Compared to vegans, meat consumers experienced both lower depression & anxiety; the more rigorous the study, the more positive and consistent the relation between meat consumption and better mental health

Meat and mental health: A meta-analysis of meat consumption, depression, and anxiety. Urska Dobersek et al. Critical Reviews in Food Science and Nutrition, Oct 6 2021. https://www.tandfonline.com/doi/full/10.1080/10408398.2021.1974336

Abstract: In this meta-analysis, we examined the quantitative relation between meat consumption or avoidance, depression, and anxiety. In June 2020, we searched five online databases for primary studies examining differences in depression and anxiety between meat abstainers and meat consumers that offered a clear (dichotomous) distinction between these groups. Twenty studies met the selection criteria representing 171,802 participants with 157,778 meat consumers and 13,259 meat abstainers. We calculated the magnitude of the effect between meat consumers and meat abstainers with bias correction (Hedges’s g effect size) where higher and positive scores reflect better outcomes for meat consumers. Meat consumption was associated with lower depression (Hedges’s g = 0.216, 95% CI [0.14 to 0.30], p < .001) and lower anxiety (g = 0.17, 95% CI [0.03 to 0.31], p = .02) compared to meat abstention. Compared to vegans, meat consumers experienced both lower depression (g = 0.26, 95% CI [0.01 to 0.51], p = .041) and anxiety (g = 0.15, 95% CI [-0.40 to 0.69], p = .598). Sex did not modify these relations. Study quality explained 58% and 76% of between-studies heterogeneity in depression and anxiety, respectively. The analysis also showed that the more rigorous the study, the more positive and consistent the relation between meat consumption and better mental health. The current body of evidence precludes causal and temporal inferences.

Keywords: anxietydepressionmeatmental healthveganvegetarianismsex

Discussion

This meta-analysis extends the findings of our prior systematic review (Dobersek et al. 2020) by presenting a quantitative evaluation of the relation between meat consumption/abstention and mental health. It included 171,802 participants aged 11 to 105 years, from varied geographic regions, including Europe, Asia, North America, and Oceania. The findings show a significant association between meat consumption/abstention and depression and anxiety. Specifically, individuals who consumed meat had lower average depression and anxiety levels than meat abstainers. We also showed that vegans experienced greater levels of depression than meat consumers. Sex did not modify these relations. Study quality explained a significant proportion of between-studies heterogeneity and a cumulative meta-analysis confirmed these findings. Specifically, the higher the study quality, the more positive the benefit of meat consumption.

Our results may explain the equivocal nature of prior research. In contrast to our clear findings (both past (Dobersek et al. 2020 and present), other systematic reviews and meta-analytic results were inconsistent or contradictory. These equivocal results suggested that vegetarians, and in some cases vegans had lower levels of depression or anxiety (Askari et al. 2020; Iguacel et al. 2020; Lai et al. 2014; Li et al. 2017; Liu et al. 2016; Nucci et al. 2020; Zhang et al. 2017). As detailed in our systematic review (Dobersek et al. 2020), numerous factors explain these inconsistent conclusions. Briefly, most prior studies employed invalid or unreliable assessment protocols to measure exposures and outcomes (i.e., diet and mental health, respectively). For example, it is well established that dietary recalls and FFQs produce physiologically implausible and non-falsifiable (pseudo-scientific) data (Archer, Pavela, and Lavie 2015; Archer, Hand, and Blair 2013; Archer, Lavie, and Hill 2018a; Archer, Marlow, and Lavie 2018b, 2018c). Thus, the disparity between self-reported and actual dietary intake may render definitive conclusions impossible when analyzing meat consumption as a continuous rather than dichotomous variable (Archer, Pavela, and Lavie 2015; Archer, Hand, and Blair 2013; Archer, Lavie, and Hill 2018a; Archer, Marlow, and Lavie 2018b, 2018c).

With respect to mental health, the most rigorous research relied on physician-diagnosed disorders using the Diagnostic and Statistical Manual of Mental Disorders (DSM) (Michalak, Zhang, and Jacobi 2012) (APA 2013) rather than self-reported (subjective) assessments with untested validity. The use of tools with questionable validity can lead to ambiguous findings and limited cross-study analyses.

Another major design error was the use of biased and selective sampling strategies. Several of the included studies recruited samples from vegan and vegetarian websites, social-networking groups, communities, and restaurants. We surmise this may have substantially biased data collection and may skew self-reported variables and findings if participants with a high degree of emotional or ideological commitment to their dietary behaviors intentionally or unconsciously misreport. An antecedent of this error may be a form of confirmation bias in which the flawed sampling confirms the investigators’ ideology or expectations rather than providing dispassionate data and results.

Finally, statistical and communication errors were ubiquitous. These included the failure to correct for multiple comparisons and the inappropriate use of causal language which can lead to invalid results, interpretations, and conclusions. In summary, given that these errors are widespread in the literature, valid conclusions from previous reviews that failed to examine study quality are not possible.

In the present meta-analysis, these errors taken together are related to significant between-studies variation in effect sizes. Study quality explained 58% and 76% of between-studies heterogeneity in the differences in depression and anxiety, respectively. Furthermore, our analyses (see Figures 2, 4, 6, 7, 10, and 11) demonstrated that higher quality studies showed a more positive and consistent relation between meat consumption and mental health. Higher quality studies had much larger sample sizes.

