You are seeing this message because your Web browser does not support basic Web standards. Find out more about why this message is appearing and what you can do to make your experience on this site better.


ABOUT ARCHIVES
Advanced Search

Welcome   | My Account | E-mail Alerts | Access Rights | Sign In


  Vol. 169 No. 20, November 9, 2009 TABLE OF CONTENTS
  Archives
  •  Online Features
  Original Investigation
 This Article
 •Abstract
 •PDF
 •Send to a friend
 • Save in My Folder
 •Save to citation manager
 •Permissions
 Citing Articles
 •Contact me when this article is cited
 Related Content
 •Related article
 •Similar articles in this journal
 Topic Collections
 •Neurology
 •Psychiatry
 •Obesity
 •Prognosis/ Outcomes
 •Diet
 •Alert me on articles by topic
 Social Bookmarking
  Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit Add to Technorati Add to Twitter What's this?

Long-term Effects of a Very Low-Carbohydrate Diet and a Low-Fat Diet on Mood and Cognitive Function

Grant D. Brinkworth, PhD; Jonathan D. Buckley, PhD; Manny Noakes, PhD; Peter M. Clifton, PhD; Carlene J. Wilson, PhD

Arch Intern Med. 2009;169(20):1873-1880.

ABSTRACT


Background  Very low-carbohydrate (LC) diets are often used to promote weight loss, but the long-term effects on psychological function remain unknown.

Methods  A total of 106 overweight and obese participants (mean [SE] age, 50.0 [0.8] years; mean [SE] body mass index [calculated as weight in kilograms divided by height in meters squared], 33.7 [0.4]) were randomly assigned either to an energy-restricted (approximately 1433-1672 kcal [to convert to kilojoules, multiply by 4.186]), planned isocaloric, very low-carbohydrate, high-fat (LC) diet or to a high-carbohydrate, low-fat (LF) diet for 1 year. Changes in body weight, psychological mood and well-being (Profile of Mood States, Beck Depression Inventory, and Spielberger State Anxiety Inventory scores), and cognitive functioning (working memory and speed of processing) were assessed.

Results  By 1 year, the overall mean (SE) weight loss was 13.7 (1.8) kg, with no significant difference between groups (P = .26). Over the course of the study, there were significant time x diet interactions for Spielberger State Anxiety Inventory, Beck Depression Inventory, and Profile of Mood States scores for total mood disturbance, anger-hostility, confusion-bewilderment, and depression-dejection (P < .05) as a result of greater improvements in these psychological mood states for the LF diet compared with the LC diet. Working memory improved by 1 year (P < .001 for time), but speed of processing remained largely unchanged, with no effect of diet composition on either cognitive domain.

Conclusions  Over 1 year, there was a favorable effect of an energy-restricted LF diet compared with an isocaloric LC diet on mood state and affect in overweight and obese individuals. Both diets had similar effects on working memory and speed of processing.

Trial Registration  anzctr.org.au Identifier: 12606000203550



INTRODUCTION

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

Weight loss as a result of dieting in obese individuals has been shown to reliably improve psychological state, including mood.1-3 Despite the consistency of official recommendations advocating a high-carbohydrate, low-fat (LF), energy-restricted diet for obesity treatment,4-5 the obesity epidemic has led to widespread interest in alternative dietary patterns for weight management, including very low-carbohydrate (LC) "ketogenic" diets that are typically high in protein and fat (particularly saturated fat).6 While recent clinical studies have shown that LC diets can be an effective alternative dietary approach for weight loss,7-9 their long-term effects on psychological function, including mood and cognition, have been poorly studied.

Two small short-term studies of obese women who were following a low-energy (800-950 kcal/d [to convert to kilojoules, multiply by 4.186]) LF or LC diet for 4 to 6 weeks showed that diet composition did not affect mood state.10-11 Similarly, D’Anci et al12 showed no differences in mood in overweight and obese women who were following a mild hypocaloric LF or LC diet after 3 weeks, although the LC diet resulted in transiently lower scores on the confusion subscale of the Profile of Mood States (POMS) at 2 weeks. Recently, we reported that 8 weeks of consuming either a hypocaloric LC diet or an isoenergetic conventional LF diet resulted in similar improvements in mood state in overweight and obese men and women.13 These previous findings suggest that LC and LF diets have similar effects on mood, but these data must be considered somewhat preliminary because of the short duration of the studies. Over a longer period of 24 weeks, McClernon et al14 reported that mood improved after weight loss with either an LC or an LF diet, but the improvements were greater with the LC diet owing to larger reductions in the negative affect that was suggested to be related to the antidepressant effects of a ketogenic diet. However, their study was limited in that mood was not assessed using validated scales. Rather, they used a symptom checklist developed by practitioners specifically for evaluating and treating individuals using an LC diet for weight loss that may have biased the result toward a positive effect of an LC diet as opposed to an LF diet. Also, the effects of an LC diet over the longer term remain unstudied, making it difficult to draw any definite conclusions regarding the long-term effects of an LC diet combined with moderate energy restriction on psychosocial health.

