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- Methods and Procedures
We have examined the relationship between artificially sweetened beverage (ASB) consumption and long-term weight gain in the San Antonio Heart Study. From 1979 to 1988, height, weight, and ASB consumption were measured among 5,158 adult residents of San Antonio, Texas. Seven to eight years later, 3,682 participants (74% of survivors) were re-examined. Outcome measures were incidence of overweight/obesity (OW/OBinc) and obesity (OBinc) (BMI ≥ 25 and ≥ 30 kg/m2, respectively), and BMI change by follow-up (ΔBMI, kg/m2). A significant positive dose-response relationship emerged between baseline ASB consumption and all outcome measures, adjusted for baseline BMI and demographic/behavioral characteristics. Consuming >21 ASBs/week (vs. none) was associated with almost-doubled risk of OW/OB (odds ratio (OR) = 1.93, P = 0.007) among 1,250 baseline normal-weight (NW) individuals, and doubled risk of obesity (OR = 2.03, P = 0.0005) among 2,571 individuals with baseline BMIs <30 kg/m2. Compared with nonusers (+1.01 kg/m2), ΔBMIs were significantly higher for ASB quartiles 2–4: +1.46 (P = 0.003), +1.50 (P = 0.002), and +1.78 kg/m2 (P < 0.0001), respectively. Overall, adjusted ΔBMIs were 47% greater among artificial sweetner (AS) users than nonusers (+1.48 kg/m2 vs. +1.01 kg/m2, respectively, P < 0.0001). In separate analyses—stratified by gender; ethnicity; baseline weight category, dieting, or diabetes status; or exercise-change category—ΔBMIs were consistently greater among AS users. These differences, though not significant among exercise increasers, or those with baseline diabetes or BMI >30 kg/m2 (P = 0.069), were significant in all 13 remaining strata. These findings raise the question whether AS use might be fueling—rather than fighting—our escalating obesity epidemic.
- Top of page
- Methods and Procedures
Table 1 presents baseline characteristics for 3,371 participants whose baseline ASB dose, baseline and follow-up BMI, and all covariate data were available. Age, education, socioeconomic index, exercise, and dieting were greater in AS users, who were more likely to be female and OW/OB, and less likely to be Hispanic or smokers (vs. non-AS-users, all P < 0.0001). Total calories, calories from carbohydrates and sucrose, and alcohol consumption were lower among AS users (P < 0.0001), whose sugar-sweetened beverage (SSB) consumption was one-fourth that of nonusers. Milk consumption was also lower among AS users (P = 0.018), but calcium intake was similar in the two groups. Percent of calories from protein, total fat, and saturated fat were significantly higher in AS users (P < 0.0001).
Table 1. Baseline characteristics by self-reported AS use: means (s.d.) and percentages
Follow-up participants and nonreturnees had comparable baseline BMIs (27.16 vs. 27.25 kg/m2, P = 0.58). Dieting rates were also similar (22.4% vs. 20.6%, respectively, P = 0.16). Returnees were older (44.6 vs. 42.1 years, < 0.001) and more likely to exercise (26.8% vs. 24.2%, P = 0.054) and use AS (47.1% vs. 44.0%, P = 0.040) at baseline, than nonreturnees. Among returnees, baseline AS users were more likely than nonusers to have decreased exercise frequency: −0.161 vs. +0.17 times/week, respectively (P = 0.005).
ORs for OW/OBinc (Figure 1a) and OBinc (Figure 1b) for 3,371 participants for whom all covariate data are available are displayed by baseline ASB consumption quartile (vs. nonusers). These ORs have been adjusted for baseline BMI, age, ethnicity, gender, education, socioeconomic index, baseline and interim change in exercise frequency, baseline smoking status, and interim smoking cessation.
Figure 1. Odds ratios (ORs) and 95% confidence intervals for OW/OBinc by 7- to 8-year follow-up. (a) ORs for becoming overweight/obese by 7- to 8-year follow-up, according to artificially sweetened beverage consumption quartile at baseline. (b) ORs for becoming obese by 7- to 8-year follow-up, according to artificially sweetened beverage consumption quartile at baseline. Panel a shows ORs for the incidence of BMI ≥25 kg/m2 at follow-up: 428 incident cases among 1,250 with BMI <25 kg/m2 at baseline. Overall P = 0.008; trend P < 0.001. Panel b shows ORs for the incidence of BMI ≥30 kg/m2: 390 incident cases among 2,571 with BMI <30 kg/m2 at baseline. Overall P = 0.005; trend P < 0.0001. Adjusted for gender and ethnicity; baseline age, education, socioeconomic index, BMI, exercise frequency, and smoking status; and interim change in exercise level and smoking cessation. *vs. none: P < 0.05; †vs. none: P < 0.01; ‡vs. none: P < 0.001. OBinc, incidence of obesity; OW/OBinc, incidence of overweight/obesity.
