Quantifying the Socio-Economic Benefits of Reducing Industrial Dietary Trans Fats: Modelling Study.

BACKGROUND: Coronary Heart Disease (CHD) remains a leading cause of UK mortality, generating a large and unequal burden of disease. Dietary trans fatty acids (TFA) represent a powerful CHD risk factor, yet to be addressed in the UK (approximately 1% daily energy) as successfully as in other nations. Potential outcomes of such measures, including effects upon health inequalities, have not been well quantified. We modelled the potential effects of specific reductions in TFA intake on CHD mortality, CHD related admissions, and effects upon socioeconomic inequalities. METHODS & RESULTS: We extended the previously validated IMPACTsec model, to estimate the potential effects of reductions (0.5% & 1% reductions in daily energy) in TFA intake in England and Wales, stratified by age, sex and socioeconomic circumstances. We estimated reductions in expected CHD deaths in 2030 attributable to these two specific reductions. Output measures were deaths prevented or postponed, life years gained and hospital admissions. A 1% reduction in TFA intake energy intake would generate approximately 3,900 (95% confidence interval (CI) 3,300-4,500) fewer deaths, 10,000 (8,800-10,300) (7% total) fewer hospital admissions and 37,000 (30,100-44,700) life years gained. This would also reduce health inequalities, preventing five times as many deaths and gaining six times as many life years in the most deprived quintile compared with the most affluent. A more modest reduction (0.5%) would still yield substantial health gains. CONCLUSIONS: Reducing intake of industrial TFA could substantially decrease CHD mortality and hospital admissions, and gain tens of thousands of life years. Crucially, this policy could also reduce health inequalities. UK strategies should therefore aim to minimise industrial TFA intake

The Andean Latin-American burden of diabetes attributable to high body mass index: a comparative risk assessment

Background:Body mass index (BMI)has increased in Latin-America, but the implications for the diabetesburden havenot been quantified. We estimated the proportion and absolute number of diabetescasesattributable to high BMI in Bolivia, Ecuador and Peru(Andean Latin-America), with estimation of region-level indicators in Peru.Methods: Weestimated the population attributable fraction (PAF) of BMI ondiabetes(regardless of type 1 or 2)from 1980 to 2014, including the number of cases attributable to overweight (BMI 25-<30), class I (30-<35),class II (BMI 35-<40) and class III(BMI ≥40)obesity.We used age-and sex-specific prevalence estimates of diabetes and BMI categories(NCD-RisC and Peru’s DHS survey)combined with relative risks from population-based cohortsin Peru. Findings: Across Andean Latin-Americain 2014, there were 1,258,313diabetes cases attributable to high BMI: 209,855 in Bolivia, 367,440in Ecuadorand681,018in Peru. Between 1980-2010, the absolute proportion of diabetes cases attributable toclass I obesity increased the most (from 12.9% to 27.2%) across the region. The second greatest increase was for class II obesity (from 3.6% to 16.5%). There was heterogeneity in the fraction of diabetes cases attributable to high BMI by region in Peru, ascoastal regions hadthelargestfractions,andso did high-income regions. Interpretation: Over one milliondiabetes cases are attributable to high BMI in Andean Latin-America. Public health efforts should focus on implementing population-based interventions to reduce high BMI and to developfocused interventions targeted at those at highest risk of diabetes

Contributions of diseases and injuries to widening life expectancy inequalities in England from 2001 to 2016: population-based analysis of vital registration data

Background Life expectancy inequalities in England have increased steadily since the 1980s. Our aim was to investigate how much deaths from different diseases and injuries and at different ages have contributed to this rise to inform policies that aim to reduce health inequalities. Methods We used vital registration data from the Office for National Statistics on population and deaths in England, by underlying cause of death, from 2001 to 2016, stratified by sex, 5-year age group, and decile of the Index of Multiple Deprivation (based on the ranked scores of Lower Super Output Areas in England in 2015). We grouped the 7·65 million deaths by their assigned International Classification of Diseases (10th revision) codes to create categories of public health and clinical relevance. We used a Bayesian hierarchical model to obtain robust estimates of cause-specific death rates by sex, age group, year, and deprivation decile. We calculated life expectancy at birth by decile of deprivation and year using life-table methods. We calculated the contributions of deaths from each disease and injury, in each 5-year age group, to the life expectancy gap between the most deprived and affluent deciles using Arriaga's method. Findings The life expectancy gap between the most affluent and most deprived deciles increased from 6·1 years (95% credible interval 5·9–6·2) in 2001 to 7·9 years (7·7–8·1) in 2016 in females and from 9·0 years (8·8–9·2) to 9·7 years (9·6–9·9) in males. Since 2011, the rise in female life expectancy has stalled in the third, fourth, and fifth most deprived deciles and has reversed in the two most deprived deciles, declining by 0·24 years (0·10–0·37) in the most deprived and 0·16 years (0·02–0·29) in the second-most deprived by 2016. Death rates from every disease and at every age were higher in deprived areas than in affluent ones in 2016. The largest contributors to life expectancy inequalities were deaths in children younger than 5 years (mostly neonatal deaths), respiratory diseases, ischaemic heart disease, and lung and digestive cancers in working ages, and dementias in older ages. From 2001 to 2016, the contributions to inequalities declined for deaths in children younger than 5 years, ischaemic heart disease (for both sexes), and stroke and intentional injuries (for men), but increased for most other causes. Interpretation Recent trends in life expectancy in England have not only resulted in widened inequalities but the most deprived communities are now seeing no life expectancy gain. These inequalities are driven by a diverse group of diseases that can be effectively prevented and treated. Adoption of the principle of proportionate universalism to prevention and health and social care can postpone deaths into older ages for all communities and reduce life expectancy inequalities

Is the Healthy Start scheme associated with increased food expenditure in low-income families with young children in the United Kingdom?

