research paper on physical illness

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• Published: 26 December 2019

The relationship between physical activity, mental wellbeing and symptoms of mental health disorder in adolescents: a cohort study

• Sarah Louise Bell   ORCID: orcid.org/0000-0003-1181-9591 1 ,
• Suzanne Audrey 1 ,
• David Gunnell 1 , 2 ,
• Ashley Cooper 2 , 3 &
• Rona Campbell 1  

International Journal of Behavioral Nutrition and Physical Activity volume  16 , Article number:  138 ( 2019 ) Cite this article

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Mental illness is a worldwide public health concern. In the UK, there is a high prevalence of mental illness and poor mental wellbeing among young people. The aim of this study was to investigate whether physical activity is associated with better mental wellbeing and reduced symptoms of mental health disorder in adolescents.

A cohort of 928 12–13 year olds (Year 8) from six secondary schools in England, who had participated in the AHEAD trial, ‘Activity and Healthy Eating in Adolescence’, were followed up three years later (when 15–16 years old, Year 11). At baseline, physical activity was measured using accelerometers. At follow-up, mental wellbeing was measured using the ‘Warwick Edinburgh Mental Wellbeing Scale’ (WEMWBS) and symptoms of mental health disorder using the ‘Strengths and Difficulties Questionnaire’ (SDQ). Multivariable linear regression analyses were used to investigate associations between physical activity and both mental wellbeing and symptoms of mental health disorder.

794 (86%) of the eligible 928 young people provided valid accelerometer data at baseline. 668 (72%) provided complete mental wellbeing data and 673 (73%) provided complete symptoms of mental health disorder data at follow-up. The multivariable analyses showed no evidence of an association between physical activity volume (counts per minute (cpm)) or intensity (Moderate to Vigorous Physical Activity (MVPA)) and mental wellbeing (WEMWBS overall score) or overall symptoms of mental health disorder (SDQ Total Difficulties Score). However, higher levels of physical activity volume at age 12–13 years were associated with lower scores on the emotional problems subscale of the SDQ at age 15–16 years.

Conclusions

This cohort study found no strong evidence that physical activity is associated with better mental wellbeing or reduced symptoms of mental health disorder in adolescents. However, a protective association between physical activity and the emotional problems subscale of the SDQ was found. This suggests that physical activity has the potential to reduce symptoms of depression and anxiety in adolescents. Future cohort study designs should allow for repeated measures to fully explore the temporal nature of any relationship.

Mental illness is a worldwide public health concern [ 1 ]. It is currently the largest single cause of disability in the UK representing an estimated 28% of the total disease burden (compared to 16% each for cancer and heart disease) [ 2 ]. The World Health Organization (2013) estimates that, worldwide, 20% of adolescents in any given year may experience mental illness. In England, the most recent population survey (2017) reported 14.4% (1 in 7) of young people aged 11–16 years were identified with a mental health disorder [ 3 ]. Emotional disorders (present in 9%) were the most common type at this age followed by behavioural (conduct) disorders (6.2%) [ 3 ]. Mental health disorder has diverse and long-term negative effects on individuals, their families, and wider society [ 4 ].

Population surveys have also found increased levels of low wellbeing in young people [ 3 ]. Mental wellbeing is conceptualised as more than the absence of mental illness [ 5 ]. It has been described as encompassing hedonic (happiness, life satisfaction, and affect) and eudaimonic (positive functioning, sense of purpose, and self-acceptance) wellbeing [ 6 , 7 , 8 , 9 , 10 ]. Mental wellbeing is protective for a range of health outcomes [ 11 , 12 , 13 , 14 ] and found to be associated with higher educational outcomes in adolescence and better occupational functioning in adulthood [ 15 , 16 , 17 ]. Correlates of young peoples’ mental illness and mental wellbeing are reported to be largely distinct, stressing the importance of considering these concepts separately and avoiding their conflation [ 18 ].

While mental illness and mental wellbeing may be related, they are not necessarily distinct ends of a continuum [ 19 , 20 , 21 ]. The dual continuum model views mental illness (or mental health disorder) and mental health (or mental wellbeing) as two separate continua rather than as opposite ends of the same continuum [ 20 ]. Keyes and Lopez (2002) depicted the dual continuum model of mental illness and mental health and described four states: struggling (incomplete mental illness i.e. mental illness and high wellbeing), floundering (complete mental illness i.e. mental illness and low wellbeing), languishing (incomplete mental health i.e. no mental illness and low wellbeing), and flourishing (complete mental health i.e. no mental illness and high wellbeing). A large number of adolescents are thought to suffer from poor mental wellbeing despite being free from mental illness [ 4 , 22 ]. Therefore, promoting mental wellbeing alongside preventing and treating the symptoms of mental illness, is a growing priority. The recent Green Paper (2018) focuses on schools finding low cost and low risk interventions to promote mental wellbeing and prevent symptoms of mental health disorder [ 23 ].

Although there is evidence of physical activity improving mental wellbeing [ 24 , 25 ] and having the potential to prevent symptoms of mental health disorder [ 26 , 27 ] in adults, the evidence of any relationship in adolescents is weaker. The studies lack measurement consistency, having defined and assessed physical activity, mental wellbeing, and symptoms of mental health disorder in a variety of ways. Furthermore, few studies have used a multi-dimensional measure of mental wellbeing or symptoms of mental health disorder (most capture only one component of mental wellbeing such as self-esteem [ 28 ] or self-efficacy [ 29 ] or a specific mental health problem such as depression [ 30 , 31 , 32 , 33 , 34 ]), and studies that have used an objective measure of physical activity to assess any relationship are limited [ 35 , 36 , 37 ].

Several reviews have attempted to analyse any association in young people [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ]. A review of reviews by Biddle et al. (2011) [ 48 ] showed that physical activity has beneficial effects on mental health in children and adolescents. More recently there has been a significant increase in the number and quality of studies exploring any association, and when the review of reviews was updated in 2019 [ 49 ], physical activity continued to be shown to be associated with certain mental health outcomes in young people (a causal association was found with cognitive functioning, a partial association for depression, no association for self-esteem, and research focusing on the association of physical activity with anxiety was reported to be variable but generally showed small beneficial effects) [ 49 ]. A review by Rodriguez-Ayllon et al. (2019) [ 50 ] analysed the effects of physical activity interventions (randomised controlled trials and non-randomised controlled trials) on mental health outcomes of adolescents and also synthesised the observational evidence (both longitudinal and cross-sectional). Their review included studies that had at least one ‘psychological illbeing’ (i.e. depression, anxiety, stress or negative effect) and/or ‘psychological wellbeing’ (self-esteem, self-concept, self-efficacy, self-image, positive affect, optimism, happiness and satisfaction with life) outcome. They concluded that there was a small positive effect of physical activity interventions on mental health outcomes in adolescents [ 50 ].

The SDQ is a unique screening tool of symptoms indicating overall mental health disorder in young people. This composite measure identifies symptoms of emotional problems, hyperactivity, and behavioural/conduct problems and has been used in the UK series of surveys of the mental health of children and young people (1999, 2004 and 2017) [ 3 ] alongside other significant population surveys [ 52 ]. Despite this, few studies have used this measure when looking at the association between physical activity and symptoms of mental health disorder [ 31 , 53 , 54 , 55 ]. Of the studies identified, neither of the two longitudinal studies used an objective measure of physical activity [ 31 , 53 ].

The WEMWBS is a relatively new scale, also used in the series of surveys in the UK [ 3 ], designed to capture population mental wellbeing. The reviews that have included studies assessing the relationship between physical activity and various aspects of mental wellbeing [ 38 , 39 , 40 , 41 , 42 , 43 , 44 ; 46 , 47 , 48 , 49 , 50 ] have concluded that there is evidence of promise, but further studies are needed that use a multi-dimensional measure such as the WEMWBS.

Given the limitations of the evidence base, the aim of this study was to determine whether physical activity is associated with mental wellbeing and symptoms of mental health disorder in adolescents. This is the first study to investigate any potential relationship longitudinally using an objective measure of physical activity and valid and reliable self-report measures of both mental wellbeing, using the WEMWBS, and symptoms of mental health disorder, using the SDQ, in adolescents.

A prospective cohort was formed based on the 928 participants from six secondary schools in the South West of England who took part in a two-year school-based exploratory randomised controlled trial (RCT) of an Activity and Healthy Eating intervention for use in ADolescence: the AHEAD trial [ 56 ]. All state secondary schools in the selected local authorities were invited to participate in the study. Schools first to express an interest (ensuring variation in size, geographical area, Ofsted rating, Free School Meal entitlement, and achievement rating) were recruited to the study. Physical activity was measured in 2008 when the participants were aged 12–13 years (Year 8); mental wellbeing and symptoms of mental health disorder was measured three years later (2011) when the participants were aged 15–16 years (Year 11). The inclusion criteria were participation in the AHEAD trial and continued attendance at a study school three years later. Data collections at baseline (2008) and follow-up (2011) were conducted by a team of researchers in the schools (classrooms or school halls) during a usual lesson (approximately 60 min). There was no evidence of promise that the AHEAD intervention improved physical activity or diet.

Physical activity measure

The ActiGraph GT1M accelerometer (ActiGraph, LLC, Penscola, FL) was used to measure physical activity. Participants were instructed in the use of the accelerometers in school, and then asked to wear the instrument for seven days during waking hours, except for water-based activities such as bathing and swimming. Accelerometer data were downloaded using ActiLife software (Lifestyle Monitor System software Version 3.3.0) and processed using Kinesoft software (Version 3.3.62; Kinesoft, Saskatchewan, Canada) to generate outcome variables (10 s epochs were used to capture the sporadic nature of adolescent physical activity). Physical activity volume was computed as mean accelerometer counts per minute (cpm), and physical activity intensity (mean minutes per day of Moderate to Vigorous Physical Activity (MVPA)) was computed using established thresholds [ 57 ]. A valid day of measurement was defined as recording at least 480 min (8 h) of data (monitoring period from 7 am until 11 pm; periods of ≥60 min of consecutive zeros, with allowance for 2 min of interruption, was classed as nonwear time) and at least three valid days were required for inclusion in analyses.

Mental wellbeing and symptoms of mental health disorder measures

The ‘Warwick Edinburgh Mental Wellbeing Scale’ (WEMWBS) [ 58 ], validated for use in adolescents aged 13–16 years, was used to measure mental wellbeing. The WEMWBS has 14 positively worded items with a five-point Likert scoring scale for each item (with scores ranging from 1 = none of the time to 5 = all of the time). The responses to each item were summed to give an overall WEMWBS score; a minimum score of 14 (i.e. poor mental wellbeing) and a maximum of 70 (i.e. good mental wellbeing). The higher score, indicative of better mental wellbeing, reflects more positive thoughts, feelings and behaviours. Where scores for three or less items were missing the mean value of responses for completed items for that individual was used to replace the score for missing items, enabling a total score for that individual to be computed [ 59 ]. If more than three items were missing the data for that participant were not used. The WEMWBS was selected due to it being the first multi-dimensional scale to measure population mental wellbeing in adolescents, based on established indicators. It covers most aspects of mental wellbeing including both hedonic and eudaimonic perspectives and is suitable for looking at the relationship between physical activity and mental wellbeing.

