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Effect of Low-Fat and/or Low-Energy Diets on Anthropometric Measures in Participants of the Women’s Diet Study

Barbara Ann Karmanos Cancer Institute, Detroit, Michigan

Address correspondence to: Zora Djuric, PhD, Barbara Ann Karmanos Cancer Institute, 110 E. Warren, Detroit, MI 48201. E-mail: Djuricz{at}karmanos.org

	ABSTRACT

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
Objective: To compare the effects of low-fat, low-energy and combination low-fat/low-energy intervention on changes in six anthropometric measures in Caucasian and African-American free-living women.

Methods: The effects of dietary counseling strategies for fat and/or energy reduction were examined on anthropometric measures in 86 pre-menopausal women, average BMI of 28 kg/m², who participated in a 12-week intervention trial called the Women’s Diet Study. The dietary goals were 15% of energy from fat and/or 25% reduction in energy intake, relative to reported baseline intake, using a 2 x 2 factorial design. Analysis of covariance models were constructed to evaluate changes in anthropometric measures over the 12 weeks of study.

Results: The biggest difference by race was in women who were relatively heavier at baseline, in which case African-American women lost significantly less weight but decreased their waist:hip ratio to a significantly greater extent than Caucasian women. With regard to the effects of diet arm, weight loss varied depending on baseline weight, and in women with higher baseline weights, the combination low-fat/low-energy diet resulted in the most weight loss (6.7 kg, p < 0.05). Decreases in the other anthropometric measures at week 12 were more uniform across diet arms and did not depend on baseline values. After controlling for previous weight history and race, the decreases in BMI, percent body fat and waist circumference after 12 weeks were statistically equivalent with the low-fat, low-energy or combination low-fat/low-energy diets. The relatively greater decreases in percent body fat and waist circumference with the combination diet versus the low-fat or low-energy diets were not statistically significant.

Conclusion: The low-fat, low-energy and combination diets all resulted in similar and statistically significant decreases in BMI, percent body fat and waist circumference over 12 weeks of intervention. The extent of weight loss, however, varied depending on baseline weight, and the combination diet was the only intervention to result in significant weight loss for women who were heavier at baseline. This indicates that, although there may be an advantage for reducing dietary fat in initially heavier women, any of these counseling strategies could be effective for improving anthropometric predictors of health risks associated with overweight status. This is useful since flexibility in dietary choices may facilitate adherence to dietary counseling in some individuals.

Key words: diet, reducing, fat-restricted diet, anthropometry, body mass index, dietary intervention, analysis of covariance models

	INTRODUCTION

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
Overweight and obesity are increasing at an alarming rate and are major health risks in the United States and worldwide [1]. High-fat diets have been suggested to be one factor that can lead to obesity in free-living subjects [2]. Weight loss can be achieved with energy restriction, but there are indications that weight loss also can be achieved with low-fat diets and that low-fat diets are important for weight maintenance [2–8]. The importance of reducing dietary fat in a weight loss strategy, however, has been debated extensively in the literature [4]. A recent review of 16 studies utilizing low-fat interventions of at least two months duration in non-obese individuals showed a mean decrease in body weight of 2.55 kg [5]. At our own institution using the same low-fat intervention strategy used in the present work (goal of 15% of energy from fat), there was a weight loss of 3.4 kg over 12 months [9]. The present study had the advantage, however, of being able to compare the effects of counseling for reducing fat intake (to 15% of calories), reducing energy intake (by 25%) or reducing both fat and energy intake on anthropometric measures in women over 12 weeks [10].

