Predicting the prevalence of type 2 diabetes in Brazil: a modeling study.

Aims: We adopted a modeling approach to predict the likely future prevalence of type 2 diabetes, taking into account demographic changes and trends in obesity and smoking in Brazil. We then used the model to estimate the likely future impact of different policy scenarios, such as policies to reduce obesity. Methods: The IMPACT TYPE 2 DIABETES model uses a Markov approach to integrate population, obesity, and smoking trends to estimate future type 2 diabetes prevalence. We developed a model for the Brazilian population from 2006 to 2036. Data on the Brazilian population in relation to sex and age were collected from the Brazilian Institute of Geography and Statistics, and data on the prevalence of type 2 diabetes, obesity, and smoking were collected from the Surveillance of Risk and Protection Factors for Chronic Diseases by Telephone Survey (VIGITEL). Results: The observed prevalence of type 2 diabetes among Brazilians aged over 25 years was 10.8% (5.2-14.3%) in 2006, increasing to 13.7% (6.9-18.4%) in 2020. Between 2006 and 2020, the observed prevalence in men increased from 11.0 to 19.1% and women from 10.6 to 21.3%. The model forecasts a dramatic rise in prevalence by 2036 (27.0% overall, 17.1% in men and 35.9% in women). However, if obesity prevalence declines by 1% per year from 2020 to 2036 (Scenario 1), the prevalence of diabetes decreases from 26.3 to 23.7, which represents approximately a 10.0% drop in 16 years. If obesity declined by 5% per year in 16 years as an optimistic target (Scenario 2), the prevalence of diabetes decreased from 26.3 to 21.2, representing a 19.4% drop in diabetes prevalence. Conclusion: The model predicts an increase in the prevalence of type 2 diabetes in Brazil. Even with ambitious targets to reduce obesity prevalence, type 2 diabetes in Brazil will continue to have a large impact on Brazilian public health.

Socioeconomic inequalities in accumulation of multimorbidity in England from 2019 to 2049: a microsimulation projection study.

BACKGROUND: There are socioeconomic inequalities in the prevalence of multimorbidity and its accumulation across the life course. Estimates of multimorbidity prevalence in English primary care increased by more than two-thirds from 2004 to 2019. We developed a microsimulation model to quantify current and projected multimorbidity inequalities in the English adult population. METHODS: We used primary care data for adults in England from the Clinical Practice Research Datalink Aurum database between 2004 and 2019, linked to the 2015 English Index of Multiple Deprivation (IMD), to model time individuals spent in four health states (healthy, one chronic condition, basic multimorbidity [two or more chronic conditions], and complex multimorbidity [three or more chronic conditions affecting three or more body systems]) by sex, age, IMD quintile, birth cohort, and region. We applied these transition times in a stochastic dynamic continuous-time microsimulation model to Office for National Statistics population estimates for adults aged 30-90 years. We calculated projected prevalence and cumulative incident cases from 2019 to 2049 by IMD quintile, age group (younger than 65 years vs 65 years and older), and years to be lived without multimorbidity at age 30 years. FINDINGS: Under the assumption that all chronic conditions were lifelong, and that once diagnosed there was no recovery, we projected prevalence of multimorbidity (basic or complex) increases by 34% from 53·8% in 2019 to 71·9% (95% uncertainty interval 71·8-72·0) in 2049. This rise equates to an 84% increase in the number of people with multimorbidity: from 19·2 million in 2019 to 35·3 million in 2049 (35·3 million to 35·4 million). This projected increase is greatest in the most deprived quintile, with an excess 1·07 million (1·04 million to 1·10 million) cumulative incident basic multimorbidity cases and 0·70 million (0·67 million to 0·74 million) complex multimorbidity cases over and above the projected cases for the least deprived quintile, largely driven by inequalities in those younger than 65 years. The median expected number of years to be lived without multimorbidity at age 30 years in 2019 is 15·12 years (14·62-16·01) in the least deprived IMD quintile and 12·15 years (11·61-12·60) in the most deprived IMD quintile. INTERPRETATION: The number of people living with multimorbidity will probably increase substantially in the next 30 years, a continuation of past observed increases partly driven by changing population size and age structure. Inequalities in the multimorbidity burden increase at each stage of disease accumulation, and are projected to widen, particularly among the working-age population. Substantial action is needed now to address population health and to prepare health-care and social-care systems for coming decades. FUNDING: University of Liverpool and National Institute for Health and Care Research School for Public Health Research.

