ObjectiveTo collate and evaluate the current literature reporting the prevalence and incidence of hypoglycaemia in population based studies of type 2 diabetes.Research Design and MethodsMedline, Embase and Cochrane were searched up to February 2014 to identify population based studies reporting the proportion of people with type 2 diabetes experiencing hypoglycaemia or rate of events experienced. Two reviewers independently screened studies for eligibility and extracted data for included studies. Random effects meta-analyses were carried out to calculate the prevalence and incidence of hypoglycaemia.Results46 studies (n = 532,542) met the inclusion criteria. Prevalence of hypoglycaemia was 45% (95%CI 0.34,0.57) for mild/moderate and 6% (95%CI, 0.05,0.07) for severe. Incidence of hypoglycaemic episodes per person-year for mild/moderate and for severe was 19 (95%CI 0.00, 51.08) and 0.80 (95%CI 0.00,2.15), respectively. Hypoglycaemia was prevalent amongst those on insulin; for mild/moderate episodes the prevalence was 50% and incidence 23 events per person-year, and for severe episodes the prevalence was 21% and incidence 1 event per person-year. For treatment regimes that included a sulphonylurea, mild/moderate prevalence was 30% and incidence 2 events per person-year, and severe prevalence was 5% and incidence 0.01 events per person-year. A similar prevalence of 5% was found for treatment regimes that did not include sulphonylureas.ConclusionsCurrent evidence shows hypoglycaemia is considerably prevalent amongst people with type 2 diabetes, particularly for those on insulin, yet still fairly common for other treatment regimens. This highlights the subsequent need for educational interventions and individualisation of therapies to reduce the risk of hypoglycaemia.

Background Universal Credit, a welfare benefit reform in the UK, began to replace six existing benefit schemes in April, 2013, starting with the income-based Job Seekers Allowance. We aimed to determine the effects on mental health of the introduction of Universal Credit.Methods In this longitudinal controlled study, we linked 197 111 observations from 52 187 individuals of working age (16-64 years) in England, Wales, and Scotland who participated in the Understanding Society UK Longitudinal Household Panel Study between 2009 and 2018 with administrative data on the month when Universal Credit was introduced into the area in which each respondent lived. We included participants who had data on employment status, local authority area of residence, psychological distress, and confounding variables. We excluded individuals from Northern Ireland and people out of work with a disability. We used difference-in-differences analysis of this nationally representative, longitudinal, household survey and separated respondents into two groups: unemployed people who were eligible for Universal Credit (intervention group) and people who were not unemployed and therefore would not have generally been eligible for Universal Credit (comparison group). Using the phased roll-out of Universal Credit, we compared the change in psychological distress (self-reported via General Health Questionnaire-12) between the intervention group and the comparison group over time as the reform was introduced in the area in which each respondent lived. We defined clinically significant psychological distress as a score of greater than 3 on the General Health Questionnaire-12. We tested whether there were differential effects across subgroups (age, sex, and education). Findings The prevalence of psychological distress increased in the intervention group by 6•57 percentage points (95% CI 1•69-11•42) after the introduction of Universal Credit relative to the comparison group, after accounting for potential confounders. We estimate that between April 29, 2013, and Dec 31, 2018, an additional 63 674 (95% CI 10 042-117 307) unemployed people will have experienced levels of psychological distress that are clinically significant due to the introduction of Universal Credit; 21 760 of these individuals might reach the diagnostic threshold for depression.Interpretation Our findings suggest that the introduction of Universal Credit led to an increase in psychological distress, a measure of mental health difficulties, among those affected by the policy. Future changes to government welfare systems should be evaluated not only on a fiscal basis but on their potential to affect health and wellbeing.

