Abstract
Beneficial effects on body weight of supplementation with BCAA, including leucine, isoleucine, and valine, have been observed in animal and human studies. However, population-based studies on dietary BCAA intake and body weight are lacking. The objective of this study was to examine the association between dietary BCAA intake and risk of overweight status/obesity among multi-ethnic populations. The International Study of Macro-/Micronutrients and Blood Pressure is a cross-sectional epidemiological investigation in China, Japan, the UK, and the US. The study cohort included 4429 men and women ages 40–59 y who were free of diabetes. Diet was assessed by 4 multi-pass 24-h recalls; data on nutrients including BCAA were derived from country-specific food tables. Overweight status and obesity were defined as BMI ≥ 25 and BMI ≥ 30 kg/m2, respectively. Multivariable-adjusted OR of overweight status/obesity and 95% CI by quartiles of BCAA intake were estimated by logistic regression. Mean BCAA intake was 2.6 ± 0.6% energy; intake was significantly lower among Chinese participants and similar among participants from the other 3 countries. Compared with those in the first quartile, the multivariable-adjusted OR (95% CI) of overweight status from the 2nd to 4th quartiles of BCAA intake were 0.97 (0.80–1.17), 0.91 (0.75–1.11), and 0.70 (0.57–0.86), respectively (P-trend < 0.01). BCAA intake and obesity were also inversely associated (P-trend = 0.03). In conclusion, higher dietary BCAA intake is associated with lower prevalence of overweight status/obesity among apparently healthy middle-aged adults from East Asian and Western countries.
Introduction
Overweight status and obesity, escalating health problems worldwide (1), are major risk factors for coronary heart disease and associated with higher risk of hypertension, dyslipidemia, diabetes, certain cancers, and other chronic disorders. Nutrition is important, along with other lifestyle factors, for prevention and reduction of excess body weight; diets with higher protein and lower carbohydrate content have been reported to promote weight loss with greater loss of body fat and reduced loss of lean body mass (2–6). BCAA, including leucine, isoleucine, and valine, are essential amino acids and recent studies support the idea that they may be responsible for some of the beneficial effects of high-protein diets. BCAA play an important role in protein synthesis as well as glucose metabolism, the latter particularly during periods of restricted energy intake (7–9). One study in wrestlers found that BCAA supplementation was more effective in reducing body fat than energy restriction alone (10) and others have reported beneficial effects on body weight and body fat among obese individuals (11, 12).
Most previous studies on BCAA intake and overweight status/obesity were limited to obese individuals or involved specific interventions such as energy restriction with supplementation (10–16). To our knowledge, no study has assessed this association in a multi-ethnic population. With its high quality dietary data, the population-based International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP) Study provides a unique opportunity to test the hypothesis that BCAA intake is inversely associated with overweight status and obesity across different cultures among apparently healthy adults.
Methods
Design and participants.
INTERMAP is an international cross-sectional epidemiological investigation involving 4680 men and women ages 40–59 y from 17 randomly selected diverse population samples in Japan (4 samples, n = 1145), the People’s Republic of China (3 samples, n = 839), the UK (2 samples, n = 501), and the US (8 samples, n = 2195). The study received institutional ethics committee approval for each site and all participants provided written informed consent.
Details of the INTERMAP Study have been described (17–19). Briefly, each participant visited the local INTERMAP research center 4 times: twice on consecutive days and twice on consecutive days ∼3 wk later. Dietary data on all foods, beverages, and supplements consumed were collected by trained and certified dietary interviewers at each visit using an in-depth, multiple-pass, 24-h recall method that has been described in detail (17, 20). Nutrient intakes were derived from country-specific food tables compiled and standardized by the Nutrition Coordinating Center in Minneapolis, MN, and INTERMAP nutritionists for each country (21). Nutrients were expressed as energy density (% energy) in the present study. In addition, interviewer-administered questionnaires were used to obtain data on demographic factors and other potential confounders, as described elsewhere (18).
