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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Although increased physical activity early in life is recommended for optimizing bone health, no controlled trials on the effect of activity on bone mass accretion during periods of rapid growth have been reported. The purpose of this study was to determine whether infants randomized to a 1 year gross motor activity program had a greater bone mass accretion than infants randomized to a fine motor activity program. The gross motor program included activities that focused on loading the skeleton and were performed for 15–20 minutes/day, 5 days/week by study personnel. Infants (n = 72) were enrolled at 6 months of age, and total body bone mineral content (BMC), 3-day diet records, and activity levels were obtained at 6, 9, 12, 15, and 18 months. BMC was associated with weight, length, and bone area at all ages and correlated with earlier calcium intakes. Calcium intake appeared to modify the effect of gross motor activity on bone mass accretion; infants in both groups had similar bone accretion at moderately high calcium intakes, but at low calcium intakes infants in the gross motor program had less bone accretion than infants in the fine motor program. Compliant infants in the gross motor group had lower BMC at 18 months compared with noncompliant infants. These results indicate that BMC in infants is related to calcium intake, and we speculate that participation in a gross motor program during rapid bone growth may lead to reduced bone accretion in the presence of a moderate to moderately low calcium intake.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Development of a greater peak bone mass early in life has been suggested as an effective intervention for preventing later development of osteoporosis. Several studies have reported an association between bone mineral density (BMD) or bone mineral content (BMC) as an adult with childhood activity patterns.(1-4) In addition, cross-sectional studies have shown associations between these bone parameters in older children and their activity levels.(5-10) Children participating in competitive sports also tend to have a higher bone mass than more sedentary children.(11-13) These studies have re-emphasized the national recommendations that physical activity be increased in early childhood to optimize bone health.(14) However, the age at which increased physical activity can influence bone mass accretion is unclear and no controlled randomized trials have been reported showing a benefit of increased physical activity on bone mass accretion.

Load-bearing activities that include tension, torsion, bending, and compression loads that are of moderate strain level and rate, diversity, and repetitiveness increase BMD in both animal and human studies.(15-18) Infancy is a time of rapid bone mass accretion, and growth velocity is at its highest during this period of life. It also is a time of moderately low baseline activity levels and minimal load bearing. If increased load-bearing activity could influence bone accretion during growth, one could speculate that infancy is a time when an effect is likely to be observed. The purpose of the current study was to determine whether increased load-bearing activity in young infants could alter bone mass accretion. The specific hypothesis tested was that infants randomized to a 1-year gross motor activity program would have a greater bone mass accretion than infants randomized to a fine motor activity program.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The study was conducted in child care centers in the greater Cincinnati Area. Infants who were less than 6 months of age and were enrolled in a participating center were eligible to be enrolled in the study. Parents with infants enrolled in participating child care centers were called and the study was briefly explained to them. If they expressed an interest in knowing more about the study, the investigators arranged a time to meet with them. Written informed consent was obtained if, after the study and procedures were explained in detail, the parents were still interested in their infant participating. To be included in the study, the infant had to have been a term infant (>37 weeks gestation), formula-fed, and free of disease that would interefere with growth or bone mass accretion. The study was approved by Cincinnati Children's Hospital Medical Center Institutional Review Board.

Six-month-old infants were randomly assigned, within each center and gender, to either a gross motor or a fine motor activity program. Both activity programs consisted of different sets of four age-specific activities that were introduced at 6, 9, 12, and 15 months of age (Table 1). The activities were performed with each infant by study personnel for 15–20 minutes/day during the weekdays for 1 year. The gross motor activity group received four different daily activities each focusing on either tension, torsion, bending, or compression. The activities were modified from existing developmental programs for infants that are currently used in the home environment as a supplement to physical therapy programs (Hawaii Early Learning Profile at Home; Vort Corp., Palo Alto, CA, U.S.A.; Home Program Instruction Sheets for Infants and Young Children. Therapy Skill Builders; Developmental Programming for Infants and Young Children, University of Michigan). These activities were chosen due to their moderate strain level and rate, diversity, and repetitiveness. Although several of the activities included movements that are often seen in infants this age (pulling to stand through a half-kneel or squatting), the majority of activities are not commonly initiated by infants in this age group, such as ball-rolling and activities involving the wand. The level of compliance with the activities were recorded daily, including the number of repetitions and exact time spent in each of the activities (Table 1). Compliance was scored using the following categories: tolerated activity well (was not fussy), tolerated activity moderately well (child was distracted or a little fussy), refused to participate (cried when activities were attempted), or was not present in the child care center. Activities were performed unless the child began to cry, at which time they were stopped. Infants in the fine motor activity group were given a similar number of activities that were either fine motor or cognitive in nature. The reason for inclusion of a fine motor activity group was to ensure that all infants would be followed in a similar manner with respect to contact with investigators.