The ‘Strengths and Difficulties Questionnaire’ (SDQ) [ 60 ] was used to measure symptoms of mental health disorder. It is a behavioural screening tool used to assess social, emotional, and physical aspects of behaviour in young people [ 61 ] and has been shown to be valid and reliable for completion by 11–16 year olds [ 62 ]. The questionnaire has 25 items which comprise five subscales: (i) emotional symptoms (anxiety and depressive symptoms); (ii) conduct problems; (iii) hyperactivity/inattention; (iv) peer relationship problems; and (v) pro-social behaviour (positive behaviours such as being kind and helpful, scored in reverse of the other subscales). Response options are ‘not true, somewhat true, or certainly true’ (scored 0, 1 or 2). The SDQ ‘Total Difficulties Score’ (SDQ TDS) was generated by adding together the scores from the first four subscales and can range from 0 (low difficulties) to 40 (high difficulties). The five subscales whose scores can vary from 0 to 10 were also investigated independently. Items scores which were missing were imputed only if at least three out of five items were complete on each subscale. In this case the total subscale score for each participant was divided by the number of complete items to get the mean score and used to replace the missing item score [ 60 , 63 ]. If more than two items were missing from any sub scale the data for that subscale for that participant were not used. Participants required a score for each of the SDQ subscales to be able to compute their SDQ TDS. The SDQ was selected as the SDQ TDS provides a useful indicator of the level of symptoms of mental health disorder overall. Furthermore, the subscale items may be used to indicate specific clinical disorders in adolescents: depression, anxiety, hyperactivity attention deficit disorder (ADHD) and behavioural/conduct disorder. The SDQ is a useful screening tool for identifying young people with raised scores thus potentially at risk.

Possible confounders and mediators

The self-report behavioural questionnaires recorded a number of potential confounders and mediators of any potential relationship: age; gender; ethnicity; socioeconomic status (SES) (measured using the ‘Family Affluence Scale’ FAS II [ 64 ]); study school; number of daylight minutes (a proxy for season); baseline symptoms of mental health disorder (SDQ TDS); sleep (frequency of feeling tired when going to school in the morning); number of friends; belonging to teams and clubs; smoking; drinking alcohol; and intervention arm of the AHEAD trial [ 56 ] (the participants were randomised into two groups - the intervention arm received a physical activity and healthy eating intervention and the control arm continued with usual practice).

Confounders included were determined by the construction of a directed acyclic graph (DAG) and the availability of relevant data on study participants. Accelerometer wear time was computed from the participants accelerometer data.

Data from the self-report behavioural questionnaires were entered into a secure Access database and the accelerometer data were stored as anonymised files on a secure drive. All analyses were conducted using Stata 13 MP [ 65 ].

Statistical analysis

The analyses assessed the association between physical activity and the measures of mental wellbeing and symptoms of mental health disorder. Multivariable linear regression analyses were used to estimate exposure effects controlling for potential confounders and mediators which were investigated by grouping them as clusters of related factors in the models: i.e. socioeconomic factors (ethnic group, SES, study school); factors that may influence the physical activity data processing (daylight minutes (when volume or MVPA exposure), minutes of wear time (when MPVA exposure only); lifestyle factors (sleep, friends, belonging to teams or clubs, drinking alcohol, smoking; measured at follow-up only); baseline symptoms of mental health disorder); and then by producing a fully adjusted model containing all of these factors. Where there was evidence of confounding or mediation (associations weakened or enhanced), further models were fitted to investigate this in more detail. Confounders adjusted for were determined by the availability of relevant data on study participants. This somewhat crude epidemiological approach was used due to there being no clear evidence of associations (and whether confounders or mediators in the relationship) in the literature. Coefficients represent the linear relationship- change in WEMWBS overall score, SDQ TDS or SDQ subscale score per unit increase in physical activity (volume or intensity). Physical activity volume was defined by accelerometer counts (a dimensionless output from the accelerometer) per minute of recording (computed as total counts recorded divided by the total minutes of valid recording over the measurement period, described as counts per minute (cpm)), whilst physical activity intensity was defined as daily minutes of Moderate to Vigorous Physical Activity (MVPA). The relationship was quantified as the change in mental wellbeing or symptoms of mental health disorder score associated with an increase of 100 cpm (e.g. an increase from 508 cpm to 608 cpm, an approximately 20% increase in physical activity volume from baseline mean of the sample); or an additional 60 min of daily MVPA. Tests for interactions were carried out to investigate whether observed associations differed by gender. There was no evidence that associations between physical activity (volume and MVPA) and either mental wellbeing or symptoms of mental health disorder (WEMWBS and SDQ) differed in males and females. The test for interaction p -value ranged from p  = 0.19–0.97 so all models were based on data for males and females combined.

Ethics approval and consent to participate

The University of Bristol Faculty of Medicine and Dentistry Ethics Committee gave full approval in 2007 for the AHEAD feasibility study and pilot trial (reference number 060702) and in 2011 for the cohort study (reference number 101119).

Consent procedures were the same in the original feasibility study and pilot trial and in the subsequent cohort study. Firstly, written consent to participation was sought from each schools’ headteacher. Secondly, letters were posted by school staff to the parents/carers of all eligible school pupils explaining the study and enclosing a reply slip to be returned if parents/carers did not want their child to participate. This ‘opt-out’ method of consent has been found to be an ethical and appropriate procedure in low-risk prevention research and avoids the low response rates and potential sampling bias when opt-in parental consent procedures are used [ 66 , 67 ]. At all data collections, the young people were provided with information about the study and informed that they could ‘opt-out’ of some or all the study activities at any point and were asked to sign individual assent forms.

Cohort study profile and baseline characteristics

794 (86%) of the 928 pupils provided complete, valid baseline physical activity data and were followed-up three years later to complete mental wellbeing and symptoms of mental health disorder measures. 673 (73%) completed the SDQ and 668 (72%) completed the WEMWBS at follow-up. Those lost to follow-up were more likely to be older, male and from one particular school (due to a new headteacher using alternative educational placements for a large number of the school’s more challenging pupils). Table 1 shows the baseline characteristics of the participants included and excluded from the cohort. Figure 1 displays the study profile for the cohort study and Table 2 describes the baseline characteristics of the participants.

Study profile for cohort study

Physical activity at baseline

At baseline, overall physical activity volume (mean (SD) counts per minute (cpm)) was 508.3 cpm (169.42) and participants recorded 55.6 (21.5) (mean (SD)) daily minutes of MVPA). Females were less active than males with regard to both physical activity volume (mean difference 86.39 cpm (95% CI 111.2 cpm to 61.6 cpm, p  < 0.001) and intensity (mean difference 11.7 min (95% CI − 15.41 to − 8.82), p < 0.001).

Mental wellbeing and symptoms of mental health disorder at follow-up

There was a negative association between the WEMWBS overall score and the SDQ TDS (r = − 0.41) at follow-up. This relatively weak correlation indicates the scales are measuring different things (the WEMWBS overall score only accounts for 16% of the total variation in the SDQ TDS). At follow-up, the participants’ WEMWBS overall mean (SD) score was 48.74 (8.66) (data from a similar study (13–16 year olds) 48.8 (8.66) [ 58 ]; females ( n  = 342) 46.93 (8.90) and males ( n  = 326) 50.63 (7.99) with strong evidence of a gender difference in WEMWBS overall score (mean difference in WEMWBS overall score − 3.70 (95% CI − 4.99 to − 2.24) p  < 0.001). Females had a lower WEMWBS overall score indicating poorer mental wellbeing than males. The participants’ SDQ TDS mean score was 12.17 (5.56) (normative data (for 11–15 years) 10.3 (5.2)) [ 60 ]; females ( n  = 343) 12.66 (5.36) and males ( n  = 330) 11.66 (5.73). Again there was evidence of a gender difference in SDQ TDS (mean difference in SDQ TDS 1.00 (95% CI 0.16 to 1.84) p  = 0.02). Females had a higher SDQ TDS indicating higher symptoms of mental health disorder than males.

Main findings

The univariable (adjusted for gender, age and intervention arm of the AHEAD trial) and multivariable analyses showed no evidence of an association between physical activity (volume or intensity) and mental wellbeing (WEMWBS overall score) or overall symptoms of mental health disorder (SDQ TDS) (Table 3 ). When the five SDQ subscales were analysed independently, an association was found between both physical activity volume and intensity and the emotional problems subscale of the SDQ (scale range 0–10). However, the association found between MVPA and the emotional problems subscale of the SDQ was slightly attenuated in the fully adjusted model (when controlling for symptoms of mental health disorder at baseline (SDQ TDS)), such that confidence intervals included the null value.

For physical activity volume, a mean increase of 100 cpm (~ 20% increase in physical activity volume) was associated with a decrease in the emotional problems subscale score of 0.12 (unadjusted model) and 0.11 (fully adjusted model). The confidence intervals (95% CI) ranged from − 0.23 to − 0.00 in the fully adjusted model implying that a potential reduction in the emotional problems subscale score of 0.23 could be achieved with an additional 100 mean cpm of physical activity (the extreme end of the effect estimate). For physical activity intensity, an additional 60 min of mean daily MVPA was associated with a decrease in the emotional problems subscale score of 0.54 (unadjusted model) and 0.49 (fully adjusted model; however confidence intervals crossed zero).

To the best of our knowledge, this is the first longitudinal study to investigate the relationship between physical activity, mental wellbeing and symptoms of mental health disorder in adolescents. We also believe this is the first study to use an objective measure of physical activity (accelerometers) and composite measures of both mental wellbeing (WEMWBS) and symptoms of mental health disorder (SDQ) validated for use with young people alongside each other, to investigate any potential associations. We found no evidence of an association between physical activity (volume or MVPA) and mental wellbeing (WEMWBS overall score) or overall symptoms of mental disorder (SDQ TDS). However, a protective association was found between physical activity volume and the emotional problems subscale of the SDQ. This finding suggests that increasing physical activity volume in adolescents may have the potential to reduce their risk of emotional problems (items on the SDQ emotional problems subscale include: worrying a lot; having fears and being easily scared; being nervous in new situations and easily losing confidence; often feeling unhappy, down-hearted or tearful; and getting a lot of headaches, stomach-aches or sickness). Those adolescents accumulating more daily MVPA minutes may have more beneficial effects. Physical activity could provide an acceptable, low risk and cost-effective intervention for young people showing symptoms of depression and anxiety.

Strengths and limitations of the study

The study was based on a relatively large number of secondary school pupils drawn from six schools of different sizes and characteristics (e.g. rural schools, inner city schools) [ 56 , 68 ]; participants are likely to be broadly representative of secondary school pupils in England. Loss to follow-up was largely due to participants no longer attending a study school and this is unlikely to have biased the patterns of associations found.

A strength of this study was its use of accelerometers, which provide an objective measure of physical activity increasing the precision of measurement. However, it is important to note that accelerometers have known limitations such as not accurately measuring cycling and not being waterproof, so do not measure physical activity from water-based activities.

This study contributes to the evolving debate concerning mental wellbeing and mental illness terminology and measurement. The findings from this study support the notion that mental wellbeing and symptoms of mental health disorder are two separate concepts, captured using different measurement scales. Using validated measures of both mental wellbeing and symptoms of mental health disorder was a strength and novel aspect of this study. This study demonstrated that physical activity is not associated with mental wellbeing or overall symptoms of mental health disorder, but has a protective relationship with regards to risk of emotional problems.

The cohort study would have benefited from repeated measures of physical activity, mental wellbeing and symptoms of mental health disorder, to fully explore the temporal nature of any relationship and take account of changing patterns of physical activity. If an effect of physical activity on mental wellbeing and symptoms of mental health disorder is short-lived, then a three-year time lag would be inappropriate to investigate any association [ 69 ].