Two timed 24-h urine specimens, bracketed by the first and second pair of 24-h recalls, respectively, were used to measure sodium, potassium, calcium, urea nitrogen (an index of total protein intake), and other metabolites. Specimens were frozen, shipped periodically to the Central Laboratory in Leuven, Belgium, and analyzed using methods and equipment described previously (18) under strict internal and external quality control. Pearson correlation coefficients between urinary and dietary nutrient values, similar for men and women, were 0.42 for sodium (P < 0.01), 0.55 for potassium (P , 0.01), and 0.51 for dietary protein and urinary urea nitrogen (P , 0.01) (17).
Overweight status and obesity definitions.
Height and weight without shoes were measured at the first and 3rd visits using methods and equipment described previously (18). BMI was defined as weight in kilograms divided by the square of height in meters (kg/m2); the mean of these 2 values was used. Overweight status was defined as BMI ≥ 25 kg/m2 and obesity as BMI ≥ 30 kg/m2 (22).
Of 4680 participants, 251 were excluded for diabetes diagnosis or treatment or extreme daily energy intake [<800 kcal (3349 kJ) or >5000 kcal (20,934 kJ) for men; <600 kcal (2512 kJ) or >4000 kcal (16,747 kJ) for women]. Hence, 4429 participants (822 in China, 1106 in Japan, 492 in the UK, and 2009 in the US) were included in these analyses.
Statistical analyses.
Mean values for demographic and other risk factors, urinary measures, and dietary factors were compared across 4 quartiles of BCAA intake using ANOVA or chi-square tests as appropriate. Because partial correlation analysis showed a very high correlation between BCAA and total protein intake (r = 0.98) and nutrient densities can help to reduce the likelihood of multicollinearity (23), BCAA intake was expressed as a percentage of total protein intake (r = 0.19). Logistic regression was used to estimate the OR and 95% CI of overweight status and obesity by quartiles of BCAA intake. Wald’s Z test was used to test for cross-region or cross-country heterogeneity of findings and assessed by addition of interaction terms to the model. Correlation analysis was performed to assess the association of BCAA and BMI with dietary and nondietary factors. Potential confounders were selected based on this correlation analysis and the existing literature. OR and 95% CI for overweight status and obesity were calculated in 3 models: model 1 controlled for age, gender, and country; model 2 additionally controlled for employment status, physical activity, smoking status, special diet, total energy intake, total available carbohydrate, and saturated fat intake; model 3 further adjusted for total protein intake. Continuous BCAA (actual value) was used to examine possible linear trends. In addition, analyses were performed within countries and then overall OR and 95% CI were estimated by pooling data and weighting by inverse of variance (24). P-values were 2-sided with P ≤ 0.05 considered significant. SAS version 9.1.3 (SAS Institute) was used for analyses. Unless noted otherwise, values in the text are means ± SD.
Results
BCAA intake was 2.6 ± 0.6% energy for the 4429 participants; intake (2.1 ± 0.4% energy) was significantly lower among Chinese participants and similar across the other 3 countries (2.7–2.8% energy). BMI was significantly lower among Chinese and Japanese participants (23.1 ± 3.3 kg/m2 and 23.4 ± 2.9 kg/m2) compared with participants from the UK (27.4 ± 4.6 kg/m2) and US (28.6 ± 5.8 kg/m2). The prevalence of overweight status was 25.3, 26.3, 69.3, and 70.2% among participants from China, Japan, the UK, and the US, respectively. Prevalence of obesity was 1.9, 3.4, 22.4, and 33.3% across the 4 countries, respectively. Participant characteristics are presented by quartile of BCAA intake (Table 1). Compared with those in the first quartile of BCAA intake, participants in the 4th quartile were more likely to be male and less likely to be current smokers and had higher total protein, animal protein, and fat intake and lower carbohydrate, starch, and total energy intake.
TABLE 1.
