Lifestyle Psychiatry

Authors:
Joseph Firth
Marco Solmi
Robyn E. Wootton
Davy Vancampfoqt
Felipe B. Schuch
Erin Hoare
Simon Gilbody
John Torous
Scott B. Teasdale
Sarah E. Jackson 
Lee Smith
Melissa Eaton
Felice N. Jacka
Nicola Veronese
Wolfgang Marx 
Garcia Ashdown‐Franks
Dan Siskind
Jerome Sarris 
Simon Rosenbaum
André F. Carvalho
Brendon Stubbs 

There is increasing academic and clinical interest in how “lifestyle factors” traditionally associated with physical health may also relate to mental health and psychological well‐being. In response, international and national health bodies are producing guidelines to address health behaviors in the prevention and treatment of mental illness. However, the current evidence for the causal role of lifestyle factors in the onset and prognosis of mental disorders is unclear. We performed a systematic meta‐review of the top‐tier evidence examining how physical activity, sleep, dietary patterns and tobacco smoking impact on the risk and treatment outcomes across a range of mental disorders. Results from 29 meta‐analyses of prospective/cohort studies, 12 Mendelian randomization studies, two meta‐reviews, and two meta‐analyses of randomized controlled trials were synthesized to generate overviews of the evidence for targeting each of the specific lifestyle factors in the prevention and treatment of depression, anxiety and stress‐related disorders, schizophrenia, bipolar disorder, and attention‐deficit/hyperactivity disorder. Standout findings include: a) convergent evidence indicating the use of physical activity in primary prevention and clinical treatment across a spectrum of mental disorders; b) emerging evidence implicating tobacco smoking as a causal factor in onset of both common and severe mental illness; c) the need to clearly establish causal relations between dietary patterns and risk of mental illness, and how diet should be best addressed within mental health care; and d) poor sleep as a risk factor for mental illness, although with further research required to understand the complex, bidirectional relations and the benefits of non‐pharmacological sleep‐focused interventions. The potentially shared neurobiological pathways between multiple lifestyle factors and mental health are discussed, along with directions for future research, and recommendations for the implementation of these findings at public health and clinical service levels.Keywords: Lifestyle factors, mental disorders, psychological well‐being, physical activity, sedentary behavior, tobacco smoking, dietary patterns, sleep, depression, anxiety disorders, bipolar disorder, schizophrenia

Mental disorders affect almost 30% of individuals across the lifespan 1 , and are among the largest contributors to the global burden of disease, accounting for 32% of all years lived with disability, and 13% of disability‐adjusted life years 2 .

Despite many advances in psychotherapies and pharmacological treatments for a range of psychiatric conditions, there remains a substantial proportion of individuals who do not achieve full remission from standard treatment3, 4. Additionally, a large portion of the global population do not have access to traditional mental health care, due to the scarcity of psychiatric services available, particularly in many low‐ and middle‐income countries3, 5.

There has also been little improvement in primary prevention of mental illness, with clear gaps in both the evidence and implementation for such interventions 6 . Indeed, rates of common mental disorders (i.e., depression and anxiety) appear to even be increasing among the younger generations 7 .

Thus, new approaches towards the prevention and treatment of mental illness, which can be delivered alongside or in the absence of traditional mental health care, are needed to reduce the global and growing burden of these conditions.

An emerging body of research has linked both the onset and symptoms of various mental disorders to “lifestyle factors”, a term referring to health behaviors such as physical activity, diet, tobacco smoking and sleep 8 .

For instance, a mass of cross‐sectional evidence 9 shows that a range of psychiatric conditions (including schizophrenia, bipolar disorder, depression, and anxiety and stress‐related disorders) are associated with adverse health behaviors, such as poorer dietary and sleeping patterns, low levels of physical activity, and higher rates of tobacco smoking, compared to healthy controls. Additionally, recent findings from population‐scale studies document that the relationships between many of these lifestyle risk factors and mental illness also persist in low‐ and middle‐income countries10, 11, 12.

Although useful, this expansive body of cross‐sectional research does not uncover the causality of the observed relationships. Therefore, the evidence for which lifestyle factors should be addressed when aiming to prevent the onset of mental illness, or reduce symptoms in those with established conditions, is currently very limited.

Nonetheless, a number of national health policy documents and clinical guidelines are now beginning to address the role of specific lifestyle factors in the prevention and treatment of mental illness. For instance, both the US Physical Activity Guidelines for Americans 13 and the UK Chief Medical Officers’ Physical Activity Guidelines 14 recommend attaining at least 150 min of moderate‐to‐vigorous physical activity per week for reducing the risk of depression (including postnatal depression) (see Table ​Table11).

