CLIN. CHEM.24/5,
772-777
(1978)
Associationswith Body Weight of Selected Chemical Constituents
in Blood:EpidemiologicData
LouIs Munan, Anthea Kelly, Claude PetltClerc, and Bernard Billon
Data on 2368 subjects, ages 10 to 96 years, of both sexes
In a population probability sample were used to Identify
body weight dependencies for 12 constituents in serum,
three in plasma, and one in whole blood, independently of
age. Three patterns emerged. (a) Positive weight dependencies were seen with serum urate, glucose, lactate
dehydrogenase, and cholesterol, In that most subjects with
high concentrations of the analyte were in the high-weight
group and the fewest in the low-weight group of either sex.
Similar associations
with body weight were noted for
creatinine,
protein, blood hemoglobin,
and aspartate
transaminase, but only in males. (b) Inverse relationships
were found with respect to inorganic phosphate in either
sex and to calcium in females only, i.e., the percentage
of subjects with high concentrations of either of these
analytes was high in the low-body-weight group and low
in the high-weight group. (c) A third set of substances was
identified as not being weight dependent in either sex: Na,
K, Cl, urea nitrogen, bilirubin, and alkaline phosphatase.
These results indicate that body weight is an important
attribute in defining reference ranges of several blood
analytes once age and sex dependencies have been taken
into account.
AddItIonal
body
studies .
Keyphrases:
ranges . population
adjustment for age
weight . reference
variation, source of
-
In addition to age and sex, body weight is an important host characteristic
that varies with the concentration of several blood analytes of diagnostic importance. Although the relationships
of chemical constituents to age and sex have been explored, the associations with body weight are less widely recognized. Here,
we report results of screening 16 blood substances for
their association with body weight in either sex while
controlling for variability due to age.
Methods
A statistical
sample of 2368 persons,
1085 males and
1283 females between 10 and 96 years of age, was drawn
Epidemiology Laboratory and Laboratory of Clinical Chemistry,
Faculty of Medicine, University of Sherbrooke, Sherbrooke, Quebec,
Canada J1H 5N4.
Received Jan. 17, 1978; accepted Feb. 17, 1978.
772
CLINICALCHEMISTRY,Vol. 24, No. 5, 1978
by multistage probability methods from a population
of about 5.5 X iO noninstitutionalized
individuals living
in a region of low population density and mobility (1).
Data on thepopulationunder surveillance, on itsclinical
chemicalvalues,and on its selection appear elsewhere
(2-6). The procedure fortheselection
ofthepopulation
sample is one commonly used in health surveys inwhich
thestudygroupisidentified first by census enumeration
districts, then by blocks of households, and finally by
households. By applying various sampling fractions at
each of these three stages,the requisitenumber of
subjects is obtained.
The end result is a group of
subjects who are representative
and free of selection
bias.
A pre-breakfast sample of venous blood was obtained
at home by an experienced nurse, with the subject in the
sitting position and with the use of tourniquets
and
Vacutainer Tubes. The blood samples were immediately
placed on iceand transportedto the laboratoryand
separatedwithin4 h ofcollection,
an interval
mandated
by the considerable distances involved. Hemolyzed or
technically unacceptable
blood was discarded and another sample taken. Automated methods used for the
analysis (3) are summarized in Table 1.Body weight
and heightwere recordedatinterview on thebasisofthe
subject’s response. Respondents’ answers were validated
on a subsample ofthe populationby use ofa portable
scale; measured and stated body weight were found to
correspond
closely. For the purpose of this analysis,
weight was defined simply as the absolute body mass in
kilograms without consideration
to the individual’s
height, proportion of fatty tissue, of fluid or of muscle,
or to other corporalattributes.
All raw data were
transformed
into centiles regardless of their adherence
to gaussian frequency distributions.
The distribution
of body weight as well as that of most of the blood constituents was nonetheless
near gaussian by visual inspection,
exceptforbilirubin,
alkaline
phosphatase (EC
3.1.3.1), lactate dehydrogenase
(EC 1.1.27), and aspartate aminotransferase
(EC 2.6.1.1), among others. Age
effects were removed by calculating for each individual
the percentile for body weight and for each analyte
within the following age groups: 10-14, 15-19, 20-24,
Table 1. Summary of Laboratory Methods Used
Serum analyt.
