Unhealthy eating patterns, physical inactivity and alcohol misuse are commonly reported by individuals with severe mental illness (SMI) and significantly contribute to premature mortality. People with SMI could benefit from psychoeducational interventions focused on lifestyle modification.

To evaluate the effectiveness of the LIFESTYLE programme to improve dietary habits and physical activity levels and reduce alcohol use in individuals with SMI versus controls receiving a less structured psychoeducational programme (Italian Ministry of University and Research, trial registration number: 2015C7374S).

This multicentre randomised controlled trial (RCT) was conducted across six Italian universities and included 401 participants diagnosed with SMI, randomly allocated to either the test group or a comparison group.

At 1-year follow-up, generalised estimating equations showed that the trial intervention boosted the likelihood of higher weekly metabolic equivalents of task (METs) expended on total activity (odds ratio 1.43, 95% CI 1.08–1.89; p < 0.01), on walking (odds ratio 1.50, 95% CI 1.18–1.90; p < 0.001) and on moderate activity (odds ratio 1.85, 95% CI 1.24–2.77; p < 0.01). Improvements in dietary habits included increased intake of fish (odds ratio 1.67, 95% CI 1.45–1.97; p < 0.05), fresh fruit (odds ratio 1.36, 95% CI 1.05–1.76; p < 0.05) and vegetables (odds ratio 1.91, 95% CI 1.56–1.96; p < 0.05), along with reduced junk food consumption (OR = 0.81, 95% CI 0.63–0.99; p < 0.05) and daily alcohol use (odds ratio 0.70, 95% CI 0.52–0.95; p < 0.05).

The LIFESTYLE intervention proved effective in promoting healthier lifestyles among individuals with SMI, with sustained benefits at 1 year. This structured programme could be a valuable addition to routine mental healthcare.

Fine particulate matter (PM2.5) exposure and unfavourable lifestyle are both significant risk factors for mental health disorders, yet their combined effects on adolescent depression and anxiety remain poorly understood. This study aims to determine whether PM2.5 exposure and lifestyle are independently associated with adolescent depression and anxiety, and whether there are joint effects between these factors on mental health outcomes.

In this cross-sectional study, 19852 participants were analysed. PM2.5 concentrations were obtained from the ChinaHighAirPollutants (CHAP) dataset. Lifestyle factors were assessed through self-reported questionnaires, and a healthy lifestyle score was developed based on eight lifestyle risk factors. Depression and anxiety were assessed using the PHQ-9 and GAD-7 scales. Restricted cubic spline analysed dose–response relationships between PM2.5 exposure and mental health outcomes. The independent and joint effects were assessed using logistic regression models. Both multiplicative and additive interactions (relative excess risk due to interaction, RERI) were examined. Multiple classification approaches were incorporated to ensure robust results.

The study included 19852 participants with a mean age of 15.16 years (SD 1.60), comprising 9886 (49.8%) males and 9966 (50.2%) females. Depression and anxiety were identified in 3845 (19.37%) and 3230 (16.27%) participants, respectively. PM2.5 exposure showed a linear dose-response relationship with depression and anxiety. Joint effects analysis at the 75th percentile of PM2.5 with a lifestyle risk score of 4 revealed the strongest associations, with adjusted odds ratios of 4.49 (95% CI: 3.79–5.33) for depression, 4.01 (95% CI: 3.36–4.78) for anxiety and 4.24 (95% CI: 3.52–5.10) for their comorbidity. Simultaneously, significant additive interactions (RERI > 0) between high levels of PM2.5 exposure and unfavourable lifestyle factors were detected, suggesting synergistic effects on mental health outcomes. Subgroup and sensitivity analyses confirmed the robustness of these findings.

High PM2.5 exposure and unfavourable lifestyle factors demonstrated significant independent and joint effects on depression and anxiety among adolescents. These findings highlight that implementing stringent air pollution control measures, combined with promoting healthy lifestyle practices, may be crucial for protecting adolescent mental health.