ObjectiveTo determine whether there were inequalities in the sustained rise in infant mortality in England in recent years and the contribution of rising child poverty to these trends.DesignThis is an analysis of trends in infant mortality in local authorities grouped into five categories (quintiles) based on their level of income deprivation. Fixed-effects regression models were used to quantify the association between regional changes in child poverty and regional changes in infant mortality.Setting324 English local authorities in 9 English government office regions.ParticipantsLive-born children under 1 year of age.Main outcome measureInfant mortality rate, defined as the number of deaths in children under 1 year of age per 100 000 live births in the same year.ResultsThe sustained and unprecedented rise in infant mortality in England from 2014 to 2017 was not experienced evenly across the population. In the most deprived local authorities, the previously declining trend in infant mortality reversed and mortality rose, leading to an additional 24 infant deaths per 100 000 live births per year (95% CI 6 to 42), relative to the previous trend. There was no significant change from the pre-existing trend in the most affluent local authorities. As a result, inequalities in infant mortality increased, with the gap between the most and the least deprived local authority areas widening by 52 deaths per 100 000 births (95% CI 36 to 68). Overall from 2014 to 2017, there were a total of 572 excess infant deaths (95% CI 200 to 944) compared with what would have been expected based on historical trends. We estimated that each 1% increase in child poverty was significantly associated with an extra 5.8 infant deaths per 100 000 live births (95% CI 2.4 to 9.2). The findings suggest that about a third of the increases in infant mortality between 2014 and 2017 can be attributed to rising child poverty (172 deaths, 95% CI 74 to 266).ConclusionThis study provides evidence that the unprecedented rise in infant mortality disproportionately affected the poorest areas of the country, leaving the more affluent areas unaffected. Our analysis also linked the recent increase in infant mortality in England with rising child poverty, suggesting that about a third of the increase in infant mortality from 2014 to 2017 may be attributed to rising child poverty.

BackgroundDuring the initial wave of the COVID-19 epidemic in England, several population characteristics were associated with increased risk of mortality—including, age, ethnicity, income deprivation, care home residence and housing conditions. In order to target control measures and plan for future waves of the epidemic, public health agencies need to understand how these vulnerabilities are distributed across and clustered within communities.MethodsWe performed a cross-sectional ecological analysis across 6789 small areas in England. We assessed the association between COVID-19 mortality in each area and five vulnerability measures relating to ethnicity, poverty, prevalence of long-term health conditions, living in care homes and living in overcrowded housing. Estimates from multivariable Poisson regression models were used to derive a Small Area Vulnerability Index.ResultsFour vulnerability measures were independently associated with age-adjusted COVID-19 mortality. Each SD increase in the proportion of the population (1) living in care homes, (2) admitted to hospital in the past 5 years for a long-term health condition, (3) from an ethnic minority background and (4) living in overcrowded housing was associated with a 28%, 19% 8% and 11% increase in age-adjusted COVID-19 mortality rate, respectively.ConclusionVulnerability to COVID-19 was noticeably higher in the North West, West Midlands and North East regions, with high levels of vulnerability clustered in some communities. Our analysis indicates the communities who will be most at risk from a second wave of the pandemic.

Background: Initial reports suggest that ethnic minorities may be experiencing more severe coronavirus disease 2019 (COVID19) outcomes. We therefore assessed the association between ethnic composition, income deprivation and COVID19 mortality rates in England. Methods:We performed a cross-sectional ecological analysis across England's upper-tier local authorities. We assessed the association between the proportion of the population from Black, Asian and Minority Ethnic (BAME) backgrounds, income deprivation and COVID19 mortality rates using multivariable negative binomial regression, adjusting for population density, proportion of the population aged 50-79 and 80+ years, and the duration of the epidemic in each area.Findings: Local authorities with a greater proportion of residents from ethnic minority backgrounds had statistically significantly higher COVID19 mortality rates, as did local authorities with a greater proportion of residents experiencing deprivation relating to low income. After adjusting for income deprivation and other covariates, each percentage point increase in the proportion of the population from BAME backgrounds was associated with a 1% increase in the COVID19 mortality rate [IRR=1.01, 95%CI 1.01-1.02]. Each percentage point increase in the proportion of the population experiencing income deprivation was associated with a 2% increase in the COVID19 mortality rate [IRR=1.02, 95%CI 1.01-1.04]. Interpretation:This study provides evidence that both income deprivation and ethnicity are associated with greater COVID19 mortality. To reduce these inequalities, Government needs to target effective control and recovery measures at these disadvantaged communities, proportionate to their greater needs and vulnerabilities, during and following the pandemic.