Characteristics of INTERMAP Study participants by quartile of BCAA intake1
Quartiles of BCAA (% total protein intake) |
|||||
Variable | 1 | 2 | 3 | 4 | P2 |
Participants, n | 1107 | 1107 | 1108 | 1107 | |
BCAA, % total protein intake | 16.4 ± 0.4 | 17.1 ± 0.1 | 17.5 ± 0.1 | 18.1 ± 0.4 | |
Age, y | 49.0 ± 5.5 | 49.2 ± 5.3 | 48.7 ± 5.6 | 49.3 ± 5.4 | 0.11 |
Male, % | 43.1 | 46.6 | 53.7 | 55.6 | <0.01 |
Country, % | |||||
Japan | 16.1 | 25.9 | 32.9 | 25.0 | <0.01 |
China | 31.6 | 10.3 | 10.7 | 21.7 | |
UK | 8.9 | 9.9 | 12.7 | 12.8 | |
US | 43.4 | 53.8 | 43.8 | 40.5 | |
BMI, kg/m2 | 25.9 ± 5.1 | 26.7 ± 5.5 | 26.2 ± 5.1 | 25.8 ± 5.6 | <0.01 |
Physical activity, h/d | 3.6 ± 3.6 | 3.2 ± 3.4 | 3.3 ± 3.5 | 3.8 ± 3.7 | <0.01 |
Current smoker, % | 29.8 | 24.5 | 21.2 | 19.3 | <0.01 |
Urinary biomarkers | |||||
Urea nitrogen, g/24 h | 8.8 ± 2.6 | 9.1 ± 2.7 | 9.2 ± 2.6 | 9.1 ± 2.9 | <0.01 |
Sodium, mmol/24 h | 199.6 ± 85.8 | 178.4 ± 65.6 | 175.0 ± 65.8 | 168.3 ± 66.3 | <0.01 |
Potassium, mmol/24 h | 50.1 ± 19.7 | 52.9 ± 18.8 | 53.7 ± 19.2 | 55.1 ± 21.5 | <0.01 |
Sodium/potassium | 4.7 ± 2.8 | 3.8 ± 1.8 | 3.6 ± 1.7 | 3.5 ± 1.7 | <0.01 |
Calcium, mmol/24 h | 4.2 ± 2.0 | 4.1 ± 2.0 | 4.2 ± 2.0 | 4.4 ± 2.0 | 0.06 |
Daily nutrient intake | |||||
Total protein,% energy/d | 13.8 ± 2.9 | 15.2 ± 2.9 | 15.6 ± 3.0 | 15.6 ± 3.0 | <0.01 |
Animal protein | 6.3 ± 4.2 | 8.8 ± 3.6 | 9.2 ± 3.6 | 9.0 ± 4.1 | <0.01 |
Vegetable protein | 7.4 ± 2.6 | 6.3 ± 2.0 | 6.3 ± 1.9 | 6.5 ± 2.2 | <0.01 |
Total fat, g/d | 25.8 ± 8.2 | 29.5 ± 7.8 | 29.6 ± 7.7 | 28.6 ± 8.1 | <0.01 |
SFA | 7.5 ± 3.3 | 9.1 ± 3.4 | 9.3 ± 3.5 | 9.4 ± 4.0 | <0.01 |
MUFA | 9.7 ± 3.4 | 11.0 ± 3.2 | 10.9 ± 3.1 | 10.5 ± 3.0 | <0.01 |
PUFA | 6.5 ± 2.2 | 6.8 ± 2.2 | 6.7 ± 2.0 | 6.2 ± 1.9 | <0.01 |
Cholesterol,3mg /1000 kcal | 110.6 ± 72.9 | 144.0 ± 69.9 | 151.4 ± 72.6 | 143.3 ± 76.2 | <0.01 |
Total carbohydrate, g/d | 55.9 ± 11.4 | 51.8 ± 9.7 | 52.1 ± 8.8 | 54.1 ± 9.8 | <0.01 |
Starch, g/d | 36.5 ± 16.8 | 29.7 ± 12.2 | 30.9 ± 11.7 | 33.5 ± 15.2 | <0.01 |
Estimated total sugar, g/d | 14.2 ± 6.1 | 11.0 ± 4.8 | 10.9 ± 4.6 | 11.1 ± 4.8 | 0.86 |
Energy, Mcal/d | 2.2 ± 0.6 | 2.2 ± 0.6 | 2.1 ± 0.6 | 2.1 ± 0.6 | 0.08 |
BCAA intake was expressed as percent total protein intake; all values are unadjusted mean ± SD, unless indicated.
P are for differences across quartiles of BCAA intake.
1 kcal = 4.18 kJ.
