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Feeding behaviors and weight loss outcomes over 64 months
Eating Behaviors 3 (2002) 191 – 204
Feeding behaviors and weight loss outcomes over 64 months Richard D. Mattes* Department of Foods and Nutrition, Purdue University, 212 Stone Hall, West Lafayette, IN 47907-1264, USA
Abstract Maintenance of reduced body weight following intentional weight loss is often unsuccessful. Identification of behaviors associated with sustained reductions should aid in dietary weight management. This survey assessed associations between an array of appetitive indices and weight loss outcomes in a sample of 80 adults participating in an open-labeled, unsupervised weight management program over a 64-month period. Participants were divided into maintainers (weight loss > 5 kg at Year 1, sustained reduction >75% at Month 64), rebounders (weight loss >5 kg at Year 1, < 75% reduction at Month 64), and nonresponders (weight loss < 5 kg at Year 1). Nonresponders spent significantly more time shopping for food weekly, tended to have the highest total exposure time to food and to eat with fewer people than the other groups. Maintainers reported higher mean hunger over the course of a day, tended to spend more time preparing food and consumed less energy from fat and foods that they rated as predominantly bitter. Rebounders had significantly lower dietary restraint scores and tended to have less control over the purchase and preparation of foods in their diet. Individuals with different long-term weight loss outcomes possess distinct feeding-related attributes that may provide a basis for improved intervention strategies. D 2002 Elsevier Science Ltd. All rights reserved. Keywords: Human; Diet; Obesity; Feeding; Food; Restraint
1. Introduction There is widespread concern about the health and/or cosmetic implications of overweight. Approximately 40% of females and 25% of males are on a weight reduction diet at any given
* Tel.: +1-765-494-0662; fax: +1-765-494-0674. E-mail address: [email protected] (R.D. Mattes). 1471-0153/02/$ – see front matter D 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 4 7 1 - 0 1 5 3 ( 0 1 ) 0 0 0 5 9 - 9
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point in time (Allison, Fontaine, Heshka, Mentore, & Heymsfield, 2001). Over US$33 billion dollars are spent annually on diet foods, aids, and programs, and this figure is growing rapidly (Larkin, 1996). Despite this high level of concern, the prevalence of overweight and obesity (body mass index, BMI>25) has increased dramatically over the past two decades so that approximately 55% of the population 20 years of age or older can now be so classified (Flegal, Carroll, Kuczmarski, & Johnson, 1998). The health care costs attendant to obesity are estimated at over US$100 billion annually due to the contribution of excess body fat to chronic diseases such as hypertension, heart disease, diabetes, and osteoarthritis (Thompson, Edelsberg, Colditz, Bird, & Oster, 1999). Annual preventable deaths from obesity in the total population are approximately 280,000 (Allison, Fontaine, Manson, Stevens, & VanItallie, 1999), and the toll on productivity and quality of life are also high. Dietary approaches to treat obesity have been largely unsuccessful as defined by sustained reduction of body weight (Fletcher et al., 1993). Widely cited reports indicate that only about 5% of individuals using self-induced behavioral methods to decrease body weight achieve lasting reductions (Brownell & Rodin, 1994; Fletcher et al., 1993; Kramer, Jeffrey, & Forster, 1989). Others have argued that this value is erroneously low (Lowe, Miller-Kovach, & Phelan, 2001), but they still acknowledge that maintenance is problematic. This has prompted criticism of approaches based on adherence to hypocaloric diets (Kratina, King, & Hayes, 1996; Polivy, 1996). Alternatively, a view that the criteria for successful obesity management should be reconsidered (Atkinson, 1993; Rossner, 1997), given that even small reductions of body weight, achievable through diet modification, hold clinical benefit (Goldstein, 1992; Williamson, 1997), has emerged. One explanation for the difficulty in maintaining weight loss in many individuals may stem from a failure to recognize the multiple etiologies of obesity (Bray, 1989) and need to individualize therapeutic approaches. Just as there are marked individual differences in blood pressure responses to dietary restriction of sodium (Weinberger, Miller, Luft, Grim, & Fineberg, 1986) or serum lipid profiles to reduction of dietary fat (Schaefer et al., 1997), there may be individual variability in response to limiting dietary energy (Goldstein, 1992). To explore this hypothesis requires classification of individuals according to body weight changes to a given challenge and characterization of their relevant attributes. Recent reports on predictive indices for weight loss have begun to provide the needed data (Bild et al., 1996; Coakley, Rimm, Colditz, Kawachi, & Willett, 1998; French et al., 1994; Klem, Wing, McGuire, Seagle, & Hill, 1997; Parham, 1988; Westerterp-Plantenga, Kempen, & Saris, 1998). They have focused primarily on indices of pretreatment body weight or composition, prior history of dieting, emotional status, and physical activity. There has been limited exploration of eating-related attributes such as hunger, affective responses to foods, and meal patterns. The present exploratory study assessed the associations between weight loss outcomes and an array of dietary, behavioral, psychological, and physiological indices with the aim of identifying predictive indices for sustained weight loss that may aid in the design and targeting of dietary intervention approaches. Specifically, information was collected on the time spent in food acquisition, preparation, and consumption as a reflection of preoccupation with eating; control over the purchase and preparation of foods as an index of dietary control;
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the number of eating partners given evidence of a positive association between this variable and total energy intake (DeCastro, Brewer, Elmore, & Orozco, 1990); level of concern about ingestion of specific dietary components and health as a measure of dietary motivation (Harris, 1983; Ortega et al., 1996); body weight status of close friends to assess peer pressures (Harris, 1983); cognitive restraint, disinhibition, and hunger because of their associations with dietary compliance and weight loss maintenance (Keim, Canty, Barbieri, & Wu, 1996; Ogden, 1994; Stunkard & Wadden, 1990; Westerterp-Plantenga et al., 1998); neophobia and variety seeking as they may influence food seeking and avoidance behaviors (Hursti & Sjoden, 1997; Pliner & Hobden, 1992; Van Trijp, Lahteenmaki, & Tuorila, 1992); stress because of its reported association with energy intake and weight (Istvan, Zavela, & Weidner, 1992; Mitchell & Epstein, 1996); diet composition as relative proportions of macronutrients and fiber content have been linked with hunger, satiety, energy balance, and body weight (Blundell & Macdiarmid, 1997; Mattes, 1996; Nelson & Tucker, 1996; Pasman, WesterterpPlantenga, & Saris, 1997; Reid & Hetherington, 1997; Tiwary, Ward, & Jackson, 1997; Warwick, Hall, Pappas, & Schiffman, 1993); hunger sensations since they are widely purported cues for meal initiation (DeCastro & Elmore, 1988); energy intake and expenditure because the balance between these measures will determine body weight and, finally, selected baseline characteristics such as age, gender, weight, and BMI that have been previously linked to diet outcomes (Bild et al., 1996; Dwyer et al., 1998).