Introduction: Healthy Start is a food assistance programme in the United Kingdom (UK) which aims to provide a nutritional safety-net and enable low-income families on welfare benefits to access a healthier diet through the provision of food vouchers. Healthy Start was launched in 2006 but remains under-evaluated. This study aims to determine whether participation in the Healthy Start scheme is associated with differences in food expenditure in a nationally representative sample of households in the UK. Methods: Cross-sectional analyses of the Living Costs and Food Survey dataset (2010-2017). All households with a child (0-3 years) or pregnant woman were included in the analysis (n=4,869). Multivariable quantile regression compared the expenditure and quantity of fruit and vegetables (FV), infant formula and total food purchases. Four exposure groups were defined based on eligibility, participation and income (Healthy Start Participating, Eligible Non-participating, Nearly Eligible low-income and Ineligible high-income households). Results: Of 876 eligible households, 54% participated in Healthy Start. No significant differences were found in FV or total food purchases between participating and eligible non-participating households, but infant formula purchases were lower in Healthy Start participating households. Ineligible higher-income households had higher purchases of FV. Conclusion: This study did not find evidence of an association between Healthy Start participation and FV expenditure. Moreover, inequalities in FV purchasing persist in the UK. Higher participation and increased voucher value may be needed to improve programme performance and counteract the harmful effects of poverty on diet

Twenty-year trajectories of cardio-metabolic factors among people with type 2 diabetes by dementia status in England: a retrospective cohort study.

To assess 20-year retrospective trajectories of cardio-metabolic factors preceding dementia diagnosis among people with type 2 diabetes (T2D). We identified 227,145 people with T2D aged > 42 years between 1999 and 2018. Annual mean levels of eight routinely measured cardio-metabolic factors were extracted from the Clinical Practice Research Datalink. Multivariable multilevel piecewise and non-piecewise growth curve models assessed retrospective trajectories of cardio-metabolic factors by dementia status from up to 19 years preceding dementia diagnosis (dementia) or last contact with healthcare (no dementia). 23,546 patients developed dementia; mean (SD) follow-up was 10.0 (5.8) years. In the dementia group, mean systolic blood pressure increased 16-19 years before dementia diagnosis compared with patients without dementia, but declined more steeply from 16 years before diagnosis, while diastolic blood pressure generally declined at similar rates. Mean body mass index followed a steeper non-linear decline from 11 years before diagnosis in the dementia group. Mean blood lipid levels (total cholesterol, LDL, HDL) and glycaemic measures (fasting plasma glucose and HbA1c) were generally higher in the dementia group compared with those without dementia and followed similar patterns of change. However, absolute group differences were small. Differences in levels of cardio-metabolic factors were observed up to two decades prior to dementia diagnosis. Our findings suggest that a long follow-up is crucial to minimise reverse causation arising from changes in cardio-metabolic factors during preclinical dementia. Future investigations which address associations between cardiometabolic factors and dementia should account for potential non-linear relationships and consider the timeframe when measurements are taken

An insurance value modeling approach that captures the wider value of a novel antimicrobial to health systems, patients, and the population.

Background: Traditional health economic evaluations of antimicrobials currently underestimate their value to wider society. They can be supplemented by additional value elements including insurance value, which captures the value of an antimicrobial in preventing or mitigating impacts of adverse risk events. Despite being commonplace in other sectors, constituents of the impacts and approaches for estimating insurance value have not been investigated. Objectives: This study assessed the insurance value of a novel gram-negative antimicrobial from operational healthcare, wider population health, productivity, and informal care perspectives. Methods: A novel mixed-methods approach was used to model insurance value in the United Kingdom: (1) literature review and multidisciplinary expert workshops to identify risk events for 4 relevant scenarios: ward closures, unavoidable shortage of conventional antimicrobials, viral respiratory pandemics, and catastrophic antimicrobial resistance (AMR); (2) parameterizing mitigable costs and frequencies of risk events across perspectives and scenarios; (3) estimating insurance value through a Monte Carlo simulation model for extreme events and a dynamic disease transmission model. Results: The mean insurance value across all scenarios and perspectives over 10 years in the UK was £718 million, should AMR remain unchanged, where only £134 million related to operational healthcare costs. It would be 50%-70% higher if AMR steadily increased or if a more risk-averse view (1-in-10 year downside) of future events is taken. Discussion: The overall insurance value if AMR remains at current levels (a conservative projection), is over 5 times greater than insurance value from just the operational healthcare costs perspective, traditionally the sole perspective used in health budgeting. Insurance value was generally larger for nationwide or universal (catastrophic AMR, pandemic, and conventional antimicrobial shortages) rather than localized (ward closure) scenarios, across perspectives. Components of this insurance value match previously published estimates of operational costs and mortality impacts. Conclusions: Insurance value of novel antimicrobials can be systematically modeled and substantially augments their traditional health economic value in normal circumstances. These approaches are generalizable to similar health interventions and form a framework for health systems and governments to capture broader value in health technology assessments, improve healthcare access, and increase resilience by planning for adverse scenarios