Table Table 1..  Description of Activity Programs and the Mean (Range) Time and Number of Repetitions (Reps) Performed per Day
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Total body BMC, anthropometric measurements, 3-day diet records, 48-h activity levels using miniature motion sensors, and 6 h of direct observation were obtained at 6, 9, 12, 15, and 18 months of age. Total body BMC was measured using dual-energy X-ray absorptiometry (DXA) (QDR1000 W, pediatric whole body software, V5.56; Hologic, Inc., Waltham, MA, U.S.A.). Our coefficient of variation, determined from duplicate scans on 17 infants, 3–17 months of age, with a mean weight of 8.4 kg, was 4% for total body BMC using the pediatric software. Weight and length were determined in the Clinical Research Center at Cincinnati Children's Hospital Medical Center using standardized procedures.

Three-day diet records were obtained for two weekdays and one weekend day and were analyzed using the Minnesota Nutrient Data Base (University of Minnesota Nutrition Coordinating Center, Minneapolis, MN, U.S.A.). To minimize the potential for dietary differences between groups in calcium intake, all infants were provided with the same infant formula upon enrollment in the study and it was to be used through 12 months of age (Enfamil; Mead-Johnson, Evansville, IN, U.S.A.). There were no other dietary interventions and no recommendations were made regarding the type and introduction of solid foods. The average calcium intakes for each infant between 6 and 12 months and 12 and 18 months were used in the statistical analyses to provide stable estimates of calcium intake.

Spontaneous daily activity levels were assessed using a miniature motion sensor similar to a large-scale integrated (LSI) sensor.(19) Sensors were placed on the infant's ankle and wrist for a 48-h period every 3 months. Total counts for the ankle and wrist were combined to obtain an overall 24-h average count. Sensors were retested using a shaking apparatus at different speeds after each use to verify their accuracy.

Direct observation of spontaneous activity was conducted at the child care centers for the first minute of every 15 minutes for a total of 6 h, usually from 8 a.m. until 2 p.m. The infant did not participate in the activity program on the day that direct observation was performed. A modified children's activity rating acale (CARS) was used to record activity. The CARS has been validated in several studies in young children and encompasses a wide range of energy expenditure.(20,21) We modified the CARS slightly to have a broader range for infants in the low activity levels and utilized a scale ranging from 0 to 5 (none, minimal, light, moderate, vigorous, maximal activity levels). We determined the activity levels for each region of the body, with the movements of the head, truck, arms, and legs being assigned a score. The scores for the four body parts were summed, and the average score was calculated as the sum of the scores divided by the number of entries observed. Additional information was obtained on whether the infant was bearing weight at each observation time. Each 6-h period was scored by one trained observer.

Data analyses included general descriptive statistics and repeated measures analysis of variance using a mixed effects model that included fixed and random effects. Treatment group and age were specified as fixed and infant was specified as random. Variables that were associated with bone mass were included as covariates and a final model was obtained. Interactions between potential covariates and activity group also were tested for significance. Data are given as means ± SD. Descriptive statistics and the mixed model analysis were run on the SAS System for Windows (SAS Institute, Inc., Cary, NC, U.S.A.).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

A total of 72 white infants were randomized at 6 months of age into the study; 69 infants completed through 9 months, 66 through 12 months, 60 through 15 months, and 58 through 18 months of age. All analyses include data on the 69 infants who completed through 9 months of age. Of these 69 infants, 34 were assigned to the gross motor group and 31 were male. The reasons for withdrawal among the 14 infants included withdrawing the infant from a participating child care center (n = 8), consuming nonstudy formula between 6 and 12 months of age (n = 2), unknown reason (n = 1), and study termination (n = 3).