Studies have also investigated the effects of carbohydrate consumption and carbohydrate-restricted diets on cognitive function.12-13,15-18 In young rats, treatment with a ketogenic LC diet resulted in severe cognitive impairment.15 Acute studies in humans have shown that glucose administration improves cognitive performance,16-17,19 with the hypothesis being that this effect is attributable to increased glucose metabolism in the brain, which then elevates acetylcholine levels and leads to increases in the amplitude of synaptic potentials.16, 20 Concomitant increases in insulin levels as a result of elevations in glucose levels have also been implicated because hippocampal glucose metabolism is sensitive to insulin.21-22 Moreover, glucose-mediated secretion of gut hormones, some of which may affect brain metabolism and autonomic function, has been postulated.17 Glucose also influences the activity of neurotransmitters, including dopamine and serotonin,16 suggesting that glucose may influence cognitive function via indirect processes. In short-term interventional studies in humans, consumption of an LC diet can influence various aspects of cognition in either a positive or a negative manner.12-13,18 A small 4-week study in obese women demonstrated impaired cognitive function after consumption of a very low-energy (approximately 600 kcal) LC ketogenic diet compared with an isocaloric, higher-carbohydrate, lower-fat nonketogenic diet, with the impairment being most evident after 1 week.18 Similarly, a 3-week study in overweight and obese women showed poorer performance on a memory-based task but improved performance on a vigilance-attention task following an energy-restricted LC diet compared with a conventional LF diet.12 Although the researchers suggested that dietary macronutrient composition did not differently affect preoccupation with food or distraction of physiologic signs of hunger that could not explain the differential changes in cognitive performance, possible mechanisms for the observed effects were not studied or discussed in these prior studies.12, 18 In obese men and women, we also showed that following an energy-restricted LC diet for 8 weeks was associated with impairments in cognitive processing speed but not in working memory, relative to those following an isocaloric conventional LF diet.13 Collectively, this evidence suggests that long-term consumption of an LC diet may have implications for cognitive functioning, but so far, to our knowledge, no study has documented these effects beyond a few weeks. Herein, we extend the results of a previous investigation of the short-term effects13 of consuming either an energy-reduced LC diet or an isocaloric conventional LF diet on mood and cognitive function and report the long-term effects at 1 year.


METHODS

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

PARTICIPANTS AND DESIGN

The participants and study design have been previously described elsewhere in a study reporting on separate outcomes.23 Briefly, 118 participants (122 were recruited; 4 withdrew before randomization) aged 24 to 64 years (mean [SE] age, 50.0 [0.8] years) with abdominal obesity and at least 1 additional metabolic syndrome risk factor24 were randomized to consume either an energy-restricted LC diet (n = 57) or an isocaloric conventional LF diet (n = 61) for 52 weeks. Exclusion criteria were a history of liver, cardiovascular, peripheral vascular, respiratory, or gastrointestinal disease; diabetes; pregnancy; or cancer. The study was approved by the Human Research Ethics Committees of the Commonwealth Scientific and Industrial Research Organisation and the University of South Australia, Adelaide. All participants provided written informed consent before participation.

The participants were provided with a prescriptive dietary plan of specific food quantities to achieve specified macronutrient profiles and energy levels. Participants on the LC diet were prescribed a dietary plan aimed at providing 4% of total energy as carbohydrate, 35% as protein, and 61% as fat (20% saturated fat), with the objective to restrict carbohydrate to less than 20 g/d for the first 8 weeks and with an option to increase to less than 40 g/d for the remainder of the study. For participants on the LF diet, the prescribed dietary profile was 46% of total energy as carbohydrate, 24% as protein, and 30% as total fat (<8% saturated fat), with the objective to restrict saturated fat intake to less than 10 g/d for the study duration and with the inclusion of an approved food exchange (equivalent to the energy content of 20 g of carbohydrate) between weeks 9 and 52. Both diets were designed to be moderately energy restricted (approximately 1433 kcal/d for women and 1672 kcal/d for men), with the total energy intake and energy deficit planned to be isocaloric. The participants met individually with a qualified dietitian fortnightly during the first 8 weeks of the study and then monthly thereafter; the dietician provided detailed individualized dietary advice, meal plans, and recipe information pertaining to each diet. To facilitate dietary compliance, the participants were supplied with a selection of key foods (approximately 30% of total energy) that were representative of each diet's macronutrient profile fortnightly for the first 8 weeks, and then a A$40 food voucher was provided at each monthly diet visit during the remainder of the study. Both dietary patterns were also structured to include specific food quantities and weights to ensure that the correct macronutrient and energy requirements were achieved as previously described.13

OUTCOME MEASURES

In the morning after an overnight fast, body weight (calibrated scales, model AMZ14; Mercury Digital Scales, Tokyo, Japan) and mood were measured at baseline and at weeks 8, 24, 40, and 52. Mood was assessed using 3 validated questionnaires: (1) the POMS,25 which measures 6 separate aspects of mood, including tension-anxiety, depression-dejection, anger-hostility, vigor-activity, fatigue-inertia, and confusion-bewilderment, and provides a global score of mood disturbance (total mood disturbance score [TMDS]) that is determined by subtracting the vigor-activity score from the sum of the 5 negative mood factors; (2) the Beck Depression Inventory (BDI)26; and (3) the Spielberger State-Trait Anxiety Inventory (SAI).27 These instruments were administered using time referencing to frame the responses to the following question: "How have you felt over the past week, including today?" Cognitive function was also assessed at baseline and at weeks 8 and 52 using 2 computer-based tests: digit span backward (DSB)28 and inspection time,29 which assess working memory and speed of processing, respectively, and have been described previously in detail.13 After the cognitive and/or mood assessments at weeks 0, 8, 24, and 52, a venous blood sample was obtained for the measurement of plasma glucose and serum insulin levels using a standard enzymatic kit (Roche Diagnostics, Basel, Switzerland) and an enzyme immunoassay kit (Mercodia ELISA; ALPCO Diagnostics, Uppsala, Sweden), respectively.

