High Calcium and Milk in
Children: Bones of Steel?
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• For the last 20 years the National Academy of
Sciences, NIH and USDA have produced
guidelines and policies advocating a minimum
calcium intake of 800 mg/day calcium for
elementary school-aged children and 1300mg/day
for adolescents “to keep bones strong” for the
prevention of osteoporosis and fractures
• Milk and dairy is often promoted as the preferred
food to boost dietary calcium
• In comparison, the WHO recommends a minimum
intake of 400-500mg/day of calcium for people in
countries with a high fracture incidence over the
age of 50, with no minimum intake for children and
adolescents
Estimated Ca Adequate Intake values
lead to Strong Policies
• Federal policy requires every child who is part of the
national school lunch program to be provided milk
(and no funded alternatives) with every meal
• This is federal policy instituted with the intent of
providing enough milk to have children reach the
recommended calcium levels in order to "build strong
bones" and prevent osteoporosis later in life
• Schools and Doctor’s offices, especially pediatricians,
put up posters or hand out pamphlets encouraging
increased dairy intake for bone health (usually
provided by the National Dairy Council)
• Dairy accounts for 73% of dietary calcium
intake in the U.S., one of the highest % in the
world
• Osteoporosis and fracture rates in the U.S.
are also one of the highest in the world
Are these recommendations and strong
policies based on a solid foundation of
evidence?
• I. What studies are the current federally
recommended dietary calcium levels in
children based on?
• II. Does the scientific literature show that
increasing dietary calcium in children will
increase bone strength in the long-term?
Does increasing dietary calcium effect the
rate of childhood fractures or osteoporosis
later in life?
• III. Is milk the best source of dietary calcium?
Background: Calcium and
Bones
• Over 99% of body Ca is in bones and
teeth and approx 1/3 of bone is made
up of Ca
• Bone is constantly undergoing
resorption and new bone formation =
remodeling
Ca absorption and excretion has complex
relationship with other nutrients and
substances:
• Calcium Synergists:
Copper, potassium, boron, strontium, sodium,
CoQ10,Chromium, zinc, titanium, Vitamin B5, Vitamin K,
[Magnesium, Vitamin D]
• Calcium Antagonists / Inhibitors:
Phosphorus, iron, manganese, germanium, chloride, sodium,
chromium, zinc, sulfur, Vitamin A, Vitamin C, manganese, niacin
/ niacinamide, PABA, [magnesium, Vitamin D], phytic acid,
oxalic acid, lecithin, mineral oil, alcohol, insoluble fiber, caffeine,
alcohol, protein
• Most of the above are dose-dependent. They are cofactors at normal levels, and antagonists at higher
levels.
Ca absorption and excretion has complex
relationship with other factors:
• Estrogen: Decrease in estrogen
associated with accelerated bone loss,
especially important in postmenopausal
women
• Body composition (particularly adipose
tissue)
• Exercise: weight-bearing activity or
mechanical loading greatly affects bone
mass, shape and strength
Measurement of Bone Strength
• Dual energy X-ray absorptiometry (DXA): Two X-ray
beams with differing energy levels are aimed at the
patient's bones. Soft tissue absorption is subtracted
out to obtain the BMD, determined from the
absorption of each beam by bone
• Bone Mineral Density (BMD): The amount of
mineralized bone tissue in a given area, g/cm2
• Avg BMD = BMC/width at scanned line
• Bone Mineral Content (BMC): in g/cm, is thought to
be more appropriate to a growth study since there is
no mechanical reason why density should change
with growth
I. What is the science behind current federally
recommended dietary calcium levels for
children?
• The NIH and the most recent “Surgeon
General’s Report on Bone Health and
Osteoporosis” states on their official website
that children aged 4-8 years “need” 800mg
Ca/day and aged 9-18 years “need”
1,300mg/day to maintain Bone Health
• These AI recommendations come from the
Dietary Reference Intakes (DRI) report
prepared by the Institute of Medicine in 1997
How did DRI report (IOM 1997) set AI for
Calcium for ages 4-8?
