals compared to our caged animals.
Both of these factors could differentially influence the
relationship between SI and %BF.
Despite the data on %BF in wild animals, we were
concerned about using minimal %BF obtained by breakpoint analysis to define underweight. This concern stemmed
from the rapid weight loss and loss of FFM that was
observed when some animals neared but were still above
these critical values and the potential for serious negative
health outcomes that could accompany the loss in FFM
(13,14). This concern was amplified by the knowledge that
the measurement of %BF is accompanied by a measurement
error, and thus when the break-point values are applied to
individual animals, %BF might be overestimated and the
animal could be at risk of being underweight despite an
apparently normal %BF. Because of these two factors, we
added a safety margin of 3% to the %BF in an effort to
reduce the risk in individual animals.
Finally, it should be noted that our data were derived
from animals that were part of a long-term dietary
restriction study. Thus, there was a possibility that the
relationships between %BF and the other variables in the
diet-restricted animals were a little different from general
colony animals. No interactions between dietary treatment
and the parameters used for the above analyses were
observed, however; thus we conclude that these values to
define underweight, overweight, and obesity are reasonable.
By using these cut-offs to define nutritional status in rhesus
monkeys, comparison of studies between those conducted
in rhesus monkeys with those conducted in humans should
be easier.
ACKNOWLEDGMENTS
This work was supported by grants P01 AG-11915 (to R. Weindruch)
and P51 RR000167 (to the Wisconsin National Primate Research Center,
University of Wisconsin, Madison). This research was conducted in part at
a facility constructed with support from Research Facilities Improvement
Program grant numbers RR15459-01 and RR020141-01.
We gratefully acknowledge the excellent technical assistance provided
by J. A. Adriansjach, C. E. Armstrong, and the animal care and veterinary
staff of the Wisconsin National Primate Research Center.
Address correspondence to Dale A. Schoeller, PhD, UW-Madison,
Department of Nutritional Sciences, 1415 Linden Drive, Madison, WI
53706. E-mail: [email protected]
1524
RAMAN ET AL.
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Received May 18, 2005
Accepted July 7, 2005
Decision Editor: James R. Smith, PhD