Increasing Total Fiber Intake Reduces Risk of WeightandFatGainsinWomen 1,2

Transcription

1 The Journal of Nutrition Nutritional Epidemiology Increasing Total Fiber Intake Reduces Risk of WeightandFatGainsinWomen 1,2 Larry A. Tucker* and Kathryn S. Thomas Brigham Young University College of Health and Human Performance, Provo, UT Abstract Research investigating fiber intake and changes in weight over time has not controlled for important covariates, especially physical activity. Moreover, studies have rarely examined the influence of fiber on changes in body fat, only weight. Hence, this study was conducted to determine whether changes in fiber intake (total, soluble, and insoluble) influence risk of gaining weight and body fat over time. Another objective was to examine the influence of age, energy intake, activity, season, and other potential confounders. A prospective cohort design was used and 252 women completed baseline and follow-up assessments 20 mo apart. Diet was measured using 7-d weighed food records. Fiber was expressed per 1000 kcal (4187 kj). Body fat was assessed via the Bod Pod and physical activity was measured using accelerometers over 7 consecutive days. Across the 20 mo, almost 50% of the women gained weight and fat. For each 1 g increase in total fiber consumed, weight decreased by 0.25 kg (P ¼ ) and fat decreased by 0.25 percentage point (P ¼ ). Controlling for potential confounders did not affect the relationships, except changes in energy intake, which weakened the associations by 24 32%. Soluble and insoluble fibers were borderline predictors of changes in weight and fat. In conclusion, increasing dietary fiber significantly reduces the risk of gaining weight and fat in women, independent of several potential confounders, including physical activity, dietary fat intake, and others. Fiber s influence seems to occur primarily through reducing energy intake over time. J. Nutr. 139: , Introduction Over the past 40 y there has been a dramatic increase in the prevalence of overweight and obesity and these numbers are expected to continue to rise. Currently in the United States,.66% of adults are overweight or obese (1). For non-hispanic white females, prevalence is 64% (1). The prevalence is even higher among those aged $40 y, with.70% classified as overweight or obese (1). Compared with National Health Examination Survey I data collected in , the current prevalence of overweight and obesity represents an increase of ;40% in men and an increase of nearly 50% in women (2). Overweight and obesity increase the risk of a number of serious health problems. As body weight and body fat increase, disorders such as type 2 diabetes, cardiovascular disease, some cancers, musculoskeletal disorders, and many other deadly diseases become more prevalent (3,4). To date, most researchers agree that overweight and obesity are caused by numerous factors; however, a long-term energy imbalance between intake and expenditure appears to be the primary cause (5). Hence, limiting energy consumption is a key objective when weight loss is the goal. Over the years, much attention has been devoted to prescribing the optimal amount of food energy to achieve a healthy body weight. Some researchers 1 Supported by a grant from Brigham Young University, Provo, UT. 2 Author disclosures: L. A. Tucker and K. S. Thomas, no conflicts of interest. * To whom correspondence should be addressed. tucker@byu.edu. have looked even further and investigated the possibility that consuming certain dietary factors may aid in weight regulation. Fiber intake is a dietary factor that has received substantial attention. Reviews by several scientists (5 11) indicate that dietary fiber is inversely related to weight gain. Although a considerable amount of research has been conducted in this area, the literature still leaves some unanswered and important questions regarding the association between dietary fiber and body weight (7). Undoubtedly, more conclusive results could be obtained if research methodologies were improved. According to the literature, it is apparent that the vast majority of research investigating the fiber and weight gain relationship has relied on FFQ, 24-h recall, or 3-d food diaries to measure dietary intake. These measurement methods provide reasonable estimates, but an assessment strategy that does not require recollection of foods consumed in the past and that spans many days would likely be more representative of the typical diet (12). Perhaps of greatest concern is that in previous studies of fiber and weight gain, physical activity has rarely been controlled, yet physical activity accounts for a large portion of the energy balance equation. To understand weight change over time, physical activity must be measured. Objective measures of physical activity are best, because self-reported levels tend to include significant error (13). Furthermore, the role of fiber in body fat changes has not been explored thoroughly. Maintaining a healthy body weight over time is important. However, maintaining lean body mass while losing or limiting gains in fat mass should be emphasized /08 $8.00 ª 2009 American Society for Nutrition. 576 Manuscript received July 23, Initial review completed August 25, Revision accepted December 30, First published online January 21, 2009; doi: /jn

