- Open Access
Environmental influences on energy balance-related behaviors: A dual-process view
International Journal of Behavioral Nutrition and Physical Activity volume 3, Article number: 9 (2006)
Studies on the impact of the 'obesogenic' environment have often used non-theoretical approaches. In this journal's debate and in other papers authors have argued the necessity of formulating conceptual models for differentiating the causal role of environmental influences on behavior.
The present paper aims to contribute to the debate by presenting a dual-process view on the environment – behavior relationship. This view is conceptualized in the EnRG framework (Environmental Research framework for weight Gain prevention). In the framework, behavior is postulated to be the result of a simultaneous influence of conscious and unconscious processes. Environmental influences are hypothesized to influence behavior both indirectly and directly. The indirect causal mechanism reflects the mediating role of behavior-specific cognitions in the influence of the environment on behavior. A direct influence reflects the automatic, unconscious, influence of the environment on behavior. Specific personal and behavioral factors are postulated to moderate the causal path (i.e., inducing either the automatic or the cognitively mediated environment – behavior relation). In addition, the EnRG framework applies an energy balance-approach, stimulating the integrated study of determinants of diet and physical activity.
The application of a dual-process view may guide research towards causal mechanisms linking specific environmental features with energy balance-related behaviors in distinct populations. The present paper is hoped to contribute to the evolution of a paradigm that may help to disentangle the role of 'obesogenic' environmental factors.
Acknowledging the importance of discussions regarding the usefulness of current theories in the field of behavioral nutrition and physical activity, the IJBNPA has encouraged a debate on this issue . Jeffery  stated that current popular health behavior theories overestimate the role of cognitive determinants, and that models are needed that address relationships between the environment and behavior. In line with this call for an increased focus on the role of environmental factors, Brug and colleagues  proposed the development and application of behavior change theories that focus on how to promote action rather than mere motivation. Rothman  focused on the important role of intervention research in theory development and he argued that greater attention should be paid to the causal processes invoked by potential moderators of intervention effects. The present paper aims to contribute to the debate by integrating these calls and those of others (e.g., [5–7]) into one conceptual framework. A dual-process model is outlined that can be used to gain insight into the causal mechanisms that underlie the relationship between environmental influences and behavior. This paper will specifically focus on behaviors that may positively or negatively influence the energy balance. We will refer to these behaviors as 'energy balance-related behaviors' (EBRBs).
Toward a conceptual framework of determinants of EBRBs
The past decade, the importance of the 'obesogenic environment' has been highlighted [5, 8, 9]. However, recent reviews [10–12] have shown a lack of consistent results regarding the impact of environmental factors on EBRBs. A meta-analysis  confirmed the ambivalence in current empirical evidence. Based on sixteen studies, no single 'crude' environmental factor could be identified as consistently related to physical activity.
The evidence regarding environmental determinants of EBRBs collected to date has often been the result of non-theoretical approaches , which do not provide any knowledge on causal relationships between the identified associates of EBRB. Particularly, a lack of conceptual models for differentiating the causal role of environmental influences on behavior has been identified . As a result, Owen and colleagues  urged researchers to go beyond looking at environmental attributes on their own and to systematically study the most relevant environmental influences of physical activity behaviors. Using the application of knowledge mapping techniques, a panel of experts from diverse professional fields concluded that "research is needed to document the extent of environmental influences [on physical activity and dietary behaviors] and how they affect different individuals" ( p. S35, italics added). In order to do so, more conceptually refined models of how environments might affect behavior are necessary, such as whether they affect behavior directly or through mediating variables .
Dual-process view on environment-behavior relationship
Dual-process models in social psychology, such as the Elaboration Likelihood Model  and the MODE model  have conceived information processing as happening along a continuum. The anchors of this continuum reflect the 'duality' invoked by these models . On the one hand, people can utilize no cognitive effort, elaboration, or capacity in engaging in a particular act. Behaviour can be the result of direct 'automatic' responses to environmental cues . On the other hand, people can spend a great deal of time, effort and mental energy in systematically building beliefs and decisions. We postulate that the application of the dual-process view in the study of determinants of EBRB will help to gain insight into the circumstances under which EBRB is a conscious action or an action that is spontaneously or automatically performed under direct environmental control. Since it is inefficient to change cognitive factors regarding specific actions when these actions are unmediated by cognitions, such insights are highly relevant in order to inform intervention development.
In the following sections, the Environmental Research framework for weight Gain prevention (EnRG; Figure 1) is proposed as a dual-process model that can be used to gain insight into the most important determinants of EBRBs as well as into the causal mechanisms that underlie these behaviors. First the conceptualization of energy balance-related behavior and the 'obesogenic' environment is shortly outlined. Then, mediated and unmediated environment – behavior processes will be discussed, followed by a description of specific potential moderators of the environment – behavior relationship.