Effect of calorie labelling in the out-of-home food sector on adult obesity prevalence, cardiovascular mortality, and social inequalities in England: a modelling study.

BACKGROUND: England implemented a menu calorie labelling policy in large, out-of-home food businesses in 2022. We aimed to model the likely policy impact on population-level obesity and cardiovascular disease mortality, as well as the socioeconomic equity of estimated effects, in the adult population in England. METHODS: For this modelling analysis, we built a comparative assessment model using two scenarios: the current implementation scenario refers to actual deployment only in large (≥250 employees), out-of-home food businesses, whereas the full implementation scenario refers to deployment in every out-of-home food business. We compared each scenario with a counterfactual: the scenario in which no intervention is implemented (ie, baseline). For both scenarios, we modelled the impact of the policy through assumed changes in energy intake due to either consumer response or product reformulation by retailers. We used data from the Office for National Statistics and the National Diet and Nutrition Survey 2009-19, and modelled the effect over 20 years (ie, 2022-41) to capture the long-term impact of the policy and provided mid-period results after 10 years. We used the Monte Carlo approach (2500 iterations) to estimate the uncertainty of model parameters. For each scenario, the model generated the change in obesity prevalence and the total number of deaths prevented or postponed. FINDINGS: The current implementation scenario was estimated to reduce obesity prevalence by 0·31 percentage points (absolute; 95% uncertainty interval [UI] 0·10-0·35), which would prevent or postpone 730 cardiovascular disease deaths (UI 430-1300) of the 830 000 deaths (UI 600 000-1 200 000) expected over 20 years. However, the health benefits would be increased if calorie labelling was implemented in all out-of-home food businesses (2·65 percentage points reduction in obesity prevalence [UI 1·97-3·24] and 9200 cardiovascular disease deaths prevented or postponed [UI 5500-16 000]). Results were similar in the most and the least deprived socioeconomic groups. INTERPRETATION: This study offers the first modelled estimation of the impact of the menu calorie labelling regulation on the adult population in England, although we did not include a cost-effectiveness analysis. Calorie labelling might result in a reduction in obesity prevalence and cardiovascular disease mortality without widening health inequalities. However, our results emphasise the need for the government to be more ambitious by applying this policy to all out-of-home food businesses to maximise impact. FUNDING: European Research Council.

The Cost of Atrial Fibrillation: A Systematic Review.

OBJECTIVES: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with an increasing incidence and prevalence because of progressively aging populations. Costs related to AF are both direct and indirect. This systematic review aims to identify the main cost drivers of the illness, assess the potential economic impact resulting from changes in care strategies, and propose interventions where they are most needed. METHODS: A systematic literature search of the PubMed and Scopus databases was performed to identify analytical observational studies defining the cost of illness in cases of AF. The search strategy was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 recommendations. RESULTS: Of the 944 articles retrieved, 24 met the inclusion criteria. These studies were conducted in several countries. All studies calculated the direct medical costs, whereas 8 of 24 studies assessed indirect costs. The median annual direct medical cost per patient, considering all studies, was €9409 (13 333 US dollars in purchasing power parities), with a very large variability due to the heterogeneity of different analyses. Hospitalization costs are generally the main cost drivers. Comorbidities and complications, such as stroke, considerably increase the average annual direct medical cost of AF. CONCLUSIONS: In most of the analyzed studies, inpatient care cost represents the main component of the mean direct medical cost per patient. Stroke and heart failure are responsible for a large share of the total costs; therefore, implementing guidelines to manage comorbidities in AF is a necessary step to improve health and mitigate healthcare costs.