In addition to the effects of different types of dietary counseling, we examined two other potentially important influential factors on changes in anthropometric measures: prior weight change history and race. Obese subjects who lose weight a second time after one previous cycle of gain and loss have been shown to lose weight at a relatively slower rate during the second cycle [11]. In rats, a history of weight cycling was shown to increase the rate of subsequent body weight gain [12], confirming the possible negative influence of prior weight cycling on body weight regulation. Race also can impact on the extent of weight loss. There have been a number of studies comparing weight loss interventions by race. Most of these studies indicated that weight loss can be achieved in African Americans, but typically the extent of weight loss observed in this population has been less than in Caucasians [13]. There is also a markedly higher prevalence of obesity in African American than Caucasian women in the United States [14]. This has been attributed to many potential factors: cultural, biological and socio-economic [15]. For example, African Americans have been shown to exhibit a relatively sustained desire for sweet taste [16] and to have lower resting metabolic rates than Caucasians both before and after weight loss [17, 18]. African American women also may have a higher threshold for considering themselves as overweight [19].

Here we report in detail on the changes in body weight and related anthropometric measures that were observed with low-fat and low-energy diets, either singly or in combination. The effects of prior weight change patterns were largely not significant, but we do show the significant influence of race. The six anthropometric measures were body weight, body mass index (BMI), percent body fat, waist circumference, hip circumference, and waist to hip (W:H) ratio.

	METHODS

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
Subjects
This study was approved by the Human Investigation Committee of Wayne State University, and subjects gave their signed, informed consent to participate. The dietary intervention was described previously [10]. Briefly, pre-menopausal women, 25 to 50 years of age and not taking oral contraceptives, were eligible. Extremely obese women (more than 50% above their optimal body weight) were excluded, but the body weight of each subject was at least 5.44 kg (12 lb.) above her optimal body weight. This latter eligibility criterion accommodated the 12 pound weight loss expected with the two low-energy diets. The mean BMI of subjects was 27.8 with a range of 22.3–33.9 kg/m². The women all indicated that they had stable body weight within 1.82 kg (4 lb.) for at least two months prior to randomization. Only women who completed 12 weeks of participation were utilized in this data analysis so that both beginning and ending anthropometric measures were available for all subjects. Of the 88 women who completed 12 weeks of participation (representing 78% of those randomized), one was excluded because she had nasal surgery before the last visit, which might have altered her lifestyle. Another was excluded because her self-reported racial status (mixed race) precluded her inclusion in the statistical analyses of racial effects. Subjects who had colds or other transient minor medical problems were included. There were thus 86 analysis-eligible subjects.

Prior to randomization and every four weeks thereafter, subjects were asked to keep four-day food records (Tuesday, Thursday, Friday and Sunday). Nutrient calculations were performed using the Nutrition Data System (NDS) software (University of Minnesota, Minneapolis, MN, Food Database Version 9A; Nutrient Database Version 24, Release Date January of 1995). At baseline, each eligible participant had a fat intake above 25% of total energy and energy intake above 1600 kcal/day. These four-day food records were reviewed in person together with each subject. The dietitians probed the subjects during this review for additional foods eaten and for methods of food preparation in an attempt to capture complete dietary intake data. After stratification by race (Caucasian or African American), subjects were randomized to one of the four diets: control, low-fat (with maintenance of energy intake), low-energy (with maintenance of percent energy from fat) and a combination of low-fat and low-energy.

Anthropometric Measures
Body weight was measured to the nearest quarter pound with a Health-o-Meter Professional Beam Scale, Model 402KLS (Bridgeview, Illinois). Height was measured without shoes while standing on a level, hard surface with a standard tape measure affixed to a wall. Hip and waist measures were obtained without restrictive garments to the nearest 0.1 cm with a flexible tape measure. Waist circumference was measured mid-point between the bottom rib and hip bone, taking care to keep the tape in contact with the curve of the back. Hip circumference was obtained at the widest point of the hip. Measurements of percent body fat were performed at baseline and at 12 weeks by tetrapolar bioelectrical impedance (Model BIA101S, RJL Systems, Clinton Township, MI) [20]. Subjects were instructed to fast overnight and to drink one glass of water in the morning before coming to the appointment. Women were asked to refrain from consumption of any other liquids before the measures were done.