Energy balance-related behavior
Weight gain, overweight and obesity have been associated with various dietary behaviors such as a diet high in fat or carbohydrates and low in fiber, frequent snacking and frequent consumption of soft drinks containing sugar . Physical activity is of similar complexity, consisting of a large variety of behaviors such as transport-related behavior, work-related activities, leisure time activities, and sport participation . Low levels of physical activity as a part of daily routines have been particularly identified as weight gain-related risk behavior . Note that it is impossible to focus on any single factor as a universal causal factor in obesity. It is the co-existence and interaction of these specific nutrition and physical activity behaviors that determines whether or not positive energy balance and weight gain are experienced . Moreover, specific behavioral determinants of a positive energy balance will differ for different target groups (e.g. children; see ), emphasizing the importance of thorough epidemiological investigations. Such studies of behavioral causes of weight gain should form the basis for investigations of determinants of these particular behaviors (; see  for methodological considerations regarding this issue).
Various conceptualizations of the environment have been proposed, most of them specifically applied to either physical activity or diet. Three frameworks have specifically addressed potential environmental determinants of EBRBs. These models are the ANGELO framework (ANalysis Grid for Environments Linked to Obesity; ), the Framework for Determinants of Physical Activity and Eating Behavior  and the framework recently developed by the Committee on Prevention of Obesity in Children and Youth . These models do not make inferences on the causal mechanisms that link the environment to behavior, but they are useful in conceptualizing potential determinants.
Swinburn et al.  have tried to divide the variety in types of 'obesogenic' factors into four distinct types of influence: physical (what is available), economic (what are the costs), political (what are the rules), and sociocultural (what is the social and cultural background). In addition, two levels of influence are distinguished: micro-environmental settings and macro-environmental sectors. Individuals interact with the environment in multiple micro-environmental settings, including schools, workplaces, homes and neighborhoods, which are, in turn, influenced by broader macro-environments, including health systems, governments and the food industry. When types and level of environment are crossed, it forms a grid that comprises four types of environment on one axis and two sizes of environment on the other. The application of the ANGELO framework has proven useful to categorize determinants of physical activity and dietary behavior as well as current efforts in the field of environmental interventions with respect to these behaviors . With regard to the conceptualization of environmental factors, the EnRG framework has adopted the ANGELO grid. In order to guide the formulation of specific hypotheses regarding the working mechanisms of potentially relevant environmental factors, the EnRG framework explicitly postulates environmental factors to interact with each other (see Discussion section for an elaboration of this issue).
Mediated environmental influences
Health education research and related behavior change studies have mostly been focused on proximal, cognitive, determinants of health-related behaviors . A number of different theories and models have been proposed to study health-related behaviors, such as the Health Belief Model , Protection Motivation Theory , the Transtheoretical Model  and the Theory of Planned Behavior . Based on a review of current health behavioral change models, Baranowski and colleagues  concluded that the Theory of Planned Behavior (TPB) is the most useful model for investigating cognitive determinants in the field of weight gain prevention. In the TPB, attitude, subjective norm and perceived behavioral control are the central cognitive factors. These factors are believed to influence the behavioral intention, which is assumed to be the primary determinant of behavior. Indeed, there is a large body of evidence showing that these cognitive factors are indeed associated with intentions and behavior for many health behaviors, including EBRBs (see [32, 33] for reviews).
Some environments will mainly impact EBRB through its influence on attitude, other environments will mainly impact subjective norms and others will influence behavior through perceived behavioral control. For example, poor accessibility of health foods may reduce self-efficacy expectations towards healthy eating, high prices of health foods may have a negative impact on attitudes related to healthy eating, and poor availability of exercise opportunities may result in perceived norms that are negative towards physical activity. Changes in these cognitive factors are theorized to lead to changes in intention and subsequent behavior . Empirical evidence exists regarding the mediating role of cognitive factors such as attitude or perceived behavioral control of environmental factors on physical activity behavior [34, 35] and dietary behavior [36, 37]. A review of physical activity intervention studies that have incorporated cognitive mediators in their research design provides some evidence for the mediating role of self-efficacy in intervention effects . The mediated route from environment to behavior will hold in various instances, persons and behaviors studied. However, the cognitively mediated route does not always provide a sufficient account for variations in behavior. Studies that have combined environmental factors and TPB variables have shown that environmental factors have explained additional variance in behavior, over and above the cognitive factors (e.g., [35, 36, 38, 39]). Findings of this kind are sometimes explained in terms of methodological flaws , but we postulate unmediated environmental effects to be important explanatory mechanisms in the field of EBRB.
Unmediated environmental influences
The notion of least effort or limited capacity  has been suggested to result in 'mindless', automatic, processes. Since cognitive capacity is bounded and limited, automatic mental processes free one's conscious capacity from tasks in which they are no longer needed . In this view, it would be impossible to function effectively if individuals have to deal with every aspect in life, from perceptual comprehension of the environment to choosing and guiding every action and response to the environment, in a conscious, controlled, and aware fashion .
The research field of automaticity has been growing exponentially over the past few decades . Automatic processes can include attitude activation, automatic evaluation and emotion, unconscious behavioral mimicry, automatic trait and stereotype activation, and unconscious goal pursuit . Usually, individuals are unaware of the automatic environment – behavior link, but lack of awareness is a sufficient but not necessary condition for automaticity. There are four components of automaticity: lack of awareness, lack of control, efficiency and lack of intent , but not all four need to be present for a process to be automatic (and rarely are; ).
Since the line of research presented above has not been specifically tested in the EBRB domain, empirical evidence is limited. However, experimental studies, mostly executed in laboratory settings, have provided indications on the existence of unmediated environment – behavior links in EBRB. Here, we will present some of these studies in order to show a variety of types of potential automatic environment – behavior processes: automatically activated goal-directed behavior, behavioral mimicry, implementation intentions, and body feedback.