2. Methods 2.1. Protocol All individuals participating in a long-term weight loss program were sent a packet of eight questionnaires and instructions on how they should be completed and returned. One followup call requesting the completed forms be mailed to the investigators was made if they were not received promptly. 2.2. Subjects One hundred and four of the 158 (66%) individuals from Pound or Coleman, WI who participated in an Ultra Slim-Fast diet program completed the questionnaires. Twenty-four were excluded due to the presence of health conditions at some point in the 64-month study period that could have influenced diet and energy balance (e.g., cancer, thyroid disease, pregnancy). Thus, the study population was comprised of 80 dieters—27 males and 53 females with a mean ± S.D. age of 42.6 ± 10.4 years. Their mean ± S.D. baseline BMI was 31.6 ± 5.0 kg/m2. All were Caucasian. Dieters from the original cohort not included in this analysis included 23 males and 55 females with a mean BMI of 31.7 ± 6.4 kg/m2 (both indices comparable to the study sample). The two groups also had similar changes of body weight from baseline at Years 1, 2, 3, 4, and 5. The nonparticipating subsample was slightly younger with a mean age of 36.7 ± 10.4 years ( P < .01).
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2.3. Diet program At entry, participants completed a health questionnaire and obtained medical clearance from their physician. The weight loss phase of the plan involved daily substitution of 8-oz servings of Ultra Slim-Fast for two meals and consumption of one 250–500-kcal meal plus three optional Ultra Slim-Fast snacks. Total daily energy intake was approximately 1130–1190 kcal. For weight maintenance, only one meal was replaced with the product. If a weight gain of 2–3 lb was observed during maintenance, participants were instructed to return to the weight loss plan until the desired weight was again reached. The meal substitute was provided in a variety of flavors. One serving of each contained 200–220 kcal, 11–14 g protein, 36–38 g carbohydrate, 1–4 g fat, and 4–5 g fiber (when reconstituted with nonfat milk). The snacks included, bars, popcorn, caramel corn, pretzels, cheese curls, and chocolate pudding. Participants were unsupervised but were weighed weekly for 12 weeks and twice per year between July of 1992 and November of 1997. After Year 2, the only products supplied to participants were snack bars and meal replacement bars and formula. Data for this analysis were obtained at baseline and Months 12, 24, 38, 48, and 64. Participants were provided the study products at no charge through a local supermarket. They were requested to refrain from use of medications or products for weight loss. 2.4. Questionnaires Health and demographic information (nonstandardized questionnaire), stress (Brantley, Dietz, McKnight, Jones, & Tulley, 1988), variety seeking (Van Trijp et al., 1992), food and general neophobia (Pliner & Hobden, 1992), cognitive restraint, disinhibition, and hunger (Stunkard & Messick 1985), physical activity (MONICA Optional Study of Physical Activity—MOSPA (Pereira et al., 1997), hunger sensations (nine-point category scales, 1 = not at all, 9 = extremely), as well as frequency and preferred frequency of food use (items included represented the foods contributing 90% of the energy, protein, fat, and carbohydrate in the US diet as reported by Block, Dresser, Hartman, & Carroll, 1985 using HANES II data). 2.5. Dietary record Following provision of materials to assist in estimation of sample size, participants kept a 24-h diet record. The records were coded using version 6.01 of the Genesis Nutrient Database (ESHA Research, Salem, OR) supplemented with additional data from commercial food establishments. 2.6. Statistical analyses The primary dependent variable was the percent of the initial loss of body weight maintained at the end of the 64-month study period. No significant age or sex effects were observed on this treatment outcome so data from these variables were pooled for all
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analyses. To identify personal attributes associated with treatment outcome, dietary success was defined as an initial weight loss (baseline minus weight at Year 1) of >5 kg and maintenance of at least 75% of the initial loss 64 months later. Participants meeting this criterion were classified as maintainers. Participants who achieved the requisite initial weight loss, but did not maintain the stipulated level of reduction were termed rebounders. Individuals who did not weigh at least 5 kg less at the 1-year weigh-in were considered nonresponders. Analysis of variance was used to explore differences between these groups on variables with continuous distributions. Where appropriate, the Tukey HSD test was used for post hoc analyses. Crosstabulation was used to explore associations with categorical variables. To explore the incidence of weight cycling, a cycle was defined by a reversal of body weight trend that exceeded 10% of the previous years body weight and an individual was viewed as cycling if they experienced three cycles over the 64-month period. The criterion for statistical significance was P < .05. Probability values .05 and .10 are reported as trends. Data were analyzed with the Statistical Package for the Social Sciences (SPSS, 1996).
3. Results 3.1. Dietary response In the full sample, the mean weight loss at 12 months was 8.72 ± 0.50 kg. Ninety percent of the participants weighed at least 5 kg less at 12 months than at baseline. The mean reduction at Month 64 was 5.21 ± 0.78 kg. Of those losing at least 5 kg during the initial 12 months, 47.2% maintained at least 75% of the reduction at Month 64. Fig. 1 shows the weight reduction responses of the nonresponder, rebounder, and maintainer groups over the study period. At the 12-month weigh-in, the rebounders and maintainers had lost a comparable amount of weight and significantly more than the nonresponders [ F(2,79) = 13.55, P < .001]. The difference between nonresponders and maintainers remained significant ( P = .011) at Month 24, but the rebounders were not different from either of the other groups. By Month 38, the rebounders had regained sufficient weight that they differed significantly from the maintainers ( P = .006), but not from the nonresponders. The maintainers continued to differ from the nonresponders ( P = .001). This pattern held for weigh-ins at 48 and 64 months. The mean ± S.E. percent reductions of body weight at the 12-month weigh-in for the nonresponders, rebounders, and maintainers were 1.05 ± 0.44%, 5.08 ± 0.38%, and 4.60 ± 0.26%, respectively. There was a significant group difference [ F(2,79) = 14.25, P < .001] wherein nonresponders lost a significantly smaller percent than the other groups. The rebounders and maintainers had similar percent reductions. The percent of this initial loss maintained by the three groups did not differ at 24 months, but at all subsequent weigh-ins, the rebounders had significantly smaller percent reductions (mean range = 22–47%) than the other groups (mean ranges = 103–133%) (all P < .05). These varying response patterns resulted in significant differences in body weight and BMI between the groups at Month 64. Maintainers weighed significantly less than nonresponders, 77.9 ± 3.2 vs. 96.5 ± 10.0 kg ( P = .025). The mean
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Fig. 1. Mean (S.E.) change of body weight for nonresponders, rebounders, and maintainers during 64 months of adherence to a meal-replacement weight management program.
