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2 IDIBELL, Institut Català d' Oncologia, L'Hospitalet de Llobregat, 08907, Barcelona, Spain; 3 Carolina Population Center and Department of Nutrition, University of North Carolina, Chapel Hill; 4 Dirección de Salud de Guipúzcoa, 30014 San Sebastián, Spain; 5 Instituto de Salud Pública de Navarra, 31003 Pamplona, Spain; 6 Consejería de Sanidad y Consumo, 4008 Murcia, Spain; 7 Escuela Andaluza de Salud Pública, 18080 Granada, Spain; and 8 Consejería de Sanidad y Servicios Sociales de Asturias, 44001 Oviedo, Spain
* To whom correspondence should be addressed. E-mail: mmendez{at}ico.scs.es.
| ABSTRACT |
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0.8 without this adjustment. MD adherence was not associated with incidence of overweight in initially normal-weight subjects. Nonetheless, results suggest that promoting eating habits consistent with MD patterns may be a useful part of efforts to combat obesity.
| Introduction |
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Methodological factors may contribute to these inconsistencies. Key problems include the greater tendency of obese rather than lean subjects to underreport intakes (16) and to have changed prior obesogenic dietary habits in efforts to ameliorate obesity-related disorders (17). Several cross-sectional studies, including our earlier work on MD adherence (unpublished data), have reported diet-obesity associations that emerged or were strengthened after accounting for underreporting (1820). Prospective studies may also help to mitigate effects of these factors by focusing on weight changes in initially nonobese subjects. In this study, we examine the relation between MD adherence and a 3-y incidence of obesity in the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Spain), exploring the effect of accounting for underreporting. Because there is no consensus on the definition of this dietary pattern (21), we examined associations with various food-group components incorporated in published MD indices, in addition to an overall MD score, to better facilitate an understanding of aspects of this dietary pattern that are potentially beneficial for obesity prevention.
| Materials and Methods |
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65 y at baseline; a small number (n = 18) of individuals underweight at baseline (BMI <18, where BMI = weight in kg/height in m2); several (n = 14) subjects with implausibly large self-reported changes in weight (<35 kg to 107 kg or
35 kg); and the top and bottom 0.5% of subjects with poor concordance of reported energy intakes to expenditures. These exclusions reduced the sample by 3%, to 40,310 (25,164 women; 15,132 men). Additionally, subjects obese at baseline were excluded (30.5 and 28.7% of otherwise eligible women and men, respectively), resulting in a sample of 17,238 women and 10,589 men. The Ethics Committee of the Spanish Carlos III Health Institute approved the study.
Anthropometry.
Standardized methods were used to measure height and weight at baseline (24); weight was self-reported at follow-up. Standard cutoffs for BMI were used to define overweight (
25 to <30 kg/m2) and obesity (
30 kg/m2). Incident overweight and obesity were used as measures of adverse changes in weight status to reduce problems with regression to the mean (25).
Diet. At baseline, trained nutritionists collected data on dietary intakes in the previous year using a validated, computerized diet-history instrument with >600 items (22,26).
Foods were coded into groups, 10 of which were included in this analysis: meat/meat products, poultry, fish, eggs, legumes (e.g., chickpeas, lentils), vegetables excluding potatoes, fruit, cereal products (e.g., bread, rice, and pasta), pastries and cakes, dairy products (e.g., milk, yogurt, but excluding desserts such as ice cream). Intakes were analyzed as g/MJ of energy intake.
An MD score was constructed as the sum of 8 components, based on methods previously used in other EPIC cohorts (7). Intakes of 6 postulated beneficial components [fish, vegetables, fruits, legumes, cereals, and the ratio of monounsaturated (MFA) to saturated fat (SFA)] were coded as 1 if intakes exceeded sex-specific medians. For the seventh component, moderate ethanol intakes, defined as 525 g in women and 1050 g in men, as in the original score (also considered beneficial), were assigned a value of 1. Finally, meat intakes below sex-specific medians were assigned a value of 1, as low intakes are considered beneficial. Food group components were measured as g/MJ of energy. Dairy products, which have been alternatively omitted, considered an integral beneficial component and considered detrimental in published MD scores (57,2729), were analyzed separately. Nuts, combined with fruit in the original score but elsewhere considered a separate component or omitted (5,6,8,9), were also analyzed separately.
Subjects were classified as under- or overreporters based on the ratio of reported energy intakes to estimated requirements using the method of Huang et al. (18), where requirements are predicted with equations derived from doubly labeled water studies, as well as the Goldberg method, where requirements are based on predicted basal metabolic rates (30). SD energy intake:requirement ratios were calculated using published estimates of variation in energy intakes and requirements, as well as measurement variability (18,30). Subjects within 1.5 SD limits were classified as plausible reporters, whereas those above or below these limits were classified as over- or underreporters, respectively.
Other data. Interviewer-administered questionnaires were used to collect data on sociodemographic characteristics, health history, and health behaviors, including tobacco use and physical activity patterns. Physical activity indices were developed and validated based on reported occupational and seasonal exercise habits (31,32). Changes in these factors were reported in the follow-up questionnaire.
Statistical analysis.