STATISTICAL ANALYSIS

Before hypothesis testing, data were examined for normality. Data obtained from the mood scales were skewed and normalized by log transformation before analysis. Comparisons of baseline data between experimental conditions and between study dropouts and completers were performed using independent t tests and {chi}2 tests for continuous and categorical variables, respectively. The results indicated that there were no differences in baseline parameters between dropouts and completers. This result in conjunction with other considerations (including assessment of reasons for dropout) led us to believe that the assumption of the missing data being at random is reasonable. To evaluate the outcomes of this study, 2 separate analyses were performed. First, mixed-effects models with repeated measures over time within participants were used to compare mean changes over time between the 2 treatment groups. In the models, participant sex and age were included as factors, and change in weight was included as a covariate to adjust for differences in weight loss. The primary advantages of a mixed-model analysis are that participants are treated as random effects in the repeated measures model and that complete data are not required across the entire study period; ie, there is efficient use of all available data collected from the participants in the analysis.30-31 This analysis provides more precise modeling for longitudinal changes than last-observation-carried-forward methods that could result in bias in either direction.32 Second, a completer's analysis using repeated measures analysis of covariance (ANCOVA) was used to compare treatment effects in all patients who completed the outcome measures at all planned time points, with time as the within-subject factor and treatment and sex as between-subject factors. Age and changes in body weight were included in the model as covariates. When a statistically significant main effect was found, post hoc comparisons were performed to determine differences between the 2 treatments at week 52. Statistical analyses were performed with SPSS version 16.0 (SPSS Inc, Chicago, Illinois). All statistical tests were performed with {alpha} ≤ 0.05 (2-tailed).


RESULTS

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

Of the 118 participants who were randomized, 11 (2 on the LC diet and 9 on the LF diet) withdrew from the study before it began and were not included in the analysis; a further 38 withdrew throughout the intervention, and an additional 3 participants did not complete the mood and cognitive function assessments at the end of the study at week 52 (Figure 1). Another participant in the LF group had extreme scores for these primary outcomes (>4 SDs from the sample mean) and was identified as an outlier and subsequently excluded from the analysis. Overall, there was no difference between the groups in the number of volunteers who completed the study after randomization (LC group, 32 of 55 [58%]; LF group, 33 of 51 [65%]); P = .84). Of the volunteers who began the intervention, 19 (LC group, 13 of 55 [24%]; LF group, 6 of 52 [12%]; P = .10) were taking antidepressant medication. Throughout the intervention, 1 participant in the LC group took more antidepressant medication, and 2 participants took less. The results of the analysis did not change when the participants who were taking antidepressant medication were excluded.


Figure 1
View larger version (38K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Figure 1. Flow of participants through the trial.


On mixed-model analysis using data from all participants, both groups achieved substantial reductions in body weight over the course of the study, with no significant difference between the diets (mean [SE] change in weight: LC group, 96.0 [1.6] kg to 82.3 [2.1] kg; LF group, 97.6 [1.6] kg to 83.9 [1.9] kg; P = .26 for time x diet interaction). There was an overall mean weight loss at 12 months of 13.7 (1.8) kg. Over the study period, both groups also had similar reductions in plasma glucose levels (mean [SE] change in plasma glucose levels [to convert glucose to milligrams per deciliter, divide by 0.0555]: LC group, 5.7 [0.9] mmol/L to 5.4 [0.09] mmol/L; LF group, 5.7 [0.8] mmol/L to 5.3 [0.08] mmol/L; P = .41 for time x diet interaction) and serum insulin levels (mean [SE] change in serum insulin levels [to convert insulin to picomoles per liter, multiply by 6.945]: LC group, 9.0 [0.8] µIU/mL to 5.4 [0.8] µIU/mL; LF group, 10.5 [0.7] µIU/mL to 6.5 [0.7] µIU/mL; P = .38 for time x diet interaction). A completer's analysis using ANCOVA gave similar results for these outcomes (difference in weight loss, P = .20; difference in glucose levels, P = .79; and difference in insulin levels, P = .75).

MOOD MEASURES

At baseline, there was no significant difference between groups on the BDI, SAI, or POMS subscale scores or on the TMDS score that was within 1 SD of the normal range for healthy adult populations.25, 27, 33 The data for mood scores during the intervention based on the estimated marginal means from the mixed models are presented in Figure 2. As previously reported,13 both groups had an initial reduction in scores on the BDI, SAI, and POMS (including the TMDS and the 6 subscales: tension-anxiety, depression-dejection, anger-hostility, vigor-activity, fatigue-inertia, and confusion-bewilderment) that was of similar magnitude by week 8. However, over the longer term, the overall course of change on the SAI, TMDS, and anger-hostility, confusion-bewilderment, and depression-dejection subscales of the POMS differed between the 2 treatment groups (P < .05 for time x diet interaction) because the average scores for these parameters decreased initially in both diet groups and then tended to remain low in the LF group but rebounded toward baseline levels over time in the LC group (Figure 2). Post hoc analysis showed that at week 52 the scores on the POMS subscales of anger-hostility (P = .006), confusion-bewilderment (P = .02), and depression-dejection (P = .05) and the TMDS score (P = .001) were significantly lower in the LF group than in the LC group. On the SAI, the differences were also evident between the diet groups at week 52 (P = .06). A similar pattern of change was evident on the BDI, although the difference between the diet groups did not reach statistical significance (P = .11 for time x diet interaction). The overall trajectory (ie, all time points) of changes in the scores on the remaining POMS subscales—tension-anxiety, fatigue-inertia, and vigor-activity—showed no effect of diet.