We were able to control for a wide range of possible confounders and assess the effect of possible mediators of the relationship. However, some confounders were only measured at follow-up (sleep, number of friends, smoking, drinking alcohol, belonging to teams and clubs). The possible effects of some of the confounders may be different at baseline and follow-up (e.g. smoking and drinking behaviours would be more common at follow-up). Due to the WEMWBS not being available at the time of baseline measures, the SDQ TDS was used to control for baseline wellbeing. We were only able to adjust for confounders measured as part of the AHEAD trial. This study would have been strengthened if Body Mass Index (BMI) [ 70 ] and screen viewing behaviour [ 71 ] were measured and controlled for. The possible mechanisms underlying any association between physical activity, mental wellbeing and symptoms of mental health disorder in adolescents are complex [ 41 ]. It is possible that an integrative model that combined components of different hypotheses (biochemical e.g. release of endorphins, or psychosocial e.g. distraction, sense of mastery, social interaction) offers the most likely, full explanation [ 41 ]. Also, the effects may vary between individuals. Further research needs to consider confounding and mediating factors and exploration of potential mechanisms at the study design stage, to ensure candidate variables are measured appropriately.

Findings in the context of existing research

Studies that have explored the relationship between physical activity and symptoms of overall mental health disorder (using the SDQ) are scarce, and of those identified, no association was reported overall [ 31 ; 53 , 54 , 55 ]. However, Sagatun et al. (2007) [ 53 ] found that for males (but not females) the number of weekly hours (self-reported weekly hours of physical activity that makes them breathless) the boys spent on physical activity per week at age 15–16 years was negatively associated with emotional problems and peer problems at age 18–19 years. Similarly, Wiles et al. (2008) [ 31 ] reported young people (aged 11–14 years) who met recommended levels for physical activity (1 h per day) had, on average, a score on the emotional problems sub-scale of the SDQ that was 0.29 units lower (− 0.29 (95%CI − 0.61 to 0.022)) at 1 year follow-up compared to those who did not undertake recommended levels of physical activity. The association found in our study between physical activity volume and the emotional problems subscale of the SDQ (− 0.11 (95% CI − 0.23 to − 0.00)) (overall but not when gender stratified) is similar to the findings of both these studies, and supports evidence from the recent physical activity and mental health in young people reviews [ 49 , 50 ].

As noted at the outset, there are no longitudinal studies or RCTs that have used a multi-dimensional scale to investigate the relationship between physical activity and mental wellbeing in adolescents with which to compare our findings. Reviews have suggested evidence of promise [ 41 , 50 ] but studies included only used single component measures of mental wellbeing outcomes such as self-image, satisfaction with life and happiness. In the review of reviews by Biddle et al. (2019) [ 49 ] evidence for support of a causal relationship was reported for cognitive function outcome measures, as well as academic achievement and brain structure and function. Although showing an association between physical activity and cognitive function is important to emphasis the role of physical activity in schools, this literature needs to be considered alongside further studies using a composite measure of mental wellbeing.

Implications

There is no strong evidence of any relationship between physical activity, mental wellbeing and overall symptoms of mental health disorder in adolescents. However the findings from this study, together with that from two other studies, suggests a relationship between physical activity volume and emotional problems. Cohort studies, designed specifically to look at the relationship between physical activity and both mental wellbeing and symptoms of mental health disorder, are needed to confirm and explore any potential associations further. Measurement scales that focus on more than one aspect of mental health disorder or mental wellbeing should be used in population level school-based research, and both the SDQ and WEMWBS scales warrant further exploration. Alongside this literature, the association between physical activity and specific mental health disorders should continue to be explored. Measures that can confirm an International Statistical Classification of Diseases and Related Health Problems (ICD- 10 ) or Diagnostic and Statistical Manual of Mental Disorders ( DSM - 5 ) diagnosis in young people, such as the DAWBA (Development and Well-being Assessment), should be considered. Further studies that focus on mental health disorders common in adolescents, other than anxiety and depression, are needed. An objective measure of physical activity used alongside a standardised self-report physical activity questionnaire may be the best approach to understand the context of the physical activity data (e.g. physical activity outdoors may be better for mental wellbeing and team sports may prevent a particular type of mental health disorder). It is important that the self-report measure of physical activity incorporates information on general daily living activities, such as walking to and from school or playing outdoors, and captures any relevant contextual information [ 70 ]. Future study designs should allow for repeated measures to fully explore the temporal nature of any relationship, take account of changing patterns of physical activity and look at short-term associations.

This cohort study provided no strong evidence that physical activity is a protective factor for mental wellbeing or symptoms of mental health disorder in adolescents, as measured by the WEMWBS overall score and SDQ TDS. There was, however, evidence of an association between physical activity volume and the emotional problems subscale of the SDQ. This indicates that emotional problems (such as symptoms of depression and anxiety) in adolescents could be reduced by increasing their physical activity levels.

Availability of data and materials

The datasets during and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Activity and Health Eating in ADolescence

Body Mass Index

Confidence Interval

Counts Per Minute

Development and Well-being Assessment

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) FAS (Family Affluence Scale)

International Statistical Classification of Diseases and Related Health Problems

Moderate to Vigorous Physical Activity

Standard Deviation

Strengths and Difficulties Questionnaire Total Difficulties Score

Strengths and Difficulties Questionnaire

Social Economic Status

Warwick Edinburgh Mental Wellbeing Scale

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Acknowledgements

Thanks are due to the schools and young people involved as this research would not have been possible without their support and willing participation.

The AHEAD trial (during which the baseline data was collected) was funded by the Department of Health Policy Research Programme (Project Number 0600002). SB was funded by a doctoral research fellowship from the National Institute for Health Research (NIHR-DRF-2010-03-51) to complete the follow-up study. The work was undertaken with the support of The Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research Centre of Excellence. Joint funding (MR/KO232331/1) from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the Welsh Government and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The funding sources were not involved in the design of the study and collection, analysis, and interpretation of data or in writing the manuscript. DG and AC are supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol, England. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care.

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SB planned and carried out the study, conducted the data analysis and wrote the manuscript. DG and RC advised on the data analysis and reviewed the manuscript. SA led the AHEAD trial and reviewed the manuscript. AC advised on the physical activity measurement and analysis and reviewed the manuscript.

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Bell, S.L., Audrey, S., Gunnell, D. et al. The relationship between physical activity, mental wellbeing and symptoms of mental health disorder in adolescents: a cohort study. Int J Behav Nutr Phys Act 16 , 138 (2019). https://doi.org/10.1186/s12966-019-0901-7

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The association between physical activity and mental health during the first year of the COVID-19 pandemic: a systematic review

• Priscila Marconcin 1 , 2 ,
• André O. Werneck 3 ,
• Miguel Peralta 2 , 4 ,
• Andreas Ihle 5 , 6 , 7 ,
• Élvio R. Gouveia 8 , 9 ,
• Gerson Ferrari 10 ,
• Hugo Sarmento 11 &
• Adilson Marques 2 , 3  

BMC Public Health volume  22 , Article number:  209 ( 2022 ) Cite this article

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Introduction

The Coronavirus disease-19 (COVID-19) pandemic affected countries worldwide and has changed peoples’ lives. A reduction in physical activity and increased mental health problems were observed, mainly in the first year of the COVID-19 pandemic. Thus, this systematic review aims to examine the association between physical activity and mental health during the first year of the COVID-19 pandemic.

In July 2021, a search was applied to PubMed, Scopus, and Web of Science. Eligibility criteria included cross-sectional, prospective, and longitudinal study designs and studies published in English; outcomes included physical activity and mental health (e.g., depressive symptoms, anxiety, positive and negative effects, well-being).

Thirty-one studies were included in this review. Overall, the studies suggested that higher physical activity is associated with higher well-being, quality of life as well as lower depressive symptoms, anxiety, and stress, independently of age. There was no consensus for the optimal physical activity level for mitigating negative mental symptoms, neither for the frequency nor for the type of physical activity. Women were more vulnerable to mental health changes and men were more susceptive to physical activity changes.

Physical activity has been a good and effective choice to mitigate the negative effects of the COVID-19 pandemic on mental health during the first year of the COVID-19 pandemic. Public health policies should alert for possibilities to increase physical activity during the stay-at-home order in many countries worldwide.

Peer Review reports

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a highly contagious virus that infects humans and causes coronavirus disease-19 (COVID-19), which is currently having a damaging impact on almost all countries worldwide [ 1 ]. To bring this pandemic to an end, a large share of the world needs to be immune to the virus, and the safest way to achieve this is with a vaccine. Fortunately, in December 2020 the vaccination started in the United Kingdom [ 2 ] and is currently pursued in different countries [ 3 ]. Until November 2021, 53.3% of the world population has received at least one dose of a COVID-19 vaccine [ 4 ]. However, the number of infected people and deaths continues to grow [ 5 ]. The World Health Organization (WHO) published a weekly report and on 16th of November 2021 it was observed a increasing trend in new global weekly cases [ 6 ]. From the beginning of the pandemic, as a community mitigation strategy used to reduce the spread of COVID-19, most countries adopted the stay-at-home order as well as the stimulation of facemask wearing and hygiene habits [ 7 , 8 ].

As a consequence of the stay-at-home strategies, mainly during the first year of the COVID-19 pandemic, studies had reported multiple behaviour changes. Some common impacts include disturbed eating behaviours [ 9 ], changes in alcohol consumption [ 10 ], and substance use [ 11 ]. A wide range of psychological outcomes has been observed during the virus outbreak, including a reduction in well-being as well as increases in depressive and anxiety symptoms [ 12 , 13 ]. Considering the need for social distancing measures, the investigation of possible factors that can mitigate the negative effects of social distancing on mental health should help the promotion of intervention strategies.

Physical activity (PA) is well recognised as a key factor for the prevention and management of mental illness, including mental disorders such as depression and anxiety as well as the promotion of mental health such as well-being [ 14 , 15 ]. Nevertheless, globally, approximately 23% of adults and 81% of adolescents do not meet the WHO recommendations regarding PA for maintaining health [ 16 , 17 , 18 ]. This situation even worsened with the COVID-19 pandemic. Studies have demonstrated that PA declined and sedentary behaviour increased during the COVID-19 pandemic stay at home order in many countries, regardless of the subpopulation [ 19 ]. Different studies sought to investigate whether these changes in PA were associated with mental health indicators during the COVID-19 pandemic and a previous systematic review synthetised that PA is an effective strategy to face the psychological effects of the COVID-19 pandemic [ 20 ]. However, the previous review included articles published between 1 January 2019, and 15 July 2020, before the second wave of the COVID-19 pandemic. Therefore, our systematic review aimed to update those findings and clarify if PA is associated with mental health during the first full year of the COVID-19 pandemic and to analyse if PA mitigates the effects of the stay-at-home order on mental health. We aimed to explore the first year of the COVID-19 pandemic because it was the period when restrictive orders were strictest when people were strongly encouraged to comply with the stay-at-home order.

This systematic review focuses on peer-reviewed journal articles on the relationship of PA to mental health during the COVID-19 pandemic published until 30 July 2021.

Data sources and searches

A systematic review protocol was registered with the PROSPERO database on the 29th of January 2021 (IDCRD42021233921). A broad search strategy was employed. Searches were conducted on the 30th of January 2021, in the following electronic databases: PubMed, Scopus, and Web of Science. The search was performed in the three databases using the terms: (physical activity OR physical inactivity OR exercise OR training OR sport* OR fitness OR physical function* OR movement behavio* OR sedentary behavio*) AND (mental health OR psychological health OR depress* OR anxiety OR psychological function* OR mental function* OR wellbeing OR well-being OR burnout OR burn-out OR fear OR fears OR worries OR worry) AND (coronavirus disease OR COVID-19 OR SARS-CoV-2 OR lockdown OR shutdown OR quarantine OR confinement OR social isolation). These terms were searched in title and abstract of scientific articles. Additionally, cross-referencing search was performed in the full-text read of potentially included articles.