• Two publications were used to estimate Ca
accretion (60-200 mg/day) for females of this
age group:
- Leitch and Aitken, Nutr Abs Rev,1959, made
indirect estimates based on body weight
- Ellis et al., Am J Clin Nutr, 1997, used DXA to
directly estimate BMC
DRI report (IOM 1997) :Setting AI for ages
4-8
• No sufficient data for this age group available
from which to calculate Ca intake needed to
achieve estimated level of Ca accretion
• So used balance studies in older age group
(ages 9-18, which showed that for Ca
retention of up to 174mg/day, need intake of
800-900mg/day) and applied this same value
to younger age group. No balance studies in
boys, so girl values applied to both sexes.
So how does DRI report (IOM 1997) set
AI for ages 9-18?
• Three approaches were utilized as
primary indicators of adequacy:
- Balance studies to measure Ca
retention as a function of Ca intake
- Clinical trials in which BMC was
measured in response to variable Ca
intakes
- Factorial estimates of requirements
DRI report (IOM 1997): Indicators used to
set AI for ages 9-18
• Calcium Retention approach:
Determined desirable Ca retention from one study, Martin et al., Am J
Clin Nutr, 1997:
- n=228 aged 9.5-19.5 from two elementary schools using DXA
annually over 4 years to determine whole body BMC. Crosssectional analysis of pooled data used to calculate peak BMC
velocity (PBMCV). No errors reported anywhere in this publication!
- Maximum Ca retention was then calculated to be 282 mg/d for boys
(age 14.5) and 212 mg/d for girls (age 13.0)
- Using peak BMCV values for all the older (9-18) and younger (4-8)
age-groups in the DRI AI estimate translates into calculating higher
Ca retention numbers, therefore higher calculated intake needed,
ultimately leading to a higher AI
DRI report (IOM 1997) Indicators used to
set AI for ages 9-18
• Calcium Retention approach:
To estimate Ca intake that results in the levels of Ca
accretion in bone (calculated from Martin et al.), DRI
report applies a non-linear model (by Jackman et al.) to
the combined data of three existing Ca balance studies
(Jackman et al., Am J Clin Nutr, 1997; Matkovic et al.,
1990, Greger et al., 1978) in white females aged 12-15
with added estimated sweat losses (estimated from a
separate study) to come up with an intake of 1070
mg/d for girls and 1310 mg/d for boys
DRI report (IOM 1997) Indicators used to
set AI for ages 9-18
To understand the DRI approach let’s first
take a look at the Jackman et al. model
and method of determining AI
Jackman et al. measure Ca excretion as a function of Ca intake
Fecal Ca excretion (II)
Urinary Ca excretion (I)
Red lines were superimposed onto graph from Jackman et al. in order to illustrate
Jackman Ca retention data shown without model
Jackman data: What is in there?
There is a rising tendency –
But that is really all that can be inferred from this set of data.
Jackman et al. assume that the smallest amount
necessary to reach saturation should be the
recommended amount
So we need to find this point in the data by a)
determining the saturation level and b) for which
lowest intake level saturation is reached
Jackman data: Where is the Ca saturation?
Assuming that the measured window does
actually stretch into the saturation regime
and further assuming that the data > 1600
mg/d represent this saturation regime, we
find the following 95% CI (17/18 points
inside).
Jackman data: What can really be inferred?
Superimpose rising tendency with level of saturation and follow Jackman’s
reasoning (“Recommended value is point where the slope’s CI first touches
the average saturation level”), the Ca intake should be somewhere around
700 mg/d.
Jackman data with the nonlinear model function fitted to it
Jackman: What do they read out of their data? And how?
Jackman introduces a non-linear fitting function based on its ability to
fit the data (“many models were evaluated but this one gave the best
fit”).
This approach is problematic :
• As we saw, this particular data set cannot provide meaningful
information beyond an average linear trend (one free parameter)
• Generally functions with several free parameter can fit anything,
therefore the ‘best fit’ argument doesn’t make sense
• Even if the researchers insist on the existence of a well developed
saturation zone, two free parameters are sufficient, but not three, as in
the model used
• The additional third fitting parameter leads to an non-biological
model displaying positive Ca retention even at zero Ca intake
Jackman: What do they read out of their data? And how?
The three fitting parameters:
1. Height of asymptote
(plateau Ca retention for large intakes)
2. Slope
3. Vertical shift of function (Intercept)
Biologically: Non-zero Ca retention at zero Ca intake
Jackman data: Fit to the data results in pseudo-precision
For some reason the curve’s CI as drawn in fig. is not the 95% CI used
to determine value.
95% CI sketched in according to data from Jackman et al. table
Realistically, such a statement cannot be made based on these data.