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Overall, among 1,250 participants who had been NW at baseline, 428 (34.0%) had BMIs ≥25 kg/m2 by follow-up; among 2,571 with BMI <30 kg/m2 at baseline, 390 (15.2%) had BMIs ≥30 kg/m2 by follow-up. Both OW/OBinc and OBinc showed significant dose-response relationships with ASB consumption. Among users, in ASB quartiles 1–4, ORs for OW/OBinc (with 95% confidence intervals) were 1.56 (1.02, 2.40, P = 0.041), 1.74 (1.10, 2.77, P = 0.018), 1.75 (1.09, 2.82, P = 0.021), and 1.93 (1.20, 3.11, P = 0.007), respectively. ORs for OBinc for ASB consumption quartiles 1–4 were 1.34 (0.86, 2.08), 1.46 (0.96, 2.22, P = 0.075), 1.73 (1.13, 2.63, P = 0.011), and 2.03 (1.36, 3.03, P = 0.0005). Risk increased most between nonuse and quartile 1, but continued rising (trend: P < 0.001 for OW/OBinc, P < 0.0001 for OBinc) toward a doubling with peak dosage.
A positive dose-response relationship was observed between ASB use and ΔBMI (Figure 2a, P < 0.0001 for trend): mean ΔBMIs were 1.01 (0.88, 1.14), 1.11 (0.85, 1.38), 1.46 (1.20, 1.73, P = 0.003), 1.50 (1.23, 1.78, P = 0.002), and 1.78 (1.51, 2.06, P < 0.0001) kg/m2 for nonusers and ASB quartiles 1–4, respectively. Thus, participants in ASB quartile 4 experienced 78% greater ΔBMIs than nonusers. Similar results emerged from cohort 2 sub-analyses excluding interim AS adopters and discontinuers (Figure 2b): in this subset, ASB quartiles 3 and 4 experienced 74% (P = 0.013) and 83% (P = 0.003) greater ΔBMIs, respectively, compared with nonusers (P = 0.0006 for trend).
Figure 2. Change in BMI in kg/m2, by 7-to 8-year follow-up. (a) Change in BMI, in kg/m2, by 7- to 8-year follow-up, in both cohorts, according to artificially sweetened beverage consumption quartile at baseline. P < 0.0001 for trend. (b) Change in BMI, in kg/m2, by 7- to 8-year follow-up, among cohort 2 participants, with interim artificial sweetener adopters and discontinuers excluded. P < 0.0006 for trend. Adjusted for gender and ethnicity; baseline age, education, socioeconomic index, BMI, exercise frequency, and smoking status; and interim change in exercise level and smoking cessation. *vs. none: P < 0.05; †vs. none: P < 0.01; ‡vs. none: P < 0.001.
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In separate cohort 2 analyses examining baseline non-AS-users (n = 915), interim AS adopters and nonadopters experienced similar ΔBMIs: 1.08 and 1.20 kg/m2, respectively (P = 0.488). Baseline AS users (n = 920) who discontinued use by follow-up experienced 59% lower ΔBMIs than continuers (1.03 kg/m2 vs. 1.62 kg/m2, respectively, P = 0.038). Thus, AS adoption conferred no significant advantage, but discontinuation was associated with significantly lower ΔBMI.
No positive relationship emerged between SSB consumption and ΔBMI in our data. Overall, ΔBMIs were, in fact, lower among SSB users: 1.48 (1.30, 1.66) kg/m2 among SSB nonusers, compared with 1.18 (0.90, 1.45), 1.17 (0.93, 1.41; P = 0.04), 1.05 (0.83, 1.26; P = 0.003), and 1.15 (0.95, 1.34; P = 0.02) kg/m2 for SSB quartiles 1–4 (P = 0.009 for trend). In cohort 2 sub-analyses excluding AS adopters and discontinuers, however, no significant relationship was found between SSB consumption and ΔBMIs, which were 1.59 (1.34, 1.84) kg/m2 for nonusers, vs. 1.64 (1.20, 2.09), 1.40 (0.99, 1.82), 1.06 (0.71, 1.42; P = 0.02), and 1.54 (1.23, 1.85) kg/m2 for SSB quartiles 1–4 (P = 0.26 for trend).
Overall (Table 2, n = 3,371), ΔBMIs were 47% higher in AS users than nonusers (+1.48 vs. +1.01 kg/m2, respectively, P < 0.0001). Within-stratum analyses were performed for seven key variables: gender; ethnicity; weight category, diabetes and dieting status at baseline; Δexercise category; and cohort. Point estimates for all subgroups suggested greater BMI gains (or smaller losses) for AS users vs. nonusers; these differences were significant for all but three strata: those with increasing exercise frequency, and those with either diabetes or BMI ≥30 kg/m2 at baseline (P = 0.069 for the latter).
Table 2. Change in BMIa (mean ± s.e., kg/m2), by 7- to 8-year follow-up, by AS consumption
Dieting was strongly associated with AS consumption: 72% of dieters—vs. 41% of nondieters—used ASs. Overall, baseline dieters gained more weight by follow-up than nondieters (P < 0.001). Within each group, however, AS users experienced significantly higher ΔBMIs. Among dieters, mean ΔBMI was 2.00 kg/m2 for AS users, 1.23 kg/m2 for nonusers (P = 0.003). Thus, a 5′ 3″dieter might have gained 11 lbs with AS use, 7 lbs without; a 6′ 2″dieter might have gained 15 lbs with AS use, 10 lbs without.
Excess gains associated with AS use were marked among dieters (62%), men (59%), and non-Hispanic whites (65%). Within each Δexercise category, point estimates for ΔBMI were over 40% higher for AS users.
Soft drinks, tea, and coffee comprised 31.3, 39.4, and 29.3%, respectively, of AS beverage consumption. For each beverage, AS users experienced significantly higher ΔBMIs (Table 3).
Table 3. Change in BMIa (mean ± s.e., kg/m2), by AS beverage type consumed at baseline