Study selection

Observational studies (cross-sectional, prospective, or longitudinal) were eligible for this review. Furthermore, studies were also required to meet the following criteria: (1) assessing PA by a validated instrument, (2) assessing mental health by a validated instrument, (3) presenting an analysis on the association between PA and mental health. Studies with samples including pregnant women, chronic disease patients, athletes, COVID-19 survivors, and frail older adults were excluded. Besides, studies reporting PA as a moderate or mediated variable were also excluded. Two co-authors screened titles and abstracts to identify articles that met the inclusion criteria. Two co-authors read the articles and decided whether they should be included in the analysis or excluded. The inclusion decision was consensual and in cases of disagreement, the decision was made by mutual agreement.

Data extraction and synthesis of results

Data extraction was completed independently by one co-author. Data extracted from all studies included study details (author, year of publication, study design, recruitment processes, and date and location of the study); participant characteristics (sex, mean age); outcome and instruments, and main findings. A table was made for articles that analysed the association between PA and mental health among adults, and another table for the analyses of the association between PA and mental health among children and adolescents.

Quality assessment

The risk of bias was assessed by two independent reviewers, using the Newcastle-Ottawa Scale (NOS) [ 21 ] which was also adapted for cross-sectional studies [ 22 ]. Therefore, we used the original scale for cohort studies and the adapted scale for the cross-sectional studies. The original scale varies between 0 and 9, while the adapted scale for cross-sectional studies varies between 0 and 10, with higher scores indicating research of better quality.

Narrative synthesis

Considering the heterogeneity of methods used for the estimation of the exposures and outcomes, it was not possible to conduct a meta-analysis. Therefore, we compared the findings across the included articles according to each outcome.

Results of the search

From the database search, 734 records were identified. After removing duplicates, the titles and abstracts of 328 articles were screened concerning the eligibility criteria, and 205 were excluded. The full texts of the remaining 1237 articles were evaluated and 92 were excluded for the following reasons: sample characteristics ( n  = 24), data were not analysed regarding the association between PA and mental health variables ( n  = 23), review studies ( n  = 4), no valid instruments to assess PA ( n  = 31) and mental health ( n  = 6), the study was not in the period of the COVID-19 pandemic ( n  = 4). Thirty-one studies were included in this review, 27 about adults and old adults and 4 about children and adolescents. The flow diagram of study search and selection was created according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 23 ] and is presented in Fig.  1 . The mean score of quality was 5.7 ± 1.5. More details are presented in Tables 1 and 2 .

Flow diagram of study selection

The association between physical activity and mental health among adults and old adults

The details of the association between PA and mental health among adults and old adults are summarised in Table  1 , 27 studies were included [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 51 ].

Participants characteristics and date of filling the questionnaires

The number of participants in the 27 included studies varied between 66 [ 50 ] and 14,715 [ 40 ] participants. Regarding sex, with exception of four studies [ 24 , 31 , 40 , 48 ] the majority included more women than men. Concerning age, most articles presented the mean age range between 20 and 30 years [ 24 , 25 , 36 , 37 , 44 , 48 , 49 , 50 , 56 , 57 ], two article presented mean age between 30 and 40 years [ 33 , 43 ]; five articles presented mean age between 40 and 50 years [ 28 , 32 , 35 , 41 , 42 ]; and seven articles presented mean age above 50 years [ 26 , 27 , 34 , 45 , 46 , 47 , 51 ]. Four articles did not present mean age [ 31 , 38 , 39 , 40 ], for one article the age ranged between 21 and 35 years [ 31 ], for another, the age ranged between 21 and 40 years [ 38 ], for another, the age ranged between 17 and 69 years [ 40 ], and in one the age ranged between 27 and 53 years [ 39 ]. The majority of studies reported, the sample filled out online questionnaires. One study used interviewed by telephone call [ 34 ]. Twenty four studies conducted a cross-sectional analysis and four a longitudinal analysis.

Study location

The studies were carried out on five different continents. Ten studies from Europe [ 24 , 25 , 26 , 27 , 28 , 38 , 39 , 43 , 44 , 49 ], foure studies from Asia [ 36 , 40 , 46 , 48 , 50 ], seven studies from America [ 33 , 34 , 35 , 37 , 41 , 51 , 57 ] two studies from Africa [ 31 , 56 ], two study from Oceania [ 42 , 45 ], and two multi-centre study [ 32 , 47 ].

Outcomes and instruments

Concerning outcomes and instruments, 12 articles used the International Physical Activity Questionnaire (IPAQ) to assess PA and one article calculated an estimate of cardiorespiratory fitness (algorithm includes age, body composition, resting heart rate and PA) [ 57 ]. The others articles assessed PA with different instruments. Mental health included analyses of subjective well-being, sleep quality, depressive symptoms, anxiety, quality of life, psychological distress, motivation, resilience, affects (positive and negative), and health-related quality of life.

Main findings

Overall, all articles found a positive association between PA and better outcomes of mental health (e. g., depression, anxiety, well-being). Physical activity was explanatory variable for mental health [ 25 ]. Physical activity was positive associated with mental health [ 42 , 49 ]. Articles that observed a decrease in PA during the stay-at-home order also observed a decrease in well-being [ 47 , 56 ], negative changes in depressive symptoms [ 57 ], and negative changes in anxiety and stress symptoms [ 45 ]. This relationship seems to be bidirectional, since participants who decrease in mental health had greater reduction in physical activity [ 37 ]. Inactive people had worse well-being, highest depression and enxiety compared with moderately active and very active participants [ 24 , 51 ]. Also, inactive old adults had more depressive symptoms [ 26 ]. On the other hand, participants sufficiently active reported significantly lower depression and anxiety and higher life satisfaction. Moreover, it was found that exercise intensity seems to be important. Two studies founded that depression was significantly negatively correlated with moderate-intensity PA but not vigorous and walking/light exeeercuse [ 36 , 40 ]. Another one found that vigorous PA better predicted depressive symptoms than moderate PA [ 27 ]. Three studies suggested that the threshold of PA should be done to fells the benefits on mental health [ 28 , 39 , 50 ]. At least 4 h of MVPA reduced by 49% odds of depressive symptoms [ 28 ], and at leas 477 METs-min/week was associated with a 33% decrease in the probability of depressive symptoms [ 39 ]. On the other hand, a non-significant association was found between PA and anxiety [ 35 ], and between PA and health-related quality of life [ 46 ]. One study found that the decrease in mental wellbeing and increase in perceived stress was not related to changes in PA [ 44 ].

The association between physical activity and mental health among children and adolescents

The details of the association between PA and mental health among children and adolescents are shown in Table 2 , four studies were included [ 52 , 53 , 54 , 55 ].

The number of participants ranged between 64 and 4898 children and adolescents. More girls than boys participated in the studies. The mean ages were 11, 14, 15, and 16 years old. One study was longitudinal and presents two moments of assessment, also opting for phone or video calls to collect the data [ 52 ]. The other three studies were cross-sectional, and collected data by online surveys.

One study was from the USA [ 52 ], one from Greece [ 54 ] and the other two were from China [ 53 , 55 ].

Three studies assessed PA by the International physical activity questionnaire (IPAQ) questionnaire [ 53 , 54 , 55 ], and another one used a 24-h physical activity recall [ 52 ]. Regarding mental health, different outcomes were assessed, such as anxiety, positive and negative affect, insomnia, depressive symptoms, psychological well-being and mood states.

Moderate physical activity was associated with less state anxiety [ 52 , 53 ]. Positive affect was not related to physical activity [ 52 ]. Higher levels of physical activity were also significantly associated with lower levels of total mood disturbance [ 55 ]. Regarding the dose of physical activity, days of physical activity per week was stronger predictor of well-being than minutes of physical activity per week [ 54 ].

This systematic review focuses on the association between PA and mental health during the first year of the COVID-19 pandemic. In particular, we sought to answer if PA mitigates the effects of the stay-at-home order on mental health. The COVID-19 pandemic generated numerous challenges for public health, particularly the significant burden of mental health in the population [ 58 , 59 ]. In addition, PA has been recognized as an effective mitigation strategy for improving mental health [ 60 ]. The COVID-19 pandemic has been affecting all continents in the world, at different scales. This study analysed 31 research articles, 27 about adults and old adults and 4 about children and adolescents. The articles are mainly based on cross-sectional studies and five are longitudinal studies. In nearly all of the studies comprised in the present systematic review, investigators used online surveys as the main procedure to collect data. Overall, the studies suggested that higher PA is associated with less negative mental health symptoms, such as depression, anxiety, well-being, and fear, independently of age.

The studies observed that women showed more depressive symptoms than men [ 28 , 39 , 50 , 53 , 55 ], and this trend increases with age [ 24 ] Furthermore, individuals with a lower level of masculinity traits (not specifically females) increased risk of developing depression [ 36 ], and women experienced more generalised anxiety [ 41 ]. The reduction of PA levels may mostly influence the mental well-being of females [ 38 , 49 ]. Those findings are expected since the literature is consistent in signalising sex differences in most mental disorders [ 61 ]. On the whole, the prevalence rates of anxiety and depression were both higher than the rates found in previous studies before the COVID-19 pandemic [ 36 , 37 , 43 , 45 , 48 , 57 ], which highlights a worsening in mental health during the first year of the COVID-19 pandemic. Regarding age, younger individuals experienced significantly higher anxiety and depression, also income influenced mental health, lower-income participants present worse mental health [ 37 ].

Five articles conducted a longitudinal study. Among those studies, four enrolled adults and old adults [ 28 , 44 , 46 , 50 , 51 ] and in one the sample comprised children [ 52 ]. Among the studies that have collected measures before and after the stay-at-home order, both observed a significant reduction in PA [ 44 , 46 ]. Two study collected measures after the stay-at-home order and during this period physical activity mean score decreased minimally [ 51 ], and depressive symptoms increase as the weeks of isolation go [ 28 ]. Other studies also reported a reduction in self-reported PA [ 26 , 33 , 34 , 37 , 38 , 42 , 43 , 45 , 56 , 57 ] and increase in sedentary behaviour [ 25 , 26 , 34 ]. Individuals who reported larger decrease in MVPA pre to during COVID-19 reported relatively poorer mental health [ 33 ]. Participants whose mental health got “worse” or “much worse” had greater reductions in physical activity [ 37 ]. Also, increased levels of physical activity were associated with stronger effects on wellbeing [ 42 ]. The reduction was more pronounced in men than women [ 32 , 38 , 44 ], in vigorous PA [ 38 ], and between those with lower health-related quality of life scores before the COVID-19 pandemic [ 46 ]. The possible explanation for this sex-difference is that men are more engaged in group/community PA and sports in clubs or gyms, and those were more impacted by the COVID-19 restrictions. Also, women are more engaged in low and moderate physical activities, which can be done at home. Besides, women spent more time in housework activities. Women without changes in childcare provision reported more opportunities to be physically active [ 41 ]. The same sex-differences were observed in an Italian study [ 62 ]. Increases in PA were observed for a minority, but the majority of the respective study samples demonstrating a positive change were individuals who did not meet recommended PA guidelines before the COVID-19 pandemic [ 32 , 38 ]. Additional reasons could be an increase in awareness for health issues and more time to pursue PA during the stay-at-home order [ 32 ]. These behaviour changes can help to maintain a more active lifestyle during the pandemic. Another study found an increase of 40% in PA in a sample that was already active before the COVID-19 pandemic [ 35 ]. PA could be used as a coping strategy to deal with the consequences of the pandemic. The place where individuals prefer to practice PA seems to be important, since active participants reported greater connectedness to nature and nature relatedness than the inactive population [ 35 ].

