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Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Germany
2To whom correspondence should be addressed. E-mail: Bergmann{at}mail.dife.de.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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KEY WORDS: • dietary change • behavioral change • epidemiological methods • cohort studies • relative risk estimates
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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). Along with the migration to the United States, lifestyle factors and disease rates changed remarkably. Other evidence of the important role of lifestyle factors has come from time trends in disease rates. For example, stomach cancer, which was the most common cancer at the beginning of the past century in Europe and the United States, now ranks low (2
). Epidemiologic studies identified risk factors for which distribution changed over time and that therefore may be responsible for the decrease of this disease. The increase of lung cancer incidence in men and women during the past decades has a direct link with the time trends in smoking habits.
These examples illustrate the pronounced effects of changes in behavior and lifestyle on disease occurrence that often reflect global trends and span more than one generation. With the exception of body weight and smoking, it is not clear whether behavioral changes in adult life affect disease risk similarly to changes across generations. Health and nutrition guidelines are developed and distributed by scientists, the media, policy makers and producers; primary prevention goals are frequently formulated in nationwide health programs such as Healthy People 2010 (3
). Because of the publicity given to health goals, individuals start over time to consider and carry out these changes.
These behavioral changes affect epidemiologic research that uses prospective study designs, such as cohort and long-term intervention studies. An example of a cohort study with extensive data collection is the Nurses’ Health Study, which began in the early 1980s and will continue into the future (4
). An example of a large-scale intervention studies is the Alpha-Tocopherol Beta-Carotene Prevention Study, which had an intervention period of 5–8 y and is now in an ongoing observation period (5
). In both study types, the proportion of exposed subjects will change over time and the nature of the exposure itself will change. This will affect relative risk estimates because of exposure dilution and misclassification. Changes in behavior might affect intervention trials even more than do changes related to specific intervention measures.
Other distortions can be expected from factors that spur subjects to participate in an epidemiologic study. Studies with attractive research topics or desired intervention measures probably attract subjects who have already considered such changes. Results from such studies may be questionable with respect to external validity because the study may not appropriately reflect the situation in the entire population.
Therefore, methodological implications of behavioral changes as well as health effects due to these changes will have to become an important research topic in longitudinal studies. In this article, a particular focus is on dietary changes because diet is one of the most important determinants of health. Despite the high interest of public health officials in this topic and despite the changes that occur in the population, research into the nutritional epidemiology of dietary changes has been neglected. Because advanced theoretical concepts are missing and empirical data are scarce, we concentrate here on a description of key points.
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Empirical results on dietary change in the EPIC-Potsdam study |
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TOPABSTRACTINTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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). The Potsdam cohort comprises 27,548 inhabitants of the city of Potsdam and adjacent municipalities who were aged 35–64 y at baseline in 1994–1998. Of the invited individuals, 22% participated in the baseline examination (7
). The active follow-up is based on questionnaires that are mailed at 2-y intervals to each study participant and has a response rate of 
96% in each wave (8
). The first follow-up questionnaire included questions on changes in diet during the past 2 y, reasons for the change in diet and an open question about what was changed. The following results are based on questionnaires returned between July 1, 1997, and December 31, 2000. At that time 25,170 participants (92%) had replied, 11,726 (46%) of whom reported a change in diet during the follow-up period; this was 42% of the 9789 men and 49% of the 15,381 women. This proportion appears to be high and leads to suspicion about existing selection factors for the cohort. Selection factors that were previously described focused on sociodemographic variables, relative weight and smoking status (7
). The EPIC-Potsdam study participants obviously also were interested in diet and the prevention of chronic diseases. After the baseline examination, participants were given a general analysis of their diet as assessed with the food-frequency questionnaire. As a result of this dietary information, a higher proportion of participants than expected in the general population may have been inspired to make dietary changes. This high proportion of subjects who changed their diet offers a unique opportunity to investigate the future health benefits due to dietary changes in this cohort.
Weight problems (desired weight loss, avoiding weight gain) and the prevention or treatment of metabolic diseases were the most frequently reported reasons for a dietary change by men and women (Table 1
). However, the proportion of women who reported metabolic diseases as the reason for dietary change is much lower than that of men. Primary prevention was not an important reason for either gender; the proportion of those reporting this reason was <10%. To investigate the determinants of self-reported dietary change in the past 2 y (yes or partly vs. no), logistic regression models were used, controlling for all variables simultaneously (Table 2
). Participants most likely to report a change in diet were female, obese (body mass index 
30 and <35), those with <2 kg weight loss and those with 1 or more incidents of nutrition-related diseases. A positive response to the question of change in the diet during the 12 mo before baseline examination increased the probability twofold that the dietary change question was also answered positively at follow-up.
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More than 50% of the 10,745 men and women who gave information in the open question on what they have changed reported a higher intake in vegetables and fruits; 40% reported that they eat less fat, 33% reported a decrease in consumption of animal products and >25% reported an increase in fiber intake. The consumption of more low fat products and less sweets, sugar and cake was reported by 33% of the participants. More men than women reported an increase in fiber intake and a decrease in sweets, sugar and cake.