2 Very few studies evaluating the effects of fiber consumption have measured body fat in addition to body weight and fewer still have used accurate methods to assess body fat. Hence, the present study was conducted to determine the role of fiber consumption in the prevention of weight and fat gains over time using objective, high-quality tools of measurement. The current study focused on determining intake of dietary fiber and risk of gaining body weight and body fat over a 20-mo period in 252 women. Because fiber intake generally increases as total energy intake increases, individuals who eat larger quantities of food tend to consume larger quantities of fiber. In the present study, fiber consumption per 1000 kcal (4187 kj) was used to control for this situation. An auxiliary objective was to examine the degree to which age, dietary fat intake, season of assessment, energy intake, time between assessments, and objectively measured physical activity influence the association between fiber intake and changes in body weight and body fat over time. Materials and Methods Subjects. Cohort characteristics and subject recruitment have been reported previously (14,15). Recruitment via newspaper advertisements, flyers, and company mass s was conducted in 2 metropolitan areas in the Mountain West covering ;15 cities, including Salt Lake City and Provo, Utah, and surrounding cities. A telephone interview was performed with interested individuals to ensure that each potential participant fit baseline requirements. To negate the influence of illness, menopause, smoking, and pregnancy on weight change, only women free from serious disease who were premenopausal, nonsmokers, and not planning tobecome pregnant during the duration of the study were eligible. At baseline, participants consisted of an original cohort of 275 middleaged women. Mean age was 40.1 y, ;80% were married, 60% were employed at least part-time, and all but 1 woman had a high school diploma. Approximately one-half of the cohort reported attending school at a college or university at some point in their lives. Complete follow-up data were available for 252 women (i.e. 92% of the original cohort) 20 mo later. A written informed consent form, approved by the Brigham Young University Institutional Review Board, was signed by each woman before participating at baseline and again at the follow-up appointment. Measurements. In this study, energy intake, dietary fat intake, fiber intake, body weight, body fat percentage, physical activity, season of assessment, age, and time between assessments were measured. Laboratory measurements were made in the Human Performance Research Center at Brigham Young University. Testing protocols at baseline and follow-up were kept constant. Fiber, fat, and energy intake. Fiber intake, (i.e. total, soluble, and insoluble), fat consumption (i.e. percentage of energy from fat), and energy intake were measured by having women weigh and record everything they ate and drank over 7 consecutive days at baseline and follow-up. To control for the fact that fiber intake tends to increase as total food intake increases, fiber intake was calculated per 1000 kcal. Before beginning the 7-d food recording, women were educated regarding how to keep accurate diet records using sample food logs and a food scale. Plastic food models were employed to help teach each woman how to weigh foods and beverages. Women were also given printed instructions to take home and refer to. Additionally, the women were encouraged to not change their eating pattern during the 7 d of recording by eating less or by consuming healthier-appearing meals. Each woman was reminded that she should not gain or lose weight during the week of recording and that her body weight was being recorded before and after the week to ensure that she ate a normal, weight maintenance diet. Seven diet logs and a food scale (Ohaus 2000) were issued to each woman before leaving the laboratory. During the week, a research assistant called the women to answer questions. A registered dietician analyzed the diet records using ESHA Research software, version 7.6. which uses the USDA database and several dozen other food databases covering a tremendous variety of foods and beverages. There are several advantages to using 7-d weighed-diet records to assess diet compared with other methods. There is no dependence on women s memory of actual foods eaten or perception of portion sizes when using weighed-diet records (12). This is a tremendous benefit. Moreover, because eating patterns can differ from day to day, particularly between weekdays and weekends, 7-d diet records generally reflect typical dietary intake better than dietary assessment methods that focus on fewer than 7 d (12,16). The 7-d weighed-diet