Original Communication

European Journal of Clinical Nutrition (2005) 59, 861–867. doi:10.1038/sj.ejcn.1602147 Published online 25 May 2005

Dietary calcium and body mass index in Portuguese children

Guarantors: P Moreira and C Padez.

Contributors: PM established the main idea of the study design, carried out the field study, as well as arranged data analysis, and wrote the paper. CP coordinated and supervised the group, carried out the field study and collaborated in writing the manuscript. IM and VR carried out the field study and collaborated in writing the manuscript.

P Moreira1, C Padez2, I Mourão3 and V Rosado4

  1. 1Faculty of Nutrition, University of Porto, Porto, Portugal
  2. 2Department of Anthropology, University of Coimbra, Coimbra, Portugal
  3. 3Department of Sports, University of Trás-os-Montes Alto Douro, Vila Real, Portugal
  4. 4Center of Anthropobiology, Instituto Investigação Cientifica Tropical, Lisboa, Portugal

Correspondence: P Moreira, Faculty of Nutrition, University of Porto, Porto, Portugal. E-mail: pedromoreira@fcna.up.pt

Received 16 August 2004; Revised 28 January 2005; Accepted 16 February 2005; Published online 25 May 2005.





The objective of our study was to assess nutritional intake in school children (7–9-y-old) and relate calcium intake to body mass index (BMI).



This study was a cross-sectional analysis.



The data were derived from a community-based survey of children from primary schools of Portugal.



In all, 3044 Portuguese children (1503 girls and 1541 boys) from a community-based sample of 7–9-y-olds.



Height and weight were measured according to international standards, and BMI was calculated. Children's parents completed a self-administered questionnaire that provided information on general family background characteristics and children's physical activity. Children's dietary intake was measured using a 24-h dietary recall. Calcium intake was expressed as the calcium-to-protein ratio, and regression analysis was used to estimate the association between calcium intake and BMI, adjusting for energy intake and confounders.



The prevalence of children with calcium intake below the Dietary Reference Intake was higher in girls (36.4 vs 33.0%, P=0.053). Calcium-to-protein ratio predicts BMI only in girls (beta=-0.052, P=0.002), even after adjusting for age, energy intake, parental education, and physical activity.



We found an inverse relationship between calcium intake and BMI only in girls. These data reinforce the need for controlled trials to assess the effects of dietary calcium on body mass in each gender.



Fundação Ciência e Tecnologia POCTI/ESP/43238/2001.


dietary calcium, body mass index, obesity, children



Overweight is one of the most prevalent and serious health problems in children (Rosner et al, 1998; Padez et al, 2004). The related disease risks include diabetes mellitus, hypertension, heart disease, stroke, gout, arthritis, and cancer (Tershakovec et al, 1994; Hill & Trowbridge, 1998). The primary causes, experts agree, are related to low activity level and inadequate nutrition (Sothern & Gordon, 2003). More recently, several human and animal studies (Davies et al, 2000; Lin et al, 2000; Zemel et al, 2000; Shi et al, 2001; Zemel 2001; Pereira et al, 2002; Zemel, 2002; Bray, 2004; Lelovics, 2004; Loos et al, 2004; Soares et al, 2004) have suggested a specific role for calcium in modulating body weight, body mass index (BMI) or adiposity, and dietary calcium is now well recognized as playing an important role in the regulation of energy metabolism and obesity risk. This appears to be mediated primarily by dietary calcium modulation of circulating calcitriol, which in turn regulates adipocyte intracellular calcium. Increased intracellular calcium stimulates lipogenic gene expression and activity and inhibits lipolysis, resulting in increased adipocyte lipid accumulation. Since calcitriol stimulates adipocyte Ca2+ influx, low-calcium diets promote adiposity, while dietary calcium suppression of calcitriol reduces adiposity (Zemel & Miller, 2004). Dairy sources of calcium markedly attenuate weight and fat gain and accelerate fat loss to a greater degree than do supplemental sources of calcium. This augmented effect of dairy products relative to supplemental calcium is likely due to additional bioactive compounds, which act synergistically with calcium to attenuate adiposity (Zemel & Miller, 2004).

The objective of our study was to assess nutritional intake in school children (7–9-y-old) and relate calcium intake to BMI.




The study was carried out from October 2002 to June 2003 and was performed in a random sample of 7–9-y-old children. This age range was chosen for practical and physiological reasons. By age 6 y the adiposity rebound occurs, following the nadir of the BMI curve (Rolland–Cachera et al, 1984). This age range is also probably a favorable period for prevention strategies, which means that it is of particular interest.

