Children's behavioural and emotional wellbeing during the COVID-19 pandemic: Findings from the Born in Bradford COVID-19 mixed methods longitudinal study.

Background: The COVID-19 pandemic led to a multitude of immediate social restrictions for many across the world. In the UK, the lives of children and young people were quickly impacted when COVID-19 restrictions led to school closures for most children and restrictions on social interactions. The Born in Bradford COVID-19 longitudinal research study explored the impact of the COVID-19 pandemic on the lives of children and their families living in Bradford. Methods: Surveys were administered during the first wave of the pandemic (March to June 2020) and compared to findings from before the pandemic. The current study examined the social and emotional wellbeing of children from before to during the pandemic, measured using the parent completed Strengths and Difficulties questionnaire (SDQ). Regression analyses looked at associations between a range of social determinants of health and changes in SDQ scores. Results: The results showed that those children most likely to experience difficulties during the pandemic were boys, younger children, those from White British ethnicity (compared to Pakistani heritage children) and those living in the most deprived areas. There were associations between experiencing difficulties and: food insecurity; financial worry; getting below recommended levels of physical activity; and having less than the recommended amount of sleep. Conclusions: The effect of COVID-19 restrictions are likely to have had negative consequences on children that could, in time, have long-lasting impacts on the health, wellbeing and development of children in the UK.

The COVID-19 pandemic caused immediate and long-lasting social restrictions to be implemented here in the UK and across the world. In the UK, children and young people were quickly affected by these restrictions that led to school closures and other restrictions that prevented these individuals from socialising in person with one another. This study explored the impact that the pandemic had on the wellbeing of children by comparing data from before the pandemic with data collected during the pandemic. The data that has been collected looks at the behavioural strengths and difficulties that children are displaying. Our exploration found that children that were most likely to experience difficulties during the pandemic were boys, younger children, those who were White British and those who lived in the most deprived areas. The effect of the COVID-19 restrictions are likely to have had a negative impact on children and young people which in time may impact the health and development of children living here in the UK.

The Impact of the Pandemic on Mental Health in Ethnically Diverse Mothers: Findings from the Born in Bradford, Tower Hamlets and Newham COVID-19 Research Programmes.

Restrictions implemented by the UK Government during the COVID-19 pandemic have served to worsen mental health outcomes, particularly amongst younger adults, women, those living with chronic health conditions, and parents of young children. Studies looking at the impact for ethnic minorities have reported inconsistent findings. This paper describes the mental health experiences of mothers from a large and highly ethnically diverse population during the pandemic, using secondary analysis of existing data from three COVID-19 research studies completed in Bradford and London (Tower Hamlets and Newham). A total of 2807 mothers participated in this study with 44% White British, 23% Asian/Asian British Pakistani, 8% Other White and 7% Asian/Asian British Bangladeshi backgrounds. We found that 28% of mothers experienced clinically important depressive symptoms and 21% anxiety symptoms during the pandemic. In unadjusted analyses, mothers from White Other, and Asian/Asian British Bangladeshi backgrounds had higher odds of experiencing symptoms, whilst mothers from Asian/Asian British Indian backgrounds were the least likely to experience symptoms. Once loneliness, social support and financial insecurity were controlled for, there were no statistically significant differences in depression and anxiety by ethnicity. Mental health problems experienced during the pandemic may have longer term consequences for public health. Policy and decision makers must have an understanding of the high risk of financial insecurity, loneliness and a lack of social support on mother's mental health, and also recognise that some ethnic groups are far more likely to experience these issues and are, therefore, more vulnerable to poor mental health as a consequence.

Risk perception and disease knowledge in attendees of a community-based lung cancer screening programme.