Figure 2
View larger version (64K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Figure 2. Estimated marginal means (SEs) of mood scores before and after 8, 24, 40, and 52 weeks of energy restriction with a low-carbohydrate, high-fat (LC) diet or a high carbohydrate, low-fat (LF) diet. Beck Depression Inventory score (A), Spielberger State-Trait Anxiety Inventory score (B), and the Profile of Mood States subscales: anger-hostility (C), depression-dejection (D), tension-anxiety (E), fatigue-inertia (F), vigor-activity (G), confusion-bewilderment (H), and total mood disturbance score (I). The asterisk indicates that the score is significantly higher compared with the LF diet (< .05).


The completer's analysis (ie, only those participants who completed the study) using ANCOVA gave a similar pattern of results on the mixed-model analysis for all mood measures presented in Figure 2. Across the course of the study, there were significant time x diet interactions for the SAI (P = .02), BDI (P = .04), TMDS (P = .004) and POMS scales: confusion-bewilderment (P = .04), anger-hostility (P = .04), depression-dejection (P = .04) such that scores improved in the LF group compared with the LC group. Again, the pattern of change for the remaining POMS subscales of tension-anxiety, fatigue-inertia, and vigor-activity did not differ between groups (P ≥ .16 for time x diet interaction).

COGNITIVE FUNCTIONING MEASURES

Values for the cognitive functioning tests are reported in the Table. At baseline, there was no significant difference between groups for working memory or speed of processing. Overall, the mixed-model analysis showed significant improvements in working memory over time (P < .001 for time effect) as a result of the long-term maintenance of improvements that occurred during the initial 8 weeks of the study; no differential effect of diet treatment was observed (P = .88 for time x diet interaction). For speed of processing, although there was a significant main effect of time (P = .011) that arose because of an initial reduction in task performance time after 8 weeks, rebound was evident after 12 months in both groups, and across the entire study period, there was no statistically significant difference between groups (P = .49 for time x diet interaction) (Table). The completer's analysis using ANCOVA gave similar results for these outcomes. At week 52, there was a significant inverse correlation between the change in working memory and the change in fasting plasma insulin levels (r = 0.34; P = .007).


View this table:
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Table. Mixed-Effects Model of the Effects of an Energy-Restricted, Low-Carbohydrate, High-Fat (LC) Diet and a High-Carbohydrate, Low-Fat (LF) Diet Over 12 Months on Working Memory (Digit Span Backward) and Inspection Time



COMMENT

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

In this large, randomized, controlled study, we compared the long-term effects of a moderate energy-restricted LC diet with those of a conventional isocaloric LF diet on mood and cognitive function in overweight and obese individuals. We previously reported marked improvements in mood with both diets over the shorter term of 8 weeks.13 In the present study, for the majority of the mood measures, including the SAI, BDI, and TMDS and the POMS subscales of anger, depression, and confusion, a significant effect of diet composition was observed showing that scores improved over the longer term and then remained stable for participants who were on the LF diet (ie, a positive effect of the diet on mood was maintained), but in the LC group, despite an initial improvement, scores returned toward baseline levels over time (ie, mood returned toward more negative baseline levels).

The sustained improvements in mood in the LF group compared with the LC group are consistent with results from epidemiological studies showing that diets high in carbohydrate and low in fat and protein are associated with lower levels of anxiety and depression and have beneficial effects on psychological well-being.34-36 However, a previous intervention study by McClernon et al14 did show reductions in negative affect following an ad libitum LC diet compared with an energy-reduced LF diet over 24 weeks. The reason for this discrepancy in findings is not entirely clear, but it is important to note that unlike our study, which used validated mood and mental health assessment instruments, the study by McClernon and colleagues derived a measure of negative affect from a nonvalidated symptom checklist developed by practitioners for use in evaluating and treating patients undergoing an LC diet for weight loss. This checklist may have biased the responses toward positive effects of an LC diet compared with an LF diet. Moreover, we compared the effects of LC and LF diets under isocaloric conditions, whereas the previous study by McClernon et al14 used different dietary approaches to deliver the LC and LF diets without specifically controlling for energy intake, which led to markedly greater weight loss with the LC diet (–12.9 kg vs –6.7 kg). Although attempts were made by McClernon and coauthors to control for weight loss in the statistical models because of the association between weight loss and psychological well-being,1, 37-38 the possibility cannot be dismissed that the greater weight loss with the LC diet accounted for the greater reductions in negative affect. McClernon et al14 also noted that in addition to dieting, individuals in the LC group received nutritional supplements while those in the LF group did not, raising the possibility that the group differences in symptoms observed could be attributed to a placebo effect of the nutritional supplements rather than to the LC diet per se.

Consistent with previous studies that have shown improvements in mood and emotional outcomes after weight loss,1, 37-38 and after participation in supervised weight-loss programs with social support,1, 39-40 improvements in mood were observed in the participants in the LF group in our study. However, despite similar and substantial weight losses in the LC group, after improvements were realized over the short term, the mood state of the participants had returned to baseline levels at the end of 1 year. This outcome suggests that some aspects of the LC diet may have had detrimental effects on mood that, over the term of 1 year, negated any positive effects of weight loss. For mood scores that realized statistically significant differences, medium effect sizes (0.5-0.7) were also determined for the difference in the changes between the diets, which have been identified as clinically relevant.41-42 Although a complete explanation for this effect cannot be determined from the current data, there are several plausible reasons. The present study was conducted as a controlled clinical trial in which participants were randomly assigned to the LC or LF diet rather than self-selecting a diet based on their food preference and eating habits. In Western society, established eating patterns and the most common traditional dietary recommendations favor a high-carbohydrate dietary pattern,4-5 with bread, pasta, rice, and fruit consumed in large quantities. Therefore, the LC diet being so far removed from normal dietary habits may have created a significant challenge for participants, leading to the possibility of food preoccupation, social eating impairment, and dysphoria. Although, in the short term, participants may have been able to meet the challenges presented by this dietary pattern, over the longer term, it may have increased participant isolation, leading to the negative impact on mood state that may provide a possible explanation for the effects that were observed. However, these social effects cannot be extrapolated from the current data, and future studies addressing this hypothesis are warranted.