weight of rebounders (87.1 ± 2.3 kg) was intermediate between the nonresponders and maintainers and did not differ significantly from either group. The same pattern of responses was observed for BMI values, maintainers (28.0 ± 0.9 kg/m2), rebounders (30.2 ± 0.8 kg/m2 ), and nonresponders (35.6 ± 3.8 kg/m2). Maintainers had significantly lower BMI values than nonresponders ( P = .005). The discrepancy between rebounders and nonresponders just failed to reach statistical significance ( P = .057). Participants in each of the weight outcome groups reported comparable typical portion sizes for items comprising the dairy, fruit, grain, meat, vegetable, and sweets/fats food groups. No significant differences in reported frequency of consumption of the foods prior to initiating the diet or during the 64-month study period were observed. The preferred frequency of use for the items recorded at the Month 64 weigh-in was also similar. Total daily energy intake, as assessed by diet records, tended to be higher in the nonresponders than the rebounders or maintainers (Table 1), but due, in large part, to the small number of individuals in this group, this difference was not statistically significant. Assessment of intake is complicated by the fact that the veracity of the diet records is uncertain. Only 50% of participants reported energy intakes that were at least 1.2 times their estimated resting metabolic rate (a conservative plausibility criterion). This percentage held in
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Table 1 Mean (S.E.) characteristics of nonresponders, rebounders, and maintainers Variable
Nonresponders
Rebounders
Maintainers
Control over food selection (1 = 0%, 5 = 75 – 100%) Shopping time (min/week) Food preparation time (min/week) Eating time (min/week) Mean no. of eating partners at meals Concern about calorie intake (1 = not at all, 9 = very) Concern about fat intake (1 = not at all, 9 = very) Concern about obesity (1 = not at all, 9 = very) Sum of weight status of three best friends (1 = overweight, 2 = normal weight, 3 = underweight) Disinhibition (0 = low, 16 = high) Cognitive hunger (0 = low, 14 = high) Restraint (0 = low, 21 = high) Food neophobia (10 = low, 70 = high) General neophobia (8 = low, 56 = high) Variety seeking (8 = low, 40 = high) Stress (average impact ratings) (1 = low, 7 = high) Total energy intake (kcal/day) Percent energy from fat Percent energy from carbohydrate Percent energy from protein Percent energy from sugars Intake of fiber (g/day) Mean number of snacks/day Percent of energy from bitter foods Self-reported hunger (mean/day) (1 = not at all, 9 = extremely) Self-reported energy expenditure (kcal/day) Baseline weight (kg) Baseline BMI (kg/m2)
4.38 ± 0.26 194 ± 118a 254 ± 58 597 ± 141 1.8 ± 0.6 6.1 ± 0.9 6.8 ± 0.9 6.4 ± 0.8 5.2 ± 0.5
4.05 ± 0.17 51 ± 7b 262 ± 38 481 ± 40 3.13 ± 0.4 5.4 ± 0.3 5.5 ± 0.4 6.4 ± 0.4 5.0 ± 0.2
4.56 ± 0.15 80 ± 9b 390 ± 45 510 ± 63 3.9 ± 0.4 6.5 ± 0.3 6.2 ± 0.4 6.9 ± 0.5 4.8 ± 0.2
11.0 ± 0.3 12.5 ± 0.4 14.0 ± 0.9a,b 38.9 ± 2.0 29.4 ± 3.8 21.4 ± 2.5 2.78 ± 0.3 2321 ± 418 37.3 ± 5.1 46.1 ± 6.0 15.8 ± 1.6 19.7 ± 4.4 19.6 ± 2.5 2.38 ± 0.32 6.3 ± 3.0 2.9 ± 0.2a,b 2862 ± 797 93.7 ± 9.3 35.0 ± 3.3
10.6 ± 0.2 12.0 ± 0.2 12.5 ± 0.4a 39.2 ± 1.0 28.6 ± 1.6 24.5 ± 1.3 2.72 ± 0.2 1982 ± 193 31.8 ± 1.8 50.6 ± 2.4 17.6 ± 1.3 21.0 ± 2.3 23.1 ± 2.8 1.74 ± 0.20 2.9 ± 1.4 2.7 ± 0.7a 2542 ± 224 89.6 ± 2.2 31.0 ± 0.6
10.6 ± 0.1 12.0 ± 0.2 14.5 ± 0.4b 36.6 ± 1.0 31.0 ± 1.5 24.3 ± 1.1 3.12 ± 0.2 2017 ± 319 27.5 ± 1.9 53.0 ± 2.9 18.8 ± 1.7 24.4 ± 2.5 23.2 ± 3.0 1.68 ± 0.19 1.0 ± 0.4 3.4 ± 0.9b 1971 ± 253 87.7 ± 23.0 31.8 ± 0.8
Values in a row with dissimilair superscripts are statistically significantly different.
all three groups. Moreover, the mean reported energy expenditure values for the nonresponders and rebounders were 932 and 717 kcal/day higher than their reported energy intake. Maintainers reported an expenditure that was 52 kcal less than reported intake, but this is due, in part, to a low estimate of expenditure. Weight cycling, as defined here, was not observed in any participant. Estimated energy expenditure also did not vary significantly between groups although the high variance may account for this finding since the mean differences were marked. If it is assumed that participants were weight stable and ratios of energy expenditure to resting metabolic rate less than 1.2 are not feasible, 38% of the nonresponders, 45% of the rebounders, and 61% of the maintainers provided low estimates. If values exceeding 2.0 are deemed unrealistically high, 25%, 18%, and 13% of the nonresponders, rebounders and maintainers had implausibly high estimates. Thus, only about a quarter to a third of participants in any group provided reasonable estimates of energy expenditure.
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3.2. Predictors of weight loss Table 1 contains data on selected variables hypothesized to contribute to differences in weight reduction outcomes. Nonresponders spent significantly more time shopping for food each week ( P = .004). They also tended to have the highest total exposure time to food (i.e., sum of purchasing, preparation, and consumption) ( P = .10) and to eat with fewer people than the other groups ( P = .076). Maintainers reported higher mean hunger over the course of a day ( P =.013) than rebounders. The same pattern was noted for peak hunger ratings with nonresponders, rebounders, and maintainers reporting maximum values of 6.0, 8.0, and 9.0, respectively. Minimum values were zero in all groups. Maintainers also reported higher mean daily thirst levels 3.2 ± 0.3 than nonresponders (2.6 ± 0.4) or rebounders (2.5 ± 0.2), although this just failed to reach statistical significance ( P = .066). Maintainers tended to spend more time preparing food than the other groups ( P = .065) and consume less energy from foods they rated as predominantly bitter ( P = .097). The percent of energy derived from fat also tended to be higher in the maintainers ( P = .057). Rebounders had significantly lower dietary restraint scores than maintainers ( P = .005). They also tended to have less control over the purchase and preparation of foods in their diet ( P = .087) and were less concerned about energy intake ( P = .082) than the other groups. No significant group differences were observed for estimates of eating time, number of eating partners, weight status of friends, disinhibition, cognitive hunger, neophobia, variety seeking, or daily number of snacks consumed.