Laboratory method
Alkaline phosphatase
Aspartate
aminotransferase
Bilirubin
Urea nitrogen
Calcium
Chloride (plasma)
Cholesterol, total
Creatinine
Glucose
Enzymatic hydrolysis of p-nitrophenyl phosphate at 37.5 #{176}C
followed by dialysis (20)
Production of oxaloacetic acid at 45 #{176}C
followed by dialysis and reaction with diazonlum salt of nbutyl-4-methoxymetanllimide
(21)
Formation of azobilirubin after dialysis (22
Reaction with diacetyl monoxime after dialysis (23)
Cresolphthaleln complexone containing 8-hydroxyquinoline after dialysis (24)
Direct reaction with mercury thiocyanate (25)
Modified Liebermann-Burchard reaction, direct (26)
Jaff#{233}
reaction (alkaline picrate) after dialysis (27)
Reduction of cupric-neocuproine chelates in alkaline medium after dialysis (28)
Hemoglobin (whole
blood)
Spectrophotometry
Lactate
Lactate to pyruvate reaction. Coupling to reduction of tetrazolium dye with NAD diaphorase at 37 #{176}C
dehydrogenase
Phosphorus, inorganic
Protein, total
Potassium (plasma)
Sodium (plasma)
Urate
(29)
Phosphomolybdic complex and reduction by SnCI2-hydrazine after dialysis (30)
Modified biuret reaction with serum blank
Flame photometry (Model IL-143 by Instrumentation Laboratories, Inc.)
Equipped with a dilutor. Manual operation
Flame photometry (Model IL-143 by Instrumentation Laboratories, Inc.)
Equipped with a dilutor. Manual operation
Phosphotunqstate reduction after dialysis (31)
25-34, 35-44, 45-54, 55-64, 65-74, and 75 years and
over. These values were used in lieu of the measured
values. The age-specific percentiles were grouped to give
age-specific quantiles for body weight and for each analyte.
For each chemical constituent,
a 5 X 5 matrix was
constructed
containing frequencies of individuals arranged by blood chemistry quintile against body-weight
quintiles. In each matrix only the upper quintile of each
analyte was retained and its frequency within each
quintile of body weight was studied. The tabular data
thus made possible the examination
of the proportion
of individuals with high concentrations
of any one analyte at each of five categories of body weight. This
approach permits the ready identification of associative
trends between body weight and each analyte. It has the
advantage of being relatively simple, especially when
the body of data is sizeable and the dependent variables
are numerous. Table 2 shows the percentile points in
absolute units defining the upper quintile (>80%) of the
analytes. With respect to body weight, the four percentile points (in kilograms) defining the quintiles by
age and sex are contained in Table 3. The analysis of the
relationship
of body weight to chemical constituents
depends on the assumption
that if there is no weight
dependency,
the proportion of persons with high concentrations
of an analyte in each of the five weight
groups should be about the same. No tests for significance were deemed necessary in view of the emphasis
given to graphical presentations
and because they become less useful if the number of observations is sizeable
as in our case.
We report data on chemical constituents under three
headings: (a) those showing graded positive or negative
changes at each successive range of body weight in both
sexes, (b) those which demonstrate
gradations
with
body weight, but only in one sex, and (c) those in which
we could discern no consistent association with body
weight.
Results
Weight-Dependent
Variables
In both sexes. Positive associations of body weight
with serum constituents are most clearly seen for urate,
glucose, lactate dehydrogenase,
and cholesterol in that
order. The percent of subjects with high concentrations
of these analytes varies directly with body weight in
either sex. Inorganic phosphate, on the other hand, is
inversely associated with body weight in either sex
(Figure 1).
In males only. The blood constituents that are clearly
weight-dependent
in males only are creatinine, protein,
hemoglobin,
and aspartate
transaminase.
High concentrations of these analytes tend to be associated with
high body weight in the same individuals (Figure 2).
In females only. The sole constituent
that varies
linearly with body weight in females only is total calcium. The relationship is an inverse one; i.e., high calcium
concentrations
are associated with low body weights
(Figure 2).
Constituents
without clearly defined weight patterns. Several analytes showed no clearly defined trends
with body weight, but are shown in Table 4 for completeness.
Discussion
The contribution
that body weight makes to the
variability of chemical components
in blood has been
the subject of many investigations
on single substances
CLINICAL CHEMISTRY,
Vol.