The schools were randomly selected in various districts of the country, and from each of them the participating children were selected using stratified randomization for age, with the aid of a table of random numbers. A total of 4511 children were included, comprising 2274 girls and 2237 boys. Some children were not included in our analysis (n=336), because they were from Asian countries (n=16), from African countries (n=114), from other European countries (n=4), from South America (n=10), three had Down syndrome, one had diabetes, and one had nanism. Finally, 187 were less than 6 y or more than 9-y-old. The response rate was 70.6%.

The number of children included was determined according to the following formula (Daniel, 1987): n=Nz2pq/d2 (N-1)+z2pq, where n is the sample, N the population size, z=1.96 for an error of 0.05, p is the prevalence estimated, q=1-p and d is the precision.

The study protocol was approved by the Ministry of Education (Direcção Regional de Educação), and informed consent was previously obtained from all the children's parents.


In each school two trained persons performed anthropometric measurements using a standardized procedure (OMS, 1995). Anthropometric measurements were performed in light indoor clothing without shoes. Height was measured using a stadiometer, with the head in the Frankfort plane, and weight was measured in an electronic scale with a precision of 100 g.

BMI was calculated as weight/height (kg/m2). The definitions of overweight and obesity were based on average centiles published by Cole et al (2000). These cutoff points are linked to the widely accepted adult cutoff points of a BMI of 25 kg/m2 (overweight) and 30 kg/m2 (obesity).

The childrens' parents completed a self-administered general questionnaire that provided information on general family background characteristics (parents education, children's birth weight, extent and duration of breast feeding).

Physical activity was also assessed, and parents were asked to report the number of days per week in which their children participated in light physical activity (walking) as well as the number of days in which they participated in rigorous physical activity (organized and unorganized sports). In addition, parents were asked to report their children's weekly frequency of physical inactivity or sedentary activity, including hours of television watched, hours of time spent on the computer, and hours spent playing video games.

In-person, 24 h dietary recalls were obtained from the children by nutritionists and specially trained interviewers. Training of interviewers included practice using photos and food models to quantify portion sizes, and experience in probing information from children without suggesting responses. The 24-h recall is the most commonly used dietary assessment method because it is easy to administer, can be performed in large-scale studies, (Dwyer et al, 2001; Kranz & Siega-Riz, 2002) and can be used to assess adequacy of energy and macronutrient intakes. During the 24-h recall, each child was asked to recall all food and beverages consumed during the past 24 h. Daily routines were used as prompts (waking up, going to bed, time between classes, and before or after school) to enhance recall. Portion sizes of foods and beverages consumed were also estimated, using food models and photos, and other props (cups, glasses, food wrappers or containers) as an aid in determining serving sizes. When the recall was complete, the child was asked how typical the 24-h recall is of his/her usual eating habits.

As an external validation of the data is necessary, (Johnson et al, 1996; Champagne et al, 1998) we use Schofield's (Schofield et al, 1985) equations to estimate the basal metabolic rate (BMR), and then Goldberg's (Goldberg et al, 1991) and Black's (Black et al, 1991; Black, 2000a, 2000b) equations to estimate energy intake to BMR ratios (EI/BMR) to define low-energy reporters (Black, 2000b). Assuming a mean physical activity level (PAL) equal to 1.68 in girls and 1.74 in boys for children from 7 to 9-y-old (Black et al, 1991, 1996), the calculated thresholds to define low-energy reporters (underreporting), were 1.64 in girls and 1.70 in boys. Since some children were not capable to recall their dietary intake (45 girls and 79 boys) and other children were considered to be low-energy reporters (726 girls and 617 boys), 1467 cases were not considered in the analysis, which resulted in a total sample of 3044 children (1503 were girls).

Calcium intake was expressed as the calcium-to-protein ratio, both because this stratagem explicitly factors in the countervailing effects of the two nutrients and eliminates most of the portion size estimation error (Church, 1975; Davies et al, 2000). Calcium intake was also compared with Dietary Reference Intakes (Food and Nutrition Board, 1997) (Table 1).

Statistical analysis

Data were analyzed using t-test, and BMI was regressed against calcium-to-protein ratio, using standard statistical methods, and the slope of the relationship was taken as the outcome variable. A P-value of less than 0.05 was considered statistically significant. Age, physical activity, and parental education variables were entered in the regression models in secondary analysis to control for the effects of these variables, and we used the energy-adjusted method (Willett et al, 1997) to obtain a measure of calcium intake that was independent of total energy intake. Statistics were performed using SPSS 12.0.



Subjects included in the study were 1503 girls and 1541 boys with an average age of 8.4 (plusminus0.8) y in both genders (P=0.948). Average BMI was 17.23plusminus2.50 kg/m2 in girls and 17.26plusminus2.53 kg/m2 in boys (P=0.712), and prevalence of overweight/obesity was 24.1% in girls and 22.2% in boys (P=0.212).