The possibility that the prescriptive nature of the dietary regimens had a negative impact on affect should also be considered. Although a major strength of the current study was the use of highly prescriptive plans by which the dietary patterns were structured to include specific food quantities combined with regular dietary advice and counseling to ensure correct macronutrient and energy requirements, this highly prescriptive method may have alienated some participants. However, the stringent structured approach did not appear to have a negative effect on mood in the LF diet; therefore, the observed response would suggest an interactive effect with diet, with the LC diet magnifying any psychological discomfort associated with the structure of the regimen. Further research should test this hypothesis. In current practice, LC diets are typically followed ad libitum, without specific prescription of energy intake, promoting unlimited intake of protein and fat, with the only food restriction being to limit the intake of carbohydrate.43-44 Whether the detrimental effects of the LC diet on mood that were observed in our study would exist if delivered ad libitium without intensive dietary control over the long term remains unknown; data reported by McClernon et al14 suggest that this may not be the case.

Mood among long-term consumers of LC diets may also be negatively affected by changes in serotogenic expression and neurotrophic factors. While a high-carbohydrate intake can increase serotonin synthesis, fat and protein intakes reduce serotonin concentrations in the brain.45-47 There is an abundance of evidence demonstrating a link between serotogenic functions of the brain and aspects of psychological functioning, particularly depression and anxiety.48-49 Mood has also been shown to be dependent on and directly proportional to brain-derived neurotrophic levels,50 with high-fat diets reducing brain-derived neurotrophic levels,51 possibly as a result of alterations in the levels of corticosterone.52-53 Further studies evaluating the psychophysiological effects of LC diets on serotonin and neurotrophic factors are required.

Despite these results, it is important to note that mood state scores on average for both groups at baseline and throughout the study remained within the normal range for healthy adults.25, 27, 33 Consequently, the present findings are limited to healthy, obese, young to middle-aged adults with normal mood state and cannot be generalized to clinical populations. In addition to mood, cognitive function has also been shown to be acutely affected by meal composition,54 with the short-term (≤8 weeks) consumption of an LC diet potentially producing negative effects on cognitive functioning.12-13,18 In a previous article, we reported that, after 8 weeks, obese participants on an LC diet had less improvement in speed of processing (inspection time task) but similar improvements in working memory compared with obese participants on a conventional LF diet.13 In the current study, the trajectory of change in speed of processing and working memory across time did not vary between participants assigned to the 2 diets over the long term. This finding is consistent with previous studies showing that short-term decrements in cognitive performance were not sustained in persons on an LC diet.12, 18 Together, the study results suggest that any decrements in cognitive performance following introduction to an LC diet are transient and short-lived.

Because it is well recognized that glucose is the brain's primary fuel55 and that hypoglycemia impairs cognitive function,56-57 it could have been hypothesized that the LC diet may have negatively affected cognitive performance relative to the LF diet. However, despite a restricted carbohydrate intake, the LC diet did not induce a hypoglycemic state, which is likely attributable to increased gluconeogenesis to maintain blood glucose levels, and after the intervention, participants in both groups had similar fasting plasma glucose levels that were within the normal range. Although it is not possible to measure local changes in brain glucose levels because the level of glucose in the blood reflects the level of glucose in the brain,58 maintenance of normal glucose levels may explain the lack of any difference in cognitive performance between the diets.

In the present study, the improvement in working memory, as assessed by DSB, that occurred after 8 weeks was sustained over 12 months in both diet groups. In contrast, previous studies have indicated that caloric restriction that leads to substantial weight loss has a minimal impact on cognitive performance, including working memory as assessed by DSB, in overweight and obese individuals.59-62 In the present study, because of the lack of a nondieting control group, improvements in working memory reflecting practice effects in both groups cannot be entirely dismissed. In contrast to the present findings, a recent study by Witte et al62 that did include a nondieting control group showed no change in a digit span task in overweight individuals after 3 months of energy restriction, suggesting that the improvements in DSB in the present study may not be explained by learning effects. However, the possibility cannot be dismissed that the differences in study duration (3 months vs 12 months) and the dietary regimens and delivery methods that were used also could have contributed to the discrepancies in the findings. Alternatively, Witte and colleagues demonstrated substantial improvements in episodic memory performance as assessed by a word-recall task after energy restriction, which was correlated with decreases in fasting plasma levels of insulin. We also observed a significant inverse correlation between the change in DSB (a measure of working memory) scores and the change in fasting plasma insulin levels; ie, the DSB scores increased with decreases in the plasma insulin levels. This association leads to the hypothesis that if episodic memory had been assessed in the present study, even greater improvements may have occurred compared with the study by Witte et al.62 These data also provide additional support to the postulated suggestion of improved memory after caloric restriction via improved insulin signaling in the brain.62 Further research is needed to examine the cause of the improvement in memory performance with dieting.