There were no significant differences between groups in mean weight, length, average sensor readings, percentage time bearing weight on the legs, and dietary intakes of energy, calcium, or vitamin D over the period of the study (Table 2). Infants in the gross motor group had a slightly lower activity score at 15 months than infants in the fine motor group (5.9 ± 1.5 vs. 5.1 ± 1.2, p = 0.04). The proportion of infants on different types of diet (human milk, soy-based formula, or cow milk-based formula) during the first 6 months were similar between groups. Baseline bone measurements were similar between the fine motor and gross motor groups at 6 months of age (163 ± 20 g and 165 ± 22 g, respectively, for BMC and 601 ± 43 cm2 and 607 ± 53 cm2, respectively, for bone area).

Table Table 2..  Mean (±SD) Weight, Length, Activity Measurements, Dietary Intake, and Compliance of Infants by Activity Group
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Total body BMC was associated with weight, length, and bone area at all ages (p < 0.001 for all). Mean calcium intake between 6 and 12 months correlated with BMC at 12, 15, and 18 months, while calcium intake between 12 and 18 months correlated with BMC at 15 months (Table 3). Mean calcium intakes between 6 and 12 months and 12 and 18 months were similar between the gross motor and fine motor activity groups (580 ± 126 mg/day and 566 ± 98 mg/day between 6 and 12 months and 816 ± 199 mg/day and 821 ± 239 mg/day between 12 and 18 months, respectively). At no age was total body BMC correlated with average 48-h sensor readings, activity scores, or percentage time bearing weight on the legs.

Table Table 3..  Correlation Between BMC and Calcium Intake at Different Ages
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The results of a longitudinal analysis that included weight, length, and bone area as covariates indicated a slight trend of BMC increasing over time more rapidly among infants in the fine motor group than in infants in the gross motor group (interaction term of age and activity group, p = 0.19). To determine whether calcium intake may be modifying the effect of gross motor activity on bone mass accretion, an additional model was specified that included calcium intake. The average calcium intake for each infant between 6 and 12 months and 12 and 18 months was used in the model to provide stable estimates of calcium intake. In this analysis, weight, length, bone area, and calcium intakes were included in the model as time-varying covariates. The three-way interaction term of age, calcium intake, and activity group was significant (p = 0.07) implying that the effect of activity group on the increase in bone mass with age was modified by the calcium intake; there was no effect of activity group at higher calcium intakes, whereas there was less bone accretion in the gross motor group compared with the fine motor group at lower calcium intakes. This is shown graphically in Fig. 1 by plotting the predicted bone mass for each activity group at each age using age-specific means for body weight, height, bone area, and calcium intake (Table 4). The means of the lower and upper quartiles were used in calculating predicted bone mass based on the statistical model. All data were used in developing the statistical model, whereas the graphs use the mean calcium intakes for the lower and upper quartiles for illustration purposes only. When mean activity levels were included in the statistical model, the three-way interaction term remained significant (p = 0.07).

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Figure FIG. 1.. Illustration of the effect of calcium intake on change in total body BMC over the 12-month study period of infants in the gross motor (GM) and fine motor (FM) activity programs. The following equations were obtained using a mixed model analysis: If activity group = fine motor, then BMC = −40.25 + (−1.78 × month) + (−0.82 × length) + (0.30 × bone area) + 0.01 (weight) + (−0.05 × Ca intake) + (3.02 × month) + (0.005 × month × Ca intake) + 0.05 (Ca intake) + (−0.004 × month Ca intake). If activity group = gross motor, then BMC = −8.75 + (−1.67 × month) + (−0.82 × length) + (0.30 × bone area) + 0.01 (weight) + (−0.05 × Ca intake) + (0.005 × Ca intake). The interaction term of age, activity group, and calcium intake was significant at p = 0.07.