Effect of a community-based primary healthcare programme on adverse pregnancy outcomes in Northern Ghana.

BACKGROUND: Pregnancy complications and adverse birth outcomes are among the major contributors to poor maternal and child health. Mothers in remote communities are at higher risk of adverse birth outcomes due to constraints in access to healthcare services. In Ghana, a community-based primary healthcare programme called the Ghana Essential Health Interventions Programme (GEHIP) was implemented in a rural region to help strengthen primary healthcare delivery and improve maternal and child healthcare services delivery. This study assessed the effect of this programme on adverse pregnancy outcomes. METHODS: Baseline and end-line survey data from reproductive-aged women from the GEHIP project were used in this analysis. Difference-in-differences and logistic regressions were used to examine the impact and equity effect of GEHIP on adverse pregnancy outcomes using household wealth index and maternal educational attainment as equity measures. The analysis involves the comparison of project baseline and end-line outcomes in intervention and non-intervention districts. RESULTS: The intervention had a significant effect in the reduction of adverse pregnancy outcomes (OR = 0.96, 95% CI:0.93-0.99). Although disadvantaged groups experience larger reductions in adverse pregnancy outcomes, controlling for covariates, there was no statistically significant equity effect of GEHIP on adverse pregnancy outcomes using either the household wealth index (OR = 0.99, 95% CI:0.85-1.16) or maternal educational attainment (OR = 0.68, 95% CI: 0.44-1.07) as equity measures. CONCLUSION: GEHIP's community-based healthcare programme reduced adverse pregnancy outcomes but no effect on relative equity was established. Factoring in approaches for targeting disadvantaged populations in the implementation of community-based health programs is crucial to ensuring equity in health outcomes.

US County-Level Variation in Preterm Birth Rates, 2007-2019.

Importance: Preterm birth is a leading cause of preventable neonatal morbidity and mortality. Preterm birth rates at the national level may mask important geographic variation in rates and trends at the county level. Objective: To estimate age-standardized preterm birth rates by US county from 2007 to 2019. Design, Setting, and Participants: This serial cross-sectional study used data from the National Center for Health Statistics composed of all live births in the US between 2007 and 2019. Data analyses were performed between March 22, 2022, and September 29, 2022. Main Outcomes and Measures: Age-standardized preterm birth (<37 weeks' gestation) and secondarily early preterm birth (<34 weeks' gestation) rates by county and year calculated with a validated small area estimation model (hierarchical bayesian spatiotemporal model) and percent change in preterm birth rates using log-linear regression models. Results: Between 2007 and 2019, there were 51 044 482 live births in 2383 counties. In 2007, the national age-standardized preterm birth rate was 12.6 (95% CI, 12.6-12.7) per 100 live births. Preterm birth rates varied significantly among counties, with an absolute difference between the 90th and 10th percentile counties of 6.4 (95% CI, 6.2-6.7). The gap between the highest and lowest counties for preterm births was 20.7 per 100 live births in 2007. Several counties in the Southeast consistently had the highest preterm birth rates compared with counties in California and New England, which had the lowest preterm birth rates. Although there was no statistically significant change in preterm birth rates between 2007 and 2019 at the national level (percent change, -5.0%; 95% CI, -10.7% to 0.9%), increases occurred in 15.4% (95% CI, 14.1%-16.9%) of counties. The absolute and relative geographic inequalities were similar across all maternal age groups. Higher quartile of the Social Vulnerability Index was associated with higher preterm birth rates (quartile 4 vs quartile 1 risk ratio, 1.34; 95% CI, 1.31-1.36), which persisted across the study period. Similar patterns were observed for early preterm birth rates. Conclusions and Relevance: In this serial cross-sectional study of county-level preterm and early preterm birth rates, substantial geographic disparities were observed, which were associated with place-based social disadvantage. Stability in aggregated rates of preterm birth at the national level masked increases in nearly 1 in 6 counties between 2007 and 2019.

