Toward a Better Understanding of the Influences on Physical Activity The Role of Determinants, Correlates, Causal Variables, Mediators, Moderators, and Confounders Adrian E. Bauman, PhD, James F. Sallis, PhD, David A. Dzewaltowski, PhD, Neville Owen, PhD Background: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. Methods and Results: We propose that the term ���correlate��� be used, instead of ���determinant,��� to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause���effect pathway between an intervention and physical activity are termed ���mediators.��� The relationship between an intervention and physical activity behaviors may vary for different groups the strata by which they vary are levels of ���moderators��� of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as ���confounders.��� Conclusions: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity. Medical Subject Headings (MeSH): behavior, causality, confounding factors, exercise, physical fitness, research design (Am J Prev Med 2002 23(2S):5���14) �� 2002 American Journal of Preventive Medicine Introduction A range of theories and models has been used to specify variables that are believed to influence physical activity and other behaviors. Research- ers test hypotheses derived from theories by (1) exam- ining associations among theoretically derived variables with behavior that help to ���understand and predict��� the behavior, and (2) evaluating interventions that are designed to modify the influences that are believed to lead to behavior change. There are hundreds of behav- ioral studies on physical activity, with great diversity in research designs, measurement approaches, popula- tions studied, theories used, variables tested, and phys- ical activity outcomes. This diversity makes it difficult to integrate the findings and summarize the status of the field, thus limiting the ability of subsequent research to build on previous findings. This paper is divided into several sections, the first describing the criteria for causal relationships, which draws mainly from epidemiologic methods. Definitions are then provided for the key terms and examples are used to illustrate them. The third section deals with correlates of physical activity and how well they are linked to theories of behavior change. The fourth section reflects on these terms from a behavioral sci- ence perspective. It is particularly difficult to integrate the results from associational and intervention studies. Part of this dif- From the School of Community Medicine and Public Health, Uni- versity of New South Wales (Bauman), Sydney, New South Wales, Australia Department of Psychology, San Diego State University (Sallis), San Diego, California Department of Kinesiology and Office of Community Health, Kansas State University (Dzewaltowski), Man- hattan, Kansas and School of Population Health, University of Queensland (Owen), Brisbane, Queensland, Australia Address correspondence to: Adrian Bauman, PhD, FAFPHM, Epi- demiology Unit, Hugh Jardine Building, Liverpool Hospital, LMB 7017, Liverpool BC 1871, New South Wales, Australia. E-mail: a.bauman@unsw.edu.au. 5 Am J Prev Med 2002 23(2S) 0749-3797/02/$���see front matter �� 2002 American Journal of Preventive Medicine ��� Published by Elsevier Science Inc. PII S0749-3797(02)00469-5

ficulty is due to the inconsistent use of terms and misuse of logical and empiric guidelines for ascertain- ing and describing causality. The primary aim of this paper is to recommend more standardized use of selected terms related to understanding the causation of physical activity behavior. It is hoped that clarifica- tion of terms will contribute to improvements in behav- ioral research on physical activity, with the explicit goal of enhancing the effectiveness of interventions. The Logic of Causality: Defining Correlates and Determinants Identifying factors that are associated with physical activity is a basic research concern. Many studies have attempted to explain and predict behavior, as well as to test hypotheses derived from specific theories. The research literature on physical activity is replete with findings of significant cross-sectional associations be- tween a range of personal, social, and environmental variables and levels of physical activity. These are usu- ally correlational studies, and might, for example, report that socioeconomic status or social supports are associated with physical activity behavior. Such relation- ships do not support causal inferences, but may gener- ate hypotheses for further study. This section is con- cerned with clarifying and defining the logical criteria for causal relationships, and distinguishing these from evidence of association or correlation. The logic of causality is fundamental to any study of factors that act to substantially increase the probability of an outcome. This kind of thinking is applied in disease-based epidemiologic studies. For example, what causes coronary heart disease? There is a constellation of probable causal variables that include physical inac- tivity, high cholesterol levels, tobacco use, and genetic factors. This group of factors in turn may contribute to microphysiologic changes. For example, physical activ- ity may reduce coronary heart disease risk through improvements in cardiac endothelial cell function, collateral circulatory changes, or through improved oxygen uptake.1,2 These cellular and biochemical changes are shown as B1, B2, B3 in Figure 1, and in turn these cause or prevent coronary heart disease occurrence. This is a causal pathway, where a behav- ioral change makes an impact on physiology, that in turn causes a reduction in disease occurrence. Note that a behavioral change could also have a negative causal impact on health: Adopting a sedentary lifestyle or poor diet could be causal factors for ill health. The causal pathways and methods of studying them in public health and behavioral interventions are less clearly identified. The causal or etiologic factor(s) may be public health interventions that are deliberate ef- forts at achieving change. Alternatively, causal factors may be naturalistic changes in policy or in physical or social environments that are not necessarily planned, but do induce (cause) changes in the outcomes of interest. The outcome might be a measurable change in health-related behavior, health system access, service utilization, or other outcomes of relevance to improv- ing public health. There are few examples of absolute causal factors that ���cause��� the outcome in 100% of cases, but none in the behavioral realm. In behavioral research, there is also the possibility of multiple causal factors (which might ���cause��� physical activity) and also reciprocal determinism, where the causal relationships are bi- directional���this makes discussion of traditional ���caus- al��� pathways more complex. Further, exposure to a factor does not ���inevitably��� lead to the behavioral outcome. Thus, etiologic variables in behavioral sci- ences are probabilistic factors that substantially in- crease the likelihood of the outcomes subsequently occurring, but do not ���guarantee��� them. The term ���determinant,��� as it has most typically been used in the physical activity research literature, is a misnomer. The majority of studies have used the term ���determinant��� in the context of findings that demon- strate reproducible associations or predictive relation- ships (correlates), rather than the more appropriate use of the term as a cause-and-effect relationship.3 It is recommended that the term ���determinant��� be used with greater precision and not be used to describe correlates of physical activity. Determinants are most appropriately defined as causal factors, and variations in these factors are fol- lowed systematically by variations in physical activity behavior. When researchers have the purpose of iden- tifying strategies that can be influenced to modify the outcome of interest, the proposed causal factor is generally referred to as the ���independent variable��� (or study factor) and the outcome or effect as the ���depen- dent variable.���4 The relationship is more likely to be causal when variation in physical activity (dependent variable) has been produced by changes in level or intensity of external influences (independent contrib- utory variables), such as exposure to an intervention. The discipline of epidemiology has developed crite- ria against which to assess the evidence for a causal relationship.5 The first is study design, with greatest scientific weight being given to experimental evidence, where a randomized controlled trial design is used. Figure 1. Causal pathways in health and disease 6 American Journal of Preventive Medicine, Volume 23, Number 2S