There was no consensus across studies for the optimal PA levels for mitigating negative mental symptoms. The more the physical activity is frequent and vigorous, the best people feel themselves [ 24 ]. Among Chinese students, 2500 METs minute/week of PA every week was the optimal dose to alleviate negative emotion [ 50 ]. On the other hand, a Spanish community sample study showed that 477 METs-minute/week was associated with a 33% decrease in the probabilities of notable depressive symptoms [ 39 ]. The difference between the values must be relativised considering the samples’ characteristics. The first one concerns students with a mean age of 20 years [ 50 ], and the second one concerns a community sample with a mean age of 43.2 years for women and 40.5 years for men [ 39 ]. In addition, it is claimed that at least 3000 METs-minute/week reduce the odds of depressive symptoms by 47% [ 39 ]. These studies used the IPAQ to assess PA, and according to IPAQ, to reach a minimally active category at least 600 METs minute/week is needed [ 63 ]. The American College of Sports Medicine also recommends for healthy adults aged 18–65 years at least 600 METs minute/week but did not specify the minimum dose to prevent depressive symptoms [ 14 , 64 ].

Studies also examined the association between PA and mental health according to PA intensity. Moderate-intensity PA (e.g., walking or jogging on a treadmill, using an elliptical trainer, cleaning house) is associated with better mental health outcomes than vigorous-intensity PA [ 36 , 40 ], and light-intensity PA [ 40 ]. On the other hand, vigorous-intensity PA better predicted depressive symptoms than moderate-intensity PA; also the effect size was higher for the association between vigorous-intensity PA and level of resilience compared with moderate-intensity PA [ 27 ]. One study found that performing high PA levels has no positive effect on depressive symptoms [ 39 ]. Another study explored the type of PA and showed that stretching and resistance training were associated with lower anxiety, and three types of PA (household chores, stretching, and resistance training) were associated with lower depression symptoms [ 48 ].

One study explored the association of specific types of physical exercise and mental health, and founded that home-based group entertainment exercise, rope skipping and badminton, Chinese traditional sports, video dancing and sensory-motor games present a greater reduction in mental health than others types [ 40 ].

Sedentary behaviour was observed in few studies and contradictory findings were observed. No association between sedentary time and depressive symptoms was observed [ 26 , 36 ]. However, other studies have shown that sedentary behaviour was associated with poorer mental health [ 25 ], well-being [ 32 ] and perceived stress [ 44 ].

Concerning the association between PA and mental health outcomes among children and adolescents, only four articles were selected. Some issues must be highlighted. This population had to face, beyond the reality that changed from the COVID-19 pandemic, the changes in the education system such as online learning became the main learning method for students and uncertainty of academic development, which probably caused more anxiety level [ 52 , 53 ]. Both moderate and highly active groups were significantly associated with less depressive symptoms [ 53 ] and anxiety [ 52 , 53 ], and only the most active adolescents reported significantly lower insomnia symptoms [ 53 ] and better mood states [ 55 ]. Days of physical activity per week was stronger predictor of well-being than minutes of physical activity per week [ 54 ].

Regarding old-age samples, the studies mentioned the particular vulnerability to changes in social circumstances, and highlight the importance of health-related quality of life [ 46 ] and levels of resilience [ 27 ] to deal with the consequences of the COVID-19 pandemic on the PA level. The stay-at-home order can cause greater distress and feelings of sadness, considered specific risk factor for depressive symptoms [ 34 ]. Mental health and physical activity decrease pre to during stay-at-home order [ 47 ]. In a group that were previously regular participants of a formal exercise program, MVPA was significantly higher within the non-depressed group compared with depressed group [ 26 ]. Being active previously of COVID-19 confinement did not prevent 30.4% of Brazilian older adults from having depressive symptoms, but these results is much lower than prevalence of depression in Brazilian general population, which is 68% [ 34 ].

The present systematic review had some limitations that must be mentioned. First, the studies present correlative analyses, not causal ones, thus randomised controlled trials must be conducted in the context of the COVID-19 pandemic and the stay-at-home order to clarify the direction of the association. However, beyond the COVID-19 context, randomised controlled trials showed that PA interventions show beneficial effects on mental health outcomes such as depression and anxiety [ 65 ]. Thus, a nuanced perspective particularly during the COVID-19 context in future research is needed. Moreover, the included studies with community samples were limited, and the analyses were mostly based on convenience samples with college students, which had specific characteristics and low mean age. Thus, future research needs to focus on representative study samples.

This review helps to clarify the positive association between PA and mental health during the first year of the COVID-19 pandemic, especially considering the effects of the stay-at-home order worldwide. Although there is an association between increased PA and improved mental health, further studies are needed, specifically randomised clinical trials, to identify the direction of this relationship, and what kind of PA, intensity, and frequency are most indicated to maximise the effects. Also, an investigation to examine the association during the second year of the COVID-19 pandemic is needed. The impact of the COVID-19 pandemic on mental health may be continuous and long-term [ 66 , 67 ]. Thus, public health agencies must provide timely and effective interventions, in which PA and exercise should be a priority.

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Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Abbreviations

Coronavirus disease-19

Severe acute respiratory syndrome coronavirus-2

Physical activity

World Health Organization

International physical activity questionnaire

Metabolic equivalent

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AI acknowledges support from the Swiss National Centre of Competence in Research LIVES – Overcoming vulnerability: life course perspectives, granted by the Swiss National Science Foundation (grant number: 51NF40-185901). AI acknowledges support from the Swiss National Science Foundation (grant number: 10001C_189407). André Werneck is supported by the São Paulo Research Foundation (FAPESP) with a PhD scholarship (FAPESP process: 2019/24124-7). This paper presents independent research. The views expressed in this publication are those of the authors and not necessarily those of the acknowledged institutions.

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Marconcin, P., Werneck, A.O., Peralta, M. et al. The association between physical activity and mental health during the first year of the COVID-19 pandemic: a systematic review. BMC Public Health 22 , 209 (2022). https://doi.org/10.1186/s12889-022-12590-6

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Research Review: Childhood chronic physical illness and adult emotional health - a systematic review and meta-analysis

Affiliations.

• 1 EDGE Lab, School of Psychology, University of Sussex, Brighton, UK.
• 2 Department of Psychology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA.
• 3 MRC Unit for Lifelong Health & Ageing at UCL, London, UK.
• PMID: 28449285
• DOI: 10.1111/jcpp.12727

Background: Childhood chronic physical illness is associated with a greater vulnerability for emotional problems (i.e. depression and anxiety) in childhood. However, little is known about life-long effects of childhood chronic physical illness on mental health. The present study aims to systematically review evidence for associations between eight chronic physical illnesses with childhood onset (arthritis, asthma, cancer, chronic renal failure, congenital heart disease, cystic fibrosis, type 1 diabetes, and epilepsy) and adult emotional problems.

Methods: A database search of MEDLINE, PsycARTICLES, PsycINFO, and ScienceDirect was undertaken, and random effects meta-analyses were used to synthesise evidence from eligible studies.

Results: In total, 37 studies were eligible for the systematic review (n = 45,733) and of these, 34 studies were included in the meta-analyses (n = 45,358). There were overall associations between childhood chronic physical illness and adult depression (OR = 1.31; 95% CI [1.12, 1.54]) and anxiety (OR = 1.47; 95% CI [1.13, 1.92]). Separate meta-analyses for childhood asthma, type 1 diabetes and cancer were also conducted, with cancer being significantly associated with adult depression (OR = 1.19; 95% CI [1.00, 1.42]).

Conclusions: The effects of childhood chronic physical illness on the risk of emotional problems persist beyond childhood and adolescence. Mental health prevention and intervention strategies targeting children with chronic physical illnesses can have long-term benefits.

Keywords: Depression; anxiety; chronic disorders; meta-analysis; paediatrics.

© 2017 Association for Child and Adolescent Mental Health.

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Psychological Health, Well-Being, and the Mind-Heart-Body Connection: A Scientific Statement From the American Heart Association

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The Science of Mindfulness: Research and Benefits

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This chapter delves into the scientific underpinnings of mindfulness, showcasing its transformative effects on mental and physical health through neural mechanisms and empirical research. It explores how mindfulness practices influence key brain networks, including the Default Mode, Salience, and Central Executive Networks, promoting neural coherence and enhancing attentional control. The chapter highlights mindfulness’s ability to modulate the limbic system, fostering improved emotional regulation and reducing stress responses. Additionally, it outlines the positive impacts of mindfulness on attention, demonstrating increased cognitive flexibility and reduced distractibility. The clinical benefits of mindfulness are emphasized, with evidence supporting its efficacy in managing pain, anxiety, and stress-related hormonal responses. By integrating mindfulness into healthcare, individuals can cultivate resilience, empathy, and a more compassionate approach to both self-care and patient care, leading to improved overall well-being and quality of life.

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Chand, R., Sazima, G. (2024). The Science of Mindfulness: Research and Benefits. In: Mindfulness in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-031-66166-2_3

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Building Health Through Physical Activity in Schools - Volume II

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This is the second volume of the Research Topic "Building" Health Through Physical Activity in Schools, please see the first volume here . Physical activity in the school context refers to the various ways in which students engage in physical activity during the school day. This can include physical education classes, recess and lunch breaks, and extracurricular sports and activities. The importance of physical activity in schools can be seen in the numerous benefits it can provide for students' physical and mental health, academic performance, and overall well-being. Physical education classes are a key component of physical activity in schools, providing students with structured physical activity opportunities and helping them to develop the knowledge and skills needed to be physically active throughout their lives. Additionally, recess and lunch breaks can provide students with the opportunity to engage in unstructured physical activity, allowing them to socialize with their peers and blow off steam. Extracurricular sports and activities can also provide students with opportunities to be physically active, while also helping them to develop important social and teamwork skills. Research has shown that students who are physically active tend to have better academic performance, are less likely to experience obesity and related health issues and have better mental health. However, despite the many benefits of physical activity, many students do not engage in enough physical activity. Factors such as a lack of access to physical activity opportunities, limited time for recess and physical education, and a focus on academics over physical activity can all contribute to this problem. In order to promote physical activity among students, it is important for schools to provide a variety of opportunities for physical activity, and to make physical activity an integral part of the school day. Therefore, high quality articles of different types (e.g., original research, clinical trials, systematic reviews) are strongly recommended. Potential topics include, but are not limited to: • The impact of physical activity programs on the academic performance of school-aged children • Examine the effectiveness of school interventions to increase physical activity levels in children • The relationship between physical activity levels and mental health in school-aged children • Examine the influence of school policies and facilities on physical activity levels in children • The role of physical education in promoting lifelong physical activity habits in children • Investigate the impact of technology use on physical activity levels in school-aged children • Examine the effectiveness of community-based approaches to increasing physical activity levels among school-aged children • The impact of socioeconomic status on physical activity levels among school-aged children • The relationship between physical activity levels and body weight in school-aged children • Investigate the impact of school physical activity programs on reducing childhood obesity

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The impact of stress on body function: A review

Habib yaribeygi.

1 Neurosciences Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran

Yunes Panahi

2 Clinical Pharmacy Department, Faculty of Pharmacy, Baqiyatallah University of Medical Sciences, Tehran, Iran

Hedayat Sahraei

Thomas p. johnston.

3 Division of Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, Missouri, USA

Amirhossein Sahebkar

4 Biotechnology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Any intrinsic or extrinsic stimulus that evokes a biological response is known as stress. The compensatory responses to these stresses are known as stress responses. Based on the type, timing and severity of the applied stimulus, stress can exert various actions on the body ranging from alterations in homeostasis to life-threatening effects and death. In many cases, the pathophysiological complications of disease arise from stress and the subjects exposed to stress, e.g. those that work or live in stressful environments, have a higher likelihood of many disorders. Stress can be either a triggering or aggravating factor for many diseases and pathological conditions. In this study, we have reviewed some of the major effects of stress on the primary physiological systems of humans.