24, No. 5, 1978 773
Table 2. Percentile Points Defining the Upper Qulntile ( 80%) of Values for Some Chemical
Constituents, by Age and Sex
analyt.
and unIts
Blood
Sex
Alk phosphatase
(U/I)
Aspartate aminotransferase
(U/I)
Bilirubin
(imol/l)
M
F
M
F
M
F
Urea nitrogen
M
(mmol/I)
F
M
F
Calcium
(mmol/I)
M
Chloride
(mmol/l)
Cholesterol
(mmol/l)
F
M
F
M
F
M
Creatinine
(jmoI/l)
Glucose
(mmol/I)
F
Hemoglobin
M
(mmol/I)
F
M
F
M
F
M
F
M
F
M
F
M
F
Lactate dehydrogenase
(U/I)
Phosphorus
(mmol/I)
Protein
(g/I)
Potassium
(mmol/I)
Sodium
(mmol/l)
Urate
(jmol/l)
10-14
15-19
251.0
244.5
46.0
43.5
10.3
10.3
5.36
4.82
2.53
2.55
101.0
106.0
5.18
5.30
70.7
61.8
5.67
5.61
2.22
2.20
234.5
235.5
164.0
1.74
1.74
75.0
76.0
4.9
4.8
142.0
142.0
327.3
303.5
79.5
44.5
35.0
13.7
10.3
6.07
5.36
2.53
2.48
106.0
107.0
5.25
5.22
88.4
79.6
5.72
5.50
2.47
2.22
213.5
186.0
1.65
CLINICAL CHEMISTRY,
Vol.
24, No. 5, 1978
77.0
63.5
46.0
34.0
34.0
12.0
10.3
6.25
5.00
2.53
2.45
107.0
107.5
5.83
6.02
97.2
79.6
5.44
2.51
2.20
195.0
12.0
10.3
6.43
5.36
2.53
2.43
106.0
107.0
6.24
6.19
106.1
79.6
5.67
5.39
2.50
2.18
200.0
188.5
186.0
5.19
76.0
4.9
4.7
142.0
142.0
380.8
392.7
303.5
315.4
1.55
77.0
25-34
76.5
64.0
43.0
1.52
1.42
78.0
75.0
4.9
4.6
142.0
142.0
but of only a few (8-10) in which several constituents
were examined simultaneously for their association with
variables that included body weight. In the present
study we report analyses for 15 selected constituents in
serum or plasma and one in whole blood (Table 1). The
data analysis does not measure the exact contribution
of body weight to analyte variance (or their interactions)
as is customarily
done in regression analyses (6) but
fixes itself on a ready identification of those constituents
for which concentration is strongly associated with body
weight. As stated, the body weight dependency
is analyzed with the age effects minimized and without regard
to several other body attributes that could be of interest,
including height, ponderal, or similar indices.
Urate. The urate-weight
association is easily the most
striking among those studied here and demonstrates
that any interpretation
of urate values without appropriate consideration
of the subject’s weight is likely to
be misleading. The phenomenon
has been observed
repeatedly in most populations (2,8,10, 11, 13) and with
so few exceptions (14, 15) that there is little doubt about
its validity. Our data add a new facet to the knowledge
774
20-24
1.39
1.35
76.0
75.0
4.8
4.7
142.0
141.0
422.4
315.4
Ag., years
35-44
45-54
79.0
64.0
85.0
77.0
48.0
50.0
37.0
12.0
10.3
6.42
5.36
2.46
2.43
107.0
108.0
6.87
6.36
97.2
79.6
5.88
5.44
2.50
2.22
213.0
198.0
1.32
1.26
76.0
41.0
12.0
10.3
6.79
6.07
2.48
2.50
107.0
107.0
7.09
6.87
97.2
88.4
5.94
5.67
2.53
2.20
213.5
205.0
75.0
4.9
4.8
143.0
142.0
428.4
315.4
1.22
1.26
76.0
75.0
4.8
4.8
142.0
142.0
419.5
351.1
55-64
65-74
86.0
91.0
45.0
40.0
12.0
10.3
7.14
6.79
2.43
2.48
106.0
106.0
6.81
7.11
106.1
88.4
6.05
5.94
2.54
2.21
216.5
100.0
42.5
12.8
12.0
7.14
6.79
2.44
2.50
107.0
107.0
6.59
7.56
114.9
88.4
5.72
6.00
2.45
2.23
204.0
211.0
1.16
214.0
1.12
1.27
75.0
75.0
5.0
4.8
143.0
143.0
401.6
359.9
1.26
76.0
76.0
4.9
4.8
143.0
143.0
467.1
380.8
94.5
41.0
75
111.0
106.5
47.0
42.0
13.7
10.3
9.48
8.04
2.43
2.46
107.5
108.0
6.06
6.82
132.6
106.1
5.78
5.94
2.41
2.26
225.0
214.0
1.08
1.23
75.5
75.0
5.1
5.0
143.0
143.0
467.1
392.7
about this relationship,
namely, that the proportions
of hyperuricemics in each weight category is remarkably
alike in both sexes once age effects have been taken into
account.