In general, these figures reflect more recent dietary recommendations, such as the 5-a-day plan for fruits and vegetables, as well as traditional recommendations, such as increasing fiber and decreasing fat in our diet. It remains open whether participants reported what they think that they would have to change about their diet or whether they reported real changes.
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Readiness to change |
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TOPABSTRACTINTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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–24
). Algorithms for assigning stages of change for three dietary goals (a low fat diet, a high fiber diet and a diet high in fruits and vegetables), for increase in physical activity (>30 min/d) and for cessation of smoking are available in the literature. All instruments distinguish the following stages: precontemplation (subjects have no intention of changing behavior in the foreseeable future or are not aware of having a problem), contemplation (subjects are aware that they have a problem and are seriously thinking about resolving it, however, not in the near future), preparation (the decision-making stage; subjects have made the commitment to take action within the next 30 d), action (subjects make notable overt efforts to change that meets an acceptable criterion, e.g., <30% energy from fat), maintenance [subjects work to stabilize their behavior and avoid relapse (for at least 6 mo)] (11
). In an overview of studies on stages of dietary change, Kristal et al. (13
) showed that the self-rated readiness of change is associated with the respective self-reported dietary behavior. This has been observed consistently across studies. The differences of the dietary behavior (e.g., fat % energy, g fiber/1000 kcal) were especially pronounced between the precontemplation and contemplation stages and between the action and maintenance stages. The authors said that the stage-of-change model is beneficial for measuring cognitive and behavioral engagement within the dietary change process. The action and the maintenance stages are when the individual develops and maintains cognitive and behavioral vigilance about healthful food choices. Cycling between the action and maintenance stages can be viewed positively because many new dietary behaviors are tried during this process that finally result in a healthy diet.
Boyle et al. (9
) found readiness to lower dietary fat intake and increase fruit and vegetable intake highly interrelated. Readiness for dietary changes was less associated with physical activity and not with cessation of smoking. These results were cross-sectional among health maintenance organization members. In a prospective study, the readiness to change physical activity and smoking behavior might depend on whether a person is able to maintain dietary changes. Unger (15
) showed that subjects in the more advanced stages of smoking cessation practiced more healthful levels of physical activity and alcohol consumption than did those in earlier stages. Furthermore, Boyle et al. (9
) found the readiness to change health behavior to be much higher in individuals with 1 or more chronic conditions. This is comparable to our results in which the report of dietary change was associated positively with a diagnosis of 1 or more incident nutrition-related diseases.
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Consequences of dietary change for epidemiologic research |
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TOPABSTRACTINTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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) found lower death rates among Harvard alumni who increased physical activity and stopped smoking than among those who continuously had low physical activity, smoked, changed to a low activity or started smoking. Also the systematic review of the effect of weight change on cancer risk and total mortality by a panel of experts revealed a changing weight status in adult life to be associated with a change of risk (26
). However, only a few studies were able to collect data and consider weight changes by the time of disease occurrence. Most studies obtained data on weight changes in a certain period at the beginning of the study and related these data to disease occurrence during an extended follow-up period. Therefore, any further weight changes during the follow-up period could not be considered in the risk estimates. Research that concentrates on the weight change issue realized that a distinction between intentional and unintentional weight loss is necessary. These two kinds of weight loss influence disease risk differently. Unintentional weight loss is often caused by morbidity that increases mortality risk. Therefore it seems mandatory to distinguish between these two types of change for all kinds of exposure measurement. To our knowledge, no studies distinguish between comparable types of dietary change (i.e., as reaction to an incident diagnosis or as intention to primarily prevent the development of a chronic condition) and their effects on disease risk.
Public health efforts focus on the adoption of dietary recommendations by the population. It is also known that physicians give advice on behavior change mainly to patients with existing conditions or risk factors (27
). These processes are comparable to a persistent low intensity intervention on a self-help level. Behavioral changes and particularly the cycling among the preaction, action and maintenance phases are a persistent characteristic in study populations in Western societies such as the EPIC-Postdam cohort.
To account for changes in exposure and confounding variables, repeated measurements are applied in most of the large cohort studies. However, not all assessment tools applied are able to identify whether the dietary change was morbidity induced, the dietary change was linked with a general change in behavior or the observed difference in dietary measures was due to measurement error. Only the separation of the three effects will enable cohort studies to contribute substantially to the evidence on whether behavior change during adulthood is beneficial for a healthy aging. To our knowledge, no study explicitly investigated this issue until now. For ongoing and future prospective studies, we therefore recommend incorporating into the dietary assessment tools screening questions that pick up dietary changes (28
) and that measure stages of change (13
). We have to acknowledge in nutritional epidemiology that diet is a moving target. Such acknowledgment would help researchers to produce better assessments of the effect of dietary changes on disease risk.
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FOOTNOTES |
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LITERATURE CITED |
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TOPABSTRACTINTRODUCTIONEmpirical results on dietary...Readiness to changeConsequences of dietary change...LITERATURE CITED |
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