Aarts & Dijksterhuis  showed that when consistent choices are made to reach certain goals, the action is automatically activated upon the activation of the goal. In a student population, it was found that the presentation of the location 'university' automatically activated the travel mode 'bicycle use'. This 'university-bicycle link' was found to be difficult to suppress or control, indicating that active transport can become automatically associated with travel goals and thus bypass behavior-specific cognitive factors . Recent research has shown that consumer-related images (e.g. brands and their logos) can serve as environmental triggers of unconscious goals. Subliminal exposure to consumer brand logos has been found to influence consumers' actual behavior independently of previous behavior or existing brand-specific attitudes .
Investigations in the field of unconscious behavioral mimicry have shown that individuals can mimic gestures, postures and mannerisms, as well as consumption behavior (e.g., ). Ferraro et al. (see ) showed that participants in an experiment unconsciously mimicked a confederate's eating behavior (i.e. consumption of a specific type of crackers). Importantly, this study showed that, when asked to explain their dietary behavior, none of the participants mentioned the confederate in general, their eating behavior or the mimicry thereof in particular. Instead, they attributed their behavior to pre-existing evaluations and beliefs regarding the snack.
Studies with respect to 'implementation intentions' [45, 46] have provided supporting evidence regarding automatic environment – behavior relations. Implementation intentions are concrete plans of action that specify when, where and which actions should be taken to achieve an intended goal. Although this is a highly conscious action, the working mechanism of implementation intentions is postulated to involve an automatic behavioral response to specific environmental cues. Actions have gained a degree of automaticity by being under control of relevant situational cues . In the field of EBRB, Verplanken & Faes  demonstrated that implementation intentions to eat healthy were effective in establishing a more healthy diet, additive to the prediction of healthiness of eating by behavioral intentions. Armitage  showed in a controlled trial that fat intake, saturated fat intake, and the proportion of energy derived from fat decreased significantly in a group that formed an implementation intention regarding fat consumption but not in a control group. Notably, the difference between the experimental and control group could not be explained by differences in motivation.
Environments influencing body position or emotion may affect EBRB without individuals being aware of it. For example, Förster  showed that subjects who were asked to extend their arm (giving rise to bodily feedback associated with avoiding negative stimuli) consumed less cookies while watching a TV program for about 25 minutes than subjects who were asked to perform arm flexion (which gives rise to bodily feedback that signals a benign environment). Participants were not aware of the effect, and quality of taste, mood or feelings of pleasantness of the body position did not mediate the effect. Berridge and Winkielman  showed that thirsty participants exposed to subliminally presented happy faces (reflecting positive affective social environmental influences) consumed about 50% more of a fruit-flavored drink than thirsty participants who were exposed to subliminally presented neutral faces. Again, these individuals were unaware of the reaction at the moment it was caused.
In the EnRG framework, environmental influences are hypothesized to influence EBRB both indirectly and directly. The indirect causal mechanism reflects the mediating role of behavior-specific cognitions in the influence of the environment on behavior. The direct influence reflects the automatic, unconscious, influence of the environment on behavior. The postulation of behavior to be the result of a simultaneous influence of conscious and non-conscious processes represents the dual-process view. Various specific factors are postulated to moderate the causal path (i.e., inducing either the automatic or the cognitively mediated environment – behavior relation).
As argued in previous sections, EBRBs are likely to be complex. Consequently, the presence of interaction terms seems to be likely, and, as Baranowski et al.  argued, these terms should be sought. To the extent that one wishes to increase insights into causal pathways beyond the limits of models such as the TPB, it is useful to explore the more complex interactions involved in the mechanisms underlying the behaviors in question . In the EnRG framework, the level of cognitive mediation of the environmental influences on behavior is postulated to differ along the lines of person- and behavior-related factors. Note that these factors can influence the level of cognitive mediation by either moderating the environment – cognition relation (i.e., the extent to which the environment induces behavior-specific cognitions) or the cognition – behavior relation (i.e., the extent to which the cognitions lead to actual engagement in the behavior). Six types of factors are specifically proposed: demographic factors, personality, awareness, involvement, habit strength and engagement in clustered behavior. The rationale for including these potential moderators in the framework is elaborated below.
It has been suggested that environmental factors may have differential effects on various demographic sub-groups of the population [13, 53]. Although few studies have systematically explored this moderating role of demographic factors in the environment – behavior relationship, an increasing body of evidence shows the differential impact of the environment on EBRB with respect to gender [54–58], age , socioeconomic status [59, 60] and ethnicity [61, 62].
Few studies have combined the personality construct with environmental factors in the prediction of EBRBs. However, consistent evidence shows that the personality factor 'extraversion' moderates the intention – behavior relationship, with more extraverted individuals displaying more consistency [63, 64]. This result, which is particularly profound in the physical activity domain, suggests that less extraverted individuals may withdraw from opportunities or they may lack social environments necessary for intention translation . A recent study among adolescents suggested a potential moderating role of the personality factors 'agreeableness' and 'openness to experience' in fruit and vegetable consumption .