Abbreviations

ACTH: Adrenocorticotropic hormone

CNS: Central nervous system

CRH: Corticotropin releasing hormone

GI: Gastrointestinal

LTP: Long-term potentiation

NMDA : N-methyl-D-aspartate

VTA: Ventral tegmental area

Stress and the Brain Function Complications

For a long time, researchers suggested that hormones have receptors just in the peripheral tissues and do not gain access to the central nervous system (CNS) (Lupien and Lepage, 2001[ 63 ]). However, observations have demonstrated the effect of anti-inflammatory drugs (which are considered synthetic hormones) on behavioral and cognitive disorders and the phenomenon called “Steroid psychosis” (Clark et al., 1952[ 16 ]). In the early sixties, neuropeptides were recognized as compounds devoid of effects on the peripheral endocrine system. However, it was determined that hormones are able to elicit biological effects on different parts of the CNS and play an important role in behavior and cognition (De Kloet, 2000[ 22 ]). In 1968, McEven suggested for the first time that the brain of rodents is capable of responding to glucocorticoid (as one of the operators in the stress cascade). This hypothesis that stress can cause functional changes in the CNS was then accepted (McEwen et al., 1968[ 74 ]). From that time on, two types of corticotropic receptors (glucocorticosteroids and mineralocorticoids) were recognized (de Kloet et al., 1999[ 23 ]). It was determined that the affinity of glucocorticosteroid receptors to cortisol and corticosterone was about one tenth of that of mineralocorticoids (de Kloet et al., 1999[ 23 ]). The hippocampus area has both types of receptors, while other points of the brain have only glucocorticosteroid receptors (de Kloet et al., 1999[ 23 ]).

The effects of stress on the nervous system have been investigated for 50 years (Thierry et al., 1968[ 115 ]). Some studies have shown that stress has many effects on the human nervous system and can cause structural changes in different parts of the brain (Lupien et al., 2009[ 65 ]). Chronic stress can lead to atrophy of the brain mass and decrease its weight (Sarahian et al., 2014[ 100 ]). These structural changes bring about differences in the response to stress, cognition and memory (Lupien et al., 2009[ 65 ]). Of course, the amount and intensity of the changes are different according to the stress level and the duration of stress (Lupien et al., 2009[ 65 ]). However, it is now obvious that stress can cause structural changes in the brain with long-term effects on the nervous system (Reznikov et al., 2007[ 89 ]). Thus, it is highly essential to investigate the effects of stress on different aspects of the nervous system (Table 1 (Tab. 1) ; References in Table 1: Lupien et al., 2001[ 63 ]; Woolley et al., 1990[ 122 ]; Sapolsky et al., 1990[ 99 ]; Gould et al., 1998[ 35 ]; Bremner, 1999[ 10 ]; Seeman et al., 1997[ 108 ]; Luine et al., 1994[ 62 ]; Li et al., 2008[ 60 ]; Scholey et al., 2014[ 101 ]; Borcel et al., 2008[ 9 ]; Lupien et al., 2002[ 66 ]).

Stress and Memory

Memory is one of the important functional aspects of the CNS and it is categorized as sensory, short term, and long-term. Short term memory is dependent on the function of the frontal and parietal lobes, while long-term memory depends on the function of large areas of the brain (Wood et al., 2000[ 121 ]). However, total function of memory and the conversion of short term memory to long-term memory are dependent on the hippocampus; an area of the brain that has the highest density of glucocorticosteroid receptors and also represents the highest level of response to stress (Scoville and Milner, 1957[ 107 ]; Asalgoo et al., 2015[ 1 ]). Therefore, during the past several decades, the relationship between the hippocampus and stress have been hotly debated (Asalgoo et al., 2015[ 1 ]; Lupien and Lepage, 2001[ 63 ]). In 1968, it was proven that there were cortisol receptors in the hippocampus of rats (McEwen et al., 1968[ 74 ]). Later, in 1982, by using specific agonists of glucocorticosteroid and mineralocorticoid receptors, the existence of these two receptors in the brain and hippocampus area of rats was proven (Veldhuis et al., 1982[ 119 ]). It should also be noted that the amygdala is very important to assessing the emotional experiences of memory (Roozendaal et al., 2009[ 91 ]).

The results of past studies have demonstrated the effect of stress on the process of memory (Ghodrat et al., 2014[ 32 ]). Various studies have shown that stress can cause functional and structural changes in the hippocampus section of the brain (McEwen, 1999[ 72 ]). These structural changes include atrophy and neurogenesis disorders (Lupien and Lepage, 2001[ 63 ]). Also, chronic stress and, consequently, an increase in plasma cortisol, leads to a reduction in the number of dendritic branches (Woolley et al., 1990[ 122 ]) and the number of neurons (Sapolsky et al., 1990[ 99 ]), as well as structural changes in synaptic terminals (Sapolsky et al., 1990[ 99 ]) and decreased neurogenesis in the hippocampus tissue (Gould et al., 1998[ 35 ]). Glucocorticosteroids can induce these changes by either effecting the cellular metabolism of neurons (Lawrence and Sapolsky, 1994[ 58 ]), or increasing the sensitivity of hippocampus cells to stimulatory amino acids (Sapolsky and Pulsinelli, 1985[ 98 ]) and/or increasing the level of extracellular glutamate (Sapolsky and Pulsinelli, 1985[ 98 ]).

High concentrations of stress hormones can cause declarative memory disorders (Lupien and Lepage, 2001[ 63 ]). Animal studies have shown that stress can cause a reversible reduction in spatial memory as a result of atrophy of the hippocampus (Luine et al., 1994[ 62 ]). In fact, high plasma concentrations of glucocorticosteroids for extended periods of time can cause atrophy of the hippocampus leading to memory disorders (Issa et al., 1990[ 45 ]). Additionally, people with either Cushing's syndrome (with an increased secretion of glucocorticosteroids), or people who receive high dosages of exogenous synthetic anti-inflammatory drugs, are observed to have atrophy of the hippocampus and associated memory disorders (Ling et al., 1981[ 61 ]). MRI images taken from the brains of people with post-traumatic stress disorder (PTSD) have demonstrated a reduction in the volume of the hippocampus along with neurophysiologic effects such as a weak verbal memory (Bremner, 1999[ 10 ]). Several human studies have suggested that even common therapeutic doses of glucocorticosteroids and dexamethasone can cause problems with explicit memory (Keenan et al., 1995[ 49 ]; Kirschbaum et al., 1996[ 53 ]). Thus, there is an inverse relationship between the level of cortisol and memory (Ling et al., 1981[ 61 ]), such that increasing levels of plasma cortisol following prolonged stress leads to a reduction in memory (Kirschbaum et al., 1996[ 53 ]), which improves when the level of plasma cortisol decreases (Seeman et al., 1997[ 108 ]).

Stress also has negative effects on learning. Results from hippocampus-dependent loading data demonstrate that subjects are not as familiar with a new environment after having been exposed to a new environment (Bremner, 1999[ 10 ]). Moreover, adrenal steroids lead to alteration in long-term potentiation (LTP), which is an important process in memory formation (Bliss and Lømo, 1973[ 7 ]).

Two factors are involved in the memory process during stress. The first is noradrenaline, which creates emotional aspects of memories in the basolateral amygdala area (Joëls et al., 2011[ 47 ]). Secondly, this process is facilitated by corticosteroids. However, if the release of corticosteroids occurs a few hours earlier, it causes inhibition of the amygdala and corresponding behaviors (Joëls et al., 2011[ 47 ]). Thus, there is a mutual balance between these two hormones for creating a response in the memory process (Joëls et al., 2011[ 47 ]).

Stress does not always affect memory. Sometimes, under special conditions, stress can actually improve memory (McEwen and Lupien, 2002[ 71 ]). These conditions include non-familiarity, non-predictability, and life-threatening aspects of imposed stimulation. Under these specific conditions, stress can temporarily improve the function of the brain and, therefore, memory. In fact, it has been suggested that stress can sharpen memory in some situations (Schwabe et al., 2010[ 105 ]). For example, it has been shown that having to take a written examination can improve memory for a short period of time in examination participants. Interestingly, this condition is associated with a decrease in the level of cortisol in the saliva (Vedhara et al., 2000[ 118 ]). Other studies have shown that impending stress before learning occurs can also lead to either an increase in the power of memory (Domes et al., 2002[ 27 ]; Schwabe et al., 2008[ 102 ]), or decrease in the capacity for memory (Diamond et al., 2006[ 26 ]; Kirschbaum et al., 1996[ 53 ]). This paradox results from the type of imposed stress and either the degree of emotional connection to the stressful event (Payne et al., 2007[ 83 ]; Diamond et al., 2007[ 25 ]), or the period of time between the imposing stress and the process of learning (Diamond et al., 2007[ 25 ]).

The process of strengthening memory is usually reinforced after stress (Schwabe et al., 2012[ 103 ]). Various studies on animal and human models have shown that administration of either glucocorticosteroids, or stress shortly after learning has occurred facilitates memory (Schwabe et al., 2012[ 103 ]). Also, it has been shown that glucocorticosteroids (not mineralocorticoids) are necessary to improve learning and memory (Lupien et al., 2002[ 66 ]). However, the retrieval of events in memory after exposure to stress will be decreased (Schwabe et al., 2012[ 103 ]), which may result from the competition of updated data for storage in memory in a stressful state (de Kloet et al., 1999[ 23 ]). Some investigations have shown that either exposure to stress, or injection of glucocorticosteroids before a test to assess retention, decreases the power of memory in humans and rodents (Schwabe and Wolf, 2009[ 104 ]).

In summary, it has been concluded that the effect of stress on memory is highly dependent on the time of exposure to the stressful stimulus and, in terms of the timing of the imposed stress, memory can be either better or worse (Schwabe et al., 2012[ 103 ]). Moreover, recent studies have shown that using a specific-timed schedule of exposure to stress not only affects hippocampus-dependent memory, but also striatum-dependent memory, which highlights the role of timing of the imposed stressful stimulus (Schwabe et al., 2010[ 105 ]).

Stress, Cognition and Learning

Cognition is another important feature of brain function. Cognition means reception and perception of perceived stimuli and its interpretation, which includes learning, decision making, attention, and judgment (Sandi, 2013[ 95 ]). Stress has many effects on cognition that depend on its intensity, duration, origin, and magnitude (Sandi, 2013[ 95 ]). Similar to memory, cognition is mainly formed in the hippocampus, amygdala, and temporal lobe (McEwen and Sapolsky, 1995[ 73 ]). The net effect of stress on cognition is a reduction in cognition and thus, it is said that any behavioral steps undertaken to reduce stress leads to increase in cognition (Scholey et al., 2014[ 101 ]). In fact, stress activates some physiological systems, such as the autonomic nervous system, central neurotransmitter and neuropeptide system, and the hypothalamus-pituitary-adrenal axis, which have direct effects on neural circuits in the brain involved with data processing (Sandi, 2013[ 95 ]). Activation of stress results in the production and release of glucocorticosteroids. Because of the lipophilic properties of glucocorticosteroids, they can diffuse through the blood-brain barrier and exert long-term effects on processing and cognition (Sandi, 2013[ 95 ]).

