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3 Nutritional Epidemiology Program, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, 4 General Medicine Division, Massachusetts General Hospital, Boston, MA, 02114, 5 Energy Metabolism Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111; and 6 Mathematics and Statistics Department, Boston University, Boston, MA 02215
* To whom correspondence should be addressed. E-mail: nicola.mckeown{at}tufts.edu.
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ABSTRACT |
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 TOP ABSTRACT IntroductionStudy Design and MethodsResultsDiscussionLITERATURE CITED |
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2 servings/d, 188 vs. 206 pmol/L, P-trend <0.001) after adjusting for potential confounders. Sugar-sweetened drink consumption was not associated with fasting glucose or ISI0,120. Fruit juice consumption was inversely associated with fasting glucose (none vs. 2 servings/d, 5.28 vs. 5.18 mmol/L, P-trend = 0.006), but not with fasting insulin (none vs. 2 servings/d, 200 vs. 188 pmol/L, P-trend = 0.37) or ISI0,120 (none vs. 2 servings/d, 26.0 vs. 27.0, P-trend = 0.19) in multivariate models. Diet soda consumption was not associated with any surrogate measures of insulin resistance after adjustment for potential confounders (insulin: none vs. 2 servings/d, 195 vs. 193 pmol/L, P-trend = 0.59; glucose: 5.26 vs. 5.24 mmol/L, P-trend = 0.84; and ISI0,120: 26.2 vs. 26.7, P-trend = 0.37). In these healthy adults, sugar-sweetened drink consumption appears to be unfavorably associated with surrogate measures reflecting hepatic more than peripheral insulin sensitivity. Studies of long-term beverage consumption using more direct measures of insulin sensitivity are clearly warranted.
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Introduction |
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TOPABSTRACTIntroductionStudy Design and MethodsResultsDiscussionLITERATURE CITED |
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The metabolic effects of fruit juice may differ from those of sugar-sweetened drinks because these beverages provide vitamins, minerals, soluble fiber, and various phenolic compounds, in addition to sugars. In the Nurses Health Study, higher fruit juice consumption was not associated with type 2 DM risk (9), in contrast to sugar-sweetened drink consumption. Thus, we hypothesized that higher consumption of sugar-sweetened drinks, but not fruit juice consumption, is unfavorably associated with insulin sensitivity, independent of body weight. To test this hypothesis, we examined the cross-sectional relationship between sugar-sweetened drink, diet soft drink, and fruit juice consumption and glucose and insulin homeostasis measures in adult men and women.
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Study Design and Methods |
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TOPABSTRACTIntroductionStudy Design and MethodsResultsDiscussionLITERATURE CITED |
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Participants.
The Framingham Offspring Study is a longitudinal community-based study of cardiovascular disease in the offspring of the original participants of the Framingham Heart Study Cohort and their spouses (12). In 1971, 5135 participants were enrolled into the study (13). During the fifth examination cycle of the Framingham Offspring Study (1991–1995), 3799 participants underwent a standardized medical history and physical examination. Valid FFQ data were available for 3418 patients. Dietary information was considered valid if reported energy intakes were 2,512 kJ/d (600 kcal/d) for men and women or <17,585 kJ/d (4200 kcal/d) for men and 16,747 kJ/d (4,000 kcal/d) for women, respectively, or if fewer than 13 food items were left blank. Participants were excluded from analyses if they had DM (n = 396), based on the use of insulin, oral hypoglycemic medication, fasting plasma glucose 7.0 mmol/L (126 mg/dL), or 2-h post 75-g oral glucose tolerance test (OGTT) plasma glucose concentrations 11.1 mmol/L (200 mg/dL). We also excluded participants with missing information for major covariates, exposure, or outcome data, including intake of sweetened beverages, levels of fasting insulin, fasting glucose, or 2-h post-OGTT plasma glucose concentrations (n = 522). The final sample size was 2500 (1154 men and 1346 women).
Dietary data. Usual dietary intake for the previous year was assessed at the fifth study examination using a semiquantitative 126-item FFQ (14). The questionnaire was mailed to participants before the examination, and the participants were asked to bring the completed questionnaire with them to their appointment. The FFQ consisted of a list of foods with a standard serving size and a selection of 9 frequency categories, ranging from never or <1 serving/mo to >6 servings/d. Nutrient intake was calculated by multiplying the frequency of consumption of each unit of food from the FFQ by the nutrient contents of the specific portion. Participants were asked to report their frequency of beverage consumption during the previous year, of 1) sugar-sweetened drinks (including Coke, Pepsi, or other cola with sugar, caffeine-free Coke, Pepsi, or other cola with sugar, and other carbonated beverage with sugar); 2) diet soda (including low-calorie cola with caffeine, low-calorie caffeine-free cola, and other low-calorie carbonated beverages); and 3) fruit juice (including apple juice or apple cider, orange juice, grapefruit juice, and other juice). One serving of sugar-sweetened drink and diet soda was equivalent to 360 mL (12 fl oz.). One serving of fruit juice was equivalent to 180 mL (6 fl oz.). Separate questions about vitamin and mineral supplement use were also included in the FFQ. The relative validity of this FFQ has been examined in several populations for both nutrients and foods (14–18). The correlation coefficients between FFQ and multiple diet records are 0.51 for both sugar-sweetened drinks and fruit drinks, 0.66 for diet soda, and 0.76 for fruit juice (18).