4. Discussion The present data were obtained from an open-labeled, unsupervised weight reduction study initiated in 1992 that was intended to run for 12 weeks. However, data collection was continued and at the 64-month weigh-in, a battery of questionnaires assembled by a researcher independent of the initial study or corporate sponsor was administered. Approximately 66% of the initial participants volunteered to complete the forms. While there was a small age difference, participating individuals did not differ from the nonparticipants with respect to gender, initial weight, BMI, or dietary outcomes. Thus, it is unlikely the present observations reflect recruitment bias. Assessment of the external validity of the findings is more problematic. Subjects were free-living and unsupervised. However, they all reside in a northern midwest rural area and were supplied with the diet aid beverage free of charge throughout the 64-month assessment period. Because the questionnaires were completed for the first time at Month 64, it is not possible to ascribe causal explanations to the noted associations between weight outcomes and study variables. Rather, they should be viewed as hypothesis generating. The initial noteworthy observation is that the weight reduction regime was well tolerated and successful for a high proportion of individuals. Continued provision of product and follow-up of study participants was undertaken because of the popularity of the program. The
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mean weight loss was 8.72 ± 0.50 kg at Month 12 and 5.21 ± 0.78 kg at Month 64. Only eight individuals failed to achieve a weight loss of at least 5 kg at the 12-month weigh-in. Of the remaining participants, about 53% achieved a weight loss of this magnitude but failed to keep at least 75% of this loss off at Month 64. The remaining 47% maintained the weight loss for over 5 years. This prevalence of sustained reduction is markedly better than the widely cited 5% success rate for diet-based weight reduction regimens (Brownell & Rodin, 1994; Fletcher et al., 1993; Kramer et al., 1989), or, more specifically, the findings of a similar study where 94% of 24 obese females weight reduced without extensive maintenance support regained more than 25% of their initial loss within 4 years (Hensrud, Weinsier, Darnell, & Hunter, 1994). The factors accounting for this high success rate are not clear but probably include the strong peer group support fostered by the original study sponsors (Brownell, Marlatt, Lichenstein, & Wilson, 1986; Goodrick & Foreyt, 1991) and the provision of free products. The weight outcomes were reliably measured, but whether the shifts are attributable to changes of energy intake, energy expenditure, or both cannot be determined. First, because intake and expenditure were only measured at Month 64, and it is not known if these estimates held over the diet period. Secondly, a high proportion of the estimates were implausible based on comparisons with estimated energy requirements. These observations are consistent with other reports in the literature (Poppitt, Swann, Black, & Prentice, 1998; Sallis et al., 1985). Our finding that reporting errors occurred equally often in the three groups is also supported by previous observations that they occur in both the obese and postobese. Successful reduction of body weight and maintenance of the reduced weight will be determined by multiple interrelated factors (Brownell et al., 1986; Hendee, 1988; Safer, 1991). The present survey sought to identify associations between intentional weight loss outcomes and an array of behavioral, psychological, dietary, and physiological variables. A number of these indices were more prevalent in the nonresponders than the rebounders or maintainers. Nonresponders spent significantly more time shopping for food and tended to spend more time eating. Thus, their total exposure time to foods was higher than that of the other groups. This alone could foster increased intake (Rodin, Schank, & Striegel-Moore, 1989). However, they spent significantly less time preparing food for consumption. This pattern suggests an increased use of convenience foods. Reliance on such products, which tend to be high in fat and energy content, could undermine attempts to restrict energy intake. Interestingly, averaged over the day, nonresponders tended to eat with fewer individuals. This is contrary to previous findings of a positive association between number of eating partners and energy consumption under naturalistic conditions (DeCastro et al., 1990). However, the studies showing this social facilitation of eating were based on nondieting, largely normal weight individuals. The most distinguishing feature of rebounders was their lower dietary restraint scores compared to the maintainers. A similar, albeit nonsignificant difference was recently reported in a study of obese Dutch adults (Westerterp-Plantenga et al., 1998). In that study, rebounders also showed a significantly smaller shift in restraint than maintainers over the course of the weight loss period. This could not be assessed in the present sample, but was proposed as a potential predictive index for dietary outcome. The authors also reported a positive correlation between dietary restraint and disinhibition among the maintainers and argued
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the association reflects a more flexible dietary attitude, which may contribute to sustained weight loss. However, in the present sample, a positive correlation was noted only among the rebounders. Thus, the interpretation of this finding is unclear. The association between dietary restraint and weight loss has been inconsistent (Ogden, 1994). It may be more predictive of weight fluctuations than loss, but weight cycling was not observed in this survey. Rebounders also reported a tendency for less control over the purchase and preparation of foods in their diet and lower concern about the energy content of their diet. Because no baseline data are available, it cannot be determined whether this may account for their regain of weight or reflects feelings of frustration and failure due to the lack of sustained reduction. Such feelings of helplessness are widely recognized correlates of dietary failure (Goodrick & Foreyt, 1991). Characteristics associated with maintenance of reduced body weight are suggestive of a heightened sensitivity to physiological and sensory cues related to eating. Maintainers reported significantly higher mean daily hunger sensations than rebounders and nonresponders. Denial of hunger can lead to preoccupation with food and dysregulation of eating manifested by bouts of overconsumption (Polivy, 1996). The result frequently is no or only transient weight loss as noted in the nonresponders and rebounders. Maintainers also tended to spend more time with food preparation and consumed less energy from predominantly bitter foods. Assuming the increased meal preparation time reflects a higher frequency of inhome meal consumption, this finding is in agreement with data from the National Weight Control Registry where long-term successful dieters consume less than one meal per week in a fast-food restaurant and about 2.5 meals in other eating establishments (Klem et al., 1997). The lower level of energy derived from bitter items by maintainers also suggests a heightened responsivity to the sensory properties of foods. With the exception of several foods/beverages possessing psychoactive properties (e.g., caffeine, ethanol), predominantly bitter tasting items are commonly rejected (Mattes & Beauchamp, 2000). Restrained eaters, prevalent in the maintainer group, also reportedly give higher hedonic responses to food versus nonfood odors (Piacentini, Schell, & Vanderweele, 1993). Several previous studies exploring potential predictive indices for weight loss outcomes have identified feeding-related behaviors. In a study of 213 obese adults participating in an intensive multidisciplinary weight loss program (Fitzwater et al., 1991), marked and sustained loss was predicted by attendance, which, in turn, was related to low use of snack foods. Snacking was a significant predictor of weight change among a cohort of 19,478 men followed prospectively from 1988 to 1992 (Coakley et al., 1998) and can be an important source of energy in the obese (Basdevant, Craplet, & Guy-Grand, 1993). Although not statistically significant, maintainers had the lowest reported incidence of snacking and nonresponders had the highest. In another study of 33 obese adults assessing the efficacy of carbohydrate or carbohydrate plus chromium, fiber, and caffeine on weight maintenance, sustained loss was positively correlated with total carbohydrate intake and negatively correlated with total fat intake (Pasman et al., 1997). The addition of fiber to the diet did not alter maintenance success. However, data from the National Weight Control Registry does not support an association between carbohydrate intake and sustained weight loss (Shick et al., 1998), and in the present sample, carbohydrate intake was not significantly related to weight outcome. An association between low fat intake and maintenance of weight loss has
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been reported more consistently (Carmichael, Swinburn, & Wilson, 1998; Shick et al., 1998), and such a trend was noted in the present sample. In agreement with the findings of Pasman et al. (1997), fiber intake was not related to diet outcome. Low sugar intake has also been associated with successful maintenance of weight loss (Colvin & Olson, 1983), but this survey does not provide support for this observation. In summary, this survey of participants in a long-term weight management program that included regular follow-up contacts, revealed a higher than commonly observed prevalence of sustained weight loss. Further, it identified a number of distinctive feeding-related attributes associated with different weight loss outcomes. The limited sample size and cross-sectional nature of the data preclude assignment of causality to the noted associations. However, the findings suggest feeding-related attributes warrant consideration in future efforts to identify and address barriers to sustained weight reduction.
Acknowledgments The author would like to thank Leslie Bormann for her assistance in data analyses and SlimFast Foods for administering the study questionnaires and providing the weight history database. This work was supported, in part, by USDA HATCH Project no. IND084054.