Awareness of personal behavior status is likely to influence the level of cognitive energy that is put into intentions to change current EBRBs [67–69]. For example, if a person is not accurately aware of personal physical activity levels, this might lead to a false positive conclusion regarding the compliance with recommended levels. Consequently, unaware individuals lack a sense of urgency, which is hypothesized to lead to an attentional bias regarding relevant environmental cues.
Involvement can be viewed as the most important feature of the concept of motivation (see e.g., ), and refers to "... the complexity or extensiveness of cognitive and behavioral processes characterizing the overall... decision process" ( p. 185). If individuals are not involved in a particular behavior, they tend not to put much energy in the decision process . Absence of conscious reflections on behavior is likely to make an individual susceptible to environmental influences, leading to 'spontaneous' execution of behavior .
Many EBRBs, such as playing outside after school or watching TV for children or taking the bicycle to work for adults, are typically routine behaviors. They are repeatedly performed and may thus be largely determined by habit. Consequently, the concept of habit strength is important in studying these behaviors . Studies have shown that when certain behavior becomes a strong habit, it may follow automatically upon encountering the relevant environmental cues . Thus, the degree of automaticity of a particular environment – behavior relationship will strongly depend on the stability of the environmental cue and on the habitual level of the behavior in question.
Engagement in clustered behavior
Studies have shown correlations between physical activity and a prudent diet , dietary fat , fiber and sucrose intake  and fruit and vegetable consumption [77, 78], with active individuals having healthier diets. In a sample of adolescents, fruit consumption was found to be positively associated with physical activity during leisure time, and snacking behavior was positively related to using high-fat sandwich fillings . Epidemiologists label the co-occurrence of behaviors as 'clustering' if a combination of behaviors is more prevalent than can be expected on the basis of the prevalence of the separate behaviors . Clustering of behaviors within the energy balance provides evidence for the surplus value of studying multiple clustered behaviors rather than studying behaviors in isolation. For example, EBRBs can be executed simultaneously (e.g., consuming potato chips while watching TV). When specific acts are clustered, they may be simultaneously influenced by identical environmental factors.
Some authors have proposed models that aim to clarify causal relationships between environmental factors and physical activity behaviors (e.g., [80–83]). Similarly, models have been developed for environmental influences on dietary behaviors (e.g., ). These models differ substantially on proposed causal mechanisms, specific behavioral acts and target groups. Interestingly, some of these models include notions of dual-processes (e.g., [82–84]), though often not stated explicitly. However, no postulations are made regarding circumstances under which direct or mediated environmental influences will take place. Moreover, these models lack the energy balance-approach, i.e. a focus on both dietary and physical activity behaviors. In previous papers, we have argued that applying such an approach will have multiple benefits, both for determinant studies  and intervention programs .
Critics (we recommend  in this respect) would argue the uselessness of applying a dual-process view, because of a lack of definite proof of its usefulness in the study of determinants or the design of interventions in the field of obesity prevention. In addition, the proposed framework is so broadly defined that it does not generate clear hypotheses regarding specific influential environmental factors. Although we have indications from studies within the NHF-NRG project  that the framework does provide an illuminative view on environment – behavior processes and on the development and evaluation of interventions aimed at the prevention of weight gain, future studies are clearly needed to show its usefulness. The EnRG framework, in fact, is the result of an inductive reasoning process. In contrast, deductive reasoning (i.e., moving from a general model to specific observations) is now needed to narrow down the framework to specific testable hypotheses. Thus, the most desirable goal is not the validation of EnRG in its present form but in the evolution of a paradigm that may help to disentangle the role of 'obesogenic' environmental factors (see also ).
Rather than focusing on which factors may be of importance, the EnRG framework is specifically directed at generating questions related to when, how and for whom environmental factors may be influential. To illustrate this, we will present a set of research questions that can be derived from the EnRG framework. For example:
* How do prompts influence stair use?
Interventions to promote stair use have frequently and successfully applied the strategy of 'prompting', for example using posters with short messages (see  for a review). Prompts appear to bring existing beliefs into consciousness, without requiring substantial levels of attention or intention. Prompts can be presented with or without providing a reason ('take the stairs', versus 'taking the stairs is healthy'). Some studies have shown that providing prompts regarding strong beliefs (e.g., 'taking the stairs is healthy') are more effective than those referring to weaker beliefs (e.g., 'taking the stairs saves electricity') , indicating the involvement of conscious processing of arguments. However, other studies found no differences between the effectiveness of strong and weak beliefs  and a study on environmentally destructive behaviour (walking on a lawn) showed that mere announcement of reasons to act had no effect beyond that already induced by a response-specific prompt . The latter result supports the notion that prompts serve as a peripheral cue rather than as a cue that involves central, conscious, information processing . Insights into these working mechanisms will help intervention designers to optimize their interventions, and to select appropriate target groups and settings.
Other relevant examples of research questions that can be derived from the EnRG framework are:
* How do parental home rules regarding TV- and computer-use determine the screen-viewing behavior of their children?
* For whom are price reductions of fruits at the worksite influential in changing total fruit intake?
* Under which circumstances does the availability of sidewalks influence walking behavior of elderly?
The EnRG framework guides the formulation of specific hypotheses regarding the impact of moderators of environmental influences. For example:
* Parental home rules regarding screen-viewing will have direct impact on adolescents that score high on the personality dimension 'Agreeableness', while the impact will be mediated by social cognitions in adolescents scoring low on this personality characteristic.
