The use of dietary patterns empirically derived from principal components analysis and alternative strategies to identify associations between diet and disease

Dietary patterns derived empirically using principal components analysis (PCA) are widely employed for investigating diet-disease relationships. The aim of the study was to investigate whether PCA performed better at identifying associations between diet and disease than analysing each food on the FFQ separately, a process we refer to as exhaustive single food analysis (ESFA). A systematic review of nutritional epidemiology literature relating to the use of PCA in identifying dietary patterns in observational and cohort studies from 2004-2009 was employed. Furthermore, we simulated diet and disease data using real food frequency questionnaire data and assuming that a number of foods or dietary pattern intakes were causally associated with disease. In each simulation, ESFA and PCA were employed to identify foods associated with disease using logistic regression, allowing for multiple testing and adjusting for energy intake. ESFA was further adjusted for principal components, foods which were significant in unadjusted ESFA, and propensity scores. For each method, we investigated the power, with which we could identify an association between diet and disease, and the power and false discovery rate (FDR) for identifying associations with specific food intakes. We apply our innovative methodology to a real dietary dataset (GA2LEN survey). ESFA had greater power to detect an association of diet with disease than PCA, and greater power and lower FDR for identifying associations with specific foods. FDR increased with increasing sample size using both methods. However, when ESFA was adjusted for foods that were significant in unadjusted ESFA, FDRs were controlled successfully at the desired level of 20%. Our results raise questions about the use of PCA in nutritional epidemiology. Adjusted ESFA identifies foods that are causally linked to disease with a low rate of false discoveries, and surprisingly good power. These findings were not fully supported from the analysis of the GA2LEN data-set

The use of dietary patterns empirically derived from principal components analysis and alternative strategies to identify associations between diet and disease

Dietary patterns derived empirically using principal components analysis (PCA) are widely employed for investigating diet-disease relationships. The aim of the study was to investigate whether PCA performed better at identifying associations between diet and disease than analysing each food on the FFQ separately, a process we refer to as exhaustive single food analysis (ESFA). A systematic review of nutritional epidemiology literature relating to the use of PCA in identifying dietary patterns in observational and cohort studies from 2004-2009 was employed. Furthermore, we simulated diet and disease data using real food frequency questionnaire data and assuming that a number of foods or dietary pattern intakes were causally associated with disease. In each simulation, ESFA and PCA were employed to identify foods associated with disease using logistic regression, allowing for multiple testing and adjusting for energy intake. ESFA was further adjusted for principal components, foods which were significant in unadjusted ESFA, and propensity scores. For each method, we investigated the power, with which we could identify an association between diet and disease, and the power and false discovery rate (FDR) for identifying associations with specific food intakes. We apply our innovative methodology to a real dietary dataset (GA2LEN survey). ESFA had greater power to detect an association of diet with disease than PCA, and greater power and lower FDR for identifying associations with specific foods. FDR increased with increasing sample size using both methods. However, when ESFA was adjusted for foods that were significant in unadjusted ESFA, FDRs were controlled successfully at the desired level of 20%. Our results raise questions about the use of PCA in nutritional epidemiology. Adjusted ESFA identifies foods that are causally linked to disease with a low rate of false discoveries, and surprisingly good power. These findings were not fully supported from the analysis of the GA2LEN data-set

Mental health-related conversations on social media and crisis episodes: a time-series regression analysis

We aimed to investigate whether daily fluctuations in mental health-relevant Twitter posts are associated with daily fluctuations in mental health crisis episodes. We conducted a primary and replicated time-series analysis of retrospectively collected data from Twitter and two London mental healthcare providers. Daily numbers of ‘crisis episodes’ were defined as incident inpatient, home treatment team and crisis house referrals between 2010 and 2014. Higher volumes of depression and schizophrenia tweets were associated with higher numbers of same-day crisis episodes for both sites. After adjusting for temporal trends, seven-day lagged analyses showed significant positive associations on day 1, changing to negative associations by day 4 and reverting to positive associations by day 7. There was a 15% increase in crisis episodes on days with above-median schizophrenia-related Twitter posts. A temporal association was thus found between Twitter-wide mental health-related social media content and crisis episodes in mental healthcare replicated across two services. Seven-day associations are consistent with both precipitating and longer-term risk associations. Sizes of effects were large enough to have potential local and national relevance and further research is needed to evaluate how services might better anticipate times of higher risk and identify the most vulnerable groups

Comparing the characteristics of users of an online service for STI self-sampling with clinic service users: a cross-sectional analysis.