Data were analyzed separately for men and women. The significance of differences in key characteristics and selected dietary factors by level of MD adherence were assessed using
2 tests or ANOVA. Differences were considered significant at P < 0.05. Food group and nutrient intakes by MD adherence level will be presented in greater detail elsewhere. Logistic regression was used to estimate associations between dietary factors and incident obesity among subjects overweight at baseline, as well as incident overweight among normal weight subjects. Separate models were run to estimate associations with the MD score vs. individual diet factors (food group models), using cutoffs specified in constructing the score. Models were adjusted for age (continuous), special diets related to obesity or related disorders (yes/no), a categorical activity index (31), education (none, primary, secondary, university), center, height (cm), parity (in women: 0, 1, 2, 3, 4+), smoking status (never, past, current), winter season, follow-up time (mo), health status (cancer, diabetes, or heart disease) and changes in lifestyle or health during follow-up (retirement, weight-loss due to dieting, smoking cessation or initiation, any new births, menopause, incidence of cancer, diabetes, or heart disease). Two percent or fewer subjects had missing covariate data for each multivariate model and were excluded. All 10 groups were included simultaneously in the food group models. Odds ratio (OR) and 95% CI are presented with and without adjustment for under- and overreporting (hereafter, "underreporting") using dummy variables based on the method of Huang et al. (18); similar results were obtained with the Goldberg method (not shown). OR+ was used to designate results of models adjusted for underreporting. Similar results were obtained in alternative models restricting the sample to plausible reporters, limiting obesity or overweight incidence to subjects with increases of at least 1.0 kg/m2, or adjusting for additional food groups (sauces/condiments, soups, pastries, and salty snacks) (not shown). Excluding rather than adjusting for cancer, diabetes, or heart disease at baseline and/or follow-up had no meaningful effect (not shown). Results were also similar in models predicting large weight increments (
1.5 kg/y or net gains
5 kg) rather than obesity or overweight incidence (not shown). Values in the text are means ± SD.
| Results |
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Overall, 12.6% of women and 18.2% of men were defined as having high MD adherence (scores of 68) at baseline; scores were lower in women because of their lower levels of ethanol consumption. Excluding ethanol, 10.4% of women and 10.1% of men had high adherence. MD adherence was not significantly associated with incident overweight or obesity in bivariate analyses (Table 1), but was associated with other predictors of incident obesity including older age, lower education (in women), and a nonsmoking status (P < 0.05).
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45 y), because MD adherence tended to be associated (P = 0.08) with lower overweight incidence in younger (P = 0.08), but not older, subjects. Except for a positive association with meat consumption in women, individual dietary factors were not meaningfully associated with overweight incidence (not shown). | Discussion |
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To our knowledge, only one published observational study has prospectively examined the relation between MD patterns and weight change (6). This study reported a weak association that lost significance with multivariate adjustment. However, other dietary patterns that share elements of the MD pattern, such as lower meat and higher vegetable and whole-grain intakes, have been associated with lower weight gain (1013). Two prospective studies that did not find associations between similar diet patterns and weight gain used brief (428 items) food frequency questionnaires, potentially susceptible to measurement error (14,15). Several small intervention trials have also reported lower weight gains or weight loss associated with Mediterranean style diets (33,34). In addition to our previous analysis, 2 other cross-sectional studies (1 of which accounted for underreporting) found MD adherence to be inversely associated with obesity (5,8), whereas 2 more studies reported no association (7,9). Reasons for these inconsistent results are uncertain, but differences in MD score composition and effects of underreporting may play a role.
In this prospective analysis, associations between the incidence of obesity and adherence to MD were slightly stronger after accounting for underreporting. The relatively small effect of this adjustment was consistent with our expectation that prospective analyses may partially mitigate effects of underreporting. To our knowledge, this issue has not been previously explored.
In contrast to the MD score, few associations with individual dietary factors were significant, suggesting it may be easier to detect associations with obesity using more comprehensive measures of diet (35). Nonetheless, analyzing individual factors suggested that the protective effect of the MD score may be especially attributable to components such as meat consumption. Excluding meats from the score attenuated but did not eliminate associations (not shown).
An important limitation of this study is our inability to assess effects of dietary changes other than weight-loss diets. Dietary change may be an important confounder, as previous studies have found associations between dietary changes and weight gain (6,12,36). Additionally, measurement error due to the use of self-reported weight change may have attenuated our estimates. Studies of Spanish adults and other populations have found that self-reports underestimate obesity, with low sensitivity but high specificity (3739). Nonetheless, associations for obesity incidence, albeit not for overweight, were largely consistent with our previous cross-sectional analysis, which used measured weight and height (unpublished data). A relatively short follow-up period may also have reduced our ability to detect effects, but a considerable proportion of the population reported substantial weight gains, as in other studies with 35 y of follow-up (4042). Repeated gains over multiple short time periods are thought to be the most common process leading to obesity in adults (41).
As characteristics of nonrespondents are not available, the magnitude or direction of possible bias resulting from the modest baseline participation rates is uncertain. Although 96% participation in the follow-up study reduces the likelihood of substantial selection bias in analyses of obesity incidence, we may have underestimated the benefits of MD adherence if, for example, overweight subjects with healthier diets were more likely to have participated at baseline. However, the close concordance of sample education levels to national profiles (43) and the inverse association (not shown) between education and obesity, consistent with other Spanish studies (44), do not suggest substantial bias.
The Mediterranean diet pattern has been associated with reduced risk of various chronic diseases, and with prolonged survival (4547). This study suggests that this dietary pattern may also help to reduce obesity risk in adults. Potential mechanisms linking MD adherence to reduced obesity may include lower energy density, higher fiber intakes as a result of fruit, vegetable, and cereal consumption, and reduced intakes of saturated fats associated with low meat consumption; these dietary factors have all been linked to obesity (48). There are concerns about the obesogenicity of added fats in this diet (49), but despite high intakes, we did not observe associations between olive oil consumption and obesity or overweight incidence (not shown). Future research prospectively examining the relation between MD adherence and different patterns of weight gain (e.g., central fat accumulation) over longer time periods may provide additional insight into the potential benefits of promoting this eating pattern.
| FOOTNOTES |
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Manuscript received 24 March 2006. Initial review completed 3 May 2006. Revision accepted 31 August 2006.
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