Projected health and economic impacts of sugar-sweetened beverage taxation in Germany: A cross-validation modelling study.

BACKGROUND: Taxes on sugar-sweetened beverages (SSBs) have been implemented globally to reduce the burden of cardiometabolic diseases by disincentivizing consumption through increased prices (e.g., 1 peso/litre tax in Mexico) or incentivizing industry reformulation to reduce SSB sugar content (e.g., tiered structure of the United Kingdom [UK] Soft Drinks Industry Levy [SDIL]). In Germany, where no tax on SSBs is enacted, the health and economic impact of SSB taxation using the experience from internationally implemented tax designs has not been evaluated. The objective of this study was to estimate the health and economic impact of national SSBs taxation scenarios in Germany. METHODS AND FINDINGS: In this modelling study, we evaluated a 20% ad valorem SSB tax with/without taxation of fruit juice (based on implemented SSB taxes and recommendations) and a tiered tax (based on the UK SDIL) in the German adult population aged 30 to 90 years from 2023 to 2043. We developed a microsimulation model (IMPACTNCD Germany) that captures the demographics, risk factor profile and epidemiology of type 2 diabetes, coronary heart disease (CHD) and stroke in the German population using the best available evidence and national data. For each scenario, we estimated changes in sugar consumption and associated weight change. Resulting cases of cardiometabolic disease prevented/postponed and related quality-adjusted life years (QALYs) and economic impacts from healthcare (medical costs) and societal (medical, patient time, and productivity costs) perspectives were estimated using national cost and health utility data. Additionally, we assessed structural uncertainty regarding direct, body mass index (BMI)-independent cardiometabolic effects of SSBs and cross-validated results with an independently developed cohort model (PRIMEtime). We found that SSB taxation could reduce sugar intake in the German adult population by 1 g/day (95%-uncertainty interval [0.05, 1.65]) for a 20% ad valorem tax on SSBs leading to reduced consumption through increased prices (pass-through of 82%) and 2.34 g/day (95%-UI [2.32, 2.36]) for a tiered tax on SSBs leading to 30% reduction in SSB sugar content via reformulation. Through reductions in obesity, type 2 diabetes, and cardiovascular disease (CVD), 106,000 (95%-UI [57,200, 153,200]) QALYs could be gained with a 20% ad valorem tax and 192,300 (95%-UI [130,100, 254,200]) QALYs with a tiered tax. Respectively, €9.6 billion (95%-UI [4.7, 15.3]) and €16.0 billion (95%-UI [8.1, 25.5]) costs could be saved from a societal perspective over 20 years. Impacts of the 20% ad valorem tax were larger when additionally taxing fruit juice (252,400 QALYs gained, 95%-UI [176,700, 325,800]; €11.8 billion costs saved, 95%-UI [€6.7, €17.9]), but impacts of all scenarios were reduced when excluding direct health effects of SSBs. Cross-validation with PRIMEtime showed similar results. Limitations include remaining uncertainties in the economic and epidemiological evidence and a lack of product-level data. CONCLUSIONS: In this study, we found that SSB taxation in Germany could help to reduce the national burden of noncommunicable diseases and save a substantial amount of societal costs. A tiered tax designed to incentivize reformulation of SSBs towards less sugar might have a larger population-level health and economic impact than an ad valorem tax that incentivizes consumer behaviour change only through increased prices.

Quantifying the mental health and economic impacts of prospective Universal Basic Income schemes among young people in the UK: a microsimulation modelling study.