record method is not without weaknesses, however. Potential problems include the tendency of subjects to eat less than normal to reduce the work of weighing and recording the foods and beverages they consume. Likewise, some may consume less food during the 7 d to look good or to appear like a person who does not overeat. Besides the training and telephone call women received, those who did not report an mean energy intake of at least 130% of their resting metabolic rate, estimated using the Ravussin formula based on fat-free mass (17), were required to redo their diet records because of under-eating or under-reporting (18). Women who refused to repeat the procedure were dropped from the study. Additionally, immediately before and after the week of diet recording, women were weighed on an electronic scale (Tanita) to make sure that there was no significant weight change during the week of recording. Given the energy intake results of the present study, mean daily energy intake was ;2000 kcal/d (8375 kj/d); the precautions employed to prevent underreporting seemed to work. Body weight. Body weight was measured using a computer-based electronic scale that gives readings via a computer interface to the nearest kg (Tanita). Before data collection each day, the scale was calibrated using known weights. A test-retest evaluation of body weight using all of the women resulted in an intraclass correlation of (P, 0.001), showing extremely high reliability. Before their visit to the laboratory, women were asked to not eat for at least 3 h, although drinking water was permissible. Participants used the restroom to eliminate waste immediately prior to being weighed. Before weighing, women changed into a standard, light-weight nylon swim suit provided by the laboratory. To afford a more representative measurement of body weight, women were weighed a 2nd time 1 wk later in the same swimsuit, so the mean of the 2 assessments could be used to index body weight. After 20 mo of follow-up, the same procedure was followed again. Body fat percentage. Body fat percentage was measured objectively using air displacement plethysmography, the Bod Pod (Life Measurements Instruments). Body fat percentage was derived from body density by the Siri equation (19). Each woman was issued a one-piece swimsuit and a swim cap, and the Bod Pod was used to measure thoracic lung volume. Each day, the Bod Pod was calibrated with a cylinder of known volume. Body fat percentage was measured at least twice for each participant until 2 results were within 1 percentage point. These 2 results were then averaged. Several studies have shown the Bod Pod to be a reliable and valid method of measuring body composition. To ascertain the reliability of the Bod Pod, a test-retest protocol was used on 100 women in the present study. Between the 2 Bod Pod tests, the intraclass correlation was (P, ) (20). To determine the validity of the Bod Pod, dual energy X-ray absorptiometry (DEXA) (Hologic 4500W) was used to measure body fat percentage of these same 100 women. Between the 2 measures of body fat percentage, the Pearson correlation was 0.94 (P, 0.001) and the intraclass correlation was 0.97 (P, 0.001) (21). Additionally, Ballard et al. (22) compared the Bod Pod to the DEXA machine and found no significant difference when measuring body fat. They concluded that when measuring body fat in female athletes and nonathletes, the Bod Pod is a valid method. Maddalozzo et al. (23) also compared the Bod Pod to DEXA and derived similar conclusions. Physical activity. Objective measurement of physical activity was accomplished through the use of ActiGraph accelerometers (Health One Technology). At baseline, each woman was instructed regarding how to Fiber and weight gain 577

3 properly wear the monitor. A nylon belt was worn around the waist, to which the accelerometer was attached on the left side of the body. The monitor was worn at all times for 7 consecutive days and was removed only when bathing or participating in water activities. Women were required to repeat the testing week if the monitor was not worn properly. If noncompliance was a problem, the woman was dropped from the study. ActiGraph accelerometers (originally known as CSA accelerometers) have been shown to provide a reliable and objective measurement of physical activity during normal living conditions. NHANES has used the same accelerometers to measure physical activity in its participants. Further, in a study by Liu et al. (24), when compared with doubly labeled water, activity counts from the activity monitors appeared to closely represent the total amount of physical activity in free-living adults. In addition, research by Bassett et al. (25) revealed that of 4 accelerometers evaluated, this monitor was the only accelerometer that did not differ significantly from a portable metabolic system, and this activity monitor was correlated more significantly with energy expenditure (r. 0.90) measured by the metabolic system than were the other 3 accelerometers. Thus, the ActiGraph (CSA) accelerometer is a validated and reliable method of determining physical activity. In the present study, the accelerometers were programmed to sum the motion counts of each participant into 10-min epochs or intervals. Over the course of the 7 d of monitoring, each woman had a total of 1008 physical activity readings. Total physical activity was indexed by summing the 1008 activity counts for each woman. Season of assessment. Dietary intake and physical activity tend to vary according to the season of the year. Some foods are difficult to find in stores during some seasons and others are more plentiful. Likewise, during the winter months, some individuals get outside less and participate less in physical activity. Consequently, season of assessment was measured and controlled in the present study. Given the climate of the Mountain West, fall was defined as September, October, and November and winter included the months December, January, and February. Spring was defined as March, April, and May, and summer included the months June, July, and August. Time between assessments. The number of days between the baseline and follow-up assessments was not exactly the same for all women. Given that most adults tend to gain weight over time, more time between the assessments would tend to correspond to greater gains in body weight and fat. Hence, in the present study, the number of days between the baseline and follow-up assessments was calculated for each woman and controlled statistically to negate any influence on the results. Statistical analysis. Unless otherwise indicated, data are presented as means 6 SD. Changes in body weight, body fat percentage, dietary fat consumption, and fiber intake were calculated by subtracting baseline measurements from those taken at 20 mo. All fiber consumption results were presented as fiber intake (g)/1000 kcal (4187 kj). Using general linear models, regression analysis was used to determine the extent to which baseline fiber intake and changes in fiber intake, with total, soluble, and insoluble fiber consumption evaluated separately, were predictive of changes in body weight and body fat percentage. We used partial correlation to ascertain the effect of controlling for each of the potential confounding variables, considered individually and in combination, on the fiber and body composition associations. With and without adjusting for the potential confounders, regression coefficients, b, were generated for each relationship to add meaning and to aid in the interpretation of each statistical model. Pearson correlations were computed to show the extent of the linear relationships between changes in fiber intake and changes in each of the macronutrients. The extent to which each adjusted regression model differed significantly from the unadjusted model was also evaluated. Significance was set at 0.05 and SAS (version 9.1) was the software program used to analyze the data. Results Included in the 20-mo follow-up analysis were 252 (91.6%) of the original 275 baseline participants. Various reasons, including FIGURE 1 Number of women in each category reflecting the change in fiber intake (g) per 1000 kcal (4187 kj) from baseline to follow-up. The range of each category extends from the listed value to the next lower value, except for the 2 extremes. lack of interest, moving from the area, pregnancy, noncompliance, and a serious automobile accident, caused women to be dropped from the study. The time between baseline and followup assessments was d. Mean height at baseline was cm and weight was kg. BMI for the cohort was kg/m 2. Over the 20-mo period, there were significant changes in all of the key variables (Table 1). Body weight increased by kg and body fat increased by percentage point. Both changes were significant with considerable variation within the groups. Across the 20 mo, 29% of the women were weight stable, keeping their weight within 61 kg. From baseline to follow-up, 24% of the women lost.1 kg, 25% gained between 1 and 2.9 kg, 13% gained between 3 and 5 kg, and 8% gained.5 kg. In total, 47% of the sample gained.1 kg. Over the study period, mean total fiber intake increased by 0.6 g/1000 kcal (P ¼ ) (Fig. 1). Mean physical activity significantly decreased by over 150,000 counts per 7 d, or almost 23,000 counts per day over the 20 mo, an amount equivalent to ;6 7 min/d of walking. Soluble and insoluble fiber. Baseline soluble and insoluble fiber intakes were analyzed separately and neither was predictive of changes in body weight or body fat percentage. Across the 20-mo study period, changes in soluble fiber and insoluble fiber were less predictive of change in body fat percentage (F ¼ 1.8; P ¼ ; F ¼ 3.3; P ¼ , respectively) than change in body weight (F ¼ 3.0; P ¼ ; F ¼ 3.7; P ¼ , respectively). TABLE 1 Characteristics of the participating women at baseline and follow-up 1 Variable Baseline 1 Follow-up F P Weight, kg Body fat, % , Fiber intake, 2 g/1000 kcal Energy intake, kj/d , Physical activity, 3 counts/ Values are means 6 SD, n ¼ kcal ¼ kj 3 7-d accelerometer counts. 578 Tucker and Thomas

