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The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable.
Quantify mental health inequalities in disruptions to healthcare, economic activity and housing.
We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies.
Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3–33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20–1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09–1.41) for disruption to procedures to 1.33 (95% CI 1.20–1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06–1.21) and income (OR 1.12, 95% CI 1.06 –1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00–1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18–1.32) or in one domain (OR 1.11, 95% CI 1.07–1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97–1.03).
People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.
Single patient or ‘n-of-1’ trials are a pragmatic method to achieve optimal, evidence-based treatments for individual patients. Such trials could be particularly valuable in chronic, heterogeneous, difficult to treat illnesses such as schizophrenia.
To identify how often, and in what way, n-of-1 trials have been used in schizophrenia.
We performed a systematic search in the major electronic databases for studies adopting n-of-1 methodology in schizophrenia, published in English from the start of records until the end of January 2017.
We identified six studies meeting inclusion criteria. There was wide variability in study methodology and analysis. Each trial reported positive outcomes for their respective intervention, but all studies were at high risk of bias.
In conclusion, n-of-1 trials are currently underutilised in schizophrenia. Existing trials suggest the method is well tolerated and potentially effective in achieving optimal treatments for patients, but more standardised methods of design, execution and analysis are required in future trials.
Declaration of interest
S.M.L. has received grants and personal fees from Janssen, and personal fees from Otsuka and Sunovion, in the past 3 years, outside the submitted work.
To identify predictors of increasing waist circumference (WC) over a 5-year period in a contemporary population of Australian adults.
Longitudinal national cohort of adults participating in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
Australian adults in 2000 and 2005.
A total of 2521 men and 2726 women aged ≥25 years at baseline who participated in AusDiab and provided anthropometric measurements at baseline (1999–2000) and follow-up (2005).
A ≥5 % increase of baseline WC occurred in 27 % of men and 38 % of women over the 5-year period. In the multivariate analysis of the total population, there was a higher risk of ≥5 % gain in baseline WC in women, younger people, people with a lower baseline WC, people who never married compared with married/de facto, current smokers compared with never smokers, people with a poorer diet quality and people with a low energy intake. However, there was no significant association with many expected predictors of waist gain such as physical activity. There were some associations between other lifestyle factors and change of WC by sex, age, level of education and across WC categories, but the associations differed across these groups.
A ≥5 % increase of baseline WC occurred in a significant proportion of men and women over the 5-year period. Of the behavioural factors, poor diet quality was the key predictor of the ≥5 % increase of baseline WC in this cohort. The findings highlight the need to understand better the causal role of lifestyle in regard to increasing WC over time.
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