Published online August 31, 2007
PEDIATRICS Vol. 120 No. 3 September 2007, pp. e669-e677 (doi:10.1542/peds.2006-1240)
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ARTICLE

Perceived Milk Intolerance Is Related to Bone Mineral Content in 10- to 13-Year-Old Female Adolescents

Leann Matlik, MS, RDa, Dennis Savaiano, PhDb, George McCabe, PhDc, Marta VanLoan, PhDd, Carolyn L. Blue, PhD, RNe and Carol J. Boushey, PhD, RDa

a Department of Foods and Nutrition and Colleges of
b Consumer and Family Sciences
c Sciences, Purdue University, West Lafayette, Indiana
d US Department of Agriculture Western Human Nutrition Research Center, University of California, Davis, California
e School of Nursing, University of North Carolina at Greensboro, Greensboro, North Carolina


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVE. The purpose of this study was to determine associations among lactose maldigestion status, perceived milk intolerance, dietary calcium intake, and bone mineral content in early adolescent girls.

METHODS. Subjects were 291 girls who participated in a substudy of the multiple-site project Adequate Calcium Today. Lactose maldigestion status was determined with hydrogen breath testing, and questionnaires were used to assess perceived milk intolerance. Dietary calcium intake was estimated from a semiquantitative food frequency questionnaire. Anthropometric and dual-energy x-ray absorptiometric measurements (total body, spine L2–L4, total hip, and hip femoral neck) were standardized across sites.

RESULTS. Of the 230 girls who completed breath hydrogen testing, 65 were Asian, 76 were Hispanic, and 89 were non-Hispanic white. A total of 100 girls experienced increases in breath hydrogen levels of >20 ppm and were classified as lactose maldigesters. Of the 246 participants who completed useable perceived milk intolerance questionnaires, 47 considered themselves to be milk intolerant. Of the 47 girls self-reporting perceived milk intolerance, 40 completed breath hydrogen testing and 22 were not maldigesters. Girls with perceived milk intolerance consumed an average of 212 mg of total food calcium per day less than girls without perceived milk intolerance. Spinal bone mineral content was significantly lower in the girls with perceived milk intolerance, compared with the girls without perceived milk intolerance. When girls with lactose maldigestion were compared with girls without lactose maldigestion, there were no significant differences in calcium intake or bone measures.

CONCLUSIONS. These results suggest that, starting as early as 10 years of age, self-imposed restriction of dairy foods because of perceived milk intolerance is associated with lower spinal bone mineral content values. The long-term influence of these behaviors may contribute to later risk for osteoporosis.

Key Words: adolescents • bone mass • calcium • milk intolerance • lactose intolerance • ACT—Adequate Calcium Today • BMC—bone mineral content • BMD—bone mineral density • DXA—dual-energy x-ray absorptiometry • PMI—perceived milk intolerance

Osteoporosis is responsible for >1.5 million fractures annually, the majority of which are vertebral fractures.1 Attaining a high peak bone mass during adolescence is the best preventative measure against osteoporosis later in life.2–4 At least 90% of peak bone mass is achieved by 18 years of age in female subjects,5,6 and 99% is attained by 26.2 years.7 Therefore, adolescence is a critical period for laying a foundation for future bone health.8–11 Although genetics play a major role in the determination of peak bone mass, accounting for up to 80% of variation, as much as 20% can be attributed to environmental factors, including nutrition.12 Increasing evidence indicates that the development of osteoporosis is in part related to inadequate calcium intake and that high calcium intake may slow the loss of bone mass observed in postmenopausal women.13,14 Dietary calcium intake is imperative for bone maturation, because it is the only source of calcium for skeletal deposition.3 Dairy products have been shown to provide 77% of dietary calcium among teenage girls,15 but girls as young as 10 to 12 years of age have low calcium intakes.9,16,17 Research in adults showed that individuals who perceive themselves to be milk intolerant are more likely to avoid milk and not to make any effort to consume enough calcium.18,19 However, those studies did not include measures of bone mass. Studies of milk avoidance behaviors in children reported overall reduced bone mass and increased incidence of bone fractures.20,21 The exposure of perceived milk intolerance (PMI) in youths and its relationship to calcium intake and bone have not been explored.