Background: The association between Parkinson’s disease and lifestyle exposures such as smoking, coffee and alcohol consumption have been the focus of research for several decades, with varying and often conflicting results. Objective: This paper reviews the key features of observational studies investigating the relationship between alcohol drinking and PD risk, to determine potential sources of variability between the results. Methods: Relevant literature from 2000–2014 was systematically retrieved using three databases. Primary research articles were included if they reported a measure of association between quantity and frequency of alcohol intake and PD risk, and adjusted at least for the potential confounding factors of smoking and age. Results: Sixteen articles were identified. The seven case-control studies were more likely to report a weak protective association by level of alcohol consumption compared to the studies with prospective designs. Two studies reported the relationship between heavy (harmful to health) drinking and PD. There was weak evidence that associations varied by type of alcoholic beverage. Smoking may modify the association between alcohol intake and PD risk, however, the evidence does not support the theory that a confounder (such as an addiction-avoiding personality trait) produced the inverse associations between smoking, coffee and alcohol intake and PD risk. Methodological weaknesses of the studies, including selection and recall bias, residual confounding and lack of statistical power may in part account for their differences. Conclusion: The weak association between alcohol drinking and PD risk was found in studies at greater risk of selection and recall bias.

BackgroundInfectious intestinal diseases (IID) are common, affecting around 25% of people in UK each year at an estimated annual cost to the economy, individuals and the NHS of £1.5 billion. While there is evidence of higher IID hospital admissions in more disadvantaged groups, the association between socioeconomic status (SES) and risk of IID remains unclear. This study aims to investigate the relationship between SES and IID in a large community cohort.MethodsLongitudinal analysis of a prospective community cohort in the UK following 6836 participants of all ages was undertaken. Hazard ratios for IID by SES were estimated using Cox proportional hazard, adjusting for follow-up time and potential confounding factors.ResultsIn the fully adjusted analysis, hazard ratio of IID was significantly lower among routine/manual occupations compared with managerial/professional occupations (HR 0.74, 95% CI 0.61–0.90).ConclusionIn this large community cohort, lower SES was associated with lower IID risk. This may be partially explained by the low response rate which varied by SES. However, it may be related to differences in exposure or recognition of IID symptoms by SES. Higher hospital admissions associated with lower SES observed in some studies could relate to more severe consequences, rather than increased infection risk.

BackgroundThe association between socioeconomic status (SES) and health is well-documented; however limited evidence on the relationship between SES and gastrointestinal (GI) infections exists, with published studies producing conflicting results. This systematic review aimed to assess the association between SES and GI infection risk, and explore possible sources of heterogeneity in effect estimates reported in the literature.MethodsMEDLINE, Scopus, Web of Science and grey literature were searched from 1980 to October 2015 for studies reporting an association between GI infections and SES in a representative population sample from a member-country of the Organisation for Economic Co-operation and Development. Harvest plots and meta-regression were used to investigate potential sources of heterogeneity such as age; level of SES variable; GI infection measurement; and predominant mode of transmission. The protocol was registered on PROSPERO: CRD42015027231.ResultsIn total, 6021 studies were identified; 102 met the inclusion criteria. Age was identified as the only statistically significant potential effect modifier of the association between SES and GI infection risk. For children, GI infection risk was higher for those of lower SES versus high (RR 1.51, 95% CI;1.26–1.83), but there was no association for adults (RR 0.79, 95% CI;0.58–1.06). In univariate analysis, the increased risk comparing low and high SES groups was significantly higher for pathogens spread by person-to-person transmission, but lower for environmental pathogens, as compared to foodborne pathogens.ConclusionsDisadvantaged children, but not adults, have greater risk of GI infection compared to their more advantaged counterparts. There was high heterogeneity and many studies were of low quality. More high quality studies are needed to investigate the association between SES and GI infection risk, and future research should stratify analyses by age and pathogen type. Gaining further insight into this relationship will help inform policies to reduce inequalities in GI illness in children.