OBJECTIVES: In England, a risk-based approach is used to determine eligibility for lung cancer screening. Ensuring effective communication and counselling of risk is therefore increasingly important. In this study, we explore the perception of lung cancer risk in attendees of a community-based screening service, located in socio-economically deprived areas of Manchester. We analyse responses based on demographic variables, calculated risk score and screening eligibility. MATERIALS AND METHODS: The Manchester Lung Health Check (LHC) programme invited ever smokers, age 55-80, to a lung cancer risk assessment in which their 6-year risk was calculated (using the PLCOM2012 model). Those at high risk (PLCOM2012 score ≥ 1.51%) were eligible for low dose CT (LDCT) screening. Prior to their assessment, attendees were invited to complete the study questionnaire, which assessed absolute and comparative risk perception, disease knowledge (incidence, survival, and risk factors), lung cancer specific worry, and mental health. RESULTS: 371 participants completed the questionnaire; 66% (n = 243) had linked clinical data. Perceived absolute risk was markedly higher than calculated risk (median: 20% vs. 1%; p < 0.001) and higher in women than men (25% vs. 15%; p = 0.001). There was no correlation between perceived absolute and calculated risk. Overall, 30% classified themselves at higher, and 21% at lower, lung cancer risk compared to others their age. Median PLCOM2012 score increased with perceived comparative risk (p = 0.004). Those eligible for screening were more likely to: classify themselves at higher comparative risk (41% vs. 21%; p < 0.0001), report lung cancer-specific worry (27% vs. 10%; p = 0.001) and have indications of depression (20% vs. 10%; p = 0.05). Family history of lung cancer was significantly associated with higher comparative risk (adjOR 4.03, 95%CI 1.74-9.3; p = 0.001). CONCLUSION: Employing comparative rather than absolute risk may assist risk counselling. Further research is required to determine the optimal approach to risk communication in this setting.

Weight Changes in Type 2 Diabetes and Cancer Risk: A Latent Class Trajectory Model Study.

INTRODUCTION: Body mass index (BMI) is often elevated at type 2 diabetes (T2D) diagnosis. Using latent class trajectory modelling (LCTM) of BMI, we examined whether weight loss after diagnosis influenced cancer incidence and all-cause mortality. METHODS: From 1995 to 2010, we identified 7,708 patients with T2D from the Salford Integrated Record database (UK) and linked to the cancer registry for information on obesity-related cancer (ORC), non-ORC; and all-cause mortality. Repeated BMIs were used to construct sex-specific latent class trajectories. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression models. RESULTS: Four sex-specific BMI classes were identified; stable-overweight, stable-obese, obese-slightly-decreasing, and obese-steeply-decreasing; comprising 41%, 45%, 13%, and 1% of women, and 45%, 37%, 17%, and 1% of men, respectively. In women, the stable-obese class had similar ORC risks as the obese-slightly-decreasing class, whereas the stable-overweight class had lower risks. In men, the obese-slightly-decreasing class had higher risks of ORC (HR = 1.86, 95% CI: 1.05-3.32) than the stable-obese class, while the stable-overweight class had similar risks No associations were observed for non-ORC. Compared to the stable-obese class, women (HR = 1.60, 95% CI: 0.99-2.58) and men (HR = 2.37, 95% CI: 1.66-3.39) in the obese-slightly-decreasing class had elevated mortality. No associations were observed for the stable-overweight classes. CONCLUSION: Patients who lost weight after T2D diagnosis had higher risks for ORC (in men) and higher all-cause mortality (both genders) than patients with stable obesity.

Informative Observation in Health Data: Association of Past Level and Trend with Time to Next Measurement.

In routine health data, risk factors and biomarkers are typically measured irregularly in time, with the frequency of their measurement depending on a range of factors - for example, sicker patients are measured more often. This is termed informative observation. Failure to account for this in subsequent modelling can lead to bias. Here, we illustrate this issue using body mass index measurements taken on patients with type 2 diabetes in Salford, UK. We modelled the observation process (time to next measurement) as a recurrent event Cox model, and studied whether previous measurements in BMI, and trends in the BMI, were associated with changes in the frequency of measurement. Interestingly, we found that increasing BMI led to a lower propensity for future measurements. More broadly, this illustrates the need and opportunity to develop and apply models that account for, and exploit, informative observation.

Obesity paradox and mortality in adults with and without incident type 2 diabetes: a matched population-level cohort study.