OBJECTIVE: Universal Basic Income (UBI)-a largely unconditional, regular payment to all adults to support basic needs-has been proposed as a policy to increase the size and security of household incomes and promote mental health. We aimed to quantify its long-term impact on mental health among young people in England. METHODS: We produced a discrete-time dynamic stochastic microsimulation that models a close-to-reality open cohort of synthetic individuals (2010-2030) based on data from Office for National Statistics and Understanding Society. Three UBI scheme scenarios were simulated: Scheme 1-Starter (per week): £41 per child; £63 per adult over 18 and under 65; £190 per adult aged 65+; Scheme 2-Intermediate (per week): £63 per child; £145 per adult under 65; £190 per adult aged 65+; Scheme 3-Minimum Income Standard level (per week): £95 per child; £230 per adult under 65; £230 per adult aged 65+. We reported cases of anxiety and depression prevented or postponed and cost savings. Estimates are rounded to the second significant digit. RESULTS: Scheme 1 could prevent or postpone 200 000 (95% uncertainty interval: 180 000 to 210 000) cases of anxiety and depression from 2010 to 2030. This would increase to 420 000(400 000 to 440 000) for Scheme 2 and 550 000(520 000 to 570 000) for Scheme 3. Assuming that 50% of the cases are diagnosed and treated, Scheme 1 could save £330 million (£280 million to £390 million) to National Health Service (NHS) and personal social services (PSS), over the same period, with Scheme 2 (£710 million (£640 million to £790 million)) or Scheme 3 (£930 million (£850 million to £1000 million)) producing more considerable savings. Overall, total cost savings (including NHS, PSS and patients' related costs) would range from £1.5 billion (£1.2 billion to £1.8 billion) for Scheme 1 to £4.2 billion (£3.7 billion to £4.6 billion) for Scheme 3. CONCLUSION: Our modelling suggests that UBI could substantially benefit young people's mental health, producing substantial health-related cost savings.

Forecasting the mortality burden of coronary heart disease and stroke in Germany: National trends and regional inequalities.

BACKGROUND: The decline of cardiovascular disease (CVD) mortality has slowed in many countries, including Germany. We examined the implications of this trend for future coronary heart disease (CHD) and stroke mortality in Germany considering persistent mortality inequalities between former East and West Germany. METHODS: We retrieved demographic and mortality data from 1991 to 2019 from the German Federal Statistical Office. Using a Bayesian age-period-cohort framework, we projected CHD and stroke mortality from 2019 to 2035, stratified by sex and German region. We decomposed annual changes in deaths into three components (mortality rates, population age structure and population size) and assessed regional inequalities with age-sex-standardized mortality ratios. RESULTS: We confirmed that declines of CVD mortality rates in Germany will likely stagnate. From 2019 to 2035, we projected fewer annual CHD deaths (114,600 to 103,500 [95%-credible interval: 81,700; 134,000]) and an increase in stroke deaths (51,300 to 53,700 [41,400; 72,000]). Decomposing past and projected mortality, we showed that population ageing was and is offset by declining mortality rates. This likely reverses after 2030 leading to increased CVD deaths thereafter. Inequalities between East and West declined substantially since 1991 and are projected to stabilize for CHD but narrow for stroke. CONCLUSIONS: CVD deaths in Germany likely keep declining until 2030, but may increase thereafter due to population ageing if the reduction in mortality rates slows further. East-West mortality inequalities for CHD remain stable but may converge for stroke. Underlying risk factor trends need to be monitored and addressed by public health policy.

Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Equity in maternal healthcare utilisation in Ghana: Do community-based primary health care programmes matter?