Glucose. The percent of subjects with high serum
glucose concentrations
varies directly with body weight
in either sex. Lellouch and collaborators,
for example,
in a study of about 4000 men between 46 and 52 years
of age (10) reported that, when body fat ranged from
less than 8 kg to 30 kg or more, the proportion of hyperglycemics (>1.30 g/liter) rose from about 1 to over
10%.
Lactate
dehydrogenase.
This enzyme shows remarkable weight dependency in our study, in agreement
with Winkelman et al. (9), who reported significantly
higher activity in overweight individuals than in those
of normal weight.
Cholesterol. The cholesterol-body
weight association
is not as remarkable as some might be led to believe,
especially in males (12). It certainly is not as marked as
that of serum urate in either sex (Figure 1). Cholesterol
gradients that are not as sharp as those found in tn-
Table 3. Percentile Points (in kg) Defining Body-Weight Quintiles8 by Age and Sex
Body-weight
p.rc.ntlI.
points at four p.rc.ntII.
Isysis
r.mau,s
Malls
Ags, a
20th
40th
10-14
32.5
15-19
56.0
36.0
40.5
n146
Range, 24-70 kgb
58.0
63.0
80th
80th
20th
40th
52.0
33.0
67.0
46.0
40.0
45.0
n=150
Range, 24-76 kgb
49.0
53.5
n150
Range,31-135 kg
20-24
58.0
63.0
67.0
35-44
63.0
65.0
67.0
74.5
n183
Range, 5 1-135 kg
72.0
79.0
77.0
47.0
50.0
65.0
55-64
62.0
70.0
n139
79.0
83.0
49.0
54.0
72.0
86.0
52.0
62.5
Range, 54-106 kg
66.0
72.0
56.0
58.0
63.0
70.0
51.5
77.0
52.0
57.0
n190
Quintile defined by 20th, 40th, 60th, and 80th percentile
Extreme range: 0 to 100percentIle for each age group.
58.0
65.0
61.0
67.5
63.0
70.0
Range,36-106 kg
61.0
65.0
72.0
n=130
Range, 36-97 kg
52.0
81.0
58.0
63.0
72.0
n=104
Range,28-124 kg
81.0
48.0
54.0
n40
Range, 44-93 kg
b
58.0
Range,33-104 kg
86.0
n=92
Range,46-104 kg
>75
54.0
n166
n=103
65-74
58.0
n218
Range, 34-97 kg
Range,56-126 kg
67.0
49.0
n121
Range, 38-83 kg
n132
Range,54-117 kg
45-54
80th
n160
Range, 33-83 kg
n102
Range, 47-129 kg
25-34
60th
61.0
69.0
n=44
Range, 38-88 kg
points.
glyceride-weight
relationships
have been noted elsewhere (10). The weight-cholesterol
association studied
in 921 males by Allard and Goulet (16) revealed increases in mean serum cholesterol concentrations
as the
percentage weight above the ideal weight increased up
to 25%. Other investigators,
however, failed to find
significant
correlations
between
serum cholesterol
concentrations
and body weight in either males or females (8).
Phosphorus.
We are aware of only a few reports that
studied the covariation
of inorganic phosphate
with
body weight. Goldberg et a!. (8) found no significant
association between inorganic phosphate and weight in
519 subjects of either sex. Winkelman
et al. (9), in a
study of 423 males and 557 females, reported no significant differences in concentrations
of this analyte
between overweight
or underweight
individuals
as
compared to normals. Our data support the view that
in both sexes the percentage of individuals with high
values for inorganic phosphates
in serum is highest in
those whose body weight is lowest.