With adjustment for potential dietary and nondietary confounders (age, gender, country, employment status, physical activity, smoking status, special diet, and intakes of total energy, total carbohydrate, saturated fat, and total protein), BCAA intake was inversely related to BMI and overweight status. The multivariable-adjusted OR of overweight status was 0.70 (95% CI = 0.57–0.86; P-trend < 0.01) for the 4th quartile of BCAA intake compared with the first (Table 2). To account for variation by location, we analyzed data by country and then pooled the results with meta-analysis weighted by the inverse of variance. The results did not change appreciably (Table 2).
TABLE 2.
Multivariable-adjusted OR and 95% CI of overweight status by quartile of BCAA intake1ndash3
Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P-trend | |
Japan + P.R. China | |||||
Participants, n | 483 | 481 | 483 | 481 | |
Overweight participants, n | 134 | 146 | 132 | 89 | |
Median intake, % total protein intake | 16.35 | 17.11 | 17.54 | 18.10 | |
Model 1 | 1.00 | 1.11 (0.84, 1.46) | 0.95 (0.71, 1.26) | 0.57 (0.42, 0.78) | <0.01 |
Model 2 | 1.00 | 1.15 (0.86, 1.53) | 1.07 (0.79, 1.44) | 0.71 (0.51, 0.98) | 0.12 |
Model 3 | 1.00 | 1.13 (0.84, 1.51) | 1.03 (0.77, 1.40) | 0.68 (0.49, 0.95) | 0.08 |
UK + USA | |||||
Participants, n | 626 | 625 | 625 | 625 | |
Overweight participants, n | 436 | 434 | 442 | 440 | |
Median intake, % total protein intake | 16.65 | 17.10 | 17.47 | 17.97 | |
Model 1 | 1.00 | 1.04 (0.82, 1.33) | 1.18 (0.92, 1.52) | 1.16 (0.91, 1.49) | 0.18 |
Model 2 | 1.00 | 0.96 (0.75, 1.24) | 1.03 (0.80, 1.33) | 0.98 (0.76, 1.28) | 0.99 |
Model 3 | 1.00 | 0.89 (0.69, 1.14) | 0.89 (0.68, 1.15) | 0.81 (0.61, 1.06) | 0.09 |
Overall | |||||
Participants, n | 1109 | 1106 | 1108 | 1106 | |
Overweight participants, n | 570 | 580 | 574 | 529 | |
Median intake, % total protein intake | 16.60 | 17.11 | 17.50 | 17.99 | |
Model 1 | 1.00 | 1.08 (0.90, 1.30) | 1.08 (0.90, 1.30) | 0.88 (0.73, 1.06) | 0.15 |
Model 2 | 1.00 | 1.02 (0.85, 1.24) | 1.00 (0.83, 1.22) | 0.80 (0.66, 0.98) | 0.04 |
Model 3 | 1.00 | 0.97 (0.80, 1.17) | 0.91 (0.75, 1.11) | 0.70 (0.57, 0.86) | <0.01 |
Model 3* | 1.00 | 0.99 (0.81, 1.20) | 0.96 (0.78, 1.18) | 0.80 (0.64, 0.99) | <0.01 |
BCAA intake was expressed as percent protein intake; data are OR and 95% CI unless otherwise indicated.
Model 1: adjusted for age, gender and country. Model 2: additionally adjusted for employment status, physical activity, smoking status, special diet and intakes of total energy intake, total available carbohydrate, and saturated fat. Model 3: additionally adjusted for total protein intake. Model 3*: estimated odds ratios within countries and calculation of overall odds ratios using meta-analysis weighted by inverse of variance; adjustment for the same covariates as in model 3.
-values for the differences of OR of overweight status between Eastern and Western countries for the 3 higher quartiles are 0.40, 0.87, and 0.06, respectively.
Because of the low prevalence of obesity in China (1.9%) and Japan (3.4%), we examined the association between BCAA and obesity only among participants from the UK and the US. Multivariable adjusted OR of obesity were 0.75 (95% CI = 0.58–0.98; P-trend = 0.03) for the 4th quartile of BCAA intake compared with the first. A significant inverse association prevailed for the Western countries and for the UK separately. For the US, the inverse direction remained, but the trend became nonsignificant (P-trend = 0.12) (Table 3).
TABLE 3.