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Stunkard, A. J., & Messick, S. (1985). The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. Journal of Psychosomatic Research, 29 (1), 71 – 83. Stunkard, A. J., & Wadden, T. A. (1990). Restrained eating and human obesity. Nutrition Reviews, 48, 78 – 86. Thompson, D., Edelsberg, J., Colditz, G. A., Bird, A. P., & Oster, G. (1999). Lifetime health and economic consequences of obesity. Archives of Internal Medicine, 159, 2177 – 2183. Tiwary, C. M., Ward, J. A., & Jackson, B. A. (1997). Effect of pectin on satiety in healthy US army adults. Journal of the American College of Nutrition, 16, 423 – 428. Van Trijp, H. C. M., Lahteenmaki, L., & Tuorila, H. (1992). Variety seeking in the consumption of spread and cheese. Appetite, 18, 155 – 164. Warwick, Z. S., Hall, W. G., Pappas, T. N., & Schiffman, S. S. (1993). Taste and smell sensations enhance the satiating effect of both a high-carbohydrate and a high-fat meal in humans. Physiology & Behavior, 53, 553 – 563. Weinberger, M. H., Miller, J. Z., Luft, F. C., Grim, C. E., & Fineberg, N. S. (1986). Definitions and characteristics of sodium sensitivity and blood pressure resistance. Hypertension, 8 (Suppl. II), II127 – II134. Westerterp-Plantenga, M. S., Kempen, K. P. G., & Saris, W. H. M. (1998). Determinants of weight maintenance in women after diet-induced weight reduction. International Journal of Obesity, 22, 1 – 6. Williamson, D. F. (1997). Intentional weight loss: patterns in the general population and its association with morbidity and mortality. International Journal of Obesity, 21 (Suppl. 1), S14 – S19.
Feeding behaviors and weight loss outcomes over 64 months Richard D. Mattes* Department of Foods and Nutrition, Purdue University, 212 Stone Hall, West Lafayette, IN 47907-1264, USA
Abstract Maintenance of reduced body weight following intentional weight loss is often unsuccessful. Identification of behaviors associated with sustained reductions should aid in dietary weight management. This survey assessed associations between an array of appetitive indices and weight loss outcomes in a sample of 80 adults participating in an open-labeled, unsupervised weight management program over a 64-month period. Participants were divided into maintainers (weight loss > 5 kg at Year 1, sustained reduction >75% at Month 64), rebounders (weight loss >5 kg at Year 1, < 75% reduction at Month 64), and nonresponders (weight loss < 5 kg at Year 1). Nonresponders spent significantly more time shopping for food weekly, tended to have the highest total exposure time to food and to eat with fewer people than the other groups. Maintainers reported higher mean hunger over the course of a day, tended to spend more time preparing food and consumed less energy from fat and foods that they rated as predominantly bitter. Rebounders had significantly lower dietary restraint scores and tended to have less control over the purchase and preparation of foods in their diet. Individuals with different long-term weight loss outcomes possess distinct feeding-related attributes that may provide a basis for improved intervention strategies. D 2002 Elsevier Science Ltd. All rights reserved. Keywords: Human; Diet; Obesity; Feeding; Food; Restraint
1. Introduction There is widespread concern about the health and/or cosmetic implications of overweight. Approximately 40% of females and 25% of males are on a weight reduction diet at any given
* Tel.: +1-765-494-0662; fax: +1-765-494-0674. E-mail address: [email protected] (R.D. Mattes). 1471-0153/02/$ – see front matter D 2002 Elsevier Science Ltd. All rights reserved. PII: S 1 4 7 1 - 0 1 5 3 ( 0 1 ) 0 0 0 5 9 - 9
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point in time (Allison, Fontaine, Heshka, Mentore, & Heymsfield, 2001). Over US$33 billion dollars are spent annually on diet foods, aids, and programs, and this figure is growing rapidly (Larkin, 1996). Despite this high level of concern, the prevalence of overweight and obesity (body mass index, BMI>25) has increased dramatically over the past two decades so that approximately 55% of the population 20 years of age or older can now be so classified (Flegal, Carroll, Kuczmarski, & Johnson, 1998). The health care costs attendant to obesity are estimated at over US$100 billion annually due to the contribution of excess body fat to chronic diseases such as hypertension, heart disease, diabetes, and osteoarthritis (Thompson, Edelsberg, Colditz, Bird, & Oster, 1999). Annual preventable deaths from obesity in the total population are approximately 280,000 (Allison, Fontaine, Manson, Stevens, & VanItallie, 1999), and the toll on productivity and quality of life are also high. Dietary approaches to treat obesity have been largely unsuccessful as defined by sustained reduction of body weight (Fletcher et al., 1993). Widely cited reports indicate that only about 5% of individuals using self-induced behavioral methods to decrease body weight achieve lasting reductions (Brownell & Rodin, 1994; Fletcher et al., 1993; Kramer, Jeffrey, & Forster, 1989). Others have argued that this value is erroneously low (Lowe, Miller-Kovach, & Phelan, 2001), but they still acknowledge that maintenance is problematic. This has prompted criticism of approaches based on adherence to hypocaloric diets (Kratina, King, & Hayes, 1996; Polivy, 1996). Alternatively, a view that the criteria for successful obesity management should be reconsidered (Atkinson, 1993; Rossner, 1997), given that even small reductions of body weight, achievable through diet modification, hold clinical benefit (Goldstein, 1992; Williamson, 1997), has emerged. One explanation for the difficulty in maintaining weight loss in many individuals may stem from a failure to recognize the multiple etiologies of obesity (Bray, 1989) and need to individualize therapeutic approaches. Just as there are marked individual differences in blood pressure responses to dietary restriction of sodium (Weinberger, Miller, Luft, Grim, & Fineberg, 1986) or serum lipid profiles to reduction of dietary fat (Schaefer et al., 1997), there may be individual variability in response to limiting dietary energy (Goldstein, 1992). To explore this hypothesis requires classification of individuals according to body weight changes to a given challenge and characterization of their relevant attributes. Recent reports on predictive indices for weight loss have begun to provide the needed data (Bild et al., 1996; Coakley, Rimm, Colditz, Kawachi, & Willett, 1998; French et al., 1994; Klem, Wing, McGuire, Seagle, & Hill, 1997; Parham, 1988; Westerterp-Plantenga, Kempen, & Saris, 1998). They have focused primarily on indices of pretreatment body weight or composition, prior history of dieting, emotional status, and physical activity. There has been limited exploration of eating-related attributes such as hunger, affective responses to foods, and meal patterns. The present exploratory study assessed the associations between weight loss outcomes and an array of dietary, behavioral, psychological, and physiological indices with the aim of identifying predictive indices for sustained weight loss that may aid in the design and targeting of dietary intervention approaches. Specifically, information was collected on the time spent in food acquisition, preparation, and consumption as a reflection of preoccupation with eating; control over the purchase and preparation of foods as an index of dietary control;
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the number of eating partners given evidence of a positive association between this variable and total energy intake (DeCastro, Brewer, Elmore, & Orozco, 1990); level of concern about ingestion of specific dietary components and health as a measure of dietary motivation (Harris, 1983; Ortega et al., 1996); body weight status of close friends to assess peer pressures (Harris, 1983); cognitive restraint, disinhibition, and hunger because of their associations with dietary compliance and weight loss maintenance (Keim, Canty, Barbieri, & Wu, 1996; Ogden, 1994; Stunkard & Wadden, 1990; Westerterp-Plantenga et al., 1998); neophobia and variety seeking as they may influence food seeking and avoidance behaviors (Hursti & Sjoden, 1997; Pliner & Hobden, 1992; Van Trijp, Lahteenmaki, & Tuorila, 1992); stress because of its reported association with energy intake and weight (Istvan, Zavela, & Weidner, 1992; Mitchell & Epstein, 1996); diet composition as relative proportions of macronutrients and fiber content have been linked with hunger, satiety, energy balance, and body weight (Blundell & Macdiarmid, 1997; Mattes, 1996; Nelson & Tucker, 1996; Pasman, WesterterpPlantenga, & Saris, 1997; Reid & Hetherington, 1997; Tiwary, Ward, & Jackson, 1997; Warwick, Hall, Pappas, & Schiffman, 1993); hunger sensations since they are widely purported cues for meal initiation (DeCastro & Elmore, 1988); energy intake and expenditure because the balance between these measures will determine body weight and, finally, selected baseline characteristics such as age, gender, weight, and BMI that have been previously linked to diet outcomes (Bild et al., 1996; Dwyer et al., 1998).