Energy intake and nutritional pattern in each gender are presented in Table 1. In both genders, the diet was high in fat, particularly saturated fat, sugars and protein, and low in total carbohydrates and dietary fiber. The prevalence of children with calcium intake below the Dietary Reference Intake was higher in girls (36.4 vs 33.0%, P=0.053).

The nutritional pattern was combined with a sedentary lifestyle (Table 2). In our study, boys were more involved in sport activities than girls (57.3 vs 45.4%, P<0.001) and weekly duration of sport activities was also higher in boys (2.5plusminus1.9 vs 2.0plusminus1.3 h/week, P<0.001); leisure activity was highly sedentary, with extensive viewing of television/videos. The percentages of children, who spend 2 or more hours watching television/video, were: 16.2% of girls and 15.3% of boys, during weekdays; 56.9% of girls and 58.5% of boys, during saturdays; and 54.7% of girls and 56.8% of boys during sundays.

In relation to mother's education, the level of less than 4-y was observed in 15.8% of girls and 14.4% of boys; in 18.2% of girls and 18.6% of boys, father's level of education was less than 4-y.

The regression parameters to estimate the association between calcium intake and BMI are presented in Table 3. The slope was significantly negative only for girls (-0.052 kg/m2/mg/p, P=0.002). The intercepts represent the predicted BMI values for zero calcium intake; in girls, the predicted BMI was 17.79 kg/m2 while the mean BMI was 17.23 kg/m2. These regression relationships were also examined in multivariate models, using combinations of calcium intake, protein intake, energy intake, and after adjusting for age, physical activity, energy intake, sugars and fat intake, parental education, birth weight, extent and duration of breast-feeding; none of the models was superior to the simpler bivariate regression of BMI on calcium-to-protein ratio, and after adjustment for confounders the results remained statistically significant only for girls.



This is the largest study in Portugal about body mass and nutritional intake in children 7–9 y of age. The frequency of an inadequate dietary calcium intake was high. It is important to note that these data do not contain the calcium obtained from nutritional supplements. Therefore, they may underestimate total calcium intake. Analyses were conducted separately for girls and boys, and effects were further adjusted for confounders. We found an inverse relationship between calcium and BMI only in girls. Over the last four years, several studies support an 'antiobesity' effect of dietary calcium. Data from the Continuing Survey of Food Intake by Individuals (CSFII) noted a highly significant inverse relation between BMI and calcium consumption, and a dose–response reduction in obesity prevalence among women as calcium intake increased from the first to the second and third tertiles of calcium intake (Albertson et al, 2003). A similar inverse relationship between calcium intake and adiposity was also found for men and women in data from NHANES III (Zemel et al, 2000). The Quebec Family Study examined the relationship between calcium intake body composition in adults and found that BMI was significantly greater in adults consuming less than 600 mg of calcium per day than in those consuming higher levels of calcium (Jackmain et al, 2003).

In other studies (Davies et al, 2000), each 1.0 increment in the calcium-to-protein ratio was associated with a 0.186 kg/m2 decrement in BMI of young women, which was higher than the 0.052 kg/m2 decrement in girls' BMI obtained from our sample. As Table 3 notes, calcium intake explained only a very small percentage of the variability in BMI, which may be related to the complexity of factors that may relate to body weight. Most importantly, body weight is a highly multifactorial variable, and it is improbable that a large fraction of its variability could be attributed to a single factor, like calcium. Furthermore, assessing food intake is a difficult task, particularly in children, because it relies on self-reporting, which is a surrogate measure of the total quantity of food intake. Although children may find it easiest to recall the most recent food or beverage consumed, working backward over a 24-h period, the 24-h recall is dependent on the respondent's memory, and one single day does not represent usual intake. An additional drawback is that self-reports of food intake under-estimate food and nutrient intake (Livingstone & Black, 2003). If total energy intake is underestimated, it is probable that the intakes of other nutrients, like calcium, are also underestimated (Livingstone & Black, 2003). This problem has been identified and addressed by investigators, using several external markers of intake (Lichtman et al, 1992; Black et al, 1993; Bingham et al, 1995). Like other authors (Maillard et al, 2000), in our study we used Goldberg et al (1991) and Black et al (1991) approaches in order to identify diet reports of poor validity. However, more recently, Black (2000b) suggested that Goldberg cutoff for EI/BMR, in order to improve identification of bias to under-reporting, should be used with a questionnaire that, at least, permits classification of subjects into low, medium or high levels of activity. Nevertheless, 24-h dietary recalls are most suitable when one wishes to determine the typical intake of large groups of subjects (Wolper et al, 1995).