OBJECTIVE: Among adults with type 2 diabetes (T2D), several (but not all) studies show that being overweight (body mass index (BMI): 25.0-29.9 kg/m2) or obese I (BMI: 30.0-34.9 kg/m2) near the time of diagnosis, is unexpectedly associated with reduced all-cause mortality compared with normal weight-the obesity paradox. We addressed whether this observation is causal (eg, a true protective effect); due to confounding (including effect modification); or due to selection ('collider') bias. RESEARCH DESIGN AND METHODS: We performed a matched population-level cohort study using primary care records from Salford, UK (1995-2012) in 10 464 patients with incident T2D paired (1:3) with 31 020 individuals who never developed T2D. We estimated HRs for associations of BMI with all-cause mortality using Cox models, stratified by smoking status. RESULTS: Median follow-up was 8.7 years. For never smokers, the hazard of all-cause mortality increased from 25 kg/m2, in a linear manner, with increasing BMI in the T2D cohort (HR per 5 kg/m2: 1.23, ptrend<0.001) and in the non-diabetes cohort (HR per 5 kg/m2: 1.34, ptrend<0.001). In contrast, among ever smokers, BMI-mortality relationships were U-shaped in the T2D and non-diabetes cohorts. Evidence of the obesity paradox in ever smokers, with and without T2D, argued against a selection bias, but supported a contribution of effect modification by smoking (pinteraction=0.009). Results were stable to various sensitivity analyses. CONCLUSIONS: In this cohort, the obesity paradox is mainly explained by smoking as an effect modifier. These findings indicate that the obesity paradox does not challenge standard weight management recommendations among T2D patients.

The Obesity Paradox in Cancer: a Review.

There is a common perception that excess adiposity, commonly approximated by body mass index (BMI), is associated with reduced cancer survival. A number of studies have emerged challenging this by demonstrating that overweight and early obese states are associated with improved survival. This finding is termed the "obesity paradox" and is well recognized in the cardio-metabolic literature but less so in oncology. Here, we summarize the epidemiological findings related to the obesity paradox in cancer. Our review highlights that many observations of the obesity paradox in cancer reflect methodological mechanisms including the crudeness of BMI as an obesity measure, confounding, detection bias, reverse causality, and a specific form of the selection bias, known as collider bias. It is imperative for the oncologist to interpret the observation of the obesity paradox against the above methodological framework and avoid the misinterpretation that being obese might be "good" or "protective" for cancer patients.

The CIRCORT database: Reference ranges and seasonal changes in diurnal salivary cortisol derived from a meta-dataset comprised of 15 field studies.

Diurnal salivary cortisol profiles are valuable indicators of adrenocortical functioning in epidemiological research and clinical practice. However, normative reference values derived from a large number of participants and across a wide age range are still missing. To fill this gap, data were compiled from 15 independently conducted field studies with a total of 104,623 salivary cortisol samples obtained from 18,698 unselected individuals (mean age: 48.3 years, age range: 0.5-98.5 years, 39% females). Besides providing a descriptive analysis of the complete dataset, we also performed mixed-effects growth curve modeling of diurnal salivary cortisol (i.e., 1-16h after awakening). Cortisol decreased significantly across the day and was influenced by both, age and sex. Intriguingly, we also found a pronounced impact of sampling season with elevated diurnal cortisol in spring and decreased levels in autumn. However, the majority of variance was accounted for by between-participant and between-study variance components. Based on these analyses, reference ranges (LC/MS-MS calibrated) for cortisol concentrations in saliva were derived for different times across the day, with more specific reference ranges generated for males and females in different age categories. This integrative summary provides important reference values on salivary cortisol to aid basic scientists and clinicians in interpreting deviations from the normal diurnal cycle.

Collider Bias Is Only a Partial Explanation for the Obesity Paradox.

BACKGROUND: "Obesity paradox" refers to an association between obesity and reduced mortality (contrary to an expected increased mortality). A common explanation is collider stratification bias: unmeasured confounding induced by selection bias. Here, we test this supposition through a realistic generative model. METHODS: We quantify the collider stratification bias in a selected population using counterfactual causal analysis. We illustrate the bias for a range of scenarios, describing associations between exposure (obesity), outcome (mortality), mediator (in this example, diabetes) and an unmeasured confounder. RESULTS: Collider stratification leads to biased estimation of the causal effect of exposure on outcome. However, the bias is small relative to the causal relationships between the variables. CONCLUSIONS: Collider bias can be a partial explanation of the obesity paradox, but unlikely to be the main explanation for a reverse direction of an association to a true causal relationship. Alternative explanations of the obesity paradox should be explored. See Video Abstract at http://links.lww.com/EDE/B51.

Pioglitazone and bladder cancer risk: a multipopulation pooled, cumulative exposure analysis.