Multivariable-adjusted OR and 95% CI of obesity in the UK and US by quartile of BCAA intake1ndash3
Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P-trend | |
UK | |||||
Participants, n | 123 | 123 | 123 | 123 | |
Obese participants, n | 32 | 25 | 26 | 27 | |
Median intake, % total protein intake | 16.67 | 17.19 | 17.58 | 18.02 | |
Model 1 | 1.00 | 0.66 (0.36, 1.21) | 0.70 (0.38, 1.28) | 0.73 (0.40, 1.34) | 0.15 |
Model 2 | 1.00 | 0.65 (0.35, 1.23) | 0.67 (0.35, 1.27) | 0.69 (0.35, 1.35) | 0.16 |
Model 3 | 1.00 | 0.58 (0.31, 1.10) | 0.52 (0.27, 1.03) | 0.52 (0.26, 1.06) | 0.04 |
US | |||||
Participants, n | 503 | 502 | 502 | 502 | |
Obese participants, n | 158 | 168 | 170 | 172 | |
Median intake, % total protein intake | 16.65 | 17.09 | 17.44 | 17.95 | |
Model 1 | 1.00 | 1.10 (0.84, 1.43) | 1.12 (0.86, 1.45) | 1.14 (0.88, 1.49) | 0.24 |
Model 2 | 1.00 | 0.98 (0.75, 1.29) | 0.93 (0.70, 1.22) | 0.92 (0.70, 1.21) | 0.63 |
Model 3 | 1.00 | 0.94 (0.71, 1.23) | 0.84 (0.63, 1.11) | 0.80 (0.60, 1.07) | 0.12 |
Overall | |||||
Participants, n | 626 | 625 | 625 | 625 | |
Obese participants, n | 190 | 193 | 196 | 199 | |
Median intake, % total protein intake | 16.65 | 17.10 | 17.47 | 17.97 | |
Model 1 | 1.00 | 1.03 (0.81, 1.31) | 1.05 (0.83, 1.34) | 1.08 (0.85, 1.37) | 0.55 |
Model 2 | 1.00 | 0.94 (0.74, 1.21) | 0.91 (0.71, 1.17) | 0.89 (0.69, 1.15) | 0.40 |
Model 3 | 1.00 | 0.88 (0.69, 1.13) | 0.80 (0.62, 1.04) | 0.75 (0.58, 0.98) | 0.03 |
Model 3* | 1.00 | 0.87 (0.77, 0.99) | 0.78 (0.60, 1.01) | 0.75 (0.58, 0.98) | 0.03 |
BCAA intake was expressed as percent protein intake; data are OR and 95% CI unless otherwise indicated.
Model 1: adjusted for age, gender, and country. Model 2: additionally adjusted for employment status, physical activity, smoking status, special diet and intakes of total energy intake, total available carbohydrate, and saturated fat. Model 3: additionally adjusted for total protein intake. Model 3*: estimated OR within countries and calculation of overall OR using meta-analysis weighted by inverse of variance; adjustment for the same covariates as in model 3.
P are for differences in OR of obesity between the UK and US for the 3 higher quartiles are 0.19, 0.23, and 0.19, respectively. None of the quadratic trends are significant.
To test the robustness of our main findings, we conducted 2 sensitivity analyses. First, when we replaced total protein intake with urinary urea nitrogen in model 3 (Tables 2 and 3), the inverse associations were essentially the same. Second, when we replaced total protein intake with the other 17 of 20 naturally occurring amino acids, the inverse associations remained.
Discussion
In this international, population-based, cross-sectional study, dietary intake of BCAA was inversely associated with prevalence of overweight status among apparently healthy middle-aged adults from both East Asian and Western countries and with prevalence of obesity in Western countries.