Lactose maldigestion occurs when digestion of lactose is reduced because of low activity of the enzyme lactase.22 The condition has been estimated to occur in 75% of black and American Indian individuals and 90% of Asian individuals.23 However, most lactose maldigesters do not experience symptoms of intolerance. This suggests that lactose intolerance is highly individual and is influenced by physiologic and psychological factors.24 The purpose of this study was to investigate the associations among lactose maldigestion status, PMI, dietary calcium intake, and bone mineral content (BMC) in young Asian, Hispanic, and non-Hispanic white female subjects.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Study Design and Subject Selection
This cross-sectional study was a substudy of the Adequate Calcium Today (ACT) project, a school-randomized intervention project conducted at sites in 6 states. Because the collection of PMI data was an optional measurement, this information was collected from only 8 schools in California and 6 schools in Indiana that represented the locations for this study.

The overall recruitment goal for the ACT project was equal proportions of ethnic groups and 150 girls from each state. Middle schools that had larger proportions of Asian or Hispanic students than the state average and were located within a 1-hour distance from the designated dual-energy x-ray absorptiometry (DXA) measurement site (1 site in each state) were eligible for participation. Recruitment goals for the total numbers of Asian, Hispanic, and non-Hispanic white girls within a school were established on the basis of the ethnicity of enrollment in each school. All sixth-grade girls were recruited through posters and presentations in schools and mailed invitations. Girls were eligible if they were at least 75% Asian, Hispanic, or non-Hispanic white, as self-reported by their biological parents. Of the eligible girls involved in this substudy, 142 were from California and 149 were from Indiana. The institutional review boards of Purdue University and the University of California, Davis, approved the study protocol, and informed assent and consent were obtained from the girls and their parents, respectively.

Anthropometric Measures
Body weights were measured with calibrated digital scales (5602 Portable Stand-On Scale; Scale-Tronix Co, White Plains, NY). Heights were measured with wall-mounted stadiometers (235 Heightronic Digital Stadiometer; QuickMedical, Snoqualmie, WA). All ACT staff members were trained in standardized techniques at a central location, and a designated reference person visited each site to ensure that individuals were measuring within ±2 units. All measurements were performed by following the procedures in the Anthropometric Standardization Reference Manual.25 For the purposes of this analysis, baseline height and weight were used, as well as calculated BMI.

Lactose Maldigestion Status
Lactose maldigestion was evaluated for 230 girls by using breath-hydrogen analysis after a 12-hour fast. Participants consumed a special, low-fiber, lactose-free meal the night before the breath hydrogen test. Breath samples were collected at baseline, 30 minutes after milk ingestion, and hourly for a 3-hour period. At the testing, girls received an amount of milk equal to 0.35 g of lactose/kg of body weight, based on the subject's body weight recorded from her most-recent measurement unless she weighed >135 pounds (>61.4 kg). In such cases, the girl received an adjusted milk dose based on her weight corresponding to the 85th percentile on the Centers for Disease Control and Prevention growth charts26 for her age. This was to ensure that everyone consumed a physiologic quantity of milk. A total of 32 girls (13.9%) required adjusted milk doses. Greater proportions of Hispanic girls (21.1%; n = 16) and non-Hispanic white girls (16.9%; n = 15) than Asian girls (1.5%; n = 1) needed adjusted milk doses based on their body weights ({chi}2 = 12.187, df = 2; P = .002). No significant differences were found for weight adjustments between states ({chi}2 = 0.343, df = 1; P = .558).

The concentration of hydrogen in expired breath samples was analyzed with gas chromatography (CM2 Plus Microlyzer; Quintron Instruments, Milwaukee, WI). Changes in hydrogen concentrations were calculated by subtracting the hydrogen concentration at baseline from subsequent concentrations. As an initial standard, a >20-ppm increase in hydrogen levels from baseline was considered positive for lactose maldigestion. Data not following the expected hydrogen curve were examined more closely. Sustained elevation over the 3-hour period was also considered positive for lactose maldigestion. Results that did not reach a stable low level were considered indeterminable. Hydrogen status was not determinable for 10 subjects.