Laboratory procedures.
Blood samples were obtained from participants who had fasted for at least 8 h, and samples were stored at –70°C. Fasting plasma insulin concentrations were determined using the Coat-A-Count 125I-radioimmunoassay (Diagnostic Products). This is assay has cross-reactivity with proinsulin at the midcurve of 40%, intra- and inter-assay CV of 5–10%, and a lower limit of sensitivity of 7.9 pmol/L (1.1 µU/mL). Fasting plasma glucose concentrations were measured in fresh specimens with a hexokinase reagent kit. The intra-assay CV was <3%. The 75-g OGTT was administered according to the WHO standards (19), and 2-h post-OGTT plasma glucose and insulin concentrations were measured. Homeostatic model assessment of insulin resistance (HOMA-IR) is the surrogate measure of insulin resistance at fasting state, and it tends to represent hepatic insulin resistance (20). HOMA-IR was calculated using the following formula (21):
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A more recently proposed index for insulin sensitivity is the insulin sensitivity index (ISI0,120) (22). This measure reflects peripheral insulin resistance and glucose disposal and is a direct measurement of the ß-cell response to energy stress (20). ISI0,120 was calculated using the following formula (22):
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where
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MPG is the mean of fasting and 2-h post-OGTT glucose concentrations (mg/dL), and MSI is the mean of fasting and 2-h post-OGTT insulin concentrations (µU/L).
Potential confounding factors.
Potential confounding factors for the associations between beverage consumption and insulin resistance included sex, age (y), BMI [weight (kg)/height (m2)], waist circumference (cm), smoking dose (none, 1–15, 16–25, or 25 cigarettes/d), total energy intake (kJ/d), alcohol intake (g/d), saturated fatty acid intake (g/d), current multivitamin use (yes/no), cholesterol-lowering medication (yes/no), hypertension medication use (yes/no), and physical activity score (23). Additional potential dietary confounding factors included dietary glycemic index, dietary fiber, whole grain, fruit, and vegetable intakes.
Statistical analyses.
Statistical analyses were conducted using SAS statistical software (version 8; SAS Institute). The 
-level <0.05 was considered as significant. We tested the surrogate measures of insulin resistance for normality and, because fasting insulin concentrations and HOMA-IR were positively skewed, analyses of these measures were performed on the natural logarithm transformations. Inverse transformations were performed to provide geometric mean and 95% CI for fasting insulin concentrations and HOMA-IR. In this study population, HOMA-IR and fasting insulin are highly correlated (Spearman r = 0.96). The tables include both fasting insulin and HOMA-IR data; however because they have the same interpretation, the results are not discussed in the text.
We compared characteristics (means ± SD or %) of nonconsumers (0 servings/d) with those of consumers of sugar-sweetened drinks, diet soft drinks, and fruit juice (0.5 serving/d) using Student's t tests and 
2 tests. We also compared intakes of selected nutrients between consumers and nonconsumers using ANCOVA. All dietary variables except total energy intake were adjusted for age, sex, and total energy intake, and least squares adjusted means ± SD are presented.
To examine the relation between beverage consumption and surrogate measures of insulin resistance, we categorized beverage consumption into 4 groups: nonconsumers, <1 serving/d, 1–2 servings/d, and 2 servings/d. We compared least squares means of insulin, glucose, HOMA-IR, and ISI0,120 across consumption frequency categories for each beverage type (sugar-sweetened drink, diet soft drink, and fruit juice). In addition to age- and sex-adjusted models, we also considered multivariate models, in which we controlled for sex, age, BMI, waist circumference, physical activity, smoking status, hypertension, cholesterol-lowering medication use, multivitamin use, and intakes of alcohol, total energy, and saturated fat. Additional models further adjusted the relations between beverage consumption and measures of insulin resistance for additional dietary factors, including dietary glycemic index and dietary fiber, whole grain, and fruit and vegetable intake. In all models, tests for linear trend across 4 categories of beverage consumption were measured by assigning the median beverage intake as the value for the respective beverage categories and treating this variable in the analyses as a continuous variable. The P-value for the regression coefficient for beverage intake was reported as P for trend. We tested each association for interactions with age, sex, BMI, and waist circumference, but none of these interactions were statistically significant.