Our findings are generally consistent with previous animal and human studies. Animal studies found that rats fed whey protein (with 50–75% higher leucine content than other common food proteins) had significantly lower body weight and fat mass gain compared with rats fed red meat or casein (25, 26). In other animal studies, leucine supplementation significantly decreased body weight in obese mice (15, 16) and body fat in rats under food restriction (13) but had no weight reduction effect in normal-weight mice (16). The magnitude of weight loss among rats consuming a high-protein diet was similar to that achieved with leucine supplementation in obese mice (13). Thus, leucine or BCAA were suggested to be responsible for the potential beneficial effects of high-protein intake on body weight. In humans, most randomized controlled trials (2–6) reported that diets high in protein significantly lowered body weight in obese individuals, although 1 trial reported no independent effect of diet composition (27). BCAA intake was found to reduce body weight and body fat in intervention studies (10–12). In a short-term study, 25 wrestlers consumed 1 of 3 energy-restricted diets comprised of high protein, high BCAA, or low protein (10). Those consuming the high-BCAA diet had the greatest weight loss (−4.0 kg; P < 0.05) and decline in body fat percent (−17.3%; P < 0.05) and a significant reduction in abdominal visceral adipose tissue (−34.4%; P < 0.05) (10).
Several potential mechanisms may account for the inverse association between BCAA intake and body weight; animal studies provide some evidence that leucine may increase energy expenditure. One study using mice as subjects found that leucine supplementation was not associated with weight gain in obese mice with increased food intake (16). Leucine supplementation was also found to stimulate an increase in plasma leptin, an adipose-derived hormone regulating energy intake and expenditure, and leptin levels were reduced by 40% in rats fed a leucine-deficient meal (28). Exogenous leptin administration can suppress appetite and food intake, resulting in decreased body weight in rats (29, 30). Some animal studies using rats or mice have found that leucine supplementation also increased activity of mammalian target of rapamycin, another major regulator of energy balance (31), and consequently lowered body weight (15, 16, 32).
Another possible mechanism for the effect of BCAA on body weight is improved glucose tolerance, because impaired glucose tolerance (IGT) is suggested to be a cause of obesity (33). Although data on IGT’s possible role in obesity development are limited, 1 human study found that higher intra-abdominal adiposity was an independent risk factor for IGT among Japanese Americans (34). At present, conflicting data exist on the role of BCAA as a mechanism for this association. Results of 1 study indicate that rats consuming a high-fat, high-BCAA diet developed insulin resistance (35). Similar findings have been reported in nonobese humans (36). Conversely, increased leucine intake prevented high-fat diet-induced hyperglycemia in obese mice (16, 37). Additionally, leucine was found to stimulate insulin release from the pancreas, thereby decreasing blood glucose (38, 39). Isoleucine also has a hypoglycemic effect via an insulin-independent pathway (40, 41). Although the beneficial effect of increased BCAA intake on body weight through improved glucose metabolism may be only modest in magnitude, it could be of public health significance because of the high prevalence of IGT in overweight and obese individuals (42).
BCAA intake in the INTERMAP population was consistent with that found in other study populations. For example, in intervention studies on adult women ages 40–56 y, mean BCAA intake in the control group was ~10 g/d (11, 12). In addition, a study using stable isotopes to measure whole-body leucine metabolism reported that daily leucine intake was ~6 g/d (43), similar to that found in our study (6.1 ± 2.0 g/d). Because long-term protein intake of 1.2–2.0 g/kg body weight appears to exert no harmful effect on renal function (11), increased BCAA intake (e.g. to 20 g/d) apparently would not be harmful to health.
The cross-sectional design of the INTERMAP Study limits inferences as to the causal relationship between BCAA intake and risk of overweight status/obesity. To our knowledge, however, this is the only population-based study that has examined this issue. It adds evidence to existing literature that significant inverse associations between BCAA intake and overweight status may explain at least partially the weight loss effect of high-protein diets reported by previous intervention studies (2–6).
In conclusion, we found significant inverse associations between BCAA intake and overweight status/obesity. Our findings suggest that weight loss induced by a high-protein/low-carbohydrate diet may be partially explained by BCAA intake. Further studies are needed to investigate this long-term association and to determine a potential causal relationship.
Acknowledgments
L.Q., P.X., and K.H. designed and conducted the research; P.X. and L.Q. analyzed data; L.Q., P.X., D.B., and K.H. drafted the paper; M.L.D., L.V.H., and J.S. critically revised the manuscript for important intellectual content; P.X., D.B., and K.H. had primary responsibility for the final content. All authors read and approved the final manuscript.
Footnotes
Supported by NIH grant no. R21DK073812 and INTERMAP was supported by NIH grant no. R01HL50490.
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