Questionnaires
A baseline questionnaire was used to obtain demographic information, health status, physical activity patterns and weight history for the prior two years. This latter information was used to classify subjects into four prior weight change categories: stable, gain, loss and cycle. A weight increase or decrease of 2 kg or more was used to define a "gain" or a "loss," respectively. For the "cycle" category, a woman would have both lost and gained at least once in the previous two years. Recent weight changes, as opposed to those that occurred many years prior, might be envisioned to have a relatively greater effect on the response to the current diet. Our definition of "cycle" thus was limited to weight changes in the two years prior to randomization, and it was defined as at least one cycle of a gain followed by a loss or a loss followed by a gain. One such weight cycle may not be sufficient to elicit all the potentially adverse changes that have been observed in animals following multiple weight cycles noted in some, but not all, studies [12, 21, 22], and this is a potential limitation of our study. We could, however, compare subjects who did cycle at least once versus subjects who were of stable weight, lost weight or gained weight in the previous two years. Note, however, that all women reported stable weight within the two months prior to determination of eligibility.

Questions regarding current health, medication use and activity patterns of the subjects were asked at every biweekly visit. Physical activity was assessed from self-reports of the number of hours spent on different types of activities (sitting, standing, walking, sports etc.) at home and at work for the previous two weeks. Energy expenditure per week for the total of all activities (in METs) was calculated using standard values [23]. The ratio of energy expenditure reported at week 0 to week 12 was calculated and did not differ significantly in any diet arm (p > 0.18 in each case).

Intervention Diets
The low-fat diet goal was to consume 15% of total energy from fat, using dietary exchange goals to increase the percentage of energy from carbohydrates while keeping protein and energy intakes constant. The subjects in this group were instructed by registered dietitians to utilize food group exchange lists that were modified so that actual fat grams instead of fat exchanges were counted in an effort to more precisely control fat intake. Daily monitoring of intake in a booklet was required. The dietitians worked with all participants to help them incorporate their dietary goals into their lifestyles. The counseling required varied with each participant’s unique needs but often included help with food choices, food preparation and social support. Mean reported fat intake from four-day food records decreased by about half after 12 weeks of intervention (Table 1). Mean reported energy intake decreased very little from week 0 to week 12 (Table 1), but this was reported previously to be decreased more at intermediate time points [10].

The combination low-fat and low-energy diet had a goal of 15% energy from fat with a concomitant 25% reduction in energy. The diet was similar to the low-fat diet plan but carbohydrates were not increased to maintain baseline energy intake. Participants utilized both counting of fat grams together with the exchange list method.

Women in the non-intervention group followed their own, usual diet. Participants were counseled not to change their eating patterns while on study. These participants received a pamphlet outlining the U.S. Dietary Guidelines (which suggest a moderate fat intake). This group of women did not receive any behavior modification education on how to meet these recommendations.

Statistical Methods
Simple descriptive statistics were used to summarize the six anthropometric variables: body weight, BMI, percent body fat, waist circumference, hip circumference and W:H ratio. We found race and prior weight change category to be statistically associated with anthropometric variables for at least some subgroups of the study women. Accordingly, those two (fixed effect) classification factors were also controlled for (in addition to diet arm) in the analyses of anthropometric change from baseline to the end of the 12-week dietary intervention trial. Starting with body weight, we performed a three-factor (race, prior weight change category, diet arm) analysis of covariance (ANCOVA), with two continuous covariates (age at study entry and baseline body weight). After testing the goodness-of-fit of several ANCOVA models, we found that age was not an important covariate, and it was omitted. The ANCOVA approach then assessed the simultaneous effects of diet arm, prior weight change category and race upon mean week 12 body weight, after adjustment for baseline body weight as a covariate. In this way, treatment differences (e.g., by diet arm) in adjusted mean weight at week 12 correctly estimate change over time, after adjusting for differences in baseline weight. Inferences can then be made by focusing on the adjusted mean values of weight at week 12. The ANCOVA models were fit using PROC MIXED in SAS [24].