4 Baseline total fiber intake. Baseline total fiber intake was not predictive of changes over the 20-mo study in body weight (F ¼ 0.00; P ¼ ) or body fat percentage (F ¼ 0.35; P ¼ ). Statistical control of the potential confounding factors, considered individually and together, did not alter the nonsignificant findings. Change in total fiber intake and in body weight. Change in total fiber intake was predictive of change in body weight from baseline to 20-mo (Table 2). With none of the potential confounders controlled, the results showed that for each 1 g decrease in total fiber, 0.25 kg was gained over the 20 mo (P ¼ ). After adjusting for differences in baseline fiber consumption, the rate of weight gain was increased by 12% to 0.28 kg for each 1-g decrease in total fiber intake over the 20 mo. Controlling for differences in baseline age, body weight, energy intake, fat intake, and physical activity levels, as well as the season and time between assessments individually, did not significantly affect the fiberweight gain association. Similarly, adjusting for change in physical activity and change in fat intake individually over the study period did not affect the relationship (Table 2). Controlling for change in energy intake over the 20 mo significantly influenced the relationship between change in total fiber intake and change in body weight. Specifically, after adjusting for change in energy intake, the fiber-weight gain relationship was weakened by 32% (P ¼ 0.047). However, the relationship remained significant. After all the potentially confounding variables were controlled simultaneously, the relationship between change in total fiber intake and change in body weight was weakened but remained meaningful and significant (Table 2). Specifically, after adjusting for differences in all of the potential confounders simultaneously, for each 1-g decrease in total fiber intake, 0.20 kg was gained during the 20-mo study. Change in total fiber intake and change in body fat. With no variables controlled, the relationship between change in total fiber intake and change in body fat percentage over the 20-mo study period was significant (Table 3). Specifically, with each TABLE 2 Changes in women s body weight (kg) associated with each 1-g/1000 kcal change in fiber intake after adjusting for specific covariates over 20 mo 1 Variable controlled b 2 F P None Baseline fiber intake Baseline dietary fat intake Baseline body weight Baseline caloric intake Baseline physical activity Baseline age Season of assessment Time between assessments Changes in fat consumption Changes in energy intake Changes in physical activity All of the above kcal ¼ kj. 2 b ¼ regression coefficient. Values in the column showing regression coefficients (b) reflect changes in body weight for each 1-g increase in fiber intake over the 20 mo. 3 Controlling for the variable, changes in energy intake, weakened significantly the relationship between changes in total fiber intake and changes in body weight. None of the other potential confounders significantly affected the association. TABLE 3 reduction of 1 g of fiber, women tended to increase their body fat by 0.25 percentage point. Controlling statistically for the individual potential confounders, except changes in energy intake, had no meaningful effect on the relationship. However, controlling for changes in energy intake had a moderate effect on the relationship between change in total fiber intake and change in body fat percentage. The relationship was weakened by 24% but remained significant. When all of the potentially confounding variables were controlled statistically, the relationship between change in total fiber and change in body fat percentage was weakened but remained significant (Table 3). Specifically, after adjusting for all of the confounding variables together, for each reduction of 1 g of total fiber in the diet, body fat tended to increase by 0.19 percentage point over the 20-mo period. Change in fiber intake and change in macronutrients. Across the 20 mo, women who increased their relative total fiber intake also tended to increase their total carbohydrate consumption (r ¼ 0.30; P, ) and complex carbohydrate intake (r ¼ 0.18; P ¼ ) but not simple carbohydrate intake (r ¼ 0.02; P ¼ ). Also, those who increased their relative fiber consumption did not tend to change their protein intake (r ¼ 20.02; P ¼ ), but they tended to reduce the percent of energy they consumed from fat (r ¼ 20.32; P, ). Controlling statistically for changes in dietary fat consumption weakened the relationships between change in fiber intake and body weight and body fat change by ;12%, but the associations remained meaningful and significant. Discussion Changes in women s body fat percentage associated with each 1-g/1000 kcal change in fiber intake after adjusting for specific covariates over 20 mo 1 Variable controlled b 2 F P 3 None Baseline fiber intake Baseline dietary fat intake Baseline body fat Baseline caloric intake Baseline