AIMS/HYPOTHESIS: The evidence on the association between pioglitazone use and bladder cancer is contradictory, with many studies subject to allocation bias. The aim of our study was to examine the effect of exposure to pioglitazone on bladder cancer risk internationally across several cohorts. The potential for allocation bias was minimised by focusing on the cumulative effect of pioglitazone as the primary endpoint using a time-dependent approach. METHODS: Prescription, cancer and mortality data from people with type 2 diabetes were obtained from six populations across the world (British Columbia, Finland, Manchester, Rotterdam, Scotland and the UK Clinical Practice Research Datalink). A discrete time failure analysis using Poisson regression was applied separately to data from each centre to model the effect of cumulative drug exposure on bladder cancer incidence, with time-dependent adjustment for ever use of pioglitazone. These were then pooled using fixed and random effects meta-regression. RESULTS: Data were collated on 1.01 million persons over 5.9 million person-years. There were 3,248 cases of incident bladder cancer, with 117 exposed cases and a median follow-up duration of 4.0 to 7.4 years. Overall, there was no evidence for any association between cumulative exposure to pioglitazone and bladder cancer in men (rate ratio [RR] per 100 days of cumulative exposure, 1.01; 95% CI 0.97, 1.06) or women (RR 1.04; 95% CI 0.97, 1.11) after adjustment for age, calendar year, diabetes duration, smoking and any ever use of pioglitazone. No association was observed between rosiglitazone and bladder cancer in men (RR 1.01; 95% CI 0.98, 1.03) or women (RR 1.00; 95% CI 0.94, 1.07). CONCLUSIONS/INTERPRETATION: The cumulative use of pioglitazone or rosiglitazone was not associated with the incidence of bladder cancer in this large, pooled multipopulation analysis.

Diabetes and cancer: 5 years into the recent controversy.

Diabetes and cancer are common chronic disorders. The literature has long recognised that type 2 diabetes (T2D) is associated with an increased incident risk of several cancer types, independent of the mutual risk factor, obesity. However, in June 2009, four papers were published simultaneously in Diabetologia, the official journal of the European Association for the Study of Diabetes, raising questions of a link between diabetes therapies, notably the long-acting insulin analogue, glargine, and increased cancer risk. These papers awakened an unprecedented debate in the diabetes community, drawing in cancer experts and bringing together representatives from these two large, traditionally non-intersecting, biomedical communities. This Current Perspective summarises the events that followed the 'breaking news' from summer 2009: the pitfalls encountered; the increased mutual understanding between diabetes and cancer researchers; and the direction of current research. Much of the debate on the clinical impact of this controversy has been played out in the diabetes literature: here, we update the oncology readership.

Health equity audits in general practice: a strategy to reduce health inequalities.

BACKGROUND: This quality improvement project was set in Tower Hamlets, east London, with the aim of reducing health inequalities by ethnicity, age and gender in the management of three common chronic diseases. METHODS: Routinely collected clinical data were extracted from practice computer systems using Morbidity Information Query and Export Syntax (MIQUEST) and Egton Medical Information Systems (EMIS) Web, between 2007 and 2010. Health equity audits for 38 practices in Tower Hamlets primary care trust (PCT) were constructed to cover key process and outcome measures for each of the three major chronic diseases: coronary heart disease (CHD), type 2 diabetes mellitus and chronic obstructive pulmonary disease (COPD). The equity audit was disseminated to practices along with facilitation sessions. RESULTS: We show evidence of baseline inequalities in each condition across the three east London PCTs. The intervention tracked four key indicators (cholesterol levels in CHD, blood pressure and haemoglobin A1c levels in diabetes and % smoking in COPD). Performance for physician-driven interventions improved, but smoking rates remained static. All ethnic groups showed improvement, but there was no evidence of a reduction in differences between ethnic groups. Reductions in gender and age group differences were noted in diabetes and CHD. CONCLUSIONS: Using routine clinical data, it is possible to develop practice-level health equity reports. These can unmask previously hidden inequalities between groups, and promote discussion with practice teams to stimulate strategies for improvements in performance. Steady improvements in chronic disease management were observed, however, systematic differences between ethnic groups remain. We are not able to attribute observed changes to the audits. These reports illustrate the importance of collecting ethnicity data at practice level. Tools such as this audit can be adapted to monitor inequalities in primary care settings.