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Center for Food and Nutrition Policy, Virginia Tech-National Capital Region
Dear Editor:
Inadequate calcium consumption is a serious nutrition problem for some subpopulations in the United States, most notably African-American adolescent and young women. The nutrition community is right to search for ways to increase calcium consumption, particularly among the most at-risk subpopulations. We therefore welcome the opportunity to discuss these issues with Drs. Barr and Johnson.
In a minor point, Barr and Johnson (1) suggest that analysis of sugar-sweetened beverages, not added sugars, would be more appropriate. Because we (2) were addressing the Institute of Medicine report (3) and its ensuing policy recommendations, we were obligated to use the same variable in our analysis. In other research, we found a positive, not a negative, association between the consumption of both regular carbonated soft drinks (RCSD) and fruit drinks and calcium intake, but this association was very weak (4).
More fundamentally, Barr and Johnson contend that consumption of added sugars either adds excess energy or dilutes micronutrients. This is a false dilemma. We will show that, in general, individuals who have higher consumption of added sugars do not have higher BMI values or lower calcium intakes.
The central issue in the debate concerning the association between consumption of added sugars and micronutrient intake is the proper way to control for total energy. Barr and Johnson assert that we did not control for total energy. This is incorrect. We used a standard partition or decomposition model (5–7), and every MJ of energy was included. Barr utilized a similar specification and reported a positive association between soft drink consumption and calcium intake (8). Barr and Johnson argue that we should have used an alternative specification that controls for total energy instead of energy from sources other than added sugars (EOther). Understanding the differences between these two specifications is critical in the controversy over added sugars.
The two specifications are mathematically equivalent, but they estimate different concepts. The model we used estimates the effect of increasing energy from added sugars (EAS), while EOther is held constant. The model Barr and Johnson propose estimates the effect of substituting EAS for EOther (6,7). The specification they propose assumes that EAS displaces EOther on a 1:1 basis. That is, the specification assumes what they are claiming to prove.
The assumption that increasing EAS decreases EOther is an empirical question. The displacement argument implies that each additional unit of EAS reduces EOther by 1 unit. We regressed EAS on EOther using the same National Health and Nutrition Examination Survey III dataset as in the original article, and we found no displacement. Instead, we found that each unit of EAS increases EOther by 0.41–1.12 U depending on the age-gender group. Rather than displacing EOther, EAS was associated with increased EOther. Because the displacement assumption is not valid, claims that these models prove nutrient displacement are wrong.
The finding that consumption of EAS is associated with higher EOther brings us to the dilemma. Barr and Johnson postulate that if EAS is not displacing EOther, it must be contributing excess energy. However, the empirical evidence does not support an association between consumption of added sugars and BMI. We found that neither added sugars nor RCSD was positively associated with BMI (9,10). Although one prospective study of 548 children reported a positive correlation between sugar-sweetened beverage consumption and BMI (11), a more recent prospective study of >10,000 children found no association after controlling for total energy (12).
The proposed dilemma proves false because we are looking at relations across individuals in a population. The "average person" from a dietary survey is not a real person to whom we can give dietary advice. We need to know whether the individuals who are above or below the mean for EAS are generally above or below the means for BMI and calcium intake. Mean values for BMI, calcium intake, and EAS consumption tell us nothing about the relations among these variables. Adolescent males, for example, have relatively high consumption of EAS, relatively high calcium intake, and a relatively low prevalence of overweight. The results we have discussed show that there is little relation between EAS and calcium intake or EAS and BMI.
There are relatively few effective ways to increase calcium intake without substantially increasing total energy intake. These include increasing low-fat dairy consumption, calcium fortification, and calcium supplementation. We believe that policy efforts should emphasize these approaches to increase calcium consumption in the U.S. population.
Manuscript received 1 February 2005.
LITERATURE CITED
1. Barr, S. I. & Johnson, R. K. (2005) Effect of added sugars on dietary quality. J. Nutr. 135:1336.
2. Forshee, R. A. & Storey, M. L. (2004) Controversy and statistical issues in the use of nutrient densities in assessing diet quality. J. Nutr. 134:2733-2737.
3. Food and Nutrition Board, Institute of Medicine, National Academy of Sciences (2002) Dietary Reference Intakes: Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein and Amino Acids 2002 National Academy Press Washington, DC.
4. Storey, M. L., Forshee, R. A. & Anderson, P. A. (2004) Associations of adequate intake of calcium with diet, beverage consumption, and demographic characteristics among children and adolescents. J. Am. Coll. Nutr. 23:18-33.
5. Willett, W. C. & Stampfer, M. (1998) Implications of total energy intake for epidemiologic analysis. Willett, W. C. eds. Nutritional Epidemiology 2nd ed. 1998:273-301 Oxford University Press New York, NY. .
6. Kipnis, V., Freedman, L. S., Brown, C. C., Hartman, A., Schatzkin, A. & Wacholder, S. (1993) Interpretation of energy adjustment models for nutritional epidemiology. Am. J. Epidemiol. 137:1376-1380.
7. Mackerras, D. (1996) Energy adjustment: the concepts underlying the debate. J. Clin. Epidemiol. 49:957-962.[Medline]
8. Barr, S. I. (1994) Associations of social and demographic variables with calcium intakes of high school students. J. Am. Diet. Assoc. 94:260-266: 269.[Medline]
9. Storey, M. L., Forshee, R. A., Weaver, A. R. & Sansalone, W. R. (2003) Demographic and lifestyle factors associated with body mass index among children and adolescents. Int. J. Food Sci. Nutr. 54:491-503.[Medline]
10. Forshee, R. A., Anderson, P. A. & Storey, M. L. (2004) The role of beverage consumption, physical activity, sedentary behavior, and demographics on body mass index of adolescents. Int. J. Food Sci. Nutr. 55:463-478.[Medline]
11. Ludwig, D. S., Peterson, K. E. & Gortmaker, S. L. (2001) Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. Lancet 357:505-508.[Medline]
12. Berkey, C. S., Rockett, H.R.H., Field, A. E., Gillman, M. W. & Colditz, G.A. (2004) Sugar-added beverages and adolescent weight change. Obes. Res. 12:778-788.[Medline]
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