* Information on the number of calories in a snack will lead to cognitive processing in those individuals that are highly involved in dietary behavior, while peripheral cues (e.g., color, smell, position on shelf) will have a direct impact on behavior in individuals that are uninvolved.
* The availability of fruit at home will have a direct relation to fruit consumption when this behavior is habitual, but a cognitively mediated impact when fruit consumption behavior is not habitual.
* The impact of the availability of snacks in a school will depend on the price of these snacks.
The latter example is provided in order to illustrate the postulate that types and levels of environments do not operate in isolation, but they are likely to interact. Although empirical evidence regarding such interactions in the field of EBRBs is scarce, studies in the field of child development have shown that the impact of micro-level factors on individual behavioral developmental variability can vary as a function of contextual macro-level conditions . The existence of such 'higher order moderation' has also been suggested in the field of EBRBs. For example, the impact of behavior-specific parenting practices has been hypothesized to be moderated by general parenting styles . A major challenge for future empirical applications of the EnRG framework will be to document under what conditions higher order environmental moderation is most or least likely to occur (see also ).
We advocate the application of methodological triangulation  in the operationalization of the proposed dual-process view. Multiple types of research are needed, as well as the application of both objective and subjective measures of environmental and behavioral factors. Since environmental factors are postulated to be capable of influencing behavior without individuals being consciously aware of them, researchers cannot only rely on subjective measures of the environment. On the other hand, the individual perception of the nature of the environment, rather than the actual environment, will be critical in determining the mediated route of environmental influences on behavior. In addition, we advocate the use of multiple research designs. Although the EnRG framework is proposed to guide formulation of research questions in specific studies, no single analysis can fully apply or test it. It is the integration of results from cross-sectional studies, cohort studies, large-scale field interventions and small-scale laboratory experiments that is needed to answer hypotheses derived from the framework.
Studies on the impact of the obesogenic environment have often used non-theoretical approaches. Contributions to the Theory Debate of this journal called for formulations of theories with factors that are unmediated by social cognitions, with increased emphasis on environmental determinants and a focus on potential moderators. These calls fit well within the dual-process view that is incorporated in the EnRG framework. In addition, EnRG applies an energy balance-approach, stimulating the integrated study of determinants of diet and physical activity. The framework may guide research towards causal mechanisms linking specific environmental features with EBRBs in distinct populations. Furthermore, EnRG can inform the design of interventions as well as the formulation of evaluation protocols. Notably, the framework requires the assessment of cognitive mediators and potential moderators in order to illuminate the causality of intervention effects.
French SA, Worsley T: What is the role of theory in health behavior change interventions?. Int J Behav Nutr Phys Act. 2004, 1: 9-
Jeffery RW: How can Health Behavior Theory be made more useful for intervention research?. Int J Behav Nutr Phys Act. 2004, 1: 10-
Brug J, Oenema A, Ferreira I: Theory, evidence and Intervention Mapping to improve nutrition and physical activity interventions. Int J Behav Nutr Phys Act. 2005, 2: 2-
Rothman AJ: "Is there nothing more practical than a good theory?": Why innovations and advances in health behavior change will arise if interventions are used to test and refine theory. Int J Behav Nutr Phys Act. 2004, 1: 11-
Booth SL, Ritenbaugh C, Sallis JF, Hill JO, Birch LL, Frank LD, Glanz K, Himmelgreen DA, Mudd M, Popkin BM, Richard KA, StJeor S, Hays NP: Environmental and societal factors affect food choice and physical activity: Rationale, influences, and leverage points. Nutr Rev. 2001, 59: S21-S39.
Baranowski T, Cullen KW, Nicklas T, Thompson D, Baranowski J: Are current health behavioral change model helpful in guiding prevention of weight gain efforts?. Obes Res. 2003, 11: 23S-43S.
Owen N, Humpel N, Leslie E, Bauman A, Sallis JF: Understanding environmental influences on walking. Review and research agenda. Am J Prev Med. 2004, 27: 67-76.
Sallis JF, Bauman A, Pratt M: Environmental and policy interventions to promote physical activity. Am J Prev Med. 1998, 15: 379-397.
Swinburn B, Egger G, Raza F: Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med. 1999, 29: 563-570.
McCormack G, Giles-Corti B, Lange A, Smith T, Martin K, Pikora TJ: An update of recent evidence of the relationship between objective and self-report measures of the physical environment and physical activity behaviours. J Sci Med Sport. 2004, 7 (1 Suppl): 81-92.
Ferreira I, Van der Horst K, Wendel-Vos W, Kremers S, Van Lenthe F, Brug J: Potential environmental determinants of physical activity in youth. Environmental determinants and interventions for physical activity, nutrition and smoking: A review. Edited by: Brug J, Van Lenthe F. 2005, Zoetermeer: Speed-Print, 32-76.
Van der Horst K, Oenema A, Ferreira I, Wendel-Vos W, Giskes K, Brug J: Potential environmental determinants of selected dietary behaviours in youth. Environmental determinants and interventions for physical activity, nutrition and smoking: A review. Edited by: Brug J and Van Lenthe F. 2005, Zoetermeer: Speed-Print, 168-202.