physical activity Baseline age Season of assessment Time between assessments Changes in fat consumption Changes in caloric intake Changes in physical activity All of the above kcal ¼ kj. 2 b ¼ regression coefficient. Values in the column showing regression coefficients (b) reflect changes in body fat percentage for each 1 g increase in fiber over the 20 mo. 3 None of the potential confounding factors significantly affected the relationship between fiber change and change in body fat percentage. The prevalence of overweight and obesity continues to increase in the United States as evidenced by national surveys (1,2). The cohort of 252 middle-aged women followed in the present study was no exception to this trend. Body weight increased by 0.7 kg (P ¼ ) and body fat increased by 1.0 percentage point (P, ) over the 20-mo investigation. Closer examination Fiber and weight gain 579

5 of the data, however, revealed great variation within the sample. In fact, almost 25% of the participants lost weight (.1 kg) over the course of the study and almost 50% gained weight (.1 kg) from baseline to follow-up. Thus, it is evident that although weight gain was the norm, not all women were at equal risk. Further analysis showed that women who decreased their total relative fiber intake actually tended to gain significantly more weight than their counterparts, whereas those whose total fiber intake increased over time actually tended to lose weight. The relationship was not only significant, but it was also meaningful. For each additional 1 g of fiber consumed per 1000 kcal from baseline to follow-up, participants tended to lose 0.25 kg, and for each 1 g decrease in total fiber intake, women gained 0.25 kg, on average. In short, a daily 8-g increase in total fiber per 1000 kcal was predictive of a 2-kg weight loss in 20 mo. The relationship between change in total fiber consumption and change in body weight was independent of several potential confounding factors. Age had no influence on the relationship, nor did season of assessment or time between assessments. Baseline fiber and fat intakes did not affect the relationship, nor did initial body weight of participants. Baseline activity level, whether participants were physically active or sedentary, and baseline energy intake similarly did not influence the fiber-weight gain relationship. Changes in physical activity and changes in fat intake over the 20 mo also did not influence the relationship. The same effects were seen with the potential confounders and the relationship between change in fiber consumption and change in body fat percentage. The only potential confounding factor that had a significant and meaningful influence on the relationship was change in energy intake. Controlling for change in energy intake did not eliminate the relationship between change in fiber intake and change in body weight, but it weakened it significantly. Post hoc analyses showed why controlling for change in energy intake had such a strong effect. Specifically, change in energy intake was predictive of change in body weight (r ¼ 0.32; P, ) and body fat percentage (r ¼ 0.28; P, ), and change in fiber intake was predictive of change in energy intake (r ¼ 20.17; P ¼ 0.007). In short, as fiber intake increased, energy intake decreased and body weight and body fat decreased as well. Why? Because fiber adds to food weight and volume without increasing energy consumption. Thus, more food can be eaten without a commensurate increase in energy intake, or the same total volume of food can be consumed with less total energy. The results of this study agree with the results of other prospective studies. Liu et al. (26), in conjunction with the Nurses Health Study, used a FFQ to assess the dietary habits of their large cohort. Results indicated that women whose consumption of fiber increased the most over the 12-y period gained less weight than their counterparts. Additionally, Ludwig et al. (27), using data from the CARDIA study, found that weight gain over a 10-y period was more strongly predicted by consumption of fiber than by fat consumption. Furthermore, Newby et al. (28) and Koh-Banerjee et al. (29) saw similar results in their prospective cohort studies. Although there is substantial research supporting the inverse relationship between fiber intake and changes in body weight, some contradictory results have been published. In experimental studies by Baron et al. (30) and Thompson et al. (31), the efficacy of fiber for weight loss was not established. Moreover, the relationship between fiber intake and change in body fat has been studied minimally. The present study adds important validation to the protective role that fiber intake can play against gains in weight and body fat. The majority of previous studies have relied on estimation of serving sizes and recall of past meals, whereas 2 7-d weighed-diet records, used in the present study, provided high-quality measurement of dietary intake. Additionally, very few studies have controlled for physical activity and in those