OBJECTIVE: Improving equity in the use of maternal health services in rural and remote communities is critical to meeting the Sustainable Development Goals targets on maternal and child health. This study examines the effect of a community-based primary healthcare strengthening programme on improving the utilisation of antenatal care (ANC4+), skilled delivery and health facility delivery. METHODS: Baseline and endline survey data of women of reproductive age for intervention and comparison districts were used to examine the equity impact of the Ghana Essential Health Interventions Programme (GEHIP) on antenatal care visits, skilled delivery and health facility delivery. The Wagstaff extension of the concentration index and regression models are used to assess equity effects of the programme on the utilisation of these services by wealth index and educational attainment. RESULTS: Coverage rates increased for both intervention and comparison districts, but were generally higher in intervention districts than comparison districts at endline (90% vs. 88% for ANC4+, 88% vs. 84% for skilled delivery and 93% vs. 88% for health facility delivery). Only ANC4+ showed a statistically significant positive treatment effect of the intervention (Dif-in-Dif = 0.071, p-value = 0.010). Equity analysis showed a mixed picture with intervention districts achieving significant equity improvement for skilled delivery for both wealth index and maternal education but only education equity for health facility delivery, while comparison districts achieved both wealth and education equity improvements for two indicators (health facility delivery and skilled delivery). No significant equity/inequity effects were found for ANC4+. CONCLUSION: Efforts to improve community-based healthcare access have been associated with improved coverage of maternal health services; however, the effect on improving equity in service coverage is mixed. Results indicate a need to extend community-based primary health care development beyond general improvements in access to ensure equity in the coverage of maternal and child health services that such programmes provide.

Socioeconomic position and the effect of energy labelling on consumer behaviour: a systematic review and meta-analysis.

BACKGROUND: There are well documented socioeconomic disparities in diet quality and obesity. Menu energy labelling is a public health policy designed to improve diet and reduce obesity. However, it is unclear whether the impact energy labelling has on consumer behaviour is socially equitable or differs based on socioeconomic position (SEP). METHODS: Systematic review and meta-analysis of experimental (between-subjects) and pre-post implementation field studies examining the impact of menu energy labelling on energy content of food and/or drink selections in higher vs. lower SEP groups. RESULTS: Seventeen studies were eligible for inclusion. Meta-analyses of 13 experimental studies that predominantly examined hypothetical food and drink choices showed that energy labelling tended to be associated with a small reduction in energy content of selections that did not differ based on participant SEP (X2(1) = 0.26, p = .610). Effect estimates for higher SEP SMD = 0.067 [95% CI: -0.092 to 0.226] and lower SEP SMD = 0.115 [95% CI: -0.006 to 0.237] were similar. A meta-analysis of 3 pre-post implementation studies of energy labelling in the real world showed that the effect energy labelling had on consumer behaviour did not significantly differ based on SEP (X2(1) = 0.22, p = .636). In higher SEP the effect was SMD = 0.032 [95% CI: -0.053 to 0.117] and in lower SEP the effect was SMD = -0.005 [95% CI: -0.051 to 0.041]. CONCLUSIONS: Overall there was no convincing evidence that the effect energy labelling has on consumer behaviour significantly differs based on SEP. Further research examining multiple indicators of SEP and quantifying the long-term effects of energy labelling on consumer behaviour in real-world settings is now required. REVIEW REGISTRATION: Registered on PROSPERO (CRD42022312532) and OSF ( https://doi.org/10.17605/OSF.IO/W7RDB ).

Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework.

BACKGROUND: Policy simulation models (PSMs) have been used extensively to shape health policies before real-world implementation and evaluate post-implementation impact. This systematic review aimed to examine best practices, identify common pitfalls in tobacco control PSMs and propose a modelling quality assessment framework. METHODS: We searched five databases to identify eligible publications from July 2013 to August 2019. We additionally included papers from Feirman et al for studies before July 2013. Tobacco control PSMs that project tobacco use and tobacco-related outcomes from smoking policies were included. We extracted model inputs, structure and outputs data for models used in two or more included papers. Using our proposed quality assessment framework, we scored these models on population representativeness, policy effectiveness evidence, simulated smoking histories, included smoking-related diseases, exposure-outcome lag time, transparency, sensitivity analysis, validation and equity. FINDINGS: We found 146 eligible papers and 25 distinct models. Most models used population data from public or administrative registries, and all performed sensitivity analysis. However, smoking behaviour was commonly modelled into crude categories of smoking status. Eight models only presented overall changes in mortality rather than explicitly considering smoking-related diseases. Only four models reported impacts on health inequalities, and none offered the source code. Overall, the higher scored models achieved higher citation rates. CONCLUSIONS: While fragments of good practices were widespread across the reviewed PSMs, only a few included a 'critical mass' of the good practices specified in our quality assessment framework. This framework might, therefore, potentially serve as a benchmark and support sharing of good modelling practices.

