high calcium and milk in children: bones of steel?

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 co-factors 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. Cross-sectional 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

Fecal Ca excretion (II)

Urinary Ca excretion (I)

Jackman et al. measure Ca excretion as a function of Ca intake

Red lines were superimposed onto graph from Jackman et al. in order to illustrate methodology: Intake - Excretion = Retention

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 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?

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: What do they read out of their data? And how?

The three fitting parameters:

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

1070 mg/d

Girls

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



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 BMC2. 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…


From Chan et al., J Pediatr, 1995


From Chan et al., J Pediatr, 1995

Note the SD bars and fluctuations across the time intervals: What conclusions can one reasonably make from this data?


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


- 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, longer-term 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.


• 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)


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


• 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


• 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


• 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?


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)


• 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

- DRI report uses 127: Error disappears (all values from DRI table used in final calculation are without errors)


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 isotopes3 adolescent boys in a single study account for 19% of

final Ca sum (prior to absorption adjustment)


• 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”


• 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”

high calcium and milk in children: bones of steel?

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