The present meta-analysis is the first quantitative examination of the effect of food cue reactivity and craving on subsequent eating behavior and weight gain. Across 45 published studies and 69 reported statistics representing 3,292 participants, we found a significant medium effect (r = 0.33) of food cue reactivity and craving on eating and weight, measured prospectively with outcomes in the short-term and long-term. Our results demonstrate a robust prospective and predictive relationship between measures of food cue reactivity, including the conscious experience of craving and subsequent food-related outcomes. Further, we found consistent, medium effect sizes across several specific analyses, in confirmation of our hypotheses. In support of our first hypothesis that cue reactivity increases eating, we found that (i) exposure to food cues increases eating (‘cue condition’ studies) and (ii) the magnitude of physiological and neural cue reactivity to food cues relates prospectively to eating and weight gain over time (‘cue reactivity’ studies). In support of our second hypothesis, we found that magnitude of cue-induced craving relates prospectively to eating and weight gain. In support of our third hypothesis, we found that magnitude of tonic craving relates to eating and weight gain prospectively. We also found that real food and visual cues were both more strongly related to outcomes than olfactory cues and that BMI, age, dietary restraint and gender did not modify the strength of the findings. Overall, our results suggest that food cue reactivity and craving explain a substantial amount (7–26%) of the variance in food-related outcomes. In turn, this suggests a causal effect of cue exposure and craving on eating behavior and weight. Our results have important theoretical and methodological implications for the use and application of food cue reactivity paradigms, as well as implications for our understanding of obesity prevention and treatment.
Our work provides strong empirical support for the idea that exposure and reactivity to food cues, including craving, increase eating and weight, and thus may contribute to rising and persistent rates of obesity. Indeed, our findings are consistent with both conditioned, learning-based models [21-24] and their theoretical applications to obesity [80-84, 93, 94, 99, 141]. For instance, Jansen [8, 9] proposed that eating triggered by increased availability and advertising of food can lead to steady weight gain on a population level and interfere with the efficacy of obesity treatment. Although the increasing presence of food and food cues has been described as a ‘toxic food environment’ that causes a population-wide increase in BMI (e.g. [84, 88]), it has been difficult to determine causal relationships between the environment and obesity from cross-sectional studies . Importantly, our meta-analytic work demonstrates that responses to food cues systematically lead to subsequent eating and weight gain across both experimental and prospective studies, providing evidence of a consistent, predictive relationship on an individual level. Furthermore, these effects generalize across individual differences in BMI, age, dietary restraint and gender. Thus, our work supports the theory that, on a large scale, the abundance of food and food cues in the modern ‘toxic food environment’ may function as conditioned stimuli that serve as triggers for increased food consumption and can lead to weight gain on a population level [80-85, 93, 94, 99, 141].
Implications for obesity prevention and policy
By establishing the link between food cues and eating, our work can help build a framework to investigate how individual behavior is influenced by environment–level interventions. Because we find that exposure to food cues reliably leads to eating and weight gain, our work is consistent with the suggestion that exposure to food advertisements and increased access to unhealthy foods can have deleterious effects. In that, the findings support obesity prevention policies that reduce unhealthy food cue exposure, including limiting food advertisements or access to high-caloric, nutrient-poor foods. In one analysis, we specifically found that visual exposure to pictures or videos of food (such as in food advertising and commercials) increases eating behavior and weight, including several studies in the present meta-analysis that used real-life food advertisements as food cues in experimental settings [47, 48, 143]. Accordingly, this could support policy initiatives limiting television and print advertisements for energy dense products  as has been previously implemented for cigarettes [145, 146]. Our findings support the removal of cues to and availability of unhealthy foods in schools, an intervention that has already demonstrated some effectiveness in preventing unhealthy weight gain in children . Because we found that cue-related effects are similar in children and adults, these interventions may also be applicable for adults. Indeed, it has been shown that reducing the visibility of food cues in an office environment reduces consumption of unhealthy foods in adults . In sum, our work highlights a mechanism involved in food consumption that explains why a reduction in exposure to food cues can be an important target for obesity prevention policies.
Our work has methodological implications for the use and application of cue reactivity and craving paradigms. Learning-based models suggest that olfactory cues should be better predictors of food consumption than visual cues because olfactory cues are always present during food consumption and the conditioned stimulus that predicts the unconditioned stimulus best should elicit the strongest conditioned responses . Consistently, the use of visual stimuli has been criticized for failing to represent real-world food consumption, although it mirrors advertising for food (e.g. ). Nevertheless, we found that reactivity to visual food cues (e.g. pictures and videos) is as strongly predictive of eating behavior and weight gain as reactivity to real food (and that both are more strongly predictive than olfactory cues). That visual food cue exposure was as strongly associated with eating behavior as real food exposure suggests that cue-based learning processes are powerful for food. This finding is especially informative for neuroimaging studies that frequently use images to provoke craving [5, 53, 55, 150] and for studies that use images to investigate the regulation of craving [151, 152]. Overall, our findings support the ecological validity of a variety of food cues (including visual food cues) to elicit cue reactivity and craving and suggest that this directly relates to real-life behavior, because their effect on subsequent food-related outcomes is comparable with real food exposure.