Due to sample size limitations, all two-way (but not three-way) interaction effects of the three classification variables were tested. Both linear and quadratic effects of baseline weight were included in the model. We therefore tested both equality of slopes and equality of curvatures across the levels of each classification variable and/or its interaction (i.e., cross-product) terms. The slope or curvature refers to the regression relationship of weight at week 12 versus baseline weight. If unequal slopes or curvatures were detected, the comparisons of adjusted mean weight at week 12 were made for low (5th percentile), intermediate (median) and high (95th percentile) initial body weight. Otherwise, when slopes and curvatures were not significantly different, comparisons of adjusted mean weight at week 12 were made at the mean value of initial body weight (any baseline weight would then yield the same results). When comparing adjusted mean week 12 weight values by levels of a classification factor (e.g., diet arm), we used the multiple comparisons procedure of Holm [25] to control the Type I error rate. A similar statistical analysis was conducted for each of the other five anthropometric variables.

	RESULTS

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
The women participating in this study for a full 12 weeks reported excellent compliance to their dietary goals, as shown in Table 1. Although self-reported intake is subject to under-reporting, these four-day food records were reviewed in person together with each subject in some detail. Reported energy intake at baseline (mean for all women combined) was a 8,196 kJ/day. This is above the estimated energy expenditure of 7,669 kJ/day required for a mean baseline body weight of 75.7 kg (using an estimate of 101 kJ/kg (or 11 kcal/pound) needed for weight maintenance in largely sedentary individuals [23, 26]).

Women reported reaching the energy restriction goal of 25% in the low-energy arm. The energy decrease was 27% in the combination arm, possibly indicating a small additional decrease in energy intake due to the concomitant decrease in fat intake. Women in the two low-fat arms reported an intake of 17% to 18% of energy from fat at 12 weeks. The fat intake goal was calculated in grams to constitute 15% of baseline energy intake. Since there was a small decrease in energy intake on the two low-fat diets (Table 1), women met their fat intake goal in grams while exceeding the fat intake goal expressed as percentage of energy. In the low-energy arm, the fat intake goal was a percentage of the energy, and when energy intake was decreased, there was a decrease in total fat intake for these women. This decrease was, however, smaller than for women in the low-fat and combination arms (Table 1). It was necessary to establish the fat intake goal as a constant percentage of energy since maintaining baseline grams of fat while decreasing energy intake by 25% might result in a nutritionally unbalanced diet that would be difficult to recommend. Nevertheless, the fat and energy intakes in the three intervention arms were quite different after intervention.

The baseline body weights of the women ranged from 59.5 to 102.3 kg (median 75; mean 75.7). The baseline anthropometric data are summarized by diet arm in Table 2 and by race in Table 3. Statistical relationships between race, prior weight change category, diet arm and each anthropometric variable were explored. The results by race and by diet arm are presented in the following two sections since differences by prior weight change category were not statistically significant. The week 12 anthropometric data are presented only as adjusted means (as described in Statistical Methods) for considerations of brevity in Table 4 and Fig. 1.

View larger version (15K): [in this window] [in a new window]   Fig. 1. Select anthropometric measures by race at week 12 as predicted from the ANCOVA model. Examples of predicted measures at 12 weeks are shown for hypothetical subjects who would fall in the 5th, 50th and 95th percentile of each measure at baseline. In A, body weight relationships among women in the prior stable weight category are shown after adjustment for diet arm and baseline weight. In B, waist circumference, adjusted for diet arm category and baseline waist circumference, is shown among women in the prior stable weight category. In C, the waist to hip ratio among women in the combination diet arm is shown after adjustment for prior weight change category and baseline W:H ratio. Starred values differ significantly by race (p < 0.05).

There were no statistical interactions of prior weight change category on the remaining three anthropometric measures. Of these measures, percent body fat did not differ significantly by race. Adjusted mean hip circumference at week 12 was significantly greater in African Americans than Caucasians, and this was independent of baseline hip size (not shown). For women on any of the three intervention diets, African Americans had lower week 12 W:H ratios than did Caucasians. This difference was statistically significant only if their baseline W:H ratio was high, and this is shown in Fig. 1C for women in the combination diet arm.