Food availability and affordability in a Mediterranean urban context: associations by store type and area-level socio-economic status.

OBJECTIVE: Although food environments have been highlighted as potentially effective targets to improve population diets, evidence on Mediterranean food environments is lacking. We examined differences in food availability and affordability in Madrid (Spain) by store type and area-level socio-economic status (SES). DESIGN: Cross-sectional study. Trained researchers conducted food store audits using the validated Nutrition Environment Measures Survey in Stores for Mediterranean contexts (NEMS-S-MED) tool to measure the availability and price of twelve food groups (specific foods = 35). We computed NEMS-S-MED scores and summarised price data with a Relative Price Index (RPI, comparing prices across stores) and an Affordability Index (normalising prices by area-level income). We compared the availability and affordability of 'healthier-less healthy' food pairs, scores between food store types (supermarkets, specialised, convenience stores and others) and area-level SES using ANOVA and multi-level regression models. SETTING: City of Madrid. 2016 and 2019 to cover a representative sample. PARTICIPANTS: Food stores within a socio-economically diverse sample of sixty-three census tracts (n 151). RESULTS: Supermarkets had higher food availability (37·5/49 NEMS-S-MED points), compared to convenience stores (13·5/49) and specialised stores (8/49). Supermarkets offered lower prices (RPI: 0·83) than specialised stores (RPI: 0·97) and convenience stores (RPI: 2·06). Both 'healthy' and 'less healthy' items were more available in supermarkets. We found no differences in food availability or price by area-level SES, but affordability was higher in higher-income areas. CONCLUSIONS: Supermarkets offered higher food availability and affordability for healthy and less healthy food items. Promoting healthy food availability through supermarkets and specialised stores and/or limiting access to convenience stores are promising policy options to achieve a healthier food environment.

What will the cardiovascular disease slowdown cost? Modelling the impact of CVD trends on dementia, disability, and economic costs in England and Wales from 2020-2029.

BACKGROUND: There is uncertainty around the health impact and economic costs of the recent slowing of the historical decline in cardiovascular disease (CVD) incidence and the future impact on dementia and disability. METHODS: Previously validated IMPACT Better Ageing Markov model for England and Wales, integrating English Longitudinal Study of Ageing (ELSA) data for 17,906 ELSA participants followed from 1998 to 2012, linked to NHS Hospital Episode Statistics. Counterfactual design comparing two scenarios: Scenario 1. CVD Plateau-age-specific CVD incidence remains at 2011 levels, thus continuing recent trends. Scenario 2. CVD Fall-age-specific CVD incidence goes on declining, following longer-term trends. The main outcome measures were age-related healthcare costs, social care costs, opportunity costs of informal care, and quality adjusted life years (valued at £60,000 per QALY). FINDINGS: The total 10 year cumulative incremental net monetary cost associated with a persistent plateauing of CVD would be approximately £54 billion (95% uncertainty interval £14.3-£96.2 billion), made up of some £13 billion (£8.8-£16.7 billion) healthcare costs, £1.5 billion (-£0.9-£4.0 billion) social care costs, £8 billion (£3.4-£12.8 billion) informal care and £32 billion (£0.3-£67.6 billion) value of lost QALYs. INTERPRETATION: After previous, dramatic falls, CVD incidence has recently plateaued. That slowdown could substantially increase health and social care costs over the next ten years. Healthcare costs are likely to increase more than social care costs in absolute terms, but social care costs will increase more in relative terms. Given the links between COVID-19 and cardiovascular health, effective cardiovascular prevention policies need to be revitalised urgently.

Estimating the health and economic effects of the voluntary sodium reduction targets in Brazil: microsimulation analysis.