Method of determining Ca recommendation: Fit retention data with 3 open
parameters and then use the point where the fitted curve’s CI first touches
the asymptote (one of the fit parameters) as recommended lowest intake.
From this approach arise additional problems:
• Using the fitted asymptote together with the (same) fitted curve is
“incestuous”; parameters are correlated
• The slope of the curve is close to zero (the slope of the asymptote), making
the point of intersection (recommended Ca intake) highly sensitive to errors.
Even if assuming the model to be OK, overlap of both 95% CI starts already
at a Ca intake of 850 mg/d, and the point where retention curve lies 100%
inside the Asymptote’s CI happens at 1100 mg/d.
• This somewhat arbitrary choice of methodology strongly determines the
value
DRI Methodology:
• Analyze three sets of balance data, including Jackman. All three
sets are data from girls.
• Add estimate for Ca loss through sweating
• Use Martin et al. average peak velocity of accretion as independent
data for desirable level of Ca retention (corresponding to the
asymptote in Jackman’s approach)
• Fit data with Jackman function and use intersection of the
independently obtained desirable level with the fitted curve as the AI
DRI methodology
Boys
Girls
1070 mg/d
1310 mg/d
Problems:
• Fitting the combined data of three studies doesn’t improve the statistical problems
already seen in the Jackman study. The fitting algorithm leads to the same
misleading pseudo-accuracy. Suspiciously, the plotted 95% CI contains only about
1/3 of the data points.
• The Jackman curve runs into an asymptote that is supposed to model the same thing
as the independently obtained Martin data: desirable level of Ca retention. Now there
are two options:
– Both analyses are consistent with each other. That means the asymptote and the
Martin level are (within error) the same and there is no (meaningful) point of intersection →
method doesn’t work
– Or method works, because there is a clear point of intersection (as found in the DRI
study). This shows the inconsistency of the information obtained from the data.
•
•
Which of the two reasons for failure applies here is hard to tell, because Martin et al.
carefully avoid any error estimates of their findings in their entire publication.
The AI for boys was obtained by using the Jackman curve fitted to girl’s data and
sticking in Martin’s value for boys. In the end they decide to use the over 20% higher
boys value for both sexes.
DRI report (IOM 1997): Indicators used to
set AI for ages 9-18; Clinical trials
measuring BMC
•
Three studies were quoted in this section as providing
evidence that Ca supplementation is associated with positive
effects on bone mineral accretion:
1.
Lloyd et al., JAMA, 1993: girls with mean age of 11.9
supplemented with Ca (total daily intake 1370±303 mg and
placebo group (total intake 935±258 mg) for 18 months. After
18 months supplemented girls had 2.9% increase in lumbar
spine BMC (LSBMC) and 1.3% increase in total body BMD
(TBBMD) vs controls
-
But Ca-supplemented group falls within the range of placebo
group for daily Ca intake: So can one really call them
different?
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
• Lloyd et al., JAMA, 1993
no error bars on graphs
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QuickTime™ and a
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Note the
SD: Are the
groups
significantly
different
from each
other?
DRI report (IOM 1997): Indicators used to
set AI for ages 9-18; Clinical trials
measuring BMC
2. The next study demonstrating a positive effect of Ca
supplementation on bone mineral accretion is Chan
et al., J Pediatr, 1995:
• Girls with mean age of 12 supplemented for 12
months with dairy to reach intake of 1437±366 mg/d
compared to controls of 728 ±321, and found that
the supplemented group had “significantly greater
increases” in lumbar spine BMD and total body BMC
How significant is this data? Let’s take a look at the
graphs…
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
From Chan et al., J Pediatr, 1995
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
Note the SD
bars and
fluctuations
across the
time
intervals:
What
conclusions
can one
reasonably
make from
this data?
From Chan et al., J Pediatr, 1995
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
Chan et al., J Pediatr, 1995:
• After one year mean BMC and lumbar spine BMD were
not significantly different between the groups
• At one year an increased rate of gain in total BMC and
BMD at the lumbar spine was reported based on data
from previous graphs (with largely overlapping SDs),
but no increased rate at femoral neck or radius
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
- A reasonable conclusion of the Chan et al. study might
state:
In this limited 1 year study of 48 white adolescent girls
there appears to be a small increase in rate of gain in
the total BMC and BMD at the lumbar spine, although
the mean BMC and BMD values at one year were the
same in both groups. Additional studies will be needed
to confirm that this is a real effect. Importantly, longerterm studies would be needed to see if the increases
we observed in this study would have any lasting effect.