Maturity
Breast and pubic hair pubertal staging was performed by using line diagrams based on Tanner reference stages,27 which have been found to be highly correlated with clinical examination results.28,29 In a private setting, girls self-selected the stages (stages 1–5) most closely resembling themselves, by using line diagrams for each of the breast and pubic hair series, and recorded their responses on a questionnaire. The total Tanner score, which was the sum of the upper body breast development and lower body pubic hair development scores, was used in our analyses. Years after menarche were calculated as the date of the visit minus the self-reported date of the first period.

Bone Mineral Assessment
DXA (Lunar Prodigy enCORE 9.1 software; GE Medical Instruments, Madison, WI) was used to determine BMC and bone mineral density (BMD), as well as body composition. Matching instruments and software were used at all sites, and measurements were made by following standardized procedures. To determine within-laboratory and between-laboratory variance in DXA measurements, a whole-body phantom (Hologic, Bedford, MA) was measured at each site. The phantom was scanned 10 times, with repositioning of the phantom between scans. Phantom scans were made for the whole body, spine, femur, and forearm. The phantom measurements were analyzed and reviewed for accuracy independently by researchers at the University of California, San Francisco, who were blinded to the study locations. The mean and SDs were calculated for each scanned phantom, including BMD and BMC for the whole body, spine, femur, and forearm, lean soft-tissue mass, fat mass, and percentage of body fat. Each site had 2 DXA operators. Between-operator variances were determined through repeated testing of 10 volunteers. On the basis of analyses of the data, we concluded that site and operator adjustments were not needed for any DXA measures. Body composition and total BMD, BMC, and body area were determined from a whole-body scan. For this study, baseline BMC data for total body, spine (L2–L4), total hip, and hip femoral neck were analyzed.

PMI Status and Score
The PMI questionnaire included 3 statements derived from focus group discussions with a sample of adolescents representing the same age group and race/ethnic groups as the ACT participants.30 The statements were as follows: (1) "I am allergic to milk," (2) "I get a stomachache after drinking milk," and (3) "I have been told that milk will make my stomach hurt after I drink it." These statements were not designed to reflect precise medical statements; however, the phrases are appropriate for use with adolescents. Responses to the statements were "strongly disagree" (scored as 1) to "strongly agree" (scored as 5) or "do not know" (scored as missing). A PMI score was calculated as a mean of the responses when there were ≥2 nonmissing responses. During several pilot tests with early adolescents, the statements were found to be satisfactory in reliability by using test/retest (r = 0.53; P < .001; paired t test, P > .05) and internal consistency (Cronbach's {alpha} = 0.68) analyses. PMI status was determined from the PMI score. The frequency of responses separated distinctly above 2; therefore, a score of >2 was defined to be indicative of PMI.

Dietary Assessment
At the baseline visit, dietary calcium intakes from the past month were estimated through the use of a calcium-specific, semiquantitative, food frequency questionnaire developed for and evaluated with Asian, Hispanic, and non-Hispanic white youths.31 The food frequency questionnaire had satisfactory reliability (r = 0.68; P < .001) and accuracy, compared with two 24-hour recalls (r = 0.54; P < .001), among adolescent Asian, Hispanic, and non-Hispanic white girls and boys between 10 and 18 years of age.31 Two of the completed food frequency questionnaires were lost because of computer errors.

Estimated daily food calcium intakes that were <100 mg/day or >2500 mg/day were considered improbable, and individuals with such values were excluded from any analyses using food calcium intake. A total of 39 (13.5%) of 289 subjects were excluded. Therefore, 250 subjects provided usable dietary calcium intake data. A greater proportion of Hispanic girls (20%) had calcium intake estimates that were improbable, compared with the Asian (14%) and non-Hispanic white (8%) girls ({chi}2 = 6.282, df = 2; P = .043).

Calcium intakes from food were categorized in 5 ways, including calcium exclusively from dairy foods (eg, milk, which is exclusively dairy calcium), and calcium from nondairy foods (eg, broccoli). Calcium from foods that included calcium from both dairy and nondairy sources, such as pizza, for which some of the calcium would be from a dairy source (cheese) and some of the calcium would be from nondairy sources (crust, sauce, and vegetables), was labeled calcium from mixed foods. The category of total dairy calcium was the sum of calcium from dairy foods and calcium from mixed foods. Finally, the category of total calcium from food was the sum of calcium from the dairy foods, nondairy foods, and mixed foods groups. Milk intake was estimated separately, as cups of milk per day from milk as a beverage and on cereal.