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Table Table 4..  Mean Values Used in Fig. 1 to Illustrate the Interaction Between Activity Group and Calcium Intake on Changes in BMC over the 12-Month Study Period
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BMC among infants in the gross motor group was negatively associated with compliance with the activity program (p = 0.05): those infants who were more compliant and tolerated the activities had a lower BMC at 18 months of age compared with infants who did not tolerate the activities. Figure 2 shows the least square means of BMC for 18-month-old infants adjusted for mean calcium intake over the study period and weight and height at 18 months of age. Compliance is given as the mean proportion of days that the infant tolerated the activities moderately well to well.

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Figure FIG. 2.. There is a significant relationship between BMC at 18 months of age and mean compliance over the study period in infants in the gross motor activity program (p = 0.05). Compliance is defined as the proportion of days the infant participated moderately well to well in the activities. Least square means are shown, adjusting for weight and height at 18 months of age and mean calcium intake over the study period.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Over the last decade it has become clear that the risk of developing osteoporosis is dependent on both the rate at which bone is lost late in life and the peak bone mass attained by the end of the second decade of life. There have been reports of factors affecting bone mass accretion around the time of puberty,(7-9,22) and trials of calcium supplementation in this age group have been reported(23,24); however, little is known about factors associated with bone mass accretion in infants and toddlers.

We previously reported a greater increase in bone mass among infants fed a moderate mineral-containing formula during the first 6 months of life compared with infants fed either a low-mineral–containing formula or human milk.(25) However, when these infants were rerandomized at 6 months of age to either a moderate-mineral– or high-mineral–containing formula there was significant catch-up, resulting in no differences in bone mass among the feeding groups by 1 year of age. The infant's BMC at 12 months of age was related to the diet in the first 6 months of life and not the second 6 months. In the original design of this study, we tried to maintain similar calcium intakes among the infants by supplying the same infant formula to all participants between 6 and 12 months of age. However, we did not control the timing of the introduction of solids or the amount or type of solids given. We found that even adjusting for caloric intake and body weight there was an association between calcium intake at 6–12 months of age and BMC at 12, 15, and 18 months. The current findings are consistent with our previous study that showed a significant effect of earlier calcium intake on BMC in infants and toddlers, and we suggest that future studies of BMC in these age groups consider obtaining information on previous calcium intake in their design.

There have been several studies in adolescent children showing an association between bone mass and level of physical activity,(5,8,11,13,26,27) but few have been done in the prepubertal age group.(6,7) Cross-sectional studies have shown relationships between adult bone mass and recall of activity levels as a child.(1-4,28) Kriska and coworkers, in a study of 223 adult women, found that the relationship between adult BMD was not associated with recent activity levels, but was associated with the recall of activity levels at the youngest age queried (14–21 years). These findings are supported by similar studies that have found adult BMD to be associated with a history of increased activity levels as a child.(3-4,29,30)

There have been a few longitudinal studies that were originally designed to investigate the role of activity and diet in childhood on the development of cardiovascular risk factors that also measured bone mass or density as an adult.(22,31) Although these studies were originally designed as cardiovascular risk factor studies, they have provided an excellent opportunity to determine the role of childhood activity on bone mass as an adult. These studies have demonstrated that bone mass or density as an adult is associated with activity levels as a child, supporting recent recommendations to increase physical activity levels early in life in order to optimize bone health.(14) Despite these findings, no randomized controlled trials of physical activity have been conducted early in life.

We conducted the current study in infants 6–18 months of age in order to determine whether we could alter bone mass accretion early in life through increased physical activity. There are several reports of decreased bone mineralization in infants and children that is thought to be due to decreased activity levels. Rodriguez and coworkers found the long bones in newborn infants with neuromuscular disease to be thin and hypomineralized. They attributed the decreased mineralization to decreased intrauterine activity that is observed with this type of disease.(32) Children with fractured limbs that are immobilized for more than 8 weeks have been found to have decreased BMD, which may persist for up to 6 years following the fracture.(33) In addition, decreased activity in other pediatric diseases has been suggested as one of the major causes for the osteopenia that is often observed.(34-36) Therefore, if bone responds to inactivity during growth it also may respond to increased activity. To our knowledge, no previous study has been reported in which a randomized trial was used to study the impact of physical activity on bone mass accretion during rapid periods of growth. We chose 6 months of age to begin the activities since it is a period of high growth velocity and spontaneous or baseline bone loading is minimal.