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Results |
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TOPABSTRACTIntroductionStudy Design and MethodsResultsDiscussionLITERATURE CITED |
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Fruit juice consumers were less likely to be female and current smokers, and had a higher prevalence of hypertension than those who did not consume fruit juice (Table 1). Fruit juice drinkers had higher total energy, carbohydrate, fiber, magnesium, and dietary glycemic index, and lower saturated fat and alcohol intakes than those who did not consume fruit juice.
After adjustment for potential confounding variables, the frequency of sugar-sweetened drink intake was positively associated with fasting insulin (none vs. 2 servings/d, 188 vs. 206 pmol/L, P-trend < 0.001) (Table 2). The associations between the frequency of sugar-sweetened drink consumption and fasting plasma insulin and HOMA-IR remained statistically significant after further adjustment for dietary glycemic index, fruit intake, or vegetable intake. No significant associations were found between sugar-sweetened drink intake and fasting glucose or ISI0,120. There were positive associations between diet soda and fasting insulin and glucose, HOMA-IR, and ISI0,120 in the age- and sex-adjusted model. However, these associations were confounded by mainly BMI and waist circumference, and were no longer significant after adjusting potential confounders (Table 2). Both BMI and waist circumference were included in the multivariate models because they were significant predictors in the models. However, we performed the analysis with adjustment for either BMI or waist circumference and the associations remained unchanged.
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2 servings/d, 5.28 vs. 5.18 mmol/L, P-trend = 0.006) (Table 2). The association between fruit juice and fasting glucose remained significant after adjustment for dietary glycemic index, fiber intake, whole grain, fruit intake, or vegetable intake. We found no significant associations between fruit juice intake and fasting insulin, HOMA-IR, or ISI0,120 after adjustment for potential confounders. Mutual adjustment for other beverages did not alter the findings; for instance, adjustment for diet soda and fruit juice intakes did not change the association between sugar-sweetened drink consumption and surrogate measures of insulin resistance. |
Discussion |
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TOPABSTRACTIntroductionStudy Design and MethodsResultsDiscussionLITERATURE CITED |
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Both insulin resistance and ß-cell dysfunction precede type 2 DM, and thus increased consumption of calorically sweetened beverages containing rapidly absorbable simple sugars may contribute to an increased risk of type 2 DM. In the Nurses' Health Study, the risk of type 2 DM doubled in women who consumed at least 1 sugar-sweetened beverage a day (RR = 1.87, 95% CI: 1.42–2.36), compared with women with the lowest intake (<1/mo) (9). In contrast, sweetened beverage consumption, which included fruit punch, nondiet soda, and orange and grapefruit juice, was not related to type 2 DM risk in middle-aged adults in the Atherosclerosis Risk in Communities Study. (24). The discrepancies between studies may be in part due to the inclusion of fruit juices with sugar-added beverages in the Atherosclerosis Risk in Communities study.
Sugar-sweetened drinks contain large amounts of high fructose corn syrup (25), which consists of 
55% fructose and 45% glucose (26). The composition of high fructose corn syrup is similar to sucrose (27), and, therefore, these added caloric sweeteners should in theory be considered equivalent with respect to their effects on metabolic risk factors. Evidence from animal studies suggests that long-term sucrose consumption can lead to glucose intolerance and decreased insulin sensitivity, although this may be attributed to weight gain (28). In observational studies, dietary sucrose has been associated with higher fasting insulin in young adults (29), and positively associated with 2-h insulin concentrations after a glucose load in a small sample of Asian and European men (30). In contrast, no relationship was found between sucrose intake and HOMA-IR in middle-aged adults (31). Our findings contribute to the sparse data in the literature examining the relationship between sugar-sweetened drink consumption and surrogate markers of insulin sensitivity in adults. One cross-sectional study in overweight Latino children found that greater consumption of calorically sweetened beverages was related to insulin resistance and poor ß-cell function, as measured by a frequently sampled intravenous glucose-tolerance test and minimal model (32). This study differed from ours with respect to the age group, to the classification of calorically sweetened beverages that included any beverage containing added sugar (such as sweetened tea or coffee), and to the fact that beverage consumption was estimated from 3-d diet records (32).
Sugar-sweetened sodas and fruit drinks are the leading source of added sugar in the U.S. diet (7) and contribute to the overall glycemic index of the diet (9). Dietary glycemic index, a measure of a carbohydrate food's ability to affect postprandial glycemia, has been linked to an increased risk of type 2 DM (33–35). In the Framingham Offspring Cohort, a higher dietary glycemic index was associated with a higher HOMA-IR, and greater prevalence of the metabolic syndrome (36). In this study, the positive associations between the consumption of sugar-sweetened drinks and fasting insulin and the HOMA-IR remained statistically significant after further adjustment for dietary glycemic index, indicating that this relationship was not fully explained by the effect of the high glycemic index of sugar-sweetened drinks.