In order to preserve both overall mental health and cognitive functioning, both Canada’s 15 and Australia’s16 24‐Hour Movement Guidelines have adopted a “whole day time‐use” paradigm for young people, recommending that each day should include at least 60 min of moderate‐to‐vigorous exercise, several hours of light physical activity, no more than two hours of sedentary leisure activities, and 8‐11 hours of uninterrupted sleep. The UK Royal College of Psychiatrist’s position statement on public mental health 6also describes how the clustering of health‐risk behaviors (which include smoking, lack of exercise, and unhealthy eating) increases lifetime risk of mental illness.

Along with this surge of recognition from public health perspectives, the role of behavioral factors is also becoming a topic of increasing interest in psychiatric research and mental health services. Notably, the European Psychiatric Association’s guidelines on physical activity in mental illness 17 put forth that there is sufficient evidence to recommend structured exercise training as an effective first‐line treatment option for moderate depression, and as an adjunctive intervention for improving symptomatic recovery in severe mental illness. Additionally, the Royal Australian and New Zealand College of Psychiatrists’ clinical practice guidelines for mood disorders 18 list exercise, smoking, diet and sleep as “step zero” targets, to be addressed before implementa‐tion of pharmacotherapy and/or psychotherapy.

There are a large number of individual clinical trials, epidemiological studies, and meta‐analyses investigating the impact of other health behaviors in various psychiatric conditions. However, existing guidelines predominantly focus on physical activity, and typically only in relation to depression or schizophrenia. The broader role of lifestyle factors, across the spectrum of mental disorders, has yet to be established.

This meta‐review aimed to establish the current evidence on causal relations between key modifiable health behaviors (physical activity, dietary food intake, tobacco smoking, and sleep) and the incidence and outcomes of major mental disorders, including depression, anxiety and stress‐related disorders, attention‐deficit/hyperactivity disorder (ADHD), bipolar disorder, schizophrenia and related psychotic disorders. We sought to present an empirical overview of the field of lifestyle medicine for mental illness, and produce evidence‐based recommendations for targeting modifiable health behavior factors in the prevention and treatment of these conditions, while also identifying key evidential gaps to inform future research.Go to:

METHODS

This meta‐review aimed to systematically aggregate the most recent, top‐tier evidence for the role of “lifestyle factors” in the prevention and treatment of mental disorders, following the PRISMA statement to ensure comprehensive and transparent reporting 19 . Systematic searches were conducted on February 3, 2020 of the following databases: Allied and Complementary Medicine (AMED), PsycINFO, Ovid MEDLINE, Health Management Information Consortium, EMBASE and the NHS Economic Evaluation and Health Technology Assessment databases.

The following PICOS search algorithm was used: Participants [‘mental health or psychological well‐being or psychological outcomes or mental well‐being or psychiat* or mental illness* or mental disorder* or depress* or mood disorder* or affective disorder* or anxi* or panic or obsessive compulsive or OCD or ADHD or attention deficit or attentional deficit or phobi* or bipolar type or bipolar disorder* or psychosis or psychotic or schizophr* or schizoaffective or antipsychotic* or post traumatic* or personality disorder* or stress disorder* or dissociative disorder or antidepress* or antipsychotic*.ti]; Interventions/Exposures [physical activity or exercis* or sport* or walking or intensity activity or resistance training or muscle or sedentary or screen time or screentime or aerobic or fitness or diet* or nutri* or food* or vegan or vege* or meat or carbohy* or fibre or sugar* or adipos* or vitamin* or fruit* or sleep* or insomn* or circad* or smoke* or smoking or tobacco or nicotine or healthy or obes* or weight or bodyweight or body mass or BMI or health behav* or behavior change or behavior change or lifestyle*.ti]; Outcomes [‘meta‐analy* or metaanaly* or meta reg* or metareg* or systematic review* or Mendel* or meta‐review or reviews or umbrella review or updated review*.ti]; Study design [‘prospective or protect* or inciden* or onset or prevent* or cohort or predict* or risk or longitudinal or randomized or randomised or mendel* or bidirectional or controlled or trial* or causal’].

Separate searches of the Cochrane Database of Systematic Reviews and Google Scholar were also conducted to identify additional articles.

Eligibility criteria

The lifestyle factors examined were those pertaining to physical activity, diet, sleep and smoking.