2. Methods 2.1. Protocol All individuals participating in a long-term weight loss program were sent a packet of eight questionnaires and instructions on how they should be completed and returned. One followup call requesting the completed forms be mailed to the investigators was made if they were not received promptly. 2.2. Subjects One hundred and four of the 158 (66%) individuals from Pound or Coleman, WI who participated in an Ultra Slim-Fast diet program completed the questionnaires. Twenty-four were excluded due to the presence of health conditions at some point in the 64-month study period that could have influenced diet and energy balance (e.g., cancer, thyroid disease, pregnancy). Thus, the study population was comprised of 80 dieters—27 males and 53 females with a mean ± S.D. age of 42.6 ± 10.4 years. Their mean ± S.D. baseline BMI was 31.6 ± 5.0 kg/m2. All were Caucasian. Dieters from the original cohort not included in this analysis included 23 males and 55 females with a mean BMI of 31.7 ± 6.4 kg/m2 (both indices comparable to the study sample). The two groups also had similar changes of body weight from baseline at Years 1, 2, 3, 4, and 5. The nonparticipating subsample was slightly younger with a mean age of 36.7 ± 10.4 years ( P < .01).
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2.3. Diet program At entry, participants completed a health questionnaire and obtained medical clearance from their physician. The weight loss phase of the plan involved daily substitution of 8-oz servings of Ultra Slim-Fast for two meals and consumption of one 250–500-kcal meal plus three optional Ultra Slim-Fast snacks. Total daily energy intake was approximately 1130–1190 kcal. For weight maintenance, only one meal was replaced with the product. If a weight gain of 2–3 lb was observed during maintenance, participants were instructed to return to the weight loss plan until the desired weight was again reached. The meal substitute was provided in a variety of flavors. One serving of each contained 200–220 kcal, 11–14 g protein, 36–38 g carbohydrate, 1–4 g fat, and 4–5 g fiber (when reconstituted with nonfat milk). The snacks included, bars, popcorn, caramel corn, pretzels, cheese curls, and chocolate pudding. Participants were unsupervised but were weighed weekly for 12 weeks and twice per year between July of 1992 and November of 1997. After Year 2, the only products supplied to participants were snack bars and meal replacement bars and formula. Data for this analysis were obtained at baseline and Months 12, 24, 38, 48, and 64. Participants were provided the study products at no charge through a local supermarket. They were requested to refrain from use of medications or products for weight loss. 2.4. Questionnaires Health and demographic information (nonstandardized questionnaire), stress (Brantley, Dietz, McKnight, Jones, & Tulley, 1988), variety seeking (Van Trijp et al., 1992), food and general neophobia (Pliner & Hobden, 1992), cognitive restraint, disinhibition, and hunger (Stunkard & Messick 1985), physical activity (MONICA Optional Study of Physical Activity—MOSPA (Pereira et al., 1997), hunger sensations (nine-point category scales, 1 = not at all, 9 = extremely), as well as frequency and preferred frequency of food use (items included represented the foods contributing 90% of the energy, protein, fat, and carbohydrate in the US diet as reported by Block, Dresser, Hartman, & Carroll, 1985 using HANES II data). 2.5. Dietary record Following provision of materials to assist in estimation of sample size, participants kept a 24-h diet record. The records were coded using version 6.01 of the Genesis Nutrient Database (ESHA Research, Salem, OR) supplemented with additional data from commercial food establishments. 2.6. Statistical analyses The primary dependent variable was the percent of the initial loss of body weight maintained at the end of the 64-month study period. No significant age or sex effects were observed on this treatment outcome so data from these variables were pooled for all
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analyses. To identify personal attributes associated with treatment outcome, dietary success was defined as an initial weight loss (baseline minus weight at Year 1) of >5 kg and maintenance of at least 75% of the initial loss 64 months later. Participants meeting this criterion were classified as maintainers. Participants who achieved the requisite initial weight loss, but did not maintain the stipulated level of reduction were termed rebounders. Individuals who did not weigh at least 5 kg less at the 1-year weigh-in were considered nonresponders. Analysis of variance was used to explore differences between these groups on variables with continuous distributions. Where appropriate, the Tukey HSD test was used for post hoc analyses. Crosstabulation was used to explore associations with categorical variables. To explore the incidence of weight cycling, a cycle was defined by a reversal of body weight trend that exceeded 10% of the previous years body weight and an individual was viewed as cycling if they experienced three cycles over the 64-month period. The criterion for statistical significance was P < .05. Probability values .05 and .10 are reported as trends. Data were analyzed with the Statistical Package for the Social Sciences (SPSS, 1996).
3. Results 3.1. Dietary response In the full sample, the mean weight loss at 12 months was 8.72 ± 0.50 kg. Ninety percent of the participants weighed at least 5 kg less at 12 months than at baseline. The mean reduction at Month 64 was 5.21 ± 0.78 kg. Of those losing at least 5 kg during the initial 12 months, 47.2% maintained at least 75% of the reduction at Month 64. Fig. 1 shows the weight reduction responses of the nonresponder, rebounder, and maintainer groups over the study period. At the 12-month weigh-in, the rebounders and maintainers had lost a comparable amount of weight and significantly more than the nonresponders [ F(2,79) = 13.55, P < .001]. The difference between nonresponders and maintainers remained significant ( P = .011) at Month 24, but the rebounders were not different from either of the other groups. By Month 38, the rebounders had regained sufficient weight that they differed significantly from the maintainers ( P = .006), but not from the nonresponders. The maintainers continued to differ from the nonresponders ( P = .001). This pattern held for weigh-ins at 48 and 64 months. The mean ± S.E. percent reductions of body weight at the 12-month weigh-in for the nonresponders, rebounders, and maintainers were 1.05 ± 0.44%, 5.08 ± 0.38%, and 4.60 ± 0.26%, respectively. There was a significant group difference [ F(2,79) = 14.25, P < .001] wherein nonresponders lost a significantly smaller percent than the other groups. The rebounders and maintainers had similar percent reductions. The percent of this initial loss maintained by the three groups did not differ at 24 months, but at all subsequent weigh-ins, the rebounders had significantly smaller percent reductions (mean range = 22–47%) than the other groups (mean ranges = 103–133%) (all P < .05). These varying response patterns resulted in significant differences in body weight and BMI between the groups at Month 64. Maintainers weighed significantly less than nonresponders, 77.9 ± 3.2 vs. 96.5 ± 10.0 kg ( P = .025). The mean
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Fig. 1. Mean (S.E.) change of body weight for nonresponders, rebounders, and maintainers during 64 months of adherence to a meal-replacement weight management program.