The current study focused on the assessment of 2 critical components of cognitive functioning: working memory and speed of processing. Although these 2 domains are fundamental components of cognition and measures that have demonstrated sensitivity to dietary change,63 they do not constitute a comprehensive battery for the assessment of cognition. For example, it is possible that aspects of cognition such as attention, short-term memory, long-term memory, and executive function might be influenced more by changes in the macronutrient content of a weight-loss diet. This potential limitation affects the confidence with which conclusions can be drawn regarding the long-term effects of LC and LF diets on cognitive function. Therefore, further studies should be undertaken to assess a greater range of cognitive domains. Moreover, the current results highlight the importance of future research that recognizes the role of practice in changing cognitive performance. Studies concerned with measuring intervention effects should undertake practice sessions until asymptotic levels of performance are achieved before randomization. Notwithstanding the increase in participant burden, it is important for future studies to perform repeated testing on a more frequent basis than was performed in our study to better characterize the time course of effects.

In conclusion, we found that despite similar weight loss after energy-restricted LC and LF diets for 12 months and rapid improvements in mood during the first 8 weeks with both diets, over the long term many of the benefits regressed in the LC diet group such that participants on the LF diet achieved better outcomes. However, there was no evidence that the dietary macronutrient composition of LC and LF diets affected cognitive functioning over the long term, as changes in cognitive function were similar for both diets. Further studies are required to evaluate the effects of these diets on a wider range of cognitive domains.


AUTHOR INFORMATION

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

Correspondence: Grant D. Brinkworth, PhD, Commonwealth Scientific and Industrial Research Organisation–Food and Nutritional Sciences, PO Box 10041, Adelaide, BC, South Australia 5000 (grant.brinkworth{at}csiro.au).

Accepted for Publication: July 23, 2009.

Author Contributions: Dr Brinkworth had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Brinkworth, Noakes, Clifton, and Wilson. Acquisition of data: Brinkworth. Analysis and interpretation of data: Brinkworth, Buckley, Noakes, Clifton, and Wilson. Drafting of the manuscript: Brinkworth and Buckley. Critical revision of the manuscript for important intellectual content: Brinkworth, Buckley, Noakes, Clifton, and Wilson. Statistical analysis: Brinkworth and Clifton. Obtained funding: Brinkworth, Buckley, and Noakes. Administrative, technical, and material support: Brinkworth, Buckley, Noakes, and Wilson. Study supervision: Brinkworth.

Financial Disclosure: None reported.

Funding/Support: This study was supported by project grants from the National Heart Foundation of Australia and the National Health and Medical Research Council of Australia. Simplot Australia, Mt Buffalo Hazelnuts Victoria, Webster Walnuts Victoria, Stahmann Farms Queensland, and Scalzo Food Industries Victoria donated foods for this study.

Role of the Sponsor: The funding agencies had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.

Additional Contributions: We gratefully acknowledge Kathryn Bastiaans, Julia Weaver, Anne McGuffin, and Vanessa Courage for coordinating this trial; Angela Halyburton, Belinda Wyld, and Emily Brindal for the collection of the mood and cognitive function data; Xenia Cleanthous, Julianne McKeough, and Gemma Williams for implementation of the dietary intervention; Rosemary McArthur and Lindy Lawson for nursing expertise; Julie Syrette for data management; and Kylie Lange for statistical advice.

Author Affiliations: Preventative Health National Research Flagship, Commonwealth Scientific and Industrial Research Organisation–Food and Nutritional Sciences (Drs Brinkworth, Noakes, Clifton, and Wilson), Nutritional Physiology Research Centre, Samson Institute for Health Research, University of South Australia (Dr Buckley), and Flinders Centre for Cancer Prevention and Control, School of Medicine, Flinders University (Dr Wilson), Adelaide, Australia.


REFERENCES

 Jump to Section
 •Top
 •Introduction
 •Methods
 •Results
 •Comment
 •Author information
 •References

