The COVID-19 pandemic and associated restrictive measures affected the mental health and well-being of individuals globally. We assessed non-modifiable and modifiable factors associated with the change in well-being and mental health from before to during the COVID-19 pandemic in South Africa.

A cross-sectional online survey was conducted from 26 April, 2020, to 22 April, 2021. Paired samples t-tests were conducted to assess change in well-being (measured on The World Health Organization-Five Well-Being Index (WHO-5)) and mental health (a validated composite psychopathology p-score). Sociodemographic, environmental, clinical, and behavioural factors associated with change in outcomes were examined.

The sample comprised of 1866 adults (M age = 44.26 ± 17.36 years, female = 78.9%). Results indicated a significant decrease in well-being (p < 0.001) and increase in p-score (p < 0.001) from before to during the pandemic. Having a prior mental health condition was associated with a worsening well-being score, while being female was associated with a worsening p-score. Being of Black African descent was associated with improved p-score and higher socio-economic status (SES) was associated with improved well-being. Factors associated with worsening of both well-being and the p-score included adulthood adversity, financial loss since COVID-19, and placing greater importance on direct contact/interactions and substance use as coping strategies. Higher education level and endorsing studying/learning something new as a very important coping strategy were associated with improved well-being and p-score.

Findings inform the need for targeted interventions to reduce and prevent adverse well-being and mental health outcomes during a pandemic, especially among vulnerable groups.

Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies.

PubMed/MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 14 January 2020. Meta-analyses of observational studies examining the association between depression and levels of tumor necrosis factor-α (TNF-α), interleukin 1-β (IL-1β), interleukin-6 (IL-6), and C-reactive protein (CRP) were eligible. Errors were classified as follows: incorrect sample sizes, incorrectly used standard deviation, incorrect participant inclusion, calculation error, or analysis with insufficient data. We determined their impact on the results after correction thereof.

Errors were noted in 14 of the 15 meta-analyses included. Across 521 primary studies, 118 (22.6%) showed the following errors: incorrect sample sizes (20 studies, 16.9%), incorrect use of standard deviation (35 studies, 29.7%), incorrect participant inclusion (7 studies, 5.9%), calculation errors (33 studies, 28.0%), and analysis with insufficient data (23 studies, 19.5%). After correcting these errors, 11 (29.7%) out of 37 pooled effect sizes changed by a magnitude of more than 0.1, ranging from 0.11 to 1.15. The updated meta-analyses showed that elevated levels of TNF- α, IL-6, CRP, but not IL-1β, are associated with depression.

These findings show that data extraction errors in meta-analyses can impact findings. Efforts to reduce such errors are important in studies of the association between depression and peripheral inflammatory biomarkers, for which high heterogeneity and conflicting results have been continuously reported.

A complex interaction exists between age, body mass index, medical conditions, polypharmacotherapy, smoking, alcohol use, education, nutrition, depressive symptoms, functioning and quality of life (QoL). We aimed to examine the inter-relationships among these variables, test whether depressive symptomology plays a central role in a large sample of adults, and determine the degree of association with life-style and health variables.

Regularised network analysis was applied to 3532 North-American adults aged ⩾45 years drawn from the Osteoarthritis Initiative. Network stability (autocorrelation after case-dropping), centrality of nodes (strength, M, the sum of weight of the connections for each node), and edges/regularised partial correlations connecting the nodes were assessed.

Physical and mental health-related QoL (M = 1.681; M = 1.342), income (M = 1.891), age (M = 1.416), depressive symptoms (M = 1.214) and education (M = 1.173) were central nodes. Depressive symptoms’ stronger negative connections were found with mental health-related QoL (−0.702), income (−0.090), education (−0.068) and physical health-related QoL (−0.354). This latter was a ‘bridge node’ that connected depressive symptoms with Charlson comorbidity index, and number of medications. Physical activity and Mediterranean diet adherence were associated with income and physical health-related QoL. This latter was a ‘bridge node’ between the former two and depressive symptoms. The network was stable (stability coefficient = 0.75, i.e. highest possible value) for all centrality measures.

A stable network exists between life-style behaviors and social, environmental, medical and psychiatric variables. QoL, income, age and depressive symptoms were central in the multidimensional network. Physical health-related QoL seems to be a ‘bridge node’ connecting depressive symptoms with several life-style and health variables. Further studies should assess such interactions in the general population.