BACKGROUND: Excessive sodium consumption is one of the leading dietary risk factors for non-communicable diseases, including cardiovascular disease (CVD), mediated by high blood pressure. Brazil has implemented voluntary sodium reduction targets with food industries since 2011. This study aimed to analyse the potential health and economic impact of these sodium reduction targets in Brazil from 2013 to 2032. METHODS: We developed a microsimulation of a close-to-reality synthetic population (IMPACTNCD-BR) to evaluate the potential health benefits of setting voluntary upper limits for sodium content as part of the Brazilian government strategy. The model estimates CVD deaths and cases prevented or postponed, and disease treatment costs. Model inputs were informed by the 2013 National Health Survey, the 2008-2009 Household Budget Survey, and high-quality meta-analyses, assuming that all individuals were exposed to the policy proportionally to their sodium intake from processed food. Costs included costs of the National Health System on CVD treatment and informal care costs. The primary outcome measures of the model are cardiovascular disease cases and deaths prevented or postponed over 20 years (2013-2032), stratified by age and sex. RESULTS: The study found that the application of the Brazilian voluntary sodium targets for packaged foods between 2013 and 2032 could prevent or postpone approximately 110,000 CVD cases (95% uncertainty intervals (UI): 28,000 to 260,000) among men and 70,000 cases among women (95% UI: 16,000 to 170,000), and also prevent or postpone approximately 2600 CVD deaths (95% UI: - 1000 to 11,000), 55% in men. The policy could also produce a net cost saving of approximately US$ 220 million (95% UI: US$ 54 to 520 million) in medical costs to the Brazilian National Health System for the treatment of CHD and stroke and save approximately US$ 71 million (95% UI: US$ 17 to170 million) in informal costs. CONCLUSION: Brazilian voluntary sodium targets could generate substantial health and economic impacts. The reduction in sodium intake that was likely achieved from the voluntary targets indicates that sodium reduction in Brazil must go further and faster to achieve the national and World Health Organization goals for sodium intake.

StrokeCog Markov Model: Projected Prevalent and Incident Cases of Stroke and Poststroke Cognitive Impairment to 2035 in Ireland.

BACKGROUND AND PURPOSE: Cognitive impairment no dementia (CIND) and dementia are common stroke outcomes, with significant health and societal implications for aging populations. These outcomes are not included in current epidemiological models. We aimed to develop an epidemiological model to project incidence and prevalence of stroke, poststroke CIND and dementia, and life expectancy, in Ireland to 2035, informing policy and service planning. METHODS: We developed a probabilistic Markov model (the StrokeCog model) applied to the Irish population aged 40 to 89 years to 2035. Data sources included official population and hospital-episode statistics, longitudinal cohort studies, and published estimates. Key assumptions were varied in sensitivity analysis. Results were externally validated against independent sources. The model tracks poststroke progression into health states characterized by no cognitive impairment, CIND, dementia, disability, stroke recurrence, and death. RESULTS: We projected 69 051 people with prevalent stroke in Ireland in 2035 (22.0 per 1000 population [95% CI, 20.8-23.1]), with 25 274 (8.0 per 1000 population [95% CI, 7.1-9.0]) of those projected to have poststroke CIND, and 12 442 having poststroke dementia (4.0 per 1000 population [95% CI, 3.2-4.8]). We projected 8725 annual incident strokes in 2035 (2.8 per 1000 population [95% CI, 2.7-2.9]), with 3832 of these having CIND (1.2 per 1000 population [95% CI, 1.1-1.3]), and 1715 with dementia (0.5 per 1000 population [95% CI, 0.5-0.6]). Life expectancy for stroke survivors at age 50 was 23.4 years (95% CI, 22.3-24.5) for women and 20.7 (95% CI, 19.5-21.9) for men. CONCLUSIONS: This novel epidemiological model of stroke, poststroke CIND, and dementia draws on the best available evidence. Sensitivity analysis indicated that findings were robust to assumptions, and where there was uncertainty a conservative approach was taken. The StrokeCog model is a useful tool for service planning and cost-effectiveness analysis and is available for adaptation to other national contexts.