Creatinine.
Our analysis has shown that the percentage of persons in the upper quintile of creatinine
concentration
is highest in males whose body weight is
in the upper quintile and lowest in males who are in the
lowest quintile. Our findings agree with those of Doolan
et al. (17) with respect to the direction of the correlation
between serum creatinine and body weight. However,
did not find any linear trends in females under conditions where age effects had been taken into account
reduced.
Protein. No significant
association
between total
protein concentrations
and body weight was found by
Goldberg et al. (8) in 248 males.Our observation is that
there is a higher proportion of persons with high concentrations of serum protein among overweight males.
Table 4. Constituents Showing No Consistent
Body-Weight AssocIations
Both sexes Na, K, Cl, urea nitrogen, billrubln, alkaline
phosphatase
Males only Ca
Females
only
Protein, creatinine, hemoglobin, aspartate
aminotransferase
CLINICALCHEMISTRY,Vol. 24, No. 5, 1978 775
Fig. 1. Percentage of persons having high concentrations of a
given analyte In low (L), medium ( and high (l body weight
categories
A, sate; B, glucose; C, lactate dehydrogenase;0, cholesterol; E, phospho-
rus
Fig. 2. Percentageof persons with high concentrations of a given
analyte in low (L), medium (M), and high (! body weight categories
A, creatinine; B, protein; C, hemoglobin.
This does not apply to females and is in agreement with
the negative findings of Goldberg et a!. (8) for 271
women (8).
Hemoglobin.
Blood hemoglobin concentrations
are
also known to be directly associated with body weight
in males. Among the several confirmations
of this phenomenon are the reports by Acheson et al. (11) and by
Pincherle and Shanks (18). Both groups of investigators
found, as we have, that the direct association between
body weight and hemoglobin concentrations
was predominantly a phenomenon
confined to males.
Aspart ate aminotransferase.
Siest eta!. studied age,
sex, and body-weight dependencies
for asparate aminotransferase.
Their report states that this enzyme’s
activity is independent
of weight in all males and in
females under 70 kg. In females, there was little or no
variation in the 2.5 and 50 percentiles for asparate aminotransferase,
whereas in the other two percentile
points there are significant increases with increasing
weight over 70 kg (19). Our results support the view that
the percentage of males with high serum asparate aminotransferase
activity is lowest in the low-weight category and highest in the high-weight
category when
corrected for age effects, and, secondly, that there is no
consistent enzyme-weight
correlation in females.
Calcium. Serum calcium and body weight were not
correlated in one report on 271 females (8). Our data
demonstrate
an inverse relationship in females only, in
that the low-weight category contained the highest
proportion of subjects in the upper quintile of calcium
concentrations,
whereas the high-weight
group contained the lowest percent of subjects in the upper
quintiles of calcium concentrations.
In conclusion, we have screened some blood analytes
of diagnostic importance to try and see if their values
bear a relation to the subject’s weight. We have found
that, of the 16 analytes thus examined, 10 demonstrated
weight dependency in one or both sexes. Of these, most
tend to increase with body weight. The exceptions are
phosphorus and calcium, which decrease. It is the aim
776
CLINICALCHEMISTRY,Vol. 24, No. 5, 1978
0. aspartate
aminotransferase
of a second set of analyses to quantify and further detail
the associations so identified. It is worth restating that
the assessment of body weight dependencies
of clinical
chemistries was done under conditions where age effects
were minimized. The disagreement between our results
and those reported by other investigators
with respect
to some analytes, when not explainable
in terms of
difference due to chemical methodology, to investigative
procedures, or to population under study, may be due
to the lack of adjustment
for age effects. We have also
expressed body weight straightforwardly
and roughly
in kilograms without recourse to the several indexes
which correct for height, because their use and interpretation in population studies is highly questionable
(32) and because the relative merits of such indexes
make it difficult to select the one that would have distinct advantages over body weight in either sex.
Financial support was given by Health and Welfare, Canada (Grant
No. 605-20-63). Technical support in epidemiology was providedby
Th#{233}r#{232}se
Rancourt, Francine Vaillancourt Ho, and Bette Sisco.
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