Statistical Analyses
Data were analyzed by using SPSS for Windows 12.0 (SPSS, Chicago, IL). Normal probability plots were used to assess the need for transformations. No variable required transformation. Because California and Indiana were assigned different proportions of girls to recruit according to race/ethnic group, data were examined for differences that might preclude combining the data with regard to PMI. Adjustment of the analyses for study site (California and Indiana) gave essentially the same results as the unadjusted analyses. Therefore, summary tables presented here use the combined data for both sites.

Differences in bone status according to PMI and lactose maldigestion status were examined by using 2-sample t tests. Analysis of variance was used to determine differences in quantitative variables among race/ethnic groups, and posthoc Scheffé tests32 were used to determine specific differences after a significant analysis of variance result; {chi}2 tests were used to assess associations between categorical variables.

Multivariate linear regression was used to examine the relationship between PMI and total calcium intake from food (in milligrams), with adjustment for state, race/ethnic group, weight, and age. The same statistical model was used for calcium exclusively from dairy foods, total dairy calcium, and cups of milk per day. Multivariate linear regression was also used to examine the association between bone status and PMI while accounting for potential confounders (eg, body weight and years after menarche). The final parsimonious model included state, race/ethnic group, BMI, age, and Tanner score. This same statistical approach was used to examine the role of maldigestion status as a predictor of bone status and dietary calcium intake.

Previous studies confirmed a positive association between dietary calcium intake and bone mass (as BMC).3,8,9,11,12,33 Therefore, a hierarchical modeling approach was used to identify the degree to which dietary calcium intake could explain the association of PMI with bone status. The hierarchical arrangement of the variables was based on assumptions about the casual sequence (ie, PMI contributes to reduced dietary calcium intake, which is associated with lower BMC). If an association of PMI with bone status is detected and if this association is attenuated by inclusion of dietary calcium in the model, then the data are consistent with the pathway outlined above. These hierarchical models included only the 250 individuals with complete dietary data.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Subject Characteristics
The characteristics of the girls according to race/ethnic group at baseline are shown in Table 1. Of the 291 participants, 246 completed useable PMI questionnaires, of which 47 perceived themselves to be milk intolerant. There were no significant differences among race/ethnic groups ({chi}2 = 0.918, df = 2; P = .632). Furthermore, there were no statistically significant differences with respect to age, Tanner stage, BMI, weight, or height. PMI scores did not differ according to race/ethnic group (analysis of variance, F = 0.764, df = 2, 243; P = .467) (Table 1). Of the 230 subjects who completed the breath hydrogen test, 91 (39.6%) were determined to be lactose maldigesters. The prevalence of lactose maldigestion varied with race/ethnic group. Asian girls had the highest rate (67.7%), followed by Hispanic girls (47.4%) and non-Hispanic white girls (12.4%; {chi}2 = 51.590, df = 2; P < .001). The cross-tabulation of PMI according to lactose maldigester status is shown in Table 2.


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  		TABLE 1 Characteristics and Outcome Measures of Early Adolescent Girls According to Race/Ethnic Group

 

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  		TABLE 2 Cross-Tabulation of Lactose Maldigestion Status and PMI Among 10-to 13-Year-Old Girls

 
Calcium Intake
The results of the multivariate linear regression analysis using PMI to predict dietary calcium intake are shown in Table 3. PMI was found to be associated with decreased dietary calcium intake. The individuals who perceived themselves to be milk intolerant had reduced total calcium intake from food (P = .023), reduced calcium intake exclusively from dairy foods (P = .015), and reduced total dairy calcium intake (P = .025), compared with girls who did not perceive themselves to be milk intolerant. On average, individuals who perceived themselves to be milk intolerant consumed ~212 mg less calcium per day than did individuals who did not perceive themselves to be milk intolerant. Reported milk consumption was significantly lower (P = .006) among individuals with PMI, who consumed ~0.5 cup of milk per day less did than those without PMI, which corresponds to ~150 mg of calcium per day. Nondairy calcium sources were not associated with perception of milk intolerance. Lactose digesters did not consume significantly different amounts of dietary calcium in any form, compared with lactose maldigesters. Some examples are shown in Table 3.