weight of rebounders (87.1 ± 2.3 kg) was intermediate between the nonresponders and maintainers and did not differ significantly from either group. The same pattern of responses was observed for BMI values, maintainers (28.0 ± 0.9 kg/m2), rebounders (30.2 ± 0.8 kg/m2 ), and nonresponders (35.6 ± 3.8 kg/m2). Maintainers had significantly lower BMI values than nonresponders ( P = .005). The discrepancy between rebounders and nonresponders just failed to reach statistical significance ( P = .057). Participants in each of the weight outcome groups reported comparable typical portion sizes for items comprising the dairy, fruit, grain, meat, vegetable, and sweets/fats food groups. No significant differences in reported frequency of consumption of the foods prior to initiating the diet or during the 64-month study period were observed. The preferred frequency of use for the items recorded at the Month 64 weigh-in was also similar. Total daily energy intake, as assessed by diet records, tended to be higher in the nonresponders than the rebounders or maintainers (Table 1), but due, in large part, to the small number of individuals in this group, this difference was not statistically significant. Assessment of intake is complicated by the fact that the veracity of the diet records is uncertain. Only 50% of participants reported energy intakes that were at least 1.2 times their estimated resting metabolic rate (a conservative plausibility criterion). This percentage held in
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Table 1 Mean (S.E.) characteristics of nonresponders, rebounders, and maintainers Variable
Nonresponders
Rebounders
Maintainers
Control over food selection (1 = 0%, 5 = 75 – 100%) Shopping time (min/week) Food preparation time (min/week) Eating time (min/week) Mean no. of eating partners at meals Concern about calorie intake (1 = not at all, 9 = very) Concern about fat intake (1 = not at all, 9 = very) Concern about obesity (1 = not at all, 9 = very) Sum of weight status of three best friends (1 = overweight, 2 = normal weight, 3 = underweight) Disinhibition (0 = low, 16 = high) Cognitive hunger (0 = low, 14 = high) Restraint (0 = low, 21 = high) Food neophobia (10 = low, 70 = high) General neophobia (8 = low, 56 = high) Variety seeking (8 = low, 40 = high) Stress (average impact ratings) (1 = low, 7 = high) Total energy intake (kcal/day) Percent energy from fat Percent energy from carbohydrate Percent energy from protein Percent energy from sugars Intake of fiber (g/day) Mean number of snacks/day Percent of energy from bitter foods Self-reported hunger (mean/day) (1 = not at all, 9 = extremely) Self-reported energy expenditure (kcal/day) Baseline weight (kg) Baseline BMI (kg/m2)
4.38 ± 0.26 194 ± 118a 254 ± 58 597 ± 141 1.8 ± 0.6 6.1 ± 0.9 6.8 ± 0.9 6.4 ± 0.8 5.2 ± 0.5
4.05 ± 0.17 51 ± 7b 262 ± 38 481 ± 40 3.13 ± 0.4 5.4 ± 0.3 5.5 ± 0.4 6.4 ± 0.4 5.0 ± 0.2
4.56 ± 0.15 80 ± 9b 390 ± 45 510 ± 63 3.9 ± 0.4 6.5 ± 0.3 6.2 ± 0.4 6.9 ± 0.5 4.8 ± 0.2
11.0 ± 0.3 12.5 ± 0.4 14.0 ± 0.9a,b 38.9 ± 2.0 29.4 ± 3.8 21.4 ± 2.5 2.78 ± 0.3 2321 ± 418 37.3 ± 5.1 46.1 ± 6.0 15.8 ± 1.6 19.7 ± 4.4 19.6 ± 2.5 2.38 ± 0.32 6.3 ± 3.0 2.9 ± 0.2a,b 2862 ± 797 93.7 ± 9.3 35.0 ± 3.3
10.6 ± 0.2 12.0 ± 0.2 12.5 ± 0.4a 39.2 ± 1.0 28.6 ± 1.6 24.5 ± 1.3 2.72 ± 0.2 1982 ± 193 31.8 ± 1.8 50.6 ± 2.4 17.6 ± 1.3 21.0 ± 2.3 23.1 ± 2.8 1.74 ± 0.20 2.9 ± 1.4 2.7 ± 0.7a 2542 ± 224 89.6 ± 2.2 31.0 ± 0.6
10.6 ± 0.1 12.0 ± 0.2 14.5 ± 0.4b 36.6 ± 1.0 31.0 ± 1.5 24.3 ± 1.1 3.12 ± 0.2 2017 ± 319 27.5 ± 1.9 53.0 ± 2.9 18.8 ± 1.7 24.4 ± 2.5 23.2 ± 3.0 1.68 ± 0.19 1.0 ± 0.4 3.4 ± 0.9b 1971 ± 253 87.7 ± 23.0 31.8 ± 0.8
Values in a row with dissimilair superscripts are statistically significantly different.
all three groups. Moreover, the mean reported energy expenditure values for the nonresponders and rebounders were 932 and 717 kcal/day higher than their reported energy intake. Maintainers reported an expenditure that was 52 kcal less than reported intake, but this is due, in part, to a low estimate of expenditure. Weight cycling, as defined here, was not observed in any participant. Estimated energy expenditure also did not vary significantly between groups although the high variance may account for this finding since the mean differences were marked. If it is assumed that participants were weight stable and ratios of energy expenditure to resting metabolic rate less than 1.2 are not feasible, 38% of the nonresponders, 45% of the rebounders, and 61% of the maintainers provided low estimates. If values exceeding 2.0 are deemed unrealistically high, 25%, 18%, and 13% of the nonresponders, rebounders and maintainers had implausibly high estimates. Thus, only about a quarter to a third of participants in any group provided reasonable estimates of energy expenditure.
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3.2. Predictors of weight loss Table 1 contains data on selected variables hypothesized to contribute to differences in weight reduction outcomes. Nonresponders spent significantly more time shopping for food each week ( P = .004). They also tended to have the highest total exposure time to food (i.e., sum of purchasing, preparation, and consumption) ( P = .10) and to eat with fewer people than the other groups ( P = .076). Maintainers reported higher mean hunger over the course of a day ( P =.013) than rebounders. The same pattern was noted for peak hunger ratings with nonresponders, rebounders, and maintainers reporting maximum values of 6.0, 8.0, and 9.0, respectively. Minimum values were zero in all groups. Maintainers also reported higher mean daily thirst levels 3.2 ± 0.3 than nonresponders (2.6 ± 0.4) or rebounders (2.5 ± 0.2), although this just failed to reach statistical significance ( P = .066). Maintainers tended to spend more time preparing food than the other groups ( P = .065) and consume less energy from foods they rated as predominantly bitter ( P = .097). The percent of energy derived from fat also tended to be higher in the maintainers ( P = .057). Rebounders had significantly lower dietary restraint scores than maintainers ( P = .005). They also tended to have less control over the purchase and preparation of foods in their diet ( P = .087) and were less concerned about energy intake ( P = .082) than the other groups. No significant group differences were observed for estimates of eating time, number of eating partners, weight status of friends, disinhibition, cognitive hunger, neophobia, variety seeking, or daily number of snacks consumed.