Duncan MJ, Spence JC, Mummery WK: Perceived environment and physical activity: a meta-analysis of selected environmental characteristics. Int J Behav Nutr Phys Act. 2005, 2: 11-
Humpel N, Owen N, Leslie E: Environmental factors associated with adults' participation in physical activity: a review. Am J Prev Med. 2002, 22: 188-199.
Petty RE, Cacioppo JT: Communication and persuasion, central and peripheral routes to attitude change. 1986, New York: Springer-Verlag
Fazio RH: Multiple processes by which attitudes guide behaviour: The MODE model as an integrative framework. Advances in experimental social psychology. Edited by: Zanna MP. 1990, San Diego, CA: Academic Press, 23: 75-109.
Moskowitz GB, Skurnik I, Galinski AD: The history of dual-process notions, and the future of preconscious control. Dual Process Theories in Social Psychology. Edited by: Chaiken S, Trope Y. 1999, New York: Guilford Press, 12-36.
Bargh JA, Chartrand TL: The unbearable automaticity of being. Am Psychol. 1999, 54: 462-479.
World Health Organisation/UN Food and Agriculture Organisation: Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. 2003, Geneva: World Health Organization
Troiano RP, Macera CA, Ballard-Barbash R: Be physically active each day. How can we know?. J Nutr. 2001, 131: 451S-460S.
Westerterp KR: Pattern and intensity of physical activity. Nature. 2001, 410: 539-
Hill JO, Wyatt HR, Melanson EL: Genetic and environmental contributions to obesity. Med Clin North Am. 2000, 84: 333-345.
Rennie KL, Johnson L, Jebb SA: Behavioural determinants of obesity. Best Pract Res Clin Endocrinol Metab. 2005, 19: 343-358.
Kremers SPJ, Visscher TLS, Seidell JC, Van Mechelen W, Brug J: Cognitive determinants of energy balance-related behaviours: Measurement issues. Sports Med. 2005, 35: 923-933.
Koplan JP, Liverman CT, Kraak VI: Health in the balance. 2005, Washington DC: The National Academies Press
Brug J, Van Lenthe F: Environmental determinants and interventions for physical activity, nutrition and smoking: A review. 2005, Zoetermeer: Speed-Print
Crosby RA, Kegler MC, DiClemente RJ: Understanding and applying theory in health promotion practice and research. Emerging Theories in Health Promotion Practice and Research: Strategies for Improving the Public Health. Edited by: DiClemente RJ, Crosby RA, Kegler MC. 2002, San Francisco, CA: Josey-Bass
Janz NK, Becker MH: The health belief model: A decade later. Health Educ Quart. 1984, 11: 1-47.
Maddux JE, Rogers RW: Protection motivation and self-efficacy: A revised theory of fear appeals and attitude change. J Exp Soc Psychol. 1983, 19: 469-79.
Prochaska JO, DiClemente CC: Stages and processes of self-change of smoking: Toward an integrative model of change. J Consult Clin Psychol. 1983, 51: 295-304.
Ajzen I: Attitudes, Personality, and Behavior. 1988, Milton Keynes: Open University Press
Godin G, Kok G: The theory of planned behavior: a review of its applications to health behaviors. Am J Health Promot. 1996, 11: 87-98.
Armitage CJ, Conner M: Efficacy of the theory of planned behavior: a meta-analytic review. Br J Soc Psychol. 2001, 40: 471-499.
Brassington GS, Atienza AA, Perczek RE, DiLorenzo TM, King AC: Intervention-related cognitive versus social mediators of exercise adherence in the elderly. Am J Prev Med. 2002, 23 (2S): 80-86.
Prodaniuk TR, Plotnikoff RC, Spence JC, Wilson PM: The influence of self-efficacy and outcome expectations on the relationship between perceived environment and physical activity in the workplace. Int J Behav Nutr Phys Act. 2004, 1: 7-
De Bruijn GJ, Kremers SPJ, Van Mechelen W, Schaalma H, Brug J: Determinants of adolescent bicycle use for transportation and snacking behavior. Prev Med. 2005, 40: 658-667.
Martens M, Van Assema P, Brug J: Why do adolescents eat what they eat? Personal and social environmental predictors of fruit, snack and breakfast consumption among Dutch 12 14-year-old students. Public Health Nutr. 2005, 8 (8): 1258-65.
Lewis BA, Marcus BH, Pate RR, Dunn AL: Psychosocial mediators of physical activity behavior among adults and children. Am J Prev Med. 2002, 23 (2S): 26-35.
De Bourdeaudhuij I, Sallis J: Relative contribution of psychosocial variables to the explanation of physical activity in three population-based adult samples. Prev Med. 2002, 34: 279-288.
Ajzen I, Fishbein M: Attitudes and the attitude-behavior relation: Reasoned and automatic processes. Eur Rev Soc Psychol. 2001, 11: 1-33.
Chartrand TL: The role of conscious awareness in consumer behaviour. J Cons Psychol. 2005, 15: 203-210.
Bargh JA: The four horsemen of automaticiy: Awareness, intention, efficiency and control in social cognition. The handbook of social cognition. Edited by: Wyer Jr RS, Srull TK. 1994, Hillsdale, NJ: Lawrence Erlbaum Associates, Inc, 1-40.