1. Miller-Kovach K, Hermann M, Winick M. The psychological ramifications of weight management. J Womens Health Gend Based Med. 1999;8(4):477-482. ISI | PUBMED
2. Wadden TA, Vogt RA, Andersen RE; et al. Exercise in the treatment of obesity. J Consult Clin Psychol. 1997;65(2):269-277. FULL TEXT | ISI | PUBMED
3. Wing RR, Marcus MD, Blair EH, Burton LR. Psychological responses of obese type II diabetic subjects to very-low-calorie diet. Diabetes Care. 1991;14(7):596-599. ABSTRACT
4. Cummings S, Parham ES, Strain GW, American Dietetic Association. Position of the American Dietetic Association. J Am Diet Assoc. 2002;102(8):1145-1155. ISI | PUBMED
5. Jakicic JM, Clark K, Coleman E; et al, American College of Sports Medicine. American College of Sports Medicine position stand: appropriate intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc. 2001;33(12):2145-2156. ISI | PUBMED
6. Astrup A, Meinert Larsen T, Harper A. Atkins and other low-carbohydrate diets: hoax or an effective tool for weight loss? Lancet. 2004;364(9437):897-899. FULL TEXT | ISI | PUBMED
7. Foster GD, Wyatt HR, Hill JO; et al. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med. 2003;348(21):2082-2090. FREE FULL TEXT
8. Stern L, Iqbal N, Seshadri P; et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann Intern Med. 2004;140(10):778-785. FREE FULL TEXT
9. Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA. 2005;293(1):43-53. FREE FULL TEXT
10. Kogon MM, Krauchi K, Van der Velde P, Van der Werf H, Keller U. Psychological and metabolic effects of dietary carbohydrates and dexfenfluramine during a low-energy diet in obese women. Am J Clin Nutr. 1994;60(4):488-493. FREE FULL TEXT
11. Rosen JC, Hunt DA, Sims EA, Bogardus C. Comparison of carbohydrate-containing and carbohydrate-restricted hypocaloric diets in the treatment of obesity: effects of appetite and mood. Am J Clin Nutr. 1982;36(3):463-469. FREE FULL TEXT
12. D’Anci KE, Watts KL, Kanarek RB, Taylor HA. Low-carbohydrate weight-loss diets: effects on cognition and mood. Appetite. 2009;52(1):96-103. FULL TEXT | ISI | PUBMED
13. Halyburton AK, Brinkworth GD, Wilson CJ; et al. Low- and high-carbohydrate weight-loss diets have similar effects on mood but not cognitive performance. Am J Clin Nutr. 2007;86(3):580-587. FREE FULL TEXT
14. McClernon FJ, Yancy WS Jr, Eberstein JA, Atkins RC, Westman EC. The effects of a low-carbohydrate ketogenic diet and a low-fat diet on mood, hunger, and other self-reported symptoms. Obesity (Silver Spring). 2007;15(1):182-187. FULL TEXT | PUBMED
15. Zhao Q, Stafstrom CE, Fu DD, Hu Y, Holmes GL. Detrimental effects of the ketogenic diet on cognitive function in rats. Pediatr Res. 2004;55(3):498-506. FULL TEXT | ISI | PUBMED
16. Benton D, Owens DS, Parker PY. Blood glucose influences memory and attention in young adults. Neuropsychologia. 1994;32(5):595-607. FULL TEXT | ISI | PUBMED
17. Benton D, Brett V, Brain PF. Glucose improves attention and reaction to frustration in children. Biol Psychol. 1987;24(2):95-100. FULL TEXT | ISI | PUBMED
18. Wing RR, Vazquez JA, Ryan CM. Cognitive effects of ketogenic weight-reducing diets. Int J Obes Relat Metab Disord. 1995;19(11):811-816. ISI | PUBMED
19. Korol DL. Enhancing cognitive function across the life span. Ann N Y Acad Sci. 2002;959:167-179. ISI | PUBMED
20. Hoyland A, Lawton CL, Dye L. Acute effects of macronutrient manipulations on cognitive test performance in healthy young adults: a systematic research review. Neurosci Biobehav Rev. 2008;32(1):72-85. FULL TEXT | ISI | PUBMED
21. Hoyer S, Henneberg N, Knapp S, Lannert H, Martin ML. Brain glucose metabolism is controlled by amplification and desensitization of the neuronal insulin receptor. Ann N Y Acad Sci. 1996;777:374-379. ISI | PUBMED
22. Park CR. Cognitive effects of insulin in the central nervous system. Neurosci Biobehav Rev. 2001;25(4):311-323. FULL TEXT | ISI | PUBMED
23. Brinkworth GD, Noakes M, Buckley JD, Keogh JB, Clifton PM. Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo. Am J Clin Nutr. 2009;90(1):23-32. FREE FULL TEXT
24. Grundy SM, Cleeman JI, Daniels SR; et al. Diagnosis and management of the metabolic syndrome. Curr Opin Cardiol. 2006;21(1):1-6. ISI | PUBMED
25. McNair DM, Lorr M, Droppleman FF. Manual: Profile of Mood States. San Diego, CA: Eduational and Industrial Testing Service; 1971.
26. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:561-571. FREE FULL TEXT
27. Spielberger CD, Gorsuch RL, Lushene R, Vagg PR, Jacobs GA. Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press Inc; 1983.
28. Wecshler D. Wechsler Adult Intelligence Scale. 3rd ed. San Antonio, TX: Psychological Corporation and Harcourt Brace Jovanovich; 1997.
29. Petrill AA, Deary IJ. Inspection time and intelligence: celebrating 25 years of research. Intelligence. 2001;29(6):441-442. FULL TEXT | ISI
30. Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data. Stat Med. 1997;16(20):2349-2380. FULL TEXT | ISI | PUBMED
31. Gadbury GL, Coffey CS, Allison DB. Modern statistical methods for handling missing repeated measurements in obesity trial data: beyond LOCF. Obes Rev. 2003;4(3):175-184. FULL TEXT | PUBMED
32. Heyting A, Tolboom JT, Essers JG. Statistical handling of drop-outs in longitudinal clinical trials. Stat Med. 1992;11(16):2043-2061. ISI | PUBMED
33. Beck AT, Steer RA, Brown GK. Beck Depression Inventory Manual. 2nd ed. San Antonio, TX: Psychological Corp; 1996.