Few studies examine the relationship between physical activity, multiple physical fitness domains (cardiorespiratory fitness, strength, speed), and cognition. Our objective was to investigate the association between physical activity and executive function in middle-aged and older adults and examine whether modifiable physical fitness components explain the relationship between physical activity and cognition.

Self-reported moderate-to-vigorous physical activity and objective measures of cardiorespiratory fitness (2-minute walk test), strength (grip strength), speed (4-meter walk test), and executive function were collected from 623 adults within the Human Connectome Project–Aging (ages 36 – 100 years; mean = 59.2 years; 57.8% female). Relative importance metrics, multiple regression, and conditional process analysis were used to examine relationships of age, physical activity, and physical fitness with executive function.

Greater physical fitness was related to better executive function performance (β = 0.28, p < .001). Physical activity was not associated with executive function (β = −0.04, p = .16). There was an indirect relationship between physical activity and executive function through physical fitness (ab = 0.02, 95% CI: 0.004 – 0.04). This association was explained primarily by the indirect association of cardiorespiratory fitness with physical activity and executive function. The indirect association of cardiorespiratory fitness with physical activity and executive function was significant in older study participants (mean (59 years) and + 1 SD (74 years)), but not younger (−1 SD (44 years)), although between-group comparisons were not significant.

These data highlight potential differential associations with cognition when considering physical activity and physical fitness, and the importance of considering multiple domains of physical fitness in relation to physical activity and cognitive performance.

To determine the prevalence and characteristics of plant-based patterns in the Spanish population and assess their potential impact on individuals with similar socio-demographic backgrounds.

We estimated vegetarian and vegan individuals’ national and regional prevalence and analysed their socio-demographic characteristics and weekly dietary intake patterns. Individuals with a plant-based dietary pattern were matched to a control group (1:4) with similar socio-demographic characteristics. Associations with the prevalence risk of common chronic diseases, self-reported health status, lifestyle and healthcare use were analysed with unadjusted and adjusted logistic regression models.

A population-based survey of individuals residing in Spain.

Data from 22 072 participants were examined.

The prevalence of plant-based diets was 5·62‰ (95 % CI: 4·33, 7·28), and adherents were female (68·6 %), single (62·3 %) and university-educated 41·8 %) (P < 0·001). They reported higher rates of ‘never’ consuming snacks (50 % v. 35 %), fast food (58 % v. 36 %) and sweets (33 % v. 14 %). Lifestyle factors did not differ between the plant-based and omnivorous groups; however, adherence to plant-based diets was associated with a prevalence risk of depressive symptoms (OR 2·58, 95 % CI: 1·00, 6·65), stroke (OR 7·08, 95 % CI: 1·27, 39·46) and increased consultations for mental health and complementary medicine (OR 3·21, 95 % CI: 1·38, 7·43).

Plant-based diets are uncommon and are associated with specific socio-demographic profiles, particularly sex. When comparing individuals with similar socio-demographic characteristics, individuals with plant-based diets and omnivores had similar lifestyles. Addressing patient concerns regarding diet and personal well-being might prioritise healthy behaviours over specific dietary patterns.

It is unknown whether there is a general factor that accounts for the propensity for both physical and mental conditions in different age groups and how it is associated with lifestyle and well-being.

We analyzed health conditions data from the Millennium Cohort Study (MCS) (age = 17; N = 19,239), the National Child Development Study (NCDS) (age = 44; N = 9293), and the English Longitudinal Study of Ageing (ELSA) (age ≥ 50; N = 7585). The fit of three Confirmatory Factor models was used to select the optimal solution by Comparative Fit Index, Tucker-Lewis Index, and Root Mean Square Error of Approximation. The relationship among d factor, lifestyles, and well-being was further explored.