Aarts H, Dijksterhuis A: The automatic activation of goal-directed behaviour: The case of travel habit. J Environ Psychol. 2000, 20: 75-82.
Johnston L: Behavioral mimicry and stigmatization. Soc Cogn. 2002, 20: 18-35.
Gollwitzer PM: Goal achievement: The role of intentions. Eur Rev Soc Psychol. 1993, 4: 141-185.
Gollwitzer PM: The volitional benefits of planning. In The psychology of action: Linking cognition and motivation to behavior. Edited by: Gollwitzer PM, Bargh JA. 1996, London: Guilford Press
Bargh JA, Gollwitzer PM: Environmental control of goal-directed action: Automatic and strategic contingencies between simulations and behavior. Nebraska Symposium on Motivation. 1994, 41: 71-124.
Verplanken B, Faes S: Good intentions, bad habits, and effects of forming implementation intentions on healthy eating. Eur J Soc Psychol. 1999, 29: 591-604.
Armitage CJ: Evidence that implementation intentions reduce dietary fat intake: a randomized trial. Health Psychol . 2004, 23: 319-323.
Förster J: The influence of approach and avoidance motor actions on food intake. Eur J Soc Psychol. 2003, 33: 339-350.
Berridge KC, Winkielman P: What is unconscious emotion? (The case of unconscious "liking"). Cogn Emot. 2003, 17: 181-211.
Fuhrmann A, Kuhl J: Maintaining a healthy diet: Effects of personality and self-reward versus self-punishment on commitment to and enactment of self-chosen and assigned goals. Psychol Health. 1998, 12: 651-686.
Sallis JF, Hovell MF, Hofstetter CR: Predictors of adoption and maintenance of vigorous physical activity in men and women. Prev Med. 1992, 21: 237-251.
Foster C, Hillsdon M, Thorogood M: Environmental perceptions and walking in English adults. J Epidemiol Community Health. 2004, 58: 924-928.
Humpel N, Marshall AL, Leslie E, Bauman A, Owen N: Changes in neighborhood walking are related to changes in perceptions of environmental attributes. Ann Behav Med. 2004, 27: 60-67.
Humpel N, Owen N, Iverson D, Leslie E, Bauman A: Perceived environment attributes, residential location, and walking for particular purposes. Am J Prev Med. 2004, 26: 119-125.
Bengoechea EG, Spence JC, McGannon KR: Gender differences in perceived environmental correlates of physical activity. Int J Behav Nutr Phys Act. 2005, 2: 12-
Suminski RR, Carlos Poston WS, Petosa RL, Stevens E, Katzenmoyer L: Features of the neighborhood environment and walking by U.S. adults. Am J Prev Med. 2005, 28: 149-155.
Chinn DJ, White M, Harland J, Drinkwater C, Raybould S: Barriers to physical activity and socioeconomic position: implications for health promotion. J Epidemiol Community Health. 1999, 53: 191-192.
Giles-Corti B, Donovan RJ: Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment. Prev Med. 2002, 35: 601-611.
King AC, Castro C, Wilcox S, Eyler AA, Sallis JF, Brownson RC: Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-aged and older-aged women. Health Psychol. 2000, 19: 354-364.
Eyler AA, Matson-Koffman D, Rohm Young D, Wilcox S, Wilbur J, Thompson JL, Sanderson B, Evenson KR: Quantative study of correlates of physical activity in women from diverse racial/ethnic groups. Am J Prev Med. 2003, 25 (3Si): 93-103.
Rhodes RE, Courneya KS, Hayduk LA: Does personality moderate the theory of planned behavior in the exercise domain?. J Sport Exerc Psychol. 2002, 24: 120-132.
Rhodes RE, Courneya KS, Jones LW: The theory of planned behavior and lower-order personality traits: interaction effect in the exercise domain. Pers Ind Diff. 2005, 38: 251-265.
Rhodes RE, Courneya KS, Jones LW: Personality and social cognitive influences on exercise behavior: Adding the activity trait to the theory of planned behavior. Psychol Sport Exerc. 2004, 5: 243-254.
De Bruijn GJ, Kremers SPJ, Van Mechelen W, Brug J: Is personality related to fruit and vegetable intake and physical activity in adolescents?. Health Educ Res. 2005, 20: 635-644.
Brug J, Van Assema P, Lenderink T, Glanz K, Kok GJ: Self-rated dietary fat intake: association with objective assessment of fat, psychosocial factors and intention to change. J Nutr Educ. 1994, 26: 218-223.
Lechner L, Brug J, De Vries H: Misconceptions of fruit and vegetable consumption. J Nutr Educ. 1997, 29: 313-320.
Bogers RP, Brug J, van Assema P, Dagnelie PC: Explaining fruit and vegetable consumption: the theory of planned behaviour and misconception of personal intake levels. Appetite. 2004, 42: 157-166.
Houston MJ, Rothschild ML: Conceptual and methodological perspectives in involvement. Research frontiers in marketing: dialogues and directions. Edited by: Jain S. 1978, Chicago: American Marketing Association
Kremers SPJ, Mudde AN, De Vries NK, Brug J, De Vries H: Unplanned smoking initiation: New insights and implications for interventions. Patient Educ Counsel. 2004, 55: 345-352.