“Physical activity” was considered in the broadest sense, including overall physical activity levels, structured exercise training interventions, and also studies examining the absence of physical activity, i.e. sedentary behavior. “Diet” focused on dietary food intake/interventions, and did not include studies evaluating specific nutrient treatments (as these have been already reviewed extensively in this journal 20 ) or those examining blood levels of individual vitamins/minerals/fatty acids (as blood levels of these nutrients are influenced by many genetic and environmental factors, independent from dietary intake21, 22). “Sleep” was examined as general sleep patterns, quality or quantity, along with studies examining either the impact of sleep disorders (i.e., insomnia) on risk of mental illnesses, or the efficacy of non‐pharmacological interventions directly targeting sleep to improve psychiatric symptoms. The term “smoking” was used only in reference to tobacco consumption, from personal usage or passive exposure, rather than illicit drugs, as the known psychoactive effects of these latter substances have been reviewed extensively in this journal 23 .

Mental disorders eligible to be included in this meta‐review were mood disorders (moderate or severe depression and bipolar disorder), psychotic disorders (including schizophrenia and related conditions), anxiety and stress‐related disorders, dissociative disorders, personality disorders, and ADHD. We excluded psychiatric conditions which are directly characterized by adverse health behaviors (i.e., eating disorders and alcohol or substance use disorders) along with other neurodevelopmental disorders (e.g., autism, intellectual disability) and neurodegenerative disorders (e.g., dementia), as these were considered beyond the scope of this review.

Protective factors were examined using two sources of data. First, we searched for meta‐analyses of longitudinal data that examined relationships between the various lifestyle factors and prospective risk/onset of mental illness. Eligible meta‐analyses were those presenting suitable quantitative data – as adjusted or raw odds ratios (ORs), risk ratios (RRs) or hazard ratios (HRs) – on how baseline status of behavioral variables influences the prospective risk of mental illness, including diagnosed psychiatric conditions and clinically significant symptoms (using established cutoffs on validated screening instruments, or based on percentile cutoffs of psychiatric symptom scores).

The second source of data used for examining protective factors were any Mendelian randomization (MR) studies of the link between lifestyle factors and mental illness. Briefly, MR is a causal inference method that can be used to estimate the effect of an exposure (X) on an outcome (Y) whilst minimizing bias from confounding and reverse causation24, 25. Suitable genetic instruments (usually single nucleotide polymorphisms, SNPs) are identified through genome‐wide association studies (GWAS). Individuals carrying the effect allele of the variant have higher (or lower) levels of X on average than those without the effect alleles. Following Mendel’s laws of segregation and independent assortment, the genetic variants are inherited randomly at conception, and are inherited independently of confounding lifestyle factors 26 . Therefore, MR can be considered somewhat analogous to a randomized controlled trial (RCT) of behavioral factors in the prevention of mental illness, as genetic variants randomly predispose individuals to experience different levels of these factors 26 . As genes also remain unchanged throughout the life course, they are also not altered by the outcome of interest, thus reducing bias from reverse causation 26 . Therefore, while meta‐analyses of prospective cohort studies are useful for identifying the overall strength and directionality of associations, the MR analyses were used to further infer the causal nature of the observed relationships.

The evidence for lifestyle interventions in the treatment of people with diagnosed mental disorders was examined using two different sources of data, but both based on meta‐analyses of RCTs (typically considered the top‐tier of evidence in health intervention research). First, we searched for existing meta‐reviews of meta‐analyses of RCTs published in the last five years, for each lifestyle factor, providing quantitative effects of physical activity, diet, smoking cessation or non‐pharmacological sleep interventions on psychiatric symptoms in people with mental illness. Second, for the lifestyle factors that were not covered within the existing meta‐reviews, we sought out meta‐analyses of RCTs examining their impact (using the search strategy above), and synthesized the evidence from the meta‐analyses using a methodology derived from a previous meta‐review 20 . For meta‐analyses with mixed samples, only those in which at least 75% of the sample examined the eligible mental illnesses (as described above) were included.

Data extraction

A systematic tool was applied to each eligible meta‐analysis/MR study to extract the relevant data on the association of lifestyle factors with risk of mental illness, or the effects of lifestyle interventions on psychiatric outcomes. Results of eligible meta‐reviews were extracted narratively, summarized from their respective articles.

For meta‐analyses of longitudinal studies, the strength and direction of the prospective associations between lifestyle factors and mental illness were quantified categorically, and thus extracted as ORs, HRs or RRs, with 95% confidence intervals (CIs).

