There was no association between calcium intake and FM, LM, BMC or relative BMI when the whole sample was examined, while adjusting for age and energy intake. In a gender-specific investigation, those females in the lowest calcium-intake group had higher % FM, than those in the middle and highest calcium-intake group while controlling for age and energy intake (Figure 2
). There was no association with relative BMI. For males, there was no association between the lowest and highest quartile of calcium intake and any body composition measures.
Body composition from dual energy X-ray absorptiometry for African-American females ages 11–18 in relation to calcium intake adjusted for energy intake (n = 112).
Nutrient intake was compared across calcium-intake groups, adjusting for age, gender and energy intake. As expected, those with the lower calcium intake had lower energy-adjusted intake of fiber, selected vitamins (riboflavin, folate, vitamin A, vitamin D) and mineral intake (magnesium, phosphorus, potassium, iron and zinc)(Table 3
). Those in the highest calcium-intake group had a higher percentage of participants who met the ADMR for fat and met the DRI for most nutrients, with the exception of vitamins A and C and magnesium and potassium.
In our sample of adolescents, we found no association between calcium intake and dyslipidemia, impaired glucose metabolism, hypertension, severity of overweight or combined risk of having one of these. Similarly, the mean calcium intake was not different among subjects with and without dyslipidemia (549 ± 27 vs. 537 ± 27), IGM (570 ± 38 vs. 542 ± 22), or hypertension (557 ± 26 vs. 540 ± 29), nor was there difference comparing the least with more severe overweight (541 ± 24 vs. 570 ± 31).
To our knowledge, this is the first paper that documents dietary intake and body composition of AA children and adolescents whose BMI is 111% above the 50th percentile for age and gender. The nutrient intake reflects a diet of foods low in nutrient density. Less than 10% of the sample met the DRI for calcium, magnesium, phosphorus, potassium, folate, fiber, and vitamins D, A and K. In this convenience sample of AA youth with extremely high body weight, calcium intake as a continuous variable was not related to % FM, FM, LM, or BMI for males or females. In females only, those in the lowest calcium percentile group (<314 mg/day) had higher % FM, compared to those in the highest calcium percentile group. There were no associations between diet and body composition in males.
High intake of dairy products has been shown to have beneficial effects on body weight in children and adults [26
] in some but not all studies [13
]. Studies show there is no effect of dairy products on change in weight or fat mass in young girls occurred during rapid growth [13
]. In contrast an observational study suggests 3 or more servings of milk contribute to increases in BMI in adolescents as a result of excess energy intake [27
]. Heaney and colleagues suggest increasing the intake of 1 serving of dairy at equivalent energy intake decreases a gain of a 1–2 kg in young children. Most of the studies in children/adolescents are modest in sample size and none have examined the issue of calcium or dairy products and weight in African-Americans.
Increasing dairy intake is intermingled with total energy intake. Some but not all studies show that by increasing dairy intake is compensated by the decline in energy from all foods [13
]. Estimating total energy intake in free living adolescents is difficult at best. The average energy intake reported by our sample was lower than what would be expected using the equations to determine energy requirement for overweight males and females [21
]. Using the ratio of reported energy intake to estimated intake using EER [28
], we found that 95% of the sample underreported their intake. Misreporting did not affect the number that met the RDI for any of the calcium groups. However, the mean reported energy intake to EER ratio was similar (0.59–0.81) to that reported for US children and adolescents between age 12 and 18 years [29
]. Whether the differences between actual and estimated intake were due to underreporting or under-eating during the recording period cannot be determined from our data.
Lower reported energy intake may or may not translate into a lower quality of diet depending on the selection of food. When high-calcium foods are consumed by children and adolescents in the US, the trend is toward choosing high-fat cheese and ice cream instead of low-fat dairy products [30
]. In our sample, the percent meeting the ADMR for fat (25–35%) increased with increasing calcium intake, suggesting that they may have selected sources of dairy that are lower in fat. Studies show that AA can include dairy products in their diet without symptoms of lactose maldigestion, by including milk in mixed meals, using lactose enzyme aids, or consuming low lactose products such as cheese or yogurt [31
]. Our data shows that those in the highest quartile of dairy intake consumed dairy containing lactose without incident. Those in the highest quartile of calcium intake had higher intake of potassium, vitamin A and fiber, suggesting a higher intake of fruits and vegetables. Like other reports [32
], our data support a view that the quality of the diet improves with higher calcium intake from milk products. Dairy products provide important sources of phosphorus, magnesium, riboflavin and potassium [33
] that aid in meeting the DRI for these nutrients.
Weight status using the Centers for Disease Control classification documents in the US 22 percent of AA youth between age 12 and 19 years had a BMI >95th percentile for age and gender, and 38.1% had a BMI above the 85th percentile [3
]. Given the grave implications for metabolic disorders, an expert committee on prevention, assessment and treatment of obesity in children and adolescents has suggested that a weight classification (severe obesity) be added for those >99th percentile for age and gender [39
] The severe obesity translates into a BMI between 30 to 32 kg/m2
for youths 10 to 12 years of age and BMI >34 kg/m2
for youths 14 to 16 years of age. Using this definition, 63% of our population would be characterized as extremely obese.
Eighty four percent of our sample had one or more metabolic risk factors for cardiovascular disease. This prevalence is in agreement with previous reports in children/adolescents [14
]. Pereira et al.
] recently found that among young, overweight adults in the CARDIA study, dairy consumption (100% dairy foods plus foods with dairy as the main ingredient) was inversely associated with the incidence of all components of the metabolic syndrome over 10 years, independent of ethnicity, gender, other lifestyle factors, and macronutrient and micronutrient intakes. However, incongruence with others [17
] we found no association between daily dairy intake and the presence of dyslipidemia, hypertension, severity of overweight, or abnormal glucose metabolism.
Children and adolescents at risk for overweight and obesity have a higher risk of becoming overweight or obese adults [44
]. A question remains as to whether a high-dairy would attenuate our participants’ comorbid conditions. In adults, increasing calcium intake during weight loss improves lipids in adults [45
]. Although dairy intake has been associated glucose metabolism and insulin resistance [43
], the role of calcium in controlling blood pressure in adults varies from study to study [46
]. Investigations regarding the association of calcium intake and comorbidities raise the question of whether the differences in calcium and vitamin D metabolism found between AA and Caucasians with regard to the skeletal system [47
] are related to the racial differences seen in the prevalence of obesity, glucose intolerance or type 2 diabetes [43
] The efficacy of dairy intake on weight loss or change in metabolic indices in children and adolescents is an opportunity for further research efforts.
The strength of our report lies in uniqueness of our sample children. A limitation of our report is that few of our participants reported food intake that met the DRI for calcium. With a larger distribution of calcium intake we might have seen an association using calcium as a continuous variable. Using a sensitivity analysis based on quartiles of calcium intake specific for females, our data show that a diet with very low calcium intake (<314 mg/day) appears to affect the level of fat mass. Whether this association is spurious due to chance or is real requires confirmation in other cohorts similar to ours. Given that our population is characterized by extremely overweight AA’s, a sample that has a wider BMI range may yield different results. A limited range of body fat and dietary calcium intake may have made it difficult to examine relationships between nutrients and body weight status. The cross-sectional nature of the investigation reflects a point in time and cannot be projected as long-term risk nor support causation.