Fazio RH, Towles-Schwen T: The MODE-model of attitude-behavior processes. Dual Process Theories in Social Psychology. Edited by: Chaiken S, Trope Y. 1999, New York: Guilford Press
Aarts H, Paulussen T, Schaalma H: Physical exercise habit: On the conceptualization and formation of habitual health behaviours. Health Educ Res. 1997, 12: 363-374.
Raitakari OT, Leino M, Rakkonen K, Porkka KV, Taimela S, Rasanen L, Viikari JS: Clustering of risk habits in young adults: the Cardiovascular Risk in Young Finns Study. Am J Epidemiol. 1995, 142: 36-44.
Simoes EJ, Byers T, Coates RJ, Serdula MK, Mokdad AH, Heath GW: The association between leisure-time physical activity and dietary fat in American adults. Am J Public Health. 1995, 85: 240-244.
Haraldsdottir J, Andersen LB: Dietary factors related to fitness in young men and women. Prev Med. 1994, 23: 490-497.
Johnson MF, Nichols JF, Sallis JF, Calfas KJ, Hovell MF: Interrelationships between physical activity and other health behaviors among university women and men. Prev Med. 1998, 27: 536-544.
Schuit AJ, Van Loon AJ, Tijhuis M, Ocke M: Clustering of lifestyle risk factors in a general adult population. Prev Med. 2002, 35: 219-224.
Kremers SPJ, De Bruijn GJ, Schaalma H, Brug J: Clustering of energy balance-related behaviours and their intrapersonal determinants. Psychol Health. 2004, 19: 595-606.
Welk GJ: The youth physical activity promotion model: A conceptual bridge between theory and practice. Quest. 1999, 51: 5-23.
Garcia Bengoechea E, Johnson G: Ecological systems theory and children's development in sport: Toward a process-person-context-time research paradigm. Avante. 2000, 7: 20-31.
Pikora T, Giles-Corti B, Bull F, Jamrozik K, Donovan R: Developing a framework for assesment of environmental determinants of walking and cycling. Soc Sci Med. 2003, 56: 1693-1703.
Spence JC, Lee RE: Toward a comprehensive model of physical activity. Psychol Sport Exerc. 2003, 4: 7-24.
Glanz K, Sallis JF, Saelens BE, Frank LD: Healthy nutrition environments: Concepts and measures. Am J Health Promot. 2005, 19: 330-333.
Kremers SPJ, Visscher TLS, Brug J, Chin A, Paw MJM, Schouten EG, Schuit AJ, Seidell JC, Van Baak MA, Van Mechelen W, Kemper HCG, Kok FJ, Saris WHM, Kromhout D: Netherlands Research programme weight Gain prevention (NHF-NRG): Rationale, objectives and strategies. Eur J Clin Nutr. 2005, 59: 498-507.
Oxman AD, Fretheim A, Flottorp S: The OFF theory of research utilization. J Clin Epidemiol. 2005, 58: 113-116.
Bronfenbrenner U: Environments in developmental perspective: Theoretical and operational models. Measuring environment across the life span: Emerging methods and concepts. Edited by: Friedman SL, Wachs TD. 1999, Washington, DC: American Psychological Association, 3-28.
Foster C, Hillsdon M: Changing the environment to promote health-enhancing physical activity. J Sports Sci. 2004, 22: 755-769.
Jager W, Boers S, Eckringa C, Westerhof JD: The efficacy of prompting in changing habitual behavior [in Dutch]. Neth J Psychol. 1996, 51: 173-182.
Adams J, White M: A systematic approach to the development and evaluation of an intervention promoting stair use. Health Educ J. 2002, 61: 272-286.
Smith JM, Bennett R: Several antecedent strategies in reduction of an environmentally destructive behavior. Psychol Reports. 2002, 70: 241-242.
Friedman SL, Wachs TD: Measuring environment across the life span: Emerging methods and concepts. 1999, Washington, DC: American Psychological Association
Kremers SPJ, Brug J, De Vries H, Engels RCME: Parenting style and adolescent fruit consumption. Appetite. 2003, 41: 43-50.
Wachs TD: Celebrating complexity: Conceptualization and assessment of the environment. Measuring environment across the life span: Emerging methods and concepts. Edited by: Friedman SL, Wachs TD. 1999, Washington, DC: American Psychological Association, 357-392.
Denzin NK: The research act: A theoretical introduction to sociological methods. 1978, New York: McGraw-Hill, 2
This study is part of the NHF-NRG project. NHF-NRG (Netherlands Research program weight Gain prevention) is funded by the Netherlands Heart Foundation (Top Down Project 2000z002).
The author(s) declare that they have no competing interests.
SK initiated this paper and wrote the first draft. GJdB, TV, WvM, NdV and JB discussed the draft paper with SK and provided written comments.
Authors’ original submitted files for images
Below are the links to the authors’ original submitted files for images.
Rights and permissions
Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Kremers, S.P., de Bruijn, GJ., Visscher, T.L. et al. Environmental influences on energy balance-related behaviors: A dual-process view. Int J Behav Nutr Phys Act 3, 9 (2006). https://doi.org/10.1186/1479-5868-3-9
- Environmental Influence
- Physical Activity Behavior
- Dietary Behavior
- Implementation Intention
- Weight Gain Prevention