-
Possibly could also add: Future studies comparing our results to girls of
younger age groups, non-white girls, girls supplemented with lower or
higher total daily Ca levels, and girls provided with plant-based (non-dairy)
Ca sources would be important before making any broad
recommendations.
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
• Chan et al., however, made the following conclusion
based on their data:
“For 1 year, these girls had significant gains in
their total body bone mineral and lumbar
bone density…We believe that increased
dairy consumption by young girls should be
encouraged for improved bone mineralization
and for better bone health to prevent adult
osteoporosis.”
An additional side-note, this paper is:
(as are most of Dr. Chan’s published studies)
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
3. The third clinical trial mentioned in DRI report
is a 3 year double-blind, placebo-controlled
trial of effect of Ca supplementation
(1000mg/d) on BMD of 45 pairs of identical of
identical twins ages 6-14 (Johnston et al., N
Engl J Med, 1992):
In 22 pre-pubertal pairs found larger increase in
BMD at radius 5.1% (95%CI 1.5- 8.7); L spine
2.8% (CI 1.1- 4.5); three femoral sites not
significant
For 23 pairs who went through puberty or were
post-pubertal, BMD was the same at all the
measured sites
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Clinical trials measuring BMC
• So 2/3 trials mentioned in the DRI (and used as
indicators to set AI for ages 9-18) claimed to show
differences in BMD and BMC in adolescent girls
taking 1370±303 or 1437± 366 (with questions of
significance in both studies), but the third saw
differences in younger girls, but not adolescent girls
• At the end of the section on clinical trials, the DRI
states “mounting evidence from randomized clinical
trials suggests that the bone mass gained during
childhood and adolescence through Ca or milk
supplementation is not retained post-intervention”
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
• Third method used to set AI is the Factorial
approach, which estimates Ca requirements
by combining data from 8 different studies to
calculate:
Ca needs for growth (accretion) + Ca losses
(urine, feces, sweat), then adjust for
absorption
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Factorial Approach
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Factorial Approach
• Let us assume, for now, that the approach of
taking different studies with different
parameters and different controls and adding
them up can yield numbers that are at least
somewhat meaningful (since there are no
studies that include all or most of these
estimates in one study)
• Let us take a look at some of the studies used
in the table to determine the Ca requirements
DRI report (IOM 1997): Indicators used to set AI for
ages 9-18; Factorial Approach
• Peak Ca accretion- taken from one study
Martin et al., Am J Clin Nutr, 1997:
- n=115 girls n=113 boys aged 9.5-19.5 from two
elementary schools DXA annually over 4 years to
determine whole body BMC. Cross-sectional analysis
of pooled data used to calculate peak BMC velocity
(PBMCV)
- No errors reported anywhere in this publication: Can
one interpret this data?
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
Urinary losses for girls- estimated from two small study:
• 14 white adolescent girls in 3-week Ca balance study
(Weaver et al., Am J Clin Nutr, 1995)
• 14 white adolescent girls in 4-week Ca balance study
(Greger et al., Am J Clin Nutr, 1978)
28 girls in two separate studies account for 22% of the
final Ca sum (prior to absorption adjustment)
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
• Urinary losses for boys from single analysis of multiple Ca
balance studies (not separated for gender). Loss estimated is
127±71 for ages 9-17; Matkovic, Am J Clin Nutr, 1991:
Shaded area = 95%CI; Box
includes 25th- 75th
percentile
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- DRI report uses 127: Error
disappears (all values from
DRI table used in final
calculation are without
errors)
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
Endogenous fecal Ca estimated for girls from one small
study:
• 14 white adolescent girls in 3-week calcium balance
study (Wastney et al., Am J Physiol, 1996)
14 girls in a single study accounts for 23% of the final Ca
sum (prior to absorption adjustment)
End fecal Ca estimated for boys from one small study:
• 10 children aged 10months-14 yrs, Ca kinetics were
estimated based on injecting Ca isotopes
3 adolescent boys in a single study account for 19% of
final Ca sum (prior to absorption adjustment)
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
• Estimated Ca sweat losses taken from one study
which extrapolates adult data (from separate study,
Charles et al., Am J Clin Nutr, 1991) to estimate
amount in adolescents (Peacock, Am J Clin, 1991).