It appears that being exposed to stress can cause pathophysiologic changes in the brain, and these changes can be manifested as behavioral, cognitive, and mood disorders (Li et al., 2008[ 60 ]). In fact, studies have shown that chronic stress can cause complications such as increased IL-6 and plasma cortisol, but decreased amounts of cAMP responsive element binding protein and brain-derived neurotrophic factor (BDNF), which is very similar to what is observed in people with depression and mood disorders that exhibit a wide range of cognitive problems (Song et al., 2006[ 114 ]). Additionally, the increased concentrations of inflammatory factors, like interleukins and TNF-α (which play an important role in creating cognitive disorders), proves a physiologic relationship between stress and mood-based cognitive disorders (Solerte et al., 2000[ 113 ]; Marsland et al., 2006[ 68 ]; Li et al., 2008[ 60 ]). Studies on animals suggest that cognitive disorders resulting from stress are created due to neuroendocrine and neuroamine factors and neurodegenerative processes (Li et al., 2008[ 60 ]). However, it should be noted that depression may not always be due to the over activation of the physiological-based stress response (Osanloo et al., 2016[ 81 ]).

Cognitive disorders following exposure to stress have been reported in past studies (Lupien and McEwen, 1997[ 64 ]). Stress has effects on cognition both acutely (through catecholamines) and chronically (through glucocorticosteroids) (McEwen and Sapolsky, 1995[ 73 ]). Acute effects are mainly caused by beta-adrenergic effects, while chronic effects are induced in a long-term manner by changes in gene expression mediated by steroids (McEwen and Sapolsky, 1995[ 73 ]). In general, many mechanisms modulate the effects of stress on cognition (McEwen and Sapolsky, 1995[ 73 ]; Mendl, 1999[ 75 ]). For instance, adrenal steroids affect the function of the hippocampus during cognition and memory retrieval in a biphasic manner (McEwen and Sapolsky, 1995[ 73 ]). In chronic stress, these steroids can destroy neurons with other stimulatory neurotransmitters (Sandi, 2013[ 95 ]). Exposure to stress can also cause disorders in hippocampus-related cognition; specifically, spatial memory (Borcel et al., 2008[ 9 ]; Sandi et al., 2003[ 96 ]). Additionally, stress can halt or decrease the genesis of neurons in the dentate gyrus area of the hippocampus (this area is one of the limited brain areas in which neurogenesis occurs in adults) (Gould and Tanapat, 1999[ 34 ]; Köhler et al., 2010[ 54 ]). Although age is a factor known to affect cognition, studies on animals have demonstrated that young rats exposed to high doses of adrenal steroids show the same level of decline in their cognition as older adult animals with normal plasma concentrations of glucocorticoids (Landfield et al., 1978[ 57 ]). Also, a decrease in the secretion of glucocorticosteroids causes preservation of spatial memory in adults and has also been shown to have neuroprotective effects (Montaron et al., 2006[ 78 ]). Other studies have shown that stress (or the injection of adrenal steroids) results in varied effects on cognition. For instance, injection of hydrocortisone at the time of its maximum plasma concentration (in the afternoon) leads to a decrease in reaction time and improves cognition and memory (Lupien et al., 2002[ 66 ]).

In summary, the adverse effects of stress on cognition are diverse and depend on the type, timing, intensity, and duration (Sandi, 2013[ 95 ]). Generally, it is believed that mild stress facilitates an improvement in cognitive function, especially in the case of virtual or verbal memory. However, if the intensity of stress passes beyond a predetermined threshold (which is different in each individual), it causes cognitive disorders, especially in memory and judgment. The disruption to memory and judgment is due to the effects of stress on the hippocampus and prefrontal cortex (Sandi, 2013[ 95 ]). Of course, it must be realized that factors like age and gender may also play a role in some cognitive disorders (Sandi, 2013[ 95 ]). Importantly, it should be emphasized that different people may exhibit varied responses in cognition when exposed to the very same stressful stimulus (Hatef et al., 2015[ 39 ]).

Stress and Immune System Functions

The relationship between stress and the immune system has been considered for decades (Khansari et al., 1990[ 50 ]; Dantzer and Kelley, 1989[ 21 ]). The prevailing attitude between the association of stress and immune system response has been that people under stress are more likely to have an impaired immune system and, as a result, suffer from more frequent illness (Khansari et al., 1990[ 50 ]). Also, old anecdotes describing resistance of some people to severe disease using the power of the mind and their thought processes, has promoted this attitude (Khansari et al., 1990[ 50 ]). In about 200 AC, Aelius Galenus (Galen of Pergamon) declared that melancholic women (who have high levels of stress and, thus, impaired immune function) are more likely to have cancer than women who were more positive and exposed to less stress (Reiche et al., 2004[ 88 ]). This may be the first recorded case about the relationship between the immune system and stress. In an old study in the early 1920's, researchers found that the activity of phagocytes in tuberculosis decreased when emotional stress was induced. In fact, it was also suggested that living with stress increases the risk of tuberculosis by suppressing the immune system (Ishigami, 1919[ 44 ]). Following this study, other researchers suggested that the probability of disease appearance increases following a sudden, major, and extremely stressful life style change (Holmes and Rahe, 1967[ 41 ]; Calabrese et al., 1987[ 12 ]).

Over the past several decades, there have been many studies investigating the role of stress on immune system function (Dantzer and Kelley, 1989[ 21 ]; Segerstrom and Miller, 2004[ 109 ]). These studies have shown that stress mediators can pass through the blood-brain barrier and exert their effects on the immune system (Khansari et al., 1990[ 50 ]). Thus, the effect of stress on the immune system is now an accepted relationship or association.

Stress can affect the function of the immune system by modulating processes in the CNS and neuroendocrine system (Khansari et al., 1990[ 50 ]; Kiecolt-Glaser and Glaser, 1991[ 51 ]). Following stress, some neuroendocrine and neural responses result in the release of corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and other stress mediators (Carrasco and Van de Kar, 2003[ 13 ]). However, evidence suggests that the lymphatic system, which is a part of the immune system, also plays a role in releasing these mediators (Khansari et al., 1990[ 50 ]). For instance, thymus peptides, such as thymopentine, thymopoietin, and thymosin fraction-5, cause an increase in ACTH production (Goya et al., 1993[ 36 ]). Additionally, the existence of CRH in thymus has been proven (Redei, 1992[ 87 ]). It has also been proven that interleukin-1 released from phagocytes has a role in ACTH secretion (Berkenbosch et al., 1987[ 4 ]). On the other hand, natural or synthetic glucocorticosteroids (which are the final stress operators) are known as anti-inflammatory drugs and immune suppressants and their role in the inhibition of lymphocytes and macrophages has been demonstrated as well (Elenkov et al., 1999[ 28 ]; Reiche et al., 2004[ 88 ]). Moreover, their role in inhibiting the production of cytokines and other immune mediators and decreasing their effect on target cells during exposure to stress has also been determined (Reiche et al., 2004[ 88 ]).

In addition to adrenal steroids, other hormones are affected during stress. For example, the secretion of growth hormone will be halted during severe stress. A study showed that long-term administration of CRH into the brain ventricles leads to a cessation in the release of growth hormone (Rivier and Vale, 1985[ 90 ]). Stress also causes the release of opioid peptides to be changed during the time period over which the person is exposed to stress (McCarthy et al., 2001[ 70 ]). In fact, stress modifies the secretion of hormones that play a critical role in the function of the immune system (Khansari et al., 1990[ 50 ]). To date, it has been shown that various receptors for a variety of hormones involved in immune system function are adversely affected by stress. For example, ACTH, vasoactive intestinal peptide (VIP), substance P, growth hormone, prolactin, and steroids all have receptors in various tissues of the immune system and can modulate its function (De la Fuente et al., 1996[ 24 ]; Gala, 1991[ 30 ]; Mantyh, 1991[ 67 ]). In addition, active immune cells are also able to secrete several hormones; thus, some researchers believe that these hormones, as mediators of immune system, play a significant role in balancing its function (Blalock et al., 1985[ 6 ]).

Severe stress can lead to malignancy by suppressing the immune system (Reiche et al., 2004[ 88 ]). In fact, stress can decrease the activity of cytotoxic T lymphocytes and natural killer cells and lead to growth of malignant cells, genetic instability, and tumor expansion (Reiche et al., 2004[ 88 ]). Studies have shown that the plasma concentration of norepinephrine, which increases after the induction stress, has an inverse relationship with the immune function of phagocytes and lymphocytes (Reiche et al., 2004[ 88 ]). Lastly, catecholamines and opioids that are released following stress have immune-suppressing properties (Reiche et al., 2004[ 88 ]).

Stress and the Function of the Cardiovascular System

The existence of a positive association between stress and cardiovascular disease has been verified (Rozanski et al., 1999[ 93 ]). Stress, whether acute or chronic, has a deleterious effect on the function of the cardiovascular system (Rozanski et al., 1999[ 93 ]; Kario et al., 2003[ 48 ]; Herd, 1991[ 40 ]). The effects of stress on the cardiovascular system are not only stimulatory, but also inhibitory in nature (Engler and Engler, 1995[ 29 ]). It can be postulated that stress causes autonomic nervous system activation and indirectly affects the function of the cardiovascular system (Lazarus et al., 1963[ 59 ]; Vrijkotte et al., 2000[ 120 ]). If these effects occur upon activation of the sympathetic nervous system, then it mainly results in an increase in heart rate, strength of contraction, vasodilation in the arteries of skeletal muscles, a narrowing of the veins, contraction of the arteries in the spleen and kidneys, and decreased sodium excretion by the kidneys (Herd, 1991[ 40 ]). Sometimes, stress activates the parasympathetic nervous system (Pagani et al., 1991[ 82 ]). Specifically, if it leads to stimulation of the limbic system, it results in a decrease, or even a total stopping of the heart-beat, decreased contractility, reduction in the guidance of impulses by the heart stimulus-transmission network, peripheral vasodilatation, and a decline in blood pressure (Cohen et al., 2000[ 17 ]). Finally, stress can modulate vascular endothelial cell function and increase the risk of thrombosis and ischemia, as well as increase platelet aggregation (Rozanski et al., 1999[ 93 ]).

The initial effect of stress on heart function is usually on the heart rate (Vrijkotte et al., 2000[ 120 ]). Depending upon the direction of the shift in the sympatho-vagal response, the heart beat will either increase or decrease (Hall et al., 2004[ 38 ]). The next significant effect of stress on cardiovascular function is blood pressure (Laitinen et al., 1999[ 56 ]). Stress can stimulate the autonomic sympathetic nervous system to increase vasoconstriction, which can mediate an increase in blood pressure, an increase in blood lipids, disorders in blood clotting, vascular changes, atherogenesis; all, of which, can cause cardiac arrhythmias and subsequent myocardial infarction (Rozanski et al., 1999[ 93 ]; Vrijkotte et al., 2000[ 120 ]; Sgoifo et al., 1998[ 111 ]). These effects from stress are observed clinically with atherosclerosis and leads to an increase in coronary vasoconstriction (Rozanski et al., 1999[ 93 ]). Of course, there are individual differences in terms of the level of autonomic-based responses due to stress, which depends on the personal characteristics of a given individual (Rozanski et al., 1999[ 93 ]). Thus, training programs for stress management are aimed at reducing the consequences of stress and death resulting from heart disease (Engler and Engler, 1995[ 29 ]). In addition, there are gender-dependent differences in the cardiovascular response to stress and, accordingly, it has been estimated that women begin to exhibit heart disease ten years later that men, which has been attributed to the protective effects of the estrogen hormone (Rozanski et al., 1999[ 93 ]).