4. Discussion The present data were obtained from an open-labeled, unsupervised weight reduction study initiated in 1992 that was intended to run for 12 weeks. However, data collection was continued and at the 64-month weigh-in, a battery of questionnaires assembled by a researcher independent of the initial study or corporate sponsor was administered. Approximately 66% of the initial participants volunteered to complete the forms. While there was a small age difference, participating individuals did not differ from the nonparticipants with respect to gender, initial weight, BMI, or dietary outcomes. Thus, it is unlikely the present observations reflect recruitment bias. Assessment of the external validity of the findings is more problematic. Subjects were free-living and unsupervised. However, they all reside in a northern midwest rural area and were supplied with the diet aid beverage free of charge throughout the 64-month assessment period. Because the questionnaires were completed for the first time at Month 64, it is not possible to ascribe causal explanations to the noted associations between weight outcomes and study variables. Rather, they should be viewed as hypothesis generating. The initial noteworthy observation is that the weight reduction regime was well tolerated and successful for a high proportion of individuals. Continued provision of product and follow-up of study participants was undertaken because of the popularity of the program. The
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mean weight loss was 8.72 ± 0.50 kg at Month 12 and 5.21 ± 0.78 kg at Month 64. Only eight individuals failed to achieve a weight loss of at least 5 kg at the 12-month weigh-in. Of the remaining participants, about 53% achieved a weight loss of this magnitude but failed to keep at least 75% of this loss off at Month 64. The remaining 47% maintained the weight loss for over 5 years. This prevalence of sustained reduction is markedly better than the widely cited 5% success rate for diet-based weight reduction regimens (Brownell & Rodin, 1994; Fletcher et al., 1993; Kramer et al., 1989), or, more specifically, the findings of a similar study where 94% of 24 obese females weight reduced without extensive maintenance support regained more than 25% of their initial loss within 4 years (Hensrud, Weinsier, Darnell, & Hunter, 1994). The factors accounting for this high success rate are not clear but probably include the strong peer group support fostered by the original study sponsors (Brownell, Marlatt, Lichenstein, & Wilson, 1986; Goodrick & Foreyt, 1991) and the provision of free products. The weight outcomes were reliably measured, but whether the shifts are attributable to changes of energy intake, energy expenditure, or both cannot be determined. First, because intake and expenditure were only measured at Month 64, and it is not known if these estimates held over the diet period. Secondly, a high proportion of the estimates were implausible based on comparisons with estimated energy requirements. These observations are consistent with other reports in the literature (Poppitt, Swann, Black, & Prentice, 1998; Sallis et al., 1985). Our finding that reporting errors occurred equally often in the three groups is also supported by previous observations that they occur in both the obese and postobese. Successful reduction of body weight and maintenance of the reduced weight will be determined by multiple interrelated factors (Brownell et al., 1986; Hendee, 1988; Safer, 1991). The present survey sought to identify associations between intentional weight loss outcomes and an array of behavioral, psychological, dietary, and physiological variables. A number of these indices were more prevalent in the nonresponders than the rebounders or maintainers. Nonresponders spent significantly more time shopping for food and tended to spend more time eating. Thus, their total exposure time to foods was higher than that of the other groups. This alone could foster increased intake (Rodin, Schank, & Striegel-Moore, 1989). However, they spent significantly less time preparing food for consumption. This pattern suggests an increased use of convenience foods. Reliance on such products, which tend to be high in fat and energy content, could undermine attempts to restrict energy intake. Interestingly, averaged over the day, nonresponders tended to eat with fewer individuals. This is contrary to previous findings of a positive association between number of eating partners and energy consumption under naturalistic conditions (DeCastro et al., 1990). However, the studies showing this social facilitation of eating were based on nondieting, largely normal weight individuals. The most distinguishing feature of rebounders was their lower dietary restraint scores compared to the maintainers. A similar, albeit nonsignificant difference was recently reported in a study of obese Dutch adults (Westerterp-Plantenga et al., 1998). In that study, rebounders also showed a significantly smaller shift in restraint than maintainers over the course of the weight loss period. This could not be assessed in the present sample, but was proposed as a potential predictive index for dietary outcome. The authors also reported a positive correlation between dietary restraint and disinhibition among the maintainers and argued
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the association reflects a more flexible dietary attitude, which may contribute to sustained weight loss. However, in the present sample, a positive correlation was noted only among the rebounders. Thus, the interpretation of this finding is unclear. The association between dietary restraint and weight loss has been inconsistent (Ogden, 1994). It may be more predictive of weight fluctuations than loss, but weight cycling was not observed in this survey. Rebounders also reported a tendency for less control over the purchase and preparation of foods in their diet and lower concern about the energy content of their diet. Because no baseline data are available, it cannot be determined whether this may account for their regain of weight or reflects feelings of frustration and failure due to the lack of sustained reduction. Such feelings of helplessness are widely recognized correlates of dietary failure (Goodrick & Foreyt, 1991). Characteristics associated with maintenance of reduced body weight are suggestive of a heightened sensitivity to physiological and sensory cues related to eating. Maintainers reported significantly higher mean daily hunger sensations than rebounders and nonresponders. Denial of hunger can lead to preoccupation with food and dysregulation of eating manifested by bouts of overconsumption (Polivy, 1996). The result frequently is no or only transient weight loss as noted in the nonresponders and rebounders. Maintainers also tended to spend more time with food preparation and consumed less energy from predominantly bitter foods. Assuming the increased meal preparation time reflects a higher frequency of inhome meal consumption, this finding is in agreement with data from the National Weight Control Registry where long-term successful dieters consume less than one meal per week in a fast-food restaurant and about 2.5 meals in other eating establishments (Klem et al., 1997). The lower level of energy derived from bitter items by maintainers also suggests a heightened responsivity to the sensory properties of foods. With the exception of several foods/beverages possessing psychoactive properties (e.g., caffeine, ethanol), predominantly bitter tasting items are commonly rejected (Mattes & Beauchamp, 2000). Restrained eaters, prevalent in the maintainer group, also reportedly give higher hedonic responses to food versus nonfood odors (Piacentini, Schell, & Vanderweele, 1993). Several previous studies exploring potential predictive indices for weight loss outcomes have identified feeding-related behaviors. In a study of 213 obese adults participating in an intensive multidisciplinary weight loss program (Fitzwater et al., 1991), marked and sustained loss was predicted by attendance, which, in turn, was related to low use of snack foods. Snacking was a significant predictor of weight change among a cohort of 19,478 men followed prospectively from 1988 to 1992 (Coakley et al., 1998) and can be an important source of energy in the obese (Basdevant, Craplet, & Guy-Grand, 1993). Although not statistically significant, maintainers had the lowest reported incidence of snacking and nonresponders had the highest. In another study of 33 obese adults assessing the efficacy of carbohydrate or carbohydrate plus chromium, fiber, and caffeine on weight maintenance, sustained loss was positively correlated with total carbohydrate intake and negatively correlated with total fat intake (Pasman et al., 1997). The addition of fiber to the diet did not alter maintenance success. However, data from the National Weight Control Registry does not support an association between carbohydrate intake and sustained weight loss (Shick et al., 1998), and in the present sample, carbohydrate intake was not significantly related to weight outcome. An association between low fat intake and maintenance of weight loss has
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been reported more consistently (Carmichael, Swinburn, & Wilson, 1998; Shick et al., 1998), and such a trend was noted in the present sample. In agreement with the findings of Pasman et al. (1997), fiber intake was not related to diet outcome. Low sugar intake has also been associated with successful maintenance of weight loss (Colvin & Olson, 1983), but this survey does not provide support for this observation. In summary, this survey of participants in a long-term weight management program that included regular follow-up contacts, revealed a higher than commonly observed prevalence of sustained weight loss. Further, it identified a number of distinctive feeding-related attributes associated with different weight loss outcomes. The limited sample size and cross-sectional nature of the data preclude assignment of causality to the noted associations. However, the findings suggest feeding-related attributes warrant consideration in future efforts to identify and address barriers to sustained weight reduction.
Acknowledgments The author would like to thank Leslie Bormann for her assistance in data analyses and SlimFast Foods for administering the study questionnaires and providing the weight history database. This work was supported, in part, by USDA HATCH Project no. IND084054.
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