In boys, we did not find a significant association between calcium intake and BMI, and this difference in relation to girls remains to be clarified. Although there is a strong theoretical framework in place to explain the effects of dietary calcium on adipocyte metabolism and lipid storage (Zemel & Miller, 2004), the mechanisms whereby calcium (and dairy products) augments these effects are not yet clear. In our view, it is possible that the effects depend on recognized important factors such as the dietary source of calcium (Zemel & Miller, 2004) or other(s) like gender-related characteristics. In the HERITAGE Family Study, for example, among white individuals, the strongest inverse relationship between dietary calcium and adiposity occurred in women (Loos et al, 2004). In preadolescents, the increase in percent body fat with puberty is earlier and greater in females than in males, and during middle childhood, boys have more lean body mass per centimeter of height than girls (Story et al, 2000; Isaacs, 2002). It is possible that some interaction between percent body fat and dietary calcium may occur, and the effects related to calcium intake, in order to be real, depend on a percentage of body fat above a certain threshold, which may not have occurred in male subjects.

In our study, boys were also more involved in sport activities than girls. Sport activities are another important factor that may interact in the regulation of energy metabolism since they cause important perturbations in fuel utilization, inherent to the major changes in energy expenditure which they induce. This is made evident by the fact that physically active individuals need less body fat to burn as much fat as they eat (Astrup and Flatt, 1996). In promoting fat oxidation, physical activity is a substitute for an expansion of the adipose tissue mass and this may also cause important modifications in substrate utilization and lipid storage. More recently, several authors also found that calcium (from both dairy and nondairy sources) acutely stimulated postprandial fat oxidation (Melanson et al, 2003; Cummings et al, 2004) and suppressed carbohydrate oxidation (Cummings et al, 2004).

In the present study, the consumption of sugars in both genders was very high. However, sugar intake was not significantly associated with BMI. Nevertheless, it is recognized that higher intakes of free-sugars promote a positive energy balance (World Health Organization, 2003). Although we did not assess the dietary sources of nutrients, sugar-sweetened drinks are one of the possible sources of ingested simple carbohydrates. Potential health problems associated with the high intake of sugar-sweetened drinks in children include displacement of milk consumption, resulting in lower calcium intake from milk (Committee on School Health, 2004). In our study, it is possible that the source of dietary calcium may also have had a substantial impact on the magnitude of calcium's effect on BMI (Bray, 2004), in view of the fact that the dairy sources of calcium may produce 50 to 70% greater effects on fat loss during energy restriction (Zemel & Miller, 2004). These effects from dairy sources of calcium appear to exert greater effects than supplemental or fortified sources and are most likely attributable to additional bioactive compounds in dairy which act synergistically with calcium to attenuate adiposity (Zemel & Miller, 2004). However, as previously mentioned, in the present study we did not evaluate the dietary sources of calcium.

In our study, we found in both genders a mean protein intake, expressed as percent of total energy and as g/kg body weight, higher than recommended (World Health Organization, 2003). The calciuric effect of protein consumption has been known since 1920, and there is no question that increasing dietary protein increases urinary calcium (Kerstetter et al, 2003), and some investigators (Hegsted et al, 1981; Zemel, 1988) have concluded that dietary protein is a more important regulator of urinary calcium than dietary calcium intake. There is agreement that diets moderate in protein (1.0–1.5 g protein/kg) are associated with normal calcium metabolism. In our study, 99% of children consumed quantities of protein that could be considered higher than moderate. Individuals consuming high protein intakes, particularly from omnivorous sources, develop sustained hypercalciuria that is due for the most part to an increase in intestinal calcium absorption (Kerstetter et al, 2003). The long-term implications of these findings in calcium balance are unknown. Nevertheless, in the present study, calcium intake was expressed as the calcium-to-protein ratio. As other studies (Barger-Lux et al, 1992; Heaney, 1993) have shown, the ratio better correlates with an outcome variable known to be associated with calcium intake than does either nutrient alone. In our study, calcium intake alone did not reveal significant associations with BMI, and in both genders, no reduction was found in BMI as calcium intake increased from the lowest to the highest tertiles/quartiles of calcium intake.

Several other reasons may contribute to the specific differences in the findings of our study in relation to the effects of dietary calcium on BMI in each gender, compared with those of previously mentioned studies, namely: differences in populations sampled (eg, both genders vs women only, different ethnic backgrounds ranges); differences in dietary assessment methodology (eg, dietary records, (Lelovics, 2004; Soares et al, 2004) versus 24-h dietary recalls (Skinner et al, 2003) versus food frequency questionnaires (Loos et al, 2004)); and differences in analytic methods (eg, no energy-adjusted dietary calcium (Davies et al, 2000) or energy-adjusted dietary calcium in statistical models (Loos et al, 2004)).

It should be noted that the effect noted in girls from our sample, cannot be unequivocally attributed to calcium per se or to other nutrients for which calcium was a fortuity marker. Nevertheless, these data support the evidence of an 'antiobesity' effect of dietary calcium in girls.



We found an inverse relationship between calcium intake and BMI only in girls. Controlled trials are needed to assess the effects of dietary calcium on body mass in each gender.



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