Studies have shown that psychological stress can cause alpha-adrenergic stimulation and, consequently, increase heart rate and oxygen demand (Rozanski et al., 1998[ 92 ], 1999[ 93 ]; Jiang et al., 1996[ 46 ]). As a result, coronary vasoconstriction is enhanced, which may increase the risk of myocardial infarction (Yeung et al., 1991[ 124 ]; Boltwood et al., 1993[ 8 ]; Dakak et al., 1995[ 20 ]). Several studies have demonstrated that psychological stress decreases the microcirculation in the coronary arteries by an endothelium-dependent mechanism and increases the risk of myocardial infarction (Dakak et al., 1995[ 20 ]). On the other hand, mental stress indirectly leads to potential engagement in risky behaviors for the heart, such as smoking, and directly leads to stimulation of the neuroendocrine system as part of the autonomic nervous system (Hornstein, 2004[ 43 ]). It has been suggested that severe mental stress can result in sudden death (Pignalberi et al., 2002[ 84 ]). Generally, stress-mediated risky behaviors that impact cardiovascular health can be summarized into five categories: an increase in the stimulation of the sympathetic nervous system, initiation and progression of myocardial ischemia, development of cardiac arrhythmias, stimulation of platelet aggregation, and endothelial dysfunction (Wu, 2001[ 123 ]).

Stress and Gastrointestinal Complications

The effects of stress on nutrition and the gastrointestinal (GI) system can be summarized with two aspects of GI function.

First, stress can affect appetite (Bagheri Nikoo et al., 2014[ 2 ]; Halataei et al., 2011[ 37 ]; Ranjbaran et al., 2013[ 86 ]). This effect is related to involvement of either the ventral tegmental area (VTA), or the amygdala via N-methyl-D-aspartate (NMDA) glutamate receptors (Nasihatkon et al., 2014[ 80 ]; Sadeghi et al., 2015[ 94 ]). However, it should also be noted that nutrition patterns have effects on the response to stress (Ghanbari et al., 2015[ 31 ]), and this suggests a bilateral interaction between nutrition and stress.

Second, stress adversely affects the normal function of GI tract. There are many studies concerning the effect of stress on the function of the GI system (Söderholm and Perdue, 2001[ 112 ]; Collins, 2001[ 18 ]). For instance, studies have shown that stress affects the absorption process, intestinal permeability, mucus and stomach acid secretion, function of ion channels, and GI inflammation (Collins, 2001[ 18 ]; Nabavizadeh et al., 2011[ 79 ]). Stress also increases the response of the GI system to inflammation and may reactivate previous inflammation and accelerate the inflammation process by secretion of mediators such as substance P (Collins, 2001[ 18 ]). As a result, there is an increase in the permeability of cells and recruitment of T lymphocytes. Lymphocyte aggregation leads to the production of inflammatory markers, activates key pathways in the hypothalamus, and results in negative feedback due to CRH secretion, which ultimately results in the appearance of GI inflammatory diseases (Collins, 2001[ 18 ]). This process can reactivate previous silent colitis (Million et al., 1999[ 76 ]; Qiu et al., 1999[ 85 ]). Mast cells play a crucial role in stress-induced effects on the GI system, because they cause neurotransmitters and other chemical factors to be released that affect the function of the GI system (Konturek et al., 2011[ 55 ]).

Stress can also alter the functional physiology of the intestine (Kiliaan et al., 1998[ 52 ]). Many inflammatory diseases, such as Crohn's disease and other ulcerative-based diseases of the GI tract, are associated with stress (Hommes et al., 2002[ 42 ]). It has been suggested that even childhood stress can lead to these diseases in adulthood (Schwartz and Schwartz, 1983[ 106 ]). Irritable bowel syndrome, which is a disease with an inflammatory origin, is highly related to stress (Gonsalkorale et al., 2003[ 33 ]). Studies on various animals suggest the existence of inflammatory GI diseases following induction of severe stress (Qiu et al., 1999[ 85 ]; Collins et al., 1996[ 19 ]). Additionally, pharmacological interventions, in an attempt to decrease the response of CRH to stress, have been shown to result in an increase in GI diseases in rats (Million et al., 1999[ 76 ]).

Altering the permeability of the mucosal membrane by perturbing the functions of mucosal mast cells may be another way that stress causes its effects on the GI system, since this is a normal process by which harmful and toxic substances are removed from the intestinal lumen (Söderholm and Perdue, 2001[ 112 ]). Also, stress can both decrease the removal of water from the lumen, as well as induce sodium and chloride secretion into the lumen. This most likely occurs by increasing the activity of the parasympathetic nervous system (Barclay and Turnberg, 1987[ 3 ]). Moreover, physical stress, such as trauma or surgery, can increase luminal permeability (Söderholm and Perdue, 2001[ 112 ]) (Table 2 (Tab. 2) ; References in Table 2: Halataei et al., 2011[ 37 ]; Ranjbaran et al., 2013[ 86 ]; Mönnikes et al., 2001[ 77 ]; Collins, 2001[ 18 ]; Nabavizadeh et al., 2011[ 79 ]; Barclay and Turnberg, 1987[ 3 ]; Million et al., 1999[ 76 ]; Gonsalkorale et al., 2003[ 33 ]).

Stress also affects movement of the GI tract. In this way, it prevents stomach emptying and accelerates colonic motility (Mönnikes et al., 2001[ 77 ]). In the case of irritable bowel syndrome, stress increases the movement (contractility and motility) of the large intestine (Mönnikes et al., 2001[ 77 ]). Previous studies have revealed that CRH increases movement in the terminal sections of the GI tract and decreases the movements in the proximal sections of the GI tract (Mönnikes et al., 2001[ 77 ]). A delay in stomach emptying is likely accomplished through CRH-2 receptors, while type 1 receptors affect the colon (Mönnikes et al., 2001[ 77 ]). The effects produced by CRH are so prominent that CRH is now considered an ideal candidate for the treatment of irritable bowel syndrome (Martinez and Taché, 2006[ 69 ]). When serotonin is released in response to stress (Chaouloff, 2000[ 14 ]), it leads to an increase in the motility of the colon by stimulating 5HT-3 receptors (Mönnikes et al., 2001[ 77 ]). Moreover, it has also been suggested that stress, especially mental and emotional types of stress, increase visceral sensitivity and activate mucosal mast cells (Mönnikes et al., 2001[ 77 ]). Stimulation of the CNS by stress has a direct effect on GI-specific nervous system ( i.e. , the myenteric system or plexus) and causes the above mentioned changes in the movements of the GI tract (Bhatia and Tandon, 2005[ 5 ]). In fact, stress has a direct effect on the brain-bowel axis (Konturek et al., 2011[ 55 ]). Various clinical studies have suggested a direct effect of stress on irritable bowel syndrome, intestinal inflammation, and peptic ulcers (Konturek et al., 2011[ 55 ]).

In conclusion, the effects of stress on the GI system can be classified into six different actions: GI tract movement disorders, increased visceral irritability, altered rate and extent of various GI secretions, modified permeability of the intestinal barrier, negative effects on blood flow to the GI tract, and increased intestinal bacteria counts (Konturek et al., 2011[ 55 ]).

Stress and the Endocrine System

There is a broad and mutual relationship between stress and the endocrine system. On one hand, stress has many subtle and complex effects on the activity of the endocrine system (Sapolsky, 2002[ 97 ]; Charmandari et al., 2005[ 15 ]), while on the other hand, the endocrine system has many effects on the response to stress (Ulrich-Lai and Herman, 2009[ 117 ]; Selye, 1956[ 110 ]). Stress can either activate, or change the activity of, many endocrine processes associated with the hypothalamus, pituitary and adrenal glands, the adrenergic system, gonads, thyroid, and the pancreas (Tilbrook et al., 2000[ 116 ]; Brown-Grant et al., 1954[ 11 ]; Thierry et al., 1968[ 115 ]; Lupien and McEwen, 1997[ 64 ]). In fact, it has been suggested that it is impossible to separate the response to stress from the functions of the endocrine system. This premise has been advanced due to the fact that even a minimal amount of stress can activate the hypothalamic-pituitary-adrenal axis, which itself is intricately involved with the activation of several different hormone secreting systems (Sapolsky, 2002[ 97 ]). In different locations throughout this article, we have already discussed the effects of stress on hormones and various endocrine factors and, thus, they will not be further addressed.

Altogether, stress may induce both beneficial and harmful effects. The beneficial effects of stress involve preserving homeostasis of cells/species, which leads to continued survival. However, in many cases, the harmful effects of stress may receive more attention or recognition by an individual due to their role in various pathological conditions and diseases. As has been discussed in this review, various factors, for example, hormones, neuroendocrine mediators, peptides, and neurotransmitters are involved in the body's response to stress. Many disorders originate from stress, especially if the stress is severe and prolonged. The medical community needs to have a greater appreciation for the significant role that stress may play in various diseases and then treat the patient accordingly using both pharmacological (medications and/or nutraceuticals) and non-pharmacological (change in lifestyle, daily exercise, healthy nutrition, and stress reduction programs) therapeutic interventions. Important for the physician providing treatment for stress is the fact that all individuals vary in their response to stress, so a particular treatment strategy or intervention appropriate for one patient may not be suitable or optimal for a different patient.

Yunes Panahi and Amirhossein Sahebkar (Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran, P.O. Box: 91779-48564, Iran; Tel: 985118002288, Fax: 985118002287, E-mail: [email protected], [email protected]) contributed equally as corresponding authors.

Conflict of interest

The authors declare that have no conflict of interest in this study.

Acknowledgement

The authors would like to thank the "Neurosciences Research Center of Baqiyatallah University of Medical Sciences" and the “Clinical Research Development Center of Baqiyatallah (a.s.) Hospital” for providing technical supports.

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AMRC briefing paper on embedding research in the NHS

On 19 September 2024 the Association of Medical Research Charities (AMRC) published a briefing paper on embedding research in the NHS .

The briefing outlined why research and innovation must be a central part of the solution in the NHS 10-year health plan, and how we can ensure that research is embedded effectively in the NHS by prioritising three areas:

• supporting a thriving clinical research workforce
• maximising opportunities for everyone to take part in research
• making it easy to deliver research throughout the NHS.

We welcome the briefing from AMRC and our Director of Approvals Service, Janet Messer has responded below.

“We were pleased to see the helpful briefing from AMRC following on from the publication of Lord Darzi’s review last week. It provides a further reminder of the importance of research in the NHS. “We agree that charities play a vital role in health and social care research and the AMRC briefing highlights the wide range of benefits non-commercially funded research brings to UK. “The briefing highlights three priorities to ensure research is embedded effectively in the NHS and the Health Research Authority is already working with our partners to support work in these key areas. “We are pleased to see that the HRA’s work with others to champion the importance of diversity and inclusion in research has been recognised. The UK’s diverse population, alongside the well-established research infrastructure in the NHS, provides a unique opportunity for properly representative research to be carried out. This is a key way to tackling health inequalities and to support this we will soon be asking for feedback on our draft inclusion and diversity plan and guidance which is designed to support the research community to design inclusive research. “We are also working with others to clarify how data can be used to identify and invite people to take part in research, to help increase recruitment to clinical studies and trials. “Our aim is to make it easy to do research that people can trust. This briefing makes it clear that more needs to be done to make it easier to deliver research in the NHS, and we are committed to doing everything we can to support this. We are working with others on a range of actions to speed up the set-up of research in the NHS. Across the NHS we have already made a difference to the set-up of commercial research through the National Contract Value Review (NCVR) process which removes the duplication in costing by individual NHS organisations. Thanks to NCVR in 2023 we saw that participating commercial study set-up times were over 100 days quicker compared to pre-pandemic levels. “We understand that the research community is keen to know about the upcoming changes to Clinical Trials Legislation and we have committed to ensuring that we share guidance well in advance of any changes coming into effect so that everyone understands what they need to do.”

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