Effects of Diet Arm
The effects of diet arm assignment on select anthropometric measures after 12 weeks of intervention are shown in Table 4. The means were adjusted for the baseline levels of each respective anthropometric measure, as well as for prior weight change category and race. This modeling procedure accounted for any differences in these factors between diet arms that may have been present at randomization. In addition, adjustment for baseline levels allows for direct comparisons of means at 12 weeks to determine the effects the intervention (and/or race as described above) had on each measure. For example, the difference in week 12 mean BMI between women on the control arm and combination arm was 1.3 kg/m², which is then the loss in BMI that can be expected when women are given counseling for reducing both fat and energy intake over 12 weeks.

Women on any of the three intervention arms had significantly lower week 12 adjusted mean BMI, percent body fat and waist circumference than did women on the control diet arm, and there were no statistically significant differences among the intervention diets. Unlike decreases in those anthropometric measures, the ANCOVA results indicated that weight loss obtained depended on initial weight. Examples of weight loss that would be achieved for women in the 5th, 50th and 95th percentile of baseline weight are shown in Table 4. For women of intermediate initial weight, mean body weight was significantly decreased by all three dietary interventions. For women of high initial weight, however, only the combination low-fat/low-energy diet showed significantly lower adjusted mean weight at week 12 compared to control (a decrease of 6.7 kg), and in these women the combination diet also resulted in significantly greater weight reduction than the low-energy diet (Table 4).

Changes in hip circumference by diet arm varied depending on baseline measures as well. For women of intermediate baseline hip circumference, both the low-energy and the combination diets showed significant decreases in hip circumference at week 12 (means of 104.7 cm and 104.3 cm, respectively, for the 50th percentile of baseline hip circumference) as compared to women on the control diet (mean of 108.1 cm), with p < 0.05 for the difference in each case after applying the Holm multiple comparisons procedure. Hip circumference was decreased significantly more on the low-fat diet than on the combination diet for women with initially small baseline hip circumference. For women of high initial hip size (for example, 119.5 cm or the 95th percentile), none of the diets resulted in significant reductions in hip circumference at week 12. The only significant changes in W:H ratio occurred among African-American subjects: those on the combination diet arm had a significantly lower week 12 W:H ratio than did those on the control diet (data not shown).

	DISCUSSION

 
This was a 12-week study of changes in anthropometric measures with low-fat and/or low-energy diets used in the Women’s Diet Study. Since African-American women were well represented in this study, it was possible to examine the effects of race on changes in the anthropometric measures. At baseline, the African-American women were slightly heavier than the Caucasian women (Table 3), which is in accord with national data [27]. African-American women of prior stable weight also lost less weight and had higher BMI values after intervention than Caucasian women (Fig. 1A, Results). These racial differences agree well with the growing body of literature indicating that there may be biologic as well as cultural differences that result in relatively smaller weight losses in African-American women (for example [17, 28]).

Although the African American women lost less weight than the Caucasian women, this may not necessarily be related to worse health outcomes. African Americans with high BMI values exhibit relatively lower mortality rates than Caucasians with high BMI values [29]. In addition, the mean W:H ratio after intervention was smaller in African American women than in Caucasian women (Fig. 1C). A high W:H ratio has been shown to be a relatively better predictor of overall mortality from all causes than either high BMI or waist circumference in the Iowa Women’s Health Study [30]. This indicates a relatively smaller weight loss in African Americans may have similar health benefits as a larger weight loss in Caucasians.

With regard to the effects of diet arm, the ANCOVA models that were developed produced mean levels for each of the anthropometric measures at week 12 adjusted for race, prior weight change category and baseline values. These post-intervention means are given in Table 4, and since they are adjusted for baseline values they can be used to directly compare the effects diet arm assignment had on each outcome measure. The extent of weight loss obtained depended upon baseline weight, and the statistical models allowed us to calculate examples of weight loss that could be obtained for women in the 5th, 50th and 95th percentiles of baseline weight. Interestingly, all three dietary counseling strategies resulted in significant weight loss relative to control in women of intermediate baseline weight, and there were no significant differences in the extent of weight loss across any of the three diets. For women of high initial weight, however, only the combination diet resulted in statistically significant weight loss.