that have, crude techniques such as self-reported questionnaires have been employed. In the current study, objective measurement of physical activity via accelerometers allowed for precise control of physical activity. Lastly, the vast majority of studies interested in the effects of fiber consumption have focused on gains in body weight and ignored changes in body fat. The present study included measurement of body fat percentage using the Bod Pod as well as precise measurement of body weight. In this study, some participants changed their fiber intake from baseline to follow-up, although there was no intervention. As is typically the case with dietary modifications, the fiber changes did not occur in isolation. Women who increased their fiber intake also tended to increase the percentage of energy derived from total carbohydrate, particularly complex carbohydrate. Energy intake from simple carbohydrates did not change with the fiber change, however. It appears that women increased their fiber consumption by eating more foods such as whole grains and other complex carbohydrates, possibly beans, whereas simple carbohydrates and foods such as refined flours and processed treats were not related to changes in fiber. Like simple carbohydrates, the percent of energy derived from protein was not linked to changes in fiber. However, women who increased their fiber intake also tended to decrease significantly the percent of energy they consumed from dietary fat. Further, as relative fiber consumption increased, energy intake decreased. In short, women who increased their fiber intake also tended to eat fewer foods with spreads, gravies, full-fat dairy, oil, and other high-fat ingredients, as well as fewer foods high in energy content. However, controlling statistically for differences in baseline dietary fat intake and for changes in fat consumption during the study did not significantly influence the association between fiber intake and risk of weight gain. Overall, it appears that women who increased their relative fiber intake over time tended to eat more healthfully, consuming more complex carbohydrates and fewer high-fat and high-energy foods. The current study was not without limitations. Due to the demographics of the area, the cohort was fairly homogeneous. Almost all of the participants were Caucasian and most were educated. In addition, although 20 mo is not a short duration, a longer study period would have allowed time for greater differences among those who increased their fiber consumption and those who decreased their intake. Further, although 2 7-d weighed food records represent an excellent method of dietary evaluation, this strategy still involves self-report. Self-report by nature introduces error. Additionally, use of the 7-d food record method, rather than a FFQ, prohibited reporting of the individual foods that women ate or stopped eating that resulted in changes in their fiber intakes. Due to the prospective cohort design of this study, cause and effect conclusions are not warranted. It would not be appropriate to conclude that decreases in fiber consumption cause weight gain. However, it would be correct to conclude that decreases in fiber intake increase the risk of weight gain in women. Hence, it would be wise to encourage most women to increase their fiber intake without increasing their energy intake, thus making it easier to lose weight or at least to slow the rate of weight gain. The current recommendation for fiber intake in the United States, according to the official Dietary Guidelines for Americans, 2005, is that 14 g of dietary fiber be consumed per Tucker and Thomas

6 kcal (32). The mean intake in the US is far below the recommended level, which is true of this cohort as well. Yet, it is important to note that benefits were observed in the present study by those who increased their consumption of fiber over the 20-mo period, regardless of their baseline fiber intake. Hence, a major objective of nutrition education should be to highlight and promote fiber-rich foods in the diet. Emphasis should be placed on eating whole-plant foods, such as vegetables, whole grains, fruits, and legumes. In conclusion, obesity is a serious epidemic in the United States and other westernized societies. Americans continue to get heavier each year and, as a group, the middle-aged women in the current investigation followed the same trend. It was evidenced however, that although mean body weight increased significantly, variation was substantial within the cohort. Analysis revealed that women who decreased their fiber intake over the nearly 2-y study were at much greater risk of weight gain compared with their counterparts. The converse was also true; i.e. women who increased their fiber intake over time actually increased their likelihood of losing weight. Given these findings, it would be wise to encourage greater fiber consumption to promote more effective weight management among middle-aged women. Literature Cited 1. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, JAMA. 2006;295: Ruhm CJ. Current and future prevalence of obesity and severe obesity in the United States. National Bureau of Economic Research, Working Paper No , Available from: w Pi-Sunyer FX. The obesity epidemic: pathophysiology and consequences of obesity. Obes Res. 2002;10 Suppl 2:S Li Z, Bowerman S, Heber D. Health ramifications of the obesity epidemic. Surg Clin North Am. 2005;85: Burton-Freeman B. Dietary composition and obesity: do we need to look beyond dietary fat? J Nutr. 2000;130:S Howarth NC, Saltzman E, Roberts S. Dietary fiber and weight regulation. Nutr Rev. 2001;59: Slavin JL. Dietary fiber and body weight. Nutrition. 2005;21: Schulz M, Nothlings U, Hoffman K, Bergmann MM, Boeing H. Identification of a food pattern characterized by high-fiber and low-fat food choices associated with low prospective weight change in the EPIC-Potsdam cohort. J Nutr. 2005;135: Pereira MA, Ludwig DS. Dietary fiber and body-weight regulation. Observations and mechanisms. Pediatr Clin North Am. 2001;48: Roberts SB, McCrory MA, Saltzman E. The influence of dietary composition on energy intake and body weight. J Am Coll Nutr. 2002;21:S Lara-Castro C, Garvey WT. Diet, insulin resistance, and obesity: zoning in on data for Atkins dieters living in South Beach. J Clin Endocrinol Metab. 2004;89: Buzzard M. 24-hour dietary recall and food record methods. In: Willett W, editor. Nutritional epidemiology. 2nd ed. New York: Oxford University Press; p Epstein LH, Paluch RA, Coleman KJ, Vito D, Anderson K. Determinants of physical activity in obese children assessed by accelerometer and self-report. Med Sci Sports Exerc. 1996;28: LeCheminant JD, Tucker LA, Bailey BW, Peterson TR. The relationship between intensity of physical activity and HDL cholesterol in 272 women. J Phys Act Health. 2005;2: Bailey BW, Tucker LA, Peterson TR, LeCheminant JD. A prospective study of physical activity intensity and change in adiposity in middleaged women. Am J Health Promot. 2007;21: Hartman AM, Brown CC, Palmgren J, Pietinen P, Verkasalo M, Myer D, Virtamo J. Variability in nutrient and food intakes among older middle-aged men. Implications for design of epidemiologic and validation studies using food recording. Am J Epidemiol. 1990;132: Ravussin E, Bogardus C. Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization. Am J Clin Nutr. 1989;49: Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, Prentice AM. Critical evaluation of energy intake data using fundamental principles of energy physiology. 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr. 1991;45: Siri W. Body composition from fluid spaces and density: analysis of methods. In: Brozek J, Henshel A, editors. Techniques for measuring body composition. Washington DC: National Academy of Sciences; p Bailey BW, Tucker LA, Peterson TR, LeCheminant JD. Test-retest reliability of body fat percentage results using dual energy x-ray absorptiometry and the Bod Pod. Med Sci Sports Exerc. 2001;33:S LeCheminant JD, Tucker LA, Peterson TR, Bailey BW. Differences in body fat percentage measured using dual energy x-ray absorptiometry and the Bod Pod in 100 women. Med Sci Sports Exerc. 2001;33:S Ballard TP, Fafara L, Vukovich MD. Comparison of BOD POD and DXA in female collegiate athletes. Med Sci Sports Exerc. 2004;36: Maddalozzo GF, Cardinal BJ, Snow CA. Concurrent validity of the BOD POD and dual energy X-ray absorptiometry techniques for assessing body composition in young women. J Am Diet Assoc. 2002;102: Liu AL, Li YP, Song J, Pan H, Han XM, Ma GS. Study on the validation of the Computer Science Application s activity monitor in assessing physical activity among adults using doubly labeled water method. Zhonghua Liu Xing Bing Xue Za Zhi. 2005;26: Bassett D, Ainsworth B, Swartz A, Strath S, O Brien W, King G. Validity of 4 motion sensors in measuring physical activity. Med Sci Sports Exerc. 2000;32 Suppl 5:S Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women. Am J Clin Nutr. 2003;78: Ludwig DS, Pereira MA, Kroenke CH, Hilner JE, Van Horn L, Slattery ML, Jacobs DR Jr. Dietary fiber, weight gain, and cardiovascular disease risk factors in young adults. JAMA. 1999;282: Newby PK, Muller D, Hallfrisch J, Andres R, Tucker KL. Food patterns measured by factor analysis and anthropometric changes in adults. Am J Clin Nutr. 2004;80: Koh-Banerjee P, Franz M, Sampson L, Liu S, Jacobs DR Jr, Spiegelman D, Willett W, Rimm E. Changes in whole-grain, bran, and cereal fiber consumption in relation to 8-y weight gain among men. Am J Clin Nutr. 2004;80: Baron JA, Schori A, Crow B, Carter R, Mann JI. A randomized controlled trial of low carbohydrate and low fat/high fiber diets for weight loss. Am J Public Health. 1986;76: Thompson WG, Rostad Holdman N, Janzow DJ, Slezak JM, Morris KL, Zemel MB. Effect of energy-reduced diets high in dairy products and fiber on weight loss in obese adults. Obes Res. 2005;13: U.S. Department of Health and Human Services and USDA. Dietary guidelines for Americans, th ed. Washington, DC: U.S. Government Printing Office; Fiber and weight gain 581