Finally, limited reporting of participant characteristics prevented an examination of several covariates (e.g., BMI, age of diet adoption/length of diet, clinical history, socioeconomic status, culture) that could potentially contribute to between-studies heterogeneity.

Strengths and limitations

Strengths

This meta-analysis had several strengths. First, our a priori decision to select only studies that provided a clear dichotomy between meat consumers and meat abstainers allowed for a clear and rigorous assessment. While myriad studies have examined vegetarianism along a continuum, these were excluded because the lack of a clear distinction between groups rendered inferences equivocal. This distinction is necessary because self-reported (memory-based) dietary assessments (FFQ) should not be used for quantitative analyses because of their invalidity. Any study that attempts to use FFQs as continuous variables are invalid due to nonquantifiable measurement error (Archer, Lavie, and Hill 2018a; Archer, Marlow, and Lavie 2018b; Archer, Pavela, and Lavie 2015).

Second, we limited our psychological outcomes to the most prevalent and debilitative disorders: depression and anxiety. This allowed a focused yet rigorous analysis and ameliorated the effects of poorly operationalized psychological phenomena such as disordered eating, dietary restraint, orthorexia, and neuroticism. This exclusion helps to avoid potential misclassification and concomitant pathologizing of those who simply wish to avoid specific foods or food groups (e.g., vegans). Finally, with over 170,000 participants from several geographic regions, our meta-analysis allowed for more generalizable and definitive conclusions.

Limitations

Our meta-analysis also had limitations. First, we excluded non-English-language studies. This potentially biased our results in favor of ‘Western’ norms which include meat consumption. For example, we excluded papers published in languages other than English (e.g., Japanese, Hindi). Thus, we may have omitted studies from geographic regions that follow predominantly vegetarian or plant-based dietary patterns.

Second, while our search was clearly defined and comprehensive, our inclusion criteria excluded many publications that provided data on this topic (e.g., see (Anderson et al. 2019; Barthels, Meyer, and Pietrowsky 2018; Burkert et al. 2014; Cooper, Wise, and Mann 1985; Jacka et al. 2012; Larsson et al. 2002; Li et al. 2019; Northstone, Joinson, and Emmett 2018)). Specifically, these papers were excluded because they examined constructs other than depression or anxiety (e.g., orthorexia, restrained eating behavior) or assessed meat consumption as a continuous rather than dichotomous variable. As previously stated, self-reported dietary status and FFQs lead to nonquantifiable measurement error. Nevertheless, we think that our rigorous and highly focused meta-analysis has the potential to provide stronger evidence for the medical, research, and lay communities.

Third, despite the high confidence we place in our finding that meat abstention is linked to a greater prevalence of psychological disorders, study designs precluded inferences of temporality and causality. Specifically, only two of the included studies (Lavallee et al. 2019; Velten et al. 2018) provided information on temporality. Therefore, we were unable to conclusively examine this effect. Given that there are many reasons why people abstain from meat (e.g., ethical, environmental, animal rights-related reasons), this empirical question has not been adequately addressed. However, our previous systematic review (Dobersek et al. 2020) showed conflicting evidence on the temporal relations between meat abstention and depression and anxiety. Also, conclusions on causality require evidence from rigorous RCTs. Since only one low-quality RCT met our inclusion criteria (Beezhold and Johnston 2012), no conclusions regarding causality are supported.

Finally, the results of our meta-analysis are only as valid as the data collected in the included primary studies. Given that most studies used FFQs and self-reported questionnaires, participants may have been misclassified. Merely reporting that one avoids meat is not the equivalent of actual meat abstention (Archer, Pavela, and Lavie 2015; Archer, Hand, and Blair 2013; Archer, Lavie, and Hill 2018a; Archer, Marlow, and Lavie 2018b, 2018c). In fact, self-defined vegetarians and meat abstainers may consume meat (Haddad and Tanzman 2003).

Recommendations for future directions

Future investigators should avoid the most common flaws exhibited in the included studies. First, investigators must acknowledge and address the effects of both researcher and participant biases (e.g., confirmation bias, cognitive dissonance, observer-expectancy effects/reactivity) when employing highly selective or biased samples. Individuals who are highly invested in their dietary behaviors may be predisposed to intentional and non-intentional misreporting.

Second, the use of physician-diagnosed disorders based on criteria from the DSM-V (APA 2013; Michalak, Zhang, and Jacobi 2012) is preferable to self-reported symptoms, and assists in producing more definitive results. Additionally, the severe limitations and pseudo-scientific nature of self-reported dietary data and FFQs (Archer, Pavela, and Lavie 2015; Archer, Hand, and Blair 2013; Archer, Lavie, and Hill 2018a; Archer, Marlow, and Lavie 2018b, 2018c) could be overcome in part with point-of-purchase (barcode) data (Ng and Popkin 2012). However, while these data may be less biased, they are not necessarily an accurate proxy for actual dietary consumption.

Third, the use of more rigorous study designs (e.g., RCTs) is desirable over mere observational investigations. However, it would be extremely difficult to conduct a randomized study of diets with a long enough duration to impact fundamental affective outcomes such as anxiety and depression. Furthermore, detailed participant information regarding behavioral and health-related histories and current lifestyles is essential to valid interpretation and conclusions. Finally, studies should provide complete statistical information that allow for the calculations of effect sizes. More complete reporting would enable meta-analysts to extract both effect measures and study characteristics thus allowing for exploration of potentially important but unanswered questions (e.g., how is time of diet adoption related to mental health?).