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  		TABLE 3 Multivariate Linear Regression Models for Relationship of Diet and BMC to PMI or Lactose Maldigestion Status Among 10- to 13-Year-Old Girls

 
Bone Status
Table 4 compares the bone status of subjects with PMI and subjects without PMI. Spine (L2–L4) BMC was significantly lower in the girls with PMI than in the girls without PMI (26.31 g vs 29.46 g; P = .016). Similar differences were found for other sites, but the differences failed to attain statistical significance. No statistically significant differences were found between lactose digesters and lactose maldigesters for any of the BMC measures (Table 4). Controlling for race/ethnic group and Tanner stage, subjects with PMI had significantly lower spinal (L2–L4) BMC (–2.52 g; P = .009), compared with individuals without PMI (Table 3). As was found with dietary calcium intake, differences in bone status between lactose digesters and lactose maldigesters were not evident (Table 3).


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  		TABLE 4 Univariate Analysis of Bone Status, as BMC, According to PMI or Lactose Maldigestion Status Among 10- to 13-Year-Old Girls

 
Hierarchical Modeling
Total dietary calcium intake was associated positively with spine (L2–L4) BMC, with adjustment for race/ethnic group, location, age, BMI, and Tanner score (t = 2.22, df = 286; P = .027). Because the association between PMI and dietary calcium intake was found to be significant (Table 3) and the association between PMI and bone status measures was also significant (Table 3), the hierarchical modeling approach was used. For the bone sites examined, that is, total body, spine (L2–L4), total hip, and femoral neck, the negative relationship between PMI and spine (L2–L4) BMC showed the greatest attenuation with inclusion of dietary calcium intake in the model as an explanatory variable. Of these explanatory variables, total dairy calcium resulted in the greatest attenuation of the relationship between PMI and spine (L2–L4) BMC. The mean ± SE differences were –2.62 ± 1.02 g without total dairy calcium and –2.51 ± 1.04, with total dairy calcium, controlling for age, race/ethnic group, state, BMI, and Tanner stage.


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
This is the first study to find an inverse association between PMI and dietary calcium intake in a diverse sample of early adolescent girls. Previous studies documented this observation among adults18,19,34,35 and in a small homogeneous sample of young children and adolescents.34 This is also the first study to show inverse associations between PMI and measures of bone status among early adolescent girls of Asian, Hispanic, and non-Hispanic white backgrounds.

This is the first study to examine PMI among Asian, Hispanic, and non-Hispanic white early adolescent girls. No significant differences in PMI among race/ethnic groups were observed. In contrast, Elbon et al18 observed significant differences in PMI between black and white, older, US adults. Finding no notable differences in PMI among races in this study is especially interesting because much greater proportions of the Asian (67.7%) and Hispanic (47.4%) girls were positive for lactose maldigestion, compared with non-Hispanic white girls (12.4.%). The Asian girls had lower mean heights and weights than did the other groups, which resulted in lower BMC. Despite this potential confounding, the girls with PMI still had significantly lower BMC values than did girls without PMI. Also noteworthy was the observation that, regardless of maldigestion status, girls who perceived themselves to be milk intolerant had lower dietary calcium intakes, especially total dairy calcium intakes. Klesges et al35 also found perceived milk-related gastric distress to be one of the strongest predictors of milk consumption among 32144 US Air Force recruits.

Previous studies categorized non-Hispanic white boys and girls between 3 and 10 years of age as milk avoiders on the basis of parental reports of low consumption of cow's milk.20 These milk avoiders were found to have lower intakes of calcium than a group of comparison children who consumed milk. Furthermore, the milk avoiders had lower total body BMC than did the comparison group. These differences persisted after 2 years of follow-up monitoring36 and were associated with an increased risk of fractures.21 Our primary exposure among early adolescent girls was PMI, using a self-reported scale. The perception of milk intolerance in early adolescence was associated with lower calcium and milk intakes and lower bone mass. This was true for girls with Asian, Hispanic, and non-Hispanic white ethnicities. These results were independent of the girls' lactose maldigestion status. Because milk avoiders were found to have higher risks of fractures,21 the question remains of whether the same is true for those who perceive themselves to be milk intolerant.