Same number used for both genders. DRI reports
states that “variability about these estimates are
large”
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Factorial Approach
• Finally, to adjust for absorption, the total sum (of peak Ca
accretion+urinary losses+endogenous fecal Ca+sweat losses) is
multiplied by the absorption percent.
• Absorption % value came from one small study:
14 white adolescent girls in 3-week calcium balance study (Wastney et al.,
Am J Physiol, 1996)
• In this study absorption was calculated to be 38±18%, which
was translated without errors to 38 for both genders. For girls
this is calculated to be 1276 mg/d and for boys 1505 mg/d.
If one calculates in the error, the range for adolescent girls (even
with the unlikely assumption that the previous sums are close to
accurate) would be 900-2400 mg/d and for boys 1000- 2800
mg/d. To come up with the number 1276 insinuates that it is
accurate to the last digit, which is obviously absurd
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Putting it all together
Three approaches were taken to estimate Ca needs for
ages 9-18:
• Ca retention to meet peak bone mineral accretion:
Major problems with data and models used leads to
somewhat arbitrary setting of AI
• Clinical trials in which BMC was measured to variable
Ca intakes: Inconsistent data between 3 trials and
questionable significance in 2 out of 3 studies
• Factorial approach: Most values based on very small
study sizes; each study with large errors that are
omitted in final calculation
DRI report (IOM 1997): Indicators used to set AI
for ages 9-18; Putting it all together
• Putting these three approaches together, the
DRI states a range of 1100 - 1600 mg/d to
attain a desirable level of Ca retention
• Overall, most studies used in all three
approaches above were done in white
adolescent girls (final AI given at approx 90th
percentile), so data for boys (at 75th
percentile) or other age groups are largely
extrapolated
DRI report (IOM 1997): Indicators used to set
AI; Putting it all together
• In summary, each approach used by the DRI
report to set the AI for children ages 4-18 are
based on research of often low scientific
quality (e.g. absence of error estimates) using
mathematical methods that lead to values of
misleading pseudo-accuracy
• The report also consistently pushes for higher
Ca levels when data is not good enough to
provide clearly meaningful values
• At most the DRI report is a rough estimate of
desirable Ca levels necessary to attain
maximal retention for many children.
DRI report (IOM 1997): Indicators used to set
AI; Putting it all together
Given that the variability of the data is due in
part to individual differences which are
scattered much more widely than the error of
the experimental data points, one could
reasonably question the wisdom of
recommending a single value to fit all children
of a certain age group. These
recommendations, if followed, would likely
lead to many children who would get more Ca
than they need (too much?) and some who
would still not get enough
DRI report (IOM 1997) on Calcium: Why it uses
an AI instead of a RDA
• EAR - nutrient intake value estimated to meet the
requirement defined by a specified indicator of
adequacy in 50 percent of the individuals in a life
stage and gender group
• Recommended Daily Allowance (RDA)-average daily
dietary intake level sufficient to meet the nutrient
requirements of nearly all (97-98%) individuals in a life
stage and gender group and is calculated from the
EAR:
RDA = EAR + 2 SDEAR
DRI report (IOM 1997) on Calcium: AI vs EAR
• An Adequate Intake (AI) - recommended
average daily nutrient intake level based on
observed or experimentally determined
approximations or estimates of nutrient intake
by a group (or groups) of apparently healthy
people who are assumed to be maintaining an
adequate nutritional state
• AI is expected to meet or exceed the needs of
most individuals in a specific life-stage and
gender group
• AI is used when sufficient scientific evidence is
not available to establish and EAR on which to
base an RDA
DRI report (IOM 1997) on Calcium: AI vs EAR
• The DRI report uses AIs instead of EARs due to
following concerns:
- “uncertainties in the methods inherent in and the
precise nutritional significance of values obtained
from the balance studies that form the basis of the
desirable retention model”
- “lack of concordance between observational and
experimental data (mean Ca intakes in the U.S. and
Canada are much lower than are the experimentally
derived values predicted to be required to achieve a
desirable level of Ca retention)”
- “lack of longitudinal data that could be used to verify
the association of the experimentally derived Ca
intakes for achieving a predetermined level of Ca
retention with the rate and extent of long-term bone
loss and its clinical sequelae, such as fracture”