Parallels with drug cue reactivity and addictions
As reviewed earlier, cue reactivity and craving for food and drugs share many similarities. In fact, it has been proposed that drugs ‘hijack’ a hedonic, dopamine-modulated reward system that originally evolved for food and that subserves processes including cue reactivity and craving for both food and drugs [5, 101, 153]. It is this system that is altered in addiction and may be altered in obesity and eating disorders [154-156]. Here, we report that food cue reactivity and craving predict eating and weight, which further parallels findings in addiction linking drug cue reactivity and craving to drug taking and clinical outcomes for addictive disorders [113, 121, 157]. However, despite such similarities, cue reactivity and craving are central aspects of the diagnosis and treatment of addictive disorders, whereas they are under-utilized in the context of eating behavior.
Some previous proposals to investigate similarities between food and addiction have focused on the concept of ‘food addiction’ and have been met with controversy [101-104]. We propose that continued construct-focused and mechanism-focused investigation into similarities between drug taking and eating behavior may be useful for illuminating shared processes across addictions and eating-related psychopathology (as proposed by the Research Domain Criteria framework ). Our work specifically suggests that cue reactivity and craving may be cross-diagnostic and clinically relevant. As such, they could be used to more accurately describe and measure eating behavior, as they have been in addictive disorders. This insight may further encourage the adoption of other paradigms from the addictions field to measure-related processes, such as regulation of craving, impulsivity and cognitive control. Such processes could explain additional variance in food-related outcomes and facilitate comparisons between food and drug-seeking behavior and related psychopathology.
In addition, our work is relevant to an ongoing debate in the addictions literature about the influence of cue-induced versus tonic craving on outcomes [159-163]. We found that both tonic and cue-induced craving were associated with subsequent eating and weight-related outcomes, suggesting that both of these forms of craving can serve a predictive function and may be useful to measure in clinical and treatment settings. Finally, these parallels suggest that treatment approaches for obesity and related disorders can draw from insights and findings already established for addiction, as elaborated in the succeeding discussion.
Treatment implications for obesity and related disorders
Our findings are consistent with and suggest explanatory mechanisms for the efficacy of pharmacological, behavioral and psychological treatments for obesity, eating disorders and addictions that both reduce craving and improve outcomes [73, 164-166]. For example, craving-targeting medications increase weight loss in overweight individuals, paralleling findings in addiction that demonstrate reductions in drug use with pharmacotherapy [167, 168]. Specifically, pharmacotherapies that reduce craving, such as bupropion and naltrexone, are associated with reduced self-reported craving and reduced BMI in weight loss trials [95, 169-172]. In addition, stimulants such as methylphenidate also reduce craving for and consumption of food . Similarly, in drug addiction, such pharmacotherapies reduce craving for and consumption of alcohol [174, 175], methamphetamine  and nicotine .
Several psychological treatments also target the associations between cue exposure, craving and food consumption, including cue exposure and response prevention treatments (CERP), cognitive behavioral therapy (CBT) and mindfulness-based therapies (MBTs). CERP attempts to extinguish associations between a cue, conditioned responses and a behavior by preventing the behavior from occurring in a cued context, consistent with learning models [8, 9]. Such exposures occur over prolonged periods (e.g. 60 min, multiple times per week), in contrast to the relatively short exposures used by studies included in this meta-analysis (e.g. ~10 min) [178-180]. Accordingly, prolonged exposure to chocolate cues , as well as smoking  and alcohol cues , reduces physiological reactivity in response to these cues. As a treatment, CERP also reduces self-reported craving  and binge eating in individuals with bulimia nervosa [178, 180, 184, 185]. However, extinction of cue-response pairings can be context-specific and may therefore still be reinstated in new environments [100, 186-189] or through incubation of craving , even after extinction, limiting the potential application of CERP. Consistently, clinical trials for CERP have been mixed for other eating disorders , obesity  and addictions [193, 194].