34. Pellegrin KL, O’Neil PM, Stellefson EJ; et al. Average daily nutrient intake and mood among obese women. Nutr Res. 1998;18(7):1103-1112. FULL TEXT | ISI
35. de Castro JM. Macronutrient relationships with meal patterns and mood in the spontaneous feeding behavior of humans. Physiol Behav. 1987;39(5):561-569. FULL TEXT | PUBMED
36. Muñoz MA, Fíto M, Marrugat J, Covas MI, Schröder H, REGICOR and HERMES investigators. Adherence to the Mediterranean diet is associated with better mental and physical health. Br J Nutr. 2009;101(12):1821-1827. FULL TEXT | ISI | PUBMED
37. Foster GD, Wadden TA. Social and psychological effects of weight loss. In: Brownell KD, Fairburn CG, eds. Eating Disorders and Obesity: A Comprehensive Handbook. New York, NY: Guliford Press; 1995:426-430.
38. Geliebter A, Maher MM, Gerace L, Gutin B, Heymsfield SB, Hashim SA. Effects of strength or aerobic training on body composition, resting metabolic rate, and peak oxygen consumption in obese dieting subjects. Am J Clin Nutr. 1997;66(3):557-563. FREE FULL TEXT
39. Wadden TA, Steen SN, Wingate BJ, Foster GD. Psychosocial consequences of weight reduction. Am J Clin Nutr. 1996;63(3)(suppl):461S-465S. PUBMED
40. Wing RR, Epstein LH, Marcus MD, Kupfer DJ. Mood changes in behavioral weight loss programs. J Psychosom Res. 1984;28(3):189-196. FULL TEXT | ISI | PUBMED
41. Norman GR, Sloan JA, Wyrwich KW. Interpretation of changes in health-related quality of life. Med Care. 2003;41(5):582-592. FULL TEXT | ISI | PUBMED
42. Cohen J. Statistical Power Analysis for the Behavioural Sciences. London, England: Academic Press; 1969.
43. Freedman MR, King J, Kennedy E. Popular diets: a scientific review. Obes Res. 2001;9(suppl 1):1S-40S. ISI
44. Atkins RC. Dr. Atkins' New Diet Revolution. New York, NY: Avon Books; 1998.
45. Wurtman RJ. Nutrients that modify brain function. Sci Am. 1982;246(4):50-59. ISI | PUBMED
46. Rouch C, Meile MJ, Gerozissis K. Persisting neural and endocrine modifications induced by a single fat meal. Cell Mol Neurobiol. 2005;25(6):995-1008. FULL TEXT | ISI | PUBMED
47. Benton D. Carbohydrate ingestion, blood glucose and mood. Neurosci Biobehav Rev. 2002;26(3):293-308. FULL TEXT | ISI | PUBMED
48. Ressler KJ, Nemeroff CB. Role of serotonergic and noradrenergic systems in the pathophysiology of depression and anxiety disorders. Depress Anxiety. 2000;12(suppl 1):2-19. FULL TEXT | ISI | PUBMED
49. Young SN. How to increase serotonin in the human brain without drugs. J Psychiatry Neurosci. 2007;32(6):394-399. ISI | PUBMED
50. Castrén E, Rantamäki T. Neurotrophins in depression and antidepressant effects. Novartis Found Symp. 2008;289:43-59, 87-93. FULL TEXT | PUBMED
51. Molteni R, Barnard RJ, Ying Z, Roberts CK, Gomez-Pinilla F. A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience. 2002;112(4):803-814. FULL TEXT | ISI | PUBMED
52. Schaaf MJ, Hoetelmans RW, de Kloet ER, Vreugdenhil E. Corticosterone regulates expression of BDNF and trkB but not NT-3 and trkC mRNA in the rat hippocampus. J Neurosci Res. 1997;48(4):334-341. FULL TEXT | ISI | PUBMED
53. Lindqvist A, Mohapel P, Bouter B; et al. High-fat diet impairs hippocampal neurogenesis in male rats. Eur J Neurol. 2006;13(12):1385-1388. FULL TEXT | ISI | PUBMED
54. Dye L, Lluch A, Blundell JE. Macronutrients and mental performance. Nutrition. 2000;16(10):1021-1034. FULL TEXT | ISI | PUBMED
55. Wenk GL. An hypothesis on the role of glucose in the mechanism of action of cognitive enhancers. Psychopharmacology (Berl). 1989;99(4):431-438. FULL TEXT | PUBMED
56. Brody S, Keller U, Degen L, Cox DJ, Schachinger H. Selective processing of food words during insulin-induced hypoglycemia in healthy humans. Psychopharmacology (Berl). 2004;173(1-2):217-220. FULL TEXT | PUBMED
57. Schächinger H, Cox D, Linder L, Brody S, Keller U. Cognitive and psychomotor function in hypoglycemia. Pharmacol Biochem Behav. 2003;75(4):915-920. FULL TEXT | ISI | PUBMED
58. Lund-Andersen H. Transport of glucose from blood to brain. Physiol Rev. 1979;59(2):305-352. FREE FULL TEXT
59. Kretsch MJ, Green MW, Fong AK, Elliman NA, Johnson HL. Cognitive effects of a long-term weight reducing diet. Int J Obes Relat Metab Disord. 1997;21(1):14-21. FULL TEXT | ISI | PUBMED
60. Martin CK, Anton SD, Han H; et al. Examination of cognitive function during six months of calorie restriction. Rejuvenation Res. 2007;10(2):179-190. FULL TEXT | ISI | PUBMED
61. Bryan J, Tiggemann M. The effect of weight-loss dieting on cognitive performance and psychological well-being in overweight women. Appetite. 2001;36(2):147-156. FULL TEXT | ISI | PUBMED
62. Witte AV, Fobker M, Gellner R, Knecht S, Floel A. Caloric restriction improves memory in elderly humans. Proc Natl Acad Sci U S A. 2009;106(4):1255-1260. FREE FULL TEXT
63. Osendarp SJ, Baghurst KI, Bryan J; et al, NEMO Study Group. Effect of a 12-mo micronutrient intervention on learning and memory in well-nourished and marginally nourished school-aged children. Am J Clin Nutr. 2007;86(4):1082-1093. FREE FULL TEXT


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter     What's this?

RELATED ARTICLE

In This Issue of Archives of Internal Medicine
Arch Intern Med. 2009;169(20):1828.
FULL TEXT  






HOME | CURRENT ISSUE | PAST ISSUES | TOPIC COLLECTIONS | CME | SUBMIT | SUBSCRIBE | HELP
CONDITIONS OF USE | PRIVACY POLICY | CONTACT US | SITE MAP
 
© 2009 American Medical Association. All Rights Reserved.