Supporting the existence of the d factor, the bi-factor model showed the best model fit in 17-year-olds (MCS:CFI = 0.97, TFI = 0.96, RMSEA = 0.01), 44-year-olds (NCDS:CFI = 0.96, TFI = 0.95, RMSEA = 0.02), and 50+ year-olds (ELSA:CFI = 0.97, TFI = 0.96, RMSEA = 0.02). The d factor scores significantly correlated with lifestyle and well-being, suggesting healthier lifestyles were associated with a reduced likelihood of physical and mental health comorbidities, which in turn improved well-being.

Contrary to the traditional dichotomy between mental and physical conditions, our study showed a general factor underlying the comorbidity across mental and physical diseases, related to lifestyle and well-being. Our results inform the conceptualization of mental and physical illness as well as future research assessing risk and pathways of disease transmission, intervention, and prevention. Our results also provide a strong rationale for a systematic screening for mental disorders in individuals with physical conditions and vice versa, and for integrated services addressing multimorbidity.

Little is known about the dose and pattern of moderate-to-vigorous physical activity (MVPA) to prevent depression. We aimed to assess the prospective association of dose and pattern of accelerometer-derived MVPA with the risk of diagnosed depression.

We included 74,715 adults aged 40–69 years from the UK Biobank cohort who were free of severe disease at baseline and participated in accelerometer measurements (mean age 55.2 years [SD 7.8]; 58% women). MVPA at baseline was derived through 1-week wrist-worn accelerometry. Diagnosed depression was defined by hospitalization with ICD-10 codes F32.0-F32.A. Restricted cubic splines and Cox regression determined the prospective association of dose and pattern of MVPA with the risk of incident depression.

Over a median 7.9-year follow-up, there were 3,089 (4.1%) incident cases of depression. Higher doses of MVPA were curvilinearly associated with lower depression risk, with the largest minute-per-minute added benefits occurring between 5 (HR 0.99 [95% CI 0.96–0.99]) and 280 (HR 0.67 [95% CI 0.60–0.74]) minutes per week (reference: 0 MVPA minutes).

Regardless of pattern, higher doses of MVPA were associated with lower depression risk in a curvilinear manner, with the greatest incremental benefit per minute occurring during the first 4–5 h per week. Optimal benefits occurred around 15 h/week.

Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life.

Data from the UK Biobank were available for 966 participants with BD, aged between 40 and 69 years. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; (1) health risk behaviors (physical activity, sedentary behavior, smoking, and sleep) and (2) physiological risk factors, stratified into (2a) anthropometric and clinical risk (handgrip strength, body composition, and blood pressure), and (2b) cardiometabolic disease risk biomarkers (CRP, lipid profile, and HbA1c). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models.

In the final combined model, lower mentally active and higher passive sedentary behavior, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition.

Health risk behaviors, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.

To investigate the association between a lifestyle score and all-cause mortality in the Chilean population.

Prospective study.

The score was based on seven modifiable behaviours: salt intake, fruit and vegetable intake, alcohol consumption, sleep duration, smoking, physical activity and sedentary behaviours. 1-point was assigned for each healthy recommendation. Points were summed to create an unweighted score from 0 (less healthy) to 7 (healthiest). According to their score, participants were then classified into: less healthy (0–2 points), moderately healthy (3–4 points) and the healthiest (5–7 points). Associations between the categories of lifestyle score and all-cause mortality were investigated using Cox proportional hazard models adjusted for confounders. Nonlinear associations were also investigated.

2706 participants from the Chilean National Health Survey 2009–2010.

After a median follow-up of 10·9 years, 286 (10·6 %) participants died. In the maximally adjusted model, and compared with the healthiest participants, those less healthy had 2·55 (95 % CI 1·75, 3·71) times higher mortality risk due to any cause. Similar trends were identified for the moderately healthy group. Moreover, there was a significant trend towards increasing the mortality risk when increasing unhealthy behaviours (hazard ratio model 3: 1·61 (95 % CI 1·34, 1·94)). There was no evidence of nonlinearity between the lifestyle score and all-cause mortality.

Individuals in the less healthy lifestyle category had higher mortality risk than the healthiest group. Therefore, public health strategies should be implemented to promote adherence to a healthy lifestyle across the Chilean population.