In contrast, other psychological treatment approaches assume that the association between food cues, craving and food consumption may not be perfectly extinguished and provide skills to manage diverse food-related contexts. For instance, CBT employs cognitive and behavioral strategies to reduce the influence of food cues and craving on eating behavior and weight. Cognitive strategies include the regulation of craving through cognitive reappraisal, which reduces neural reactivity and self-reported craving for high-calorie foods [116, 151, 152, 195], cigarettes [116, 151], alcohol , cocaine  and methamphetamine . Behavioral strategies to reduce the influence of food cues and craving in CBT include the following: determining the antecedents of eating behavior (e.g. food cues and craving), intervening to prevent consequences (i.e. food consumption), stimulus control (e.g. reduction of food cues in the personal environment), regular meal planning (to reduce vulnerability to food cues and craving) and exposure-based exercises (to reduce the salience of ‘trigger’ foods and contexts) . CBT is effective in the treatment of a wide range of conditions , including eating disorders [164, 201], obesity [202, 203] and drug addictions . Further, regulation of food craving specifically has been examined as part of obesity interventions for children  and adults , although this work is in its early stages. Finally, MBTs that teach individuals to notice and accept the experience of craving have demonstrated effectiveness at reducing craving for food and weight in both lean and obese adults [207-210] as well as reducing episodes of binge eating in individuals with binge eating disorder , bulimia nervosa [212, 213] or following bariatric surgery . In drug addiction, MBTs reduce craving and use of drugs [215-217], and reductions in craving reportedly mediate reductions in drug use [215, 217].
Overall, much evidence suggests that treatments that target cue-outcome associations and/or craving-outcome associations can reduce eating, improve weight outcomes and reduce drug use in addictions. We propose that the findings reported in this meta-analysis provide explanatory mechanisms for the efficacy of such treatments, although this should be investigated directly using mediation models in future clinical work (e.g. ). Such continued investigation into craving-targeted pharmacotherapy, behavioral treatment and psychotherapy for obesity and related disorders may increase the efficacy of existing treatment approaches.
Methodological issues and future work
One limitation of this meta-analysis is that it could not include all studies in the field; rather, it was inherently limited to studies that reported appropriate statistics. Unfortunately, approximately 20% of the studies that met our initial inclusion criteria were excluded because of limited or incomplete statistical reporting. This highlights the importance of reporting of sample size, means, standard deviations, test statistics and effect sizes in all future work, in order to increase accurate and transparent data reporting and to contribute to future meta-analyses and the overall development of the field.
Relatedly, we may not have been able to detect significant effects in some of our moderator analyses because of underreporting of group-based statistics or because of a small or imbalanced number of studies included in such analyses. Future work should continue to assess whether individual differences moderate the relationship between cue reactivity, craving and eating behavior as the number of published studies increases. This is especially important because some cross-sectional studies have demonstrated heightened cue reactivity in overweight individuals and restrained eaters (overweight: [1, 41, 218-220]; restrained: [17, 18, 30, 221]) as well as increased craving [19, 64, 222]. Further, failure to detect differences based on dietary restraint measurements may be due to inconsistent and varied measurement of dietary restraint across studies [223-225] (Supporting Information). If cross-sectional differences in BMI and dietary restraint extend to predictive relationships with eating and weight gain, then food cue reactivity and craving could serve as markers of increased risk for restrained eating or becoming overweight.
In addition, some of the effects we detected may be due to small or imbalanced numbers of studies included in moderator-based analyses. For instance, we detected a stronger effect in mixed gender than female-only samples, contrary to the suggestion that females are more cue reactive (e.g. ; Supporting Information). However, this comparison included almost double the number of mixed gender (NSTATISTICS = 42) compared with female-only statistics (NSTATISTICS = 26) and only one statistic in males. We hope that future studies will include more male-only and mixed-gender samples to further test for gender differences and will also test for any menstrual-cycle variations in females that may influence cue reactivity and craving. Similarly, we found that cue reactivity and craving were more strongly associated with long-term outcomes than short-term outcomes, which may also be attributable to an imbalanced number of studies (short-term: NSTUDIES = 35; long-term: NSTUDIES = 10). Future work could examine how far into the future the assessment of food cue responses and craving can predict outcomes and whether this is related to underlying trait-level individual differences.
Further, although a substantial literature suggests that appetitive conditioning increases, and depends upon, expectancy of reward (e.g. [227-231]), expectancy to eat did not affect the meta-analytic result (Supporting Information). Nevertheless, expectancy of food may be an important avenue for future work despite reported null effects on physiological reactivity to food cues , food craving  and food consumption [232, 233].
Finally, given the parallels drawn herein between food and drug cue reactivity and craving, it may be useful to statistically compare these effects in future work. Notably, one prior meta-analysis of craving and cigarette smoking found similarly sized predictive effects (rs = 0.20–0.34) . Future meta-analyses should directly compare the predictive effects of cue reactivity and craving on cigarettes-related, drug-related and food-related outcomes.