Although higher fruit juice consumption was inversely associated with lower fasting plasma glucose, no significant relationship was observed with the fasting insulin, HOMA-IR, and ISI0,120. In our cohort, the lifestyle and dietary characteristics of fruit juice consumers were more favorable for the prevention of insulin resistance. For instance, fruit juice consumers were less likely to smoke and they consumed diets lower in saturated fat and higher in total fiber intakes than nonconsumers. It is possible, therefore, that the observed inverse association between fruit juice intake and fasting glucose is potentially due to residual confounding. In middle-aged Japanese Brazilians, no relationship was observed between the consumption of fruit and fruit juice combined and risk of impaired glucose tolerance (37). Further studies on fruit juice and measures of insulin sensitivity among different populations with varying degrees of glucose tolerance are needed. To date, there is little evidence that the sugar present in fruits or fruit juices is associated with adverse metabolic effects, with the possible exception of weight gain in some populations (9,38). However, it is important to recognize that excess energy intake from fruit juice may contribute to increased body weight.
The evidence linking diet soda to adverse health consequences is scarce. Clinical studies have demonstrated that an increased consumption of caloric soda increased energy intake and body weight in healthy individuals, whereas increased consumption of diet soda significantly reduced energy intake and body weight (39). Similarly, a clinical study in overweight individuals found that daily supplementation with 152 g of sucrose caused an increase in energy intake, body weight, fat mass, and blood pressure, whereas reductions in body weight and fat mass were observed after supplementation with an equivalent amount of an artificial sweetener (40). In this study, there was no relationship between diet soda consumption and measures of glucose homeostasis. Although it is recognized that diet beverages are preferable to calorically sweetened beverages (41), little is known is about the health consequences of diet sodas. The effects of long-term consumption of sodas on metabolic risk factors have not been studied in longitudinal studies to date, and further research is clearly warranted.
Interpretation of our findings is subject to some caveats. Although the results from this study support the hypothesis that sugar-sweetened drink consumption may be an important determinant of insulin resistance, the cross-sectional design precludes assigning cause and effect. The FFQ has many limitations with respect to the assessment of beverage consumption, such as misreporting frequency of consumption and the lack of individual information on portion size. To date, the majority of observational studies on sugar-sweetened/caloric beverages and body weight have been conducted in children or adolescents, and not middle-aged or older adults (42,43). Excessive consumption of caloric beverages contributes to energy intake and may lead to a positive energy balance and subsequent weight gain. A recent systematic review of the topic suggests that sugar-sweetened beverage intake is related to weight gain (43). In this cross-sectional study, sugar-sweetened drink consumers had a lower BMI and were more physical active, whereas paradoxically, diet soda drinkers had higher BMI and were less physically active. A common practice in weight control is the consumption of noncaloric sweeteners and/or beverages (44). Our multivariate models included both BMI and waist circumference, as these measures reflect different distributions in body fat. However, because of the cross-sectional design, we cannot determine the associations between caloric and noncaloric beverages and weight gain, and thus more prospective studies of this topic are needed.
Sugar-sweetened drink consumption is high in the U.S. (45), with an estimated 76% of the population consuming sugared beverages daily (46). The 2005 Dietary Guidelines for America recommends that the public choose beverages with less caloric sweetener (47). A new proposed guidance system for beverage consumption (41) urges individuals to increase their consumption of water while limiting their intake of calorically sweetened, nutrient-poor beverages. Long-term sugar-sweetened drink consumption may lead to deterioration in insulin sensitivity, which increases an individual's risk of developing type 2 DM. However, more detailed physiological studies of the metabolic effects of sugar-sweetened drinks are needed to determine whether their consumption preferentially affects fasting vs. postprandial energy regulation. In the meantime, in accordance with current dietary recommendations (41,47), individuals are advised to limit consumption of calorically sweetened beverages.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Author disclosures: M. Yoshida, G. Rogers, J. B. Meigs, E. Saltzman, R. D'Agostino, no conflicts of interest; P. F. Jacques is a member of the Nutrition Advisory Board for Cadbury Schweppes; and N. M. McKeown has served as an independent consultant for Cadbury Schweppes.
6 Abbreviations used: DM, diabetes mellitus; HOMA-IR, homeostatic model assessment of insulin resistance; ISI0,120, insulin sensitivity index; OGTT, oral glucose tolerance test.
Manuscript received 9 April 2007. Initial review completed 23 May 2007. Revision accepted 27 June 2007.
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LITERATURE CITED |
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