OBJECTIVES: Online services for self-sampling at home could improve access to STI testing; however, little is known about those using this new modality of care. This study describes the characteristics of users of online services and compares them with users of clinic services. METHODS: We conducted a cross-sectional analysis of routinely collected data on STI testing activity from online and clinic sexual health services in Lambeth and Southwark between 1January 2016 and 31March 2016. Activity was included for chlamydia, gonorrhoea, HIV and syphilis testing for residents of the boroughs aged 16 years and older. Logistic regression models were used to explore potential associations between type of service use with age group, gender, ethnic group, sexual orientation, positivity and Index of Multiple Deprivation (IMD) quintiles. We used the same methods to explore potential associations between return of complete samples for testing with age group, gender, ethnic group, sexual orientation and IMD quintiles among online users. RESULTS: 6456 STI tests were carried out by residents in the boroughs. Of these, 3582 (55.5%) were performed using clinic services and 2874 (44.5%) using the online service. In multivariate analysis, online users were more likely than clinic users to be aged between 20 and 30 years, female, white British, homosexual or bisexual, test negative for chlamydia or gonorrhoea and live in less deprived areas. Of the individuals that ordered a kit from the online service, 72.5% returned sufficient samples. In multivariate analysis, returners were more likely than non-returners to be aged >20 years and white British. CONCLUSION: Nearly half (44.5%) of all basic STI testing was done online, although the characteristics of users of clinic and online services differed and positivity rates for those using the online service for testing were lower. Clinics remain an important point of access for some groups

COVID-19 ethnic inequalities in mental health and multimorbidities: protocol for the COVEIMM study

PURPOSE: The COVID-19 pandemic may have exacerbated ethnic health inequalities, particularly in people with multiple long-term health conditions, the interplay with mental health is unclear. This study investigates the impact of the pandemic on the association of ethnicity and multimorbidity with mortality/service use among adults, in people living with severe mental illnesses (SMI). METHODS: This study will utilise secondary mental healthcare records via the Clinical Record Interactive Search (CRIS) and nationally representative primary care records through the Clinical Practice Interactive Research Database (CPRD). Quasi-experimental designs will be employed to quantify the impact of COVID-19 on mental health service use and excess mortality by ethnicity, in people living with severe mental health conditions. Up to 50 qualitative interviews will also be conducted, co-produced with peer researchers; findings will be synthesised with quantitative insights to provide in-depth understanding of observed associations. RESULTS: 81,483 people in CRIS with schizophrenia spectrum, bipolar or affective disorder diagnoses, were alive from 1st January 2019. Psychiatric multimorbidities in the CRIS sample were comorbid somatoform disorders (30%), substance use disorders (14%) and personality disorders (12%). In CPRD, of 678,842 individuals with a prior probable diagnosis of COVID-19, 1.1% (N = 7493) had an SMI diagnosis. People in the SMI group were more likely to die (9% versus 2% in the non-SMI sample) and were more likely to have mental and physical multimorbidities. CONCLUSION: The effect of COVID-19 on people from minority ethnic backgrounds with SMI and multimorbidities remains under-studied. The present mixed methods study aims to address this gap

Key lessons learned from the INDIGO global network on mental health related stigma and discrimination

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Implementation Strategies and the Uptake of the World Health Organization Surgical Safety Checklist in Low and Middle Income Countries: A Systematic Review and Meta-analysis.

OBJECTIVES: To identify the implementation strategies used in World Health Organization Surgical Safety Checklist (SSC) uptake in low- and middle-income countries (LMICs); examine any association of implementation strategies with implementation effectiveness; and to assess the clinical impact. BACKGROUND: The SSC is associated with improved surgical outcomes but effective implementation strategies are poorly understood. METHODS: We searched the Cochrane library, MEDLINE, EMBASE and PsycINFO from June 2008 to February 2019 and included primary studies on SSC use in LMICs. Coprimary objectives were identification of implementation strategies used and evaluation of associations between strategies and implementation effectiveness. To assess the clinical impact of the SSC, we estimated overall pooled relative risks for mortality and morbidity. The study was registered on PROSPERO (CRD42018100034). RESULTS: We screened 1562 citations and included 47 papers. Median number of discrete implementation strategies used per study was 4 (IQR: 1-14, range 0-28). No strategies were identified in 12 studies. SSC implementation occurred with high penetration (81%, SD 20%) and fidelity (85%, SD 13%), but we did not detect an association between implementation strategies and implementation outcomes. SSC use was associated with a reduction in mortality (RR 0.77; 95% CI 0.67-0.89), all complications (RR 0.56; 95% CI 0.45-0.71) and infectious complications (RR 0.44; 95% CI 0.37-0.52). CONCLUSIONS: The SSC is used with high fidelity and penetration is associated with improved clinical outcomes in LMICs. Implementation appears well supported by a small number of tailored strategies. Further application of implementation science methodology is required among the global surgical community