Additional rationale for intervention during early life to increase bone mass comes primarily from animal studies. Using the rat model, bones of younger animals have been found to be more responsive to mechanical stimuli than older animals.(37) However, a recent study in young racehorses found that changes in BMC due to training were related to age(38); young horses who began training at 85 weeks of age experienced a significant decrease in BMC over an 8-week race training session compared with a significant increase in BMC among horses who began training at 93 weeks of age. It was concluded that the age at which training begins is critical in determining the bone response to the increased loads, with race training having a detrimental effect on bone mass accretion in the younger animals. These findings suggest that younger animals may be more responsive to mechanical stimuli, but the response may not be similar to that observed in older animals.

We found no beneficial effect of increased physical activity on bone mass accretion during infancy. The activity programs that were used were modified from widely accepted, developmentally appropriate activity programs that are often used by pediatric physical therapists in the home setting. We chose activities that were of moderate intensity and duration for infants this age. Although some of the activities performed, such as pulling to a stand or squatting, may normally occur at these ages, many of the activities are not normally initiated by infants this age (ball rolling and pulling with wand while standing until there was a slight resistance from body weight). Although these activities should have provided strain levels not routinely observed in infants this age, it is possible that the duration of the activity was insufficient for an osteogenic effect.

We found evidence for a possible interaction between physical activity and dietary calcium intake on bone mass accretion in this population. There was no effect of activity on bone mass accretion among infants with moderately high dietary intakes of calcium. However, among infants with moderately low calcium intake, bone mass accretion appeared to be less if they were randomized to gross motor activities compared with those infants randomized to fine motor activities. We speculate that increased bone loading during periods of rapid skeletal growth may lead to an increased demand for calcium. It may be possible that an infant with increased bone loading cannot maintain comparable bone mass accretion if this increased demand for calcium is not met. Future studies may want to evaluate biochemical markers of bone formation and resorption, as well as some of the calcitropic hormones, in order to determine biochemical responses to physical activity at varying levels of calcium intake.

We recently reported the results of a meta-analysis of physical activity trials in adults that showed an interaction between activity and calcium intake on changes in bone density.(39) We found that at moderate to moderately low calcium intakes (<1100 mg/day) there was no benefit of physical activity, whereas at intakes greater than this there was a benefit of physical activity on changes in bone density. Although the results were different than what we observed in the current study, both studies indicate that calcium intake may modify the bone response to physical activity. The actual magnitude of this response may be dependent upon whether the skeleton is growing and the rate of that growth.

In summary, a greater bone mass accretion was observed in infants with higher calcium intake, but there was no beneficial effect of gross motor activity on bone mass accretion. We speculate that calcium intake may modify the bone response to gross motor activity in infants; there does not appear to be an effect of physical activity on bone mass accretion in infants consuming a moderately high intake of calcium, whereas gross motor activity appears to lead to reduced bone mass accretion among infants consuming a moderately low calcium intake. Additional studies designed to specifically test for the interaction of calcium intake and physical activity on BMC in growing children need to be done to determine whether participation in physical activity programs can optimize bone mass accretion during growth and whether calcium intake modifies the bone response to activity.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

We acknowledge Donna Buckley and Lisa O'Connor for their outstanding work in executing the study; Gemma Uetrecht for her time performing “after-hours” scanning; and, the activity leaders who so patiently worked with these infants. A special thanks to the families for their willingness to participate in this research. This study was supported by National Institutes of Health grant R01-AR40169 and grant M01-RR08084 from the General Clinical Research Centers Program, National Center for Research Resources, National Institutes of Health.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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