For meta‐analyses of RCTs of lifestyle interventions in mental illness, effect size data were quantified as a continuous variable (i.e., magnitude of effect on psychiatric symptoms) and thus extracted as standardized mean differences (SMDs), Cohen’s d or Hedges’ g. These were then classified as small (<0.4), moderate (0.4‐0.8), or large (>0.8).

For all meta‐analyses, data on the degree of between‐study heterogeneity (quantified as I 2 values) were also extracted, where reported.

In cases where multiple eligible meta‐analyses examined a specific lifestyle factor in the risk/treatment of the same mental disorder, the most recent was used preferentially. Where older meta‐analyses featured >25% more studies than the newer versions and contained important, novel findings from unique analyses not captured in the most recent versions, these were also extracted and presented alongside the newer findings. In cases where two MR studies had examined the same lifestyle factor for the same mental health outcome, both studies (regardless of recency or sample size) were included and reviewed.

We also extracted relevant study characteristics where reported, including number of pooled comparisons within meta‐analyses (n), sample size (N), details on the specifics of lifestyle exposure or intervention examined, and sample features. The results of key subgroup/sensitivity analyses showing how different age groups, illnesses or outcomes examined, or different types of exposure/interventions modified the effect of the specific lifestyle factor were extracted as well. For the purposes of providing a concise summary of the literature, only the findings from secondary analyses which provided important, unique insights into the evidence were extracted.

Quality assessment of included studies

The National Institutes of Health (NIH)’s Quality Assessment Tool for Systematic Reviews and Meta‐Analyses was used to assess the quality of the included meta‐analyses. This tool evaluates the quality of meta‐analyses rating them for adequacy of the search question, specification of inclusion and exclusion criteria, systematic search, screening of papers, quality assessment and summaries of included studies, and tests for publication bias and heterogeneity. In accordance with previous meta‐reviews using the NIH tool27 , the quality of included meta‐analyses was categorized as “good” (7 or 8), “fair” (4‐6), or “poor” (0‐3).

As no consensus tool exists for determining the quality of MR and meta‐review studies, these were omitted from formal quality assessment.Go to:

RESULTS

Systematic search

The main search returned a total of 1,811 results, which were reduced to 834 after duplicates were excluded. A total of 92 full text papers were retrieved, from which 41 met full inclusion criteria. Of note, one seemingly eligible study 28 was excluded for invalid findings due to inconsistent coding of effect directionality. Four additional studies were identified from the supplementary searches, and thus 45 studies were included in total. Across the different lifestyle factors, 11 of the eligible papers focused on physical activity/exercise, 15 were on smoking, 12 examined diet, and 10 considered sleep. Some papers covered multiple factors.

The results below synthesize the findings of 29 meta‐analyses of prospective/cohort studies, 12 Mendelian randomization studies, two meta‐reviews, and two meta‐analyses of RCTs. Individual details for the prospective meta‐analyses and MR studies examining lifestyle risk factors for mental disorders are provided in Tables 1, ​,2,2, ​,3,3, ​,4,4, ​,5,5, ​,6,6, ​,7,7, ​,88.

Table 3

Smoking and prospective risk of mental disorders in meta‐analyses

	Outcome	n	Exposure	Main results	Summary
Luger et al 42(NIH=3)	Major ‐depressive disorder and depressive symptoms	7	Smokers vs. never smokers	OR=1.62, 95% CI: 1.1‐2.4,I2=NA	Smoking was strongly associated with risk of depression, with effects of 1.5‐2 times the risk of non‐smoking from a variety of designs, ‐measurements and populations. However, review quality scored low, and the impact of publication bias and study heterogeneity was not ‐determined.
Chaiton et al43(NIH=4)	Adolescent depression (diagnosis or clinical symptoms)	6	Smoking	OR=1.	Fair quality review showing that smoking in adolescence is associated with increased risk of future depression. However, clinical measures of ‐depression were more likely to report a bidirectional effect (i.e., depression also predicting smoking).
Han et al44(NIH=6)	Incident depressive symptoms in children	2	Early life second‐hand smoking	OR=1.51, 95% CI: 0.93‐2.09,I2=NA	Fair quality review showing that exposure to second‐hand smoking in early life was associated with increased odds of depressive symptoms in cross‐sectional studies. However, the effects in the two prospective cohort studies was non‐significant.
Chen et al45(NIH=6)	Postpartum depression	4	Prenatal smoking	OR=2.88, 95% CI: 0.99‐8.39, I2=89.3%
Hunter et al52(NIH=7)	Incident schizophrenia	6	Personal active