The greatest effect of PMI on bone status was seen in the lumbar spine vertebrae (L2–L4), which is consistent with results from studies among adults. Soroko et al37 examined BMD among postmenopausal women and found significant positive associations between milk consumption in adulthood and adolescence and BMD in the spine and midradius. Researchers from Austria found reduced BMD at the hip and the lumbar spine among postmenopausal women with the A-13910 T/C dimorphism (LCT) that is associated with subjective milk intolerance.38 The consistency of these results among early adolescents in our study and older adults is especially significant, because vertebral fractures account for the greatest number of osteoporotic fractures each year.1 Di Stefano et al39 compared bone status among women and men with a mean age of 28 years, which is just beyond the period of achieving peak bone mass. Similar to our results, lumbar and femoral BMD did not differ between maldigesters and digesters.

Aversion to food is likely the result of behavior-based conditioning.40,41 Therefore, aversions to food can be induced and reversed.42 Foreyt and Kennedy43 subjected overweight subjects to favorite foods paired with noxious odors. After the conditioning period, subjects associated the foods with the respective noxious fumes and avoided consuming those foods. Future research among early adolescent girls may consider addressing the reversal of PMI or aversion to milk.

Besides a reduction in calcium intake, avoidance of milk may contribute to lower BMC through limited dietary protein intakes. Cadogan et al33 found significantly higher insulin-like growth factor I levels and increases in BMC among early adolescent girls assigned randomly to receive 568 mL of milk per day, compared with a control group. The positive relationship of milk consumption to insulin-like growth factor I levels in children may explain the smaller skeletal size and shorter stature observed in milk avoiders.36

No differences in PMI score, PMI status, dietary calcium intake, or bone measures were found between individuals who participated in the breath hydrogen testing and those who did not participate. Therefore, we cannot conclude the possibility that PMI inhibited subjects from participating in the breath hydrogen testing. Because all participants were informed during recruitment that a requirement of the study was to drink a glass of milk, it is possible that subjects were more likely to be milk drinkers. This potential volunteer bias would tend to move the results of our study toward a null result. Therefore, we may conclude that, if all girls in the selected schools had completed the breath hydrogen testing, then the extent of the detected differences in bone mass might have been larger.


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
Results from this study indicate that PMI has a negative effect on food calcium intake, specifically dairy calcium intake. This relationship results in a statistically significant reduction in spine (L2–L4) BMC, relative to individuals who are milk tolerant. Similar patterns are seen for total body, total hip, and femoral neck BMC, but the differences do not achieve statistical significance. Individuals who perceive themselves to be milk intolerant and therefore limit their consumption of high-calcium products are compromising their bone health. Because early adolescence is a period when calcium intake has a significant effect in increasing bone mineral accrual in girls, PMI and its consequent effects on calcium intake and BMC at this young age are especially threatening for bone health.

In this study, classification of PMI was determined from average responses to 3 statements formulated from focus group discussions with adolescents. The recently published clinical report4 on optimizing bone health in the pediatric population outlined assessment questions for pediatricians to incorporate into practice. In addition to the questions suggested in the report, health practitioners may find the brief assessment used in this study useful in identifying girls potentially at risk for reduced calcium intake and lower bone mass. One of the major lessons is that lactose maldigestion does not equate to lactose intolerance. Additional evaluation of the perception of lactose intolerance among adolescents, including individuals' knowledge of lactose intolerance and sources of information concerning lactose intolerance, through focus groups or individual open-ended interviews is recommended for future research, so that appropriate health education campaigns can be mounted.

Building peak bone mass during childhood and adolescence can be the best defense against developing osteoporosis later in life.44 Clarifying misconceptions about lactose intolerance early in life is important for achieving optimal calcium intake and peak bone mass. Because lactose intolerance has been shown to increase with age,34 it is important to address misconceptions surrounding lactose intolerance at an early age, to prevent perceived lactose intolerance from reducing calcium intake, with consequent negative effects on bone status.


   FOOTNOTES
 
Accepted Feb 1, 2007.

Address correspondence to Carol J. Boushey, PhD, RD, Purdue University, 700 W State St, West Lafayette, IN 47907-2059. E-mail: boushey{at}purdue.edu

The authors have indicated they have no financial relationships relevant to this article to disclose.


   REFERENCES
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 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

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