It has been suggested previously that reducing dietary fat appears to be relatively more important for weight reduction in obese individuals, with very little influence of dietary fat on weight loss in non-obese individuals [2, 4–8]. This is still a controversial issue, and there is evidence from studies in which fat and energy reduction were compared directly that energy intake may have a stronger effect on weight loss than fat reduction [31–36]. While this may well be true since energy intake alone will govern body mass from a physiological standpoint, it is possible that a low-fat eating pattern in free living subjects can help with regulation of energy intake. Overeating can be precipitated by many factors, among which high fat foods play an important role [37]. Conversely, satiety may be reached more quickly with less energy-dense foods [38]. The women who received counseling for a low-fat diet in this study did in fact report reduced energy intake despite the fact that the counseling included emphasis on maintenance of energy intake (Table 1). In animals, it appears that regulation of energy of intake is only effective with diets of lower fat contents. Energy intake and body weight gains were similar in rats consuming ad-libitum fed diets varying in fat content from 7% to 31% of energy, but when fat content of the diet was increased to 39% of energy from fat, significant increases in energy intake and body weight occurred over 20 weeks relative to animals fed the lower fat diets [39].

Another consideration in evaluating the effects of low-fat diets for weight loss is the energy content of dietary fat and carbohydrates. There is evidence that the Attwater values of 9 kcal/g for fat and 4 kcal/g for carbohydrate may not correspond to their metabolic energy yields. Based on body fat and protein deposition in young rats, metabolic energy yield was found to be greater than expected using graded levels of dietary fat or, conversely, lower than expected using graded levels of dietary carbohydrate [40]. Human metabolism may differ, but the possibility exists that seemingly iso-energetic substitution of carbohydrate for fat may in reality result in an energy deficit.

Unlike for weight loss, which varied with baseline weight, all three dietary counseling strategies used in this study resulted in significant reduction in BMI, percent body fat and waist circumference regardless of their respective baseline levels, and there were no significant differences between the results obtained with any of the diets (Table 4). Although most of the women in this study cannot be classified as obese, decreases in BMI and waist circumference are currently accepted as markers of the health effects of dietary change [41, 42]. Waist circumference in particular is thought to be a good indication of android fat distribution that is associated with adverse effects on insulin, hormone and lipid patterns, and breast cancer risk [43–45]. Waist circumferences greater than 80 cm are suggested to be indicative of cardiovascular risks [46]. Waist circumference also appears to be a better predictor of breast cancer risk than W:H ratio [47]. The decreases in waist circumference we observed thus indicate a possible beneficial effect of all three diets and especially the combination diet with a mean waist circumference of 80.6 cm after 12 weeks of intervention (Table 4). The higher waist circumference of African American women versus Caucasian at week 12 was only significant for a small subset of the women: those with low baseline waist circumference and stable body weight prior to joining the study (Fig. 1B).

In summary, these data show that similar decreases in BMI, waist circumference and percent body fat can be obtained over 12 weeks with either low-fat, low-energy or combination low-fat/low-energy counseling strategies. These observations were, however, obtained in a study of women no more than 50% over their optimal body weight and thus may not hold true in heavier women. Most post-intervention measures (with the notable exception of W:H ratio) were higher for African American women than for Caucasians. Over 12 weeks of intervention, however, the present data indicate that either a low-fat, low-energy or combination low-fat/low-energy diet was effective for reducing BMI, percent body fat and waist circumference in both African-American and Caucasian free-living women.

	ACKNOWLEDGMENTS

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
We thank all the women who participated in the Women’s Diet Study. We also thank Lilian Naegeli for helping the dietitians with the conduct of the study. This work was supported by NIH grant CA 60812 and Cancer Center Support grant CA 22453.

	FOOTNOTES

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 
Virginia E. Uhley, RD, PhD, is now at the University of Michigan Medical Center, General Clinical Research Center, Ann Arbor, Michigan.

Received July 25, 2001. Accepted November 27, 2001.

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TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS ACKNOWLEDGMENTS REFERENCES

 

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