RESUMEN
Obesity has been associated with upper gastrointestinal cancers; however, there are limited prospective data on associations by subtype/subsite. Obesity can impact hormonal factors, which have been hypothesized to play a role in these cancers. We investigated anthropometric and reproductive factors in relation to esophageal and gastric cancer by subtype and subsite for 476,160 participants from the European Prospective Investigation into Cancer and Nutrition cohort. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox models. During a mean follow-up of 14 years, 220 esophageal adenocarcinomas (EA), 195 esophageal squamous cell carcinomas, 243 gastric cardia (GC) and 373 gastric noncardia (GNC) cancers were diagnosed. Body mass index (BMI) was associated with EA in men (BMI ≥30 vs. 18.5-25 kg/m2 : HR = 1.94, 95% CI: 1.25-3.03) and women (HR = 2.66, 95% CI: 1.15-6.19); however, adjustment for waist-to-hip ratio (WHR) attenuated these associations. After mutual adjustment for BMI and HC, respectively, WHR and waist circumference (WC) were associated with EA in men (HR = 3.47, 95% CI: 1.99-6.06 for WHR >0.96 vs. <0.91; HR = 2.67, 95% CI: 1.52-4.72 for WC >98 vs. <90 cm) and women (HR = 4.40, 95% CI: 1.35-14.33 for WHR >0.82 vs. <0.76; HR = 5.67, 95% CI: 1.76-18.26 for WC >84 vs. <74 cm). WHR was also positively associated with GC in women, and WC was positively associated with GC in men. Inverse associations were observed between parity and EA (HR = 0.38, 95% CI: 0.14-0.99; >2 vs. 0) and age at first pregnancy and GNC (HR = 0.54, 95% CI: 0.32-0.91; >26 vs. <22 years); whereas bilateral ovariectomy was positively associated with GNC (HR = 1.87, 95% CI: 1.04-3.36). These findings support a role for hormonal pathways in upper gastrointestinal cancers.
Asunto(s)
Neoplasias Esofágicas/epidemiología , Neoplasias Gástricas/epidemiología , Antropometría , Distribución de la Grasa Corporal , Estudios de Cohortes , Neoplasias Esofágicas/clasificación , Europa (Continente)/epidemiología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Modelos de Riesgos Proporcionales , Estudios Prospectivos , Historia Reproductiva , Factores de Riesgo , Neoplasias Gástricas/clasificaciónRESUMEN
Background: In the UK, obesity rates are rising concurrently with declining mortality rates. Yet, there is limited research on the shifts of mortality trends and the impact of obesity-related mortality. In this study, we examine mortality trends and the cause-specific proportional composition of deaths by body mass index. Methods: We used primary healthcare records from the Clinical Practice Research Datalink between 2004 and 2019, linked to national death registration data. There were 880,683 individuals with at least one BMI measurement and a 5-year survival period. We used discrete Poisson regression and joinpoint analysis to estimate the all-cause and cause-specific mortality rate and significance of the trends. Findings: Between January 1, 2004, and December 31, 2019, all-cause mortality rates declined in the obese category by 3% on average per year (from 23.3 to 14.6 deaths per 1000 person years) in males and 2% on average per year (from 12.5 to 9.4 deaths per 1000 person years) in females. Cardiovascular disease mortality declined 7% on average per year (from 12.4 to 4.4 deaths per 1000 person years) in males and 4% on average per year (from 5.5 to 3.0 deaths per 1000 person years) in females in the obese category. Increases in mortality rates from neurological conditions occurred in all BMI categories in males and females. By the end of the study, cancers became the primary contributor of death in males in all BMI categories and females in the overweight category. Interpretation: There have been significant declines in all-cause and cardiovascular disease mortality in males and females, leading to a diversification of mortality, with cancers contributing to the highest proportion of deaths and increases in causes such as neurological and respiratory conditions. Further screening, prevention, and treatment implementation for a broader set of diseases is necessary for continued mortality improvements. Funding: Imperial College London, Science Foundation Ireland.
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Sin or public health taxes are excise taxes imposed on the consumption of potentially harmful goods for health [sugar-sweetened beverages (SSBs), tobacco, alcohol, among others], aiming to reduce consumption, raise additional revenue and/or improve population health. This paper assesses the extent to which sin taxes (a) can reduce consumption of potentially harmful goods, (b) raise revenue for national health systems and (c) contribute to population health in Latin America. A systematic literature review was conducted on peer-reviewed and grey literature; endpoints included: impact of raising sin taxes on consumption, ability to raise revenue for health and the possibility of population health improvements. Risk of bias for each study was assessed. The synthesis of the literature on sin tax implementation showed improvements in all three endpoints across the study countries. Following the introduction of sin taxes or by simulating their potential impact, nearly all studies explicitly reported that consumption of potentially harmful goods (mainly SSBs and tobacco) declined; revenue was found to have increased in almost all countries, suggesting that there may be additional scope for further tax increase. Simulated improvements in population health have also been shown, by demonstrating a relationship between sin tax increases and reduction in prevalence of diabetes, stroke, heart attacks and associated deaths. However, sin tax effects on health would be better quantified over the long-term. Data quality and availability challenges did place some limitations on sin tax impact assessment. Sin taxes can be effective in reducing consumption of potentially harmful goods, improve population health and generate additional revenue. Promoting further research on this topic should be a priority.
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Bebidas Azucaradas , Productos de Tabaco , Humanos , América Latina , Salud Pública , ImpuestosRESUMEN
Eighteen months into the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease 2019 [COVID-19]) pandemic, epidemiologic studies indicate that diabetes is a central contributor to severe COVID-19 morbidity, and, conversely, COVID-19 has had a devastating effect on the population with diabetes. In this literature synthesis, we summarize the relationship of diabetes to COVID-19-related morbidity and mortality, discuss the predictors of severe adverse outcomes and implications of the overall pandemic, and critique the current status of and identify needs for epidemiologic studies for the next phase of the pandemic. Case series show that â¼30-40% of people with COVID-19-related hospitalization, severe morbidity requiring intensive care, and/or death have type 2 or type 1 diabetes. Among hospitalized individuals with diabetes, â¼21-43% required intensive care and case fatality is â¼25%. Risk of severe morbidity and mortality is 100-250% higher among people with diabetes than those without, even after adjustment for sociodemographic factors and comorbid conditions. Impact on the general population with diabetes has been similarly dire, as overall mortality rates were 50% higher than historical trends, a net increase more than twice that of the general population. Of the excess deaths, â¼75-80% are not officially attributed to COVID-19, which raises unanswered questions about missed attribution or collateral impact. Many predictors of poor outcomes have been identified, particularly comorbid conditions (chronic kidney disease, coronary heart disease, and heart failure), concurrent obesity, and acute and chronic poor HbA1c control, that point to the potential to reduce severe morbidity and mortality in its next stages. However, response to the continuing pandemic will benefit from population-wide studies with broader examination of the risks of exposure, infection, and hospitalization, for which few data currently exist. The indirect impact of the pandemic's effects on health services, health behaviors, disease management, care, control, and complications has not been well quantified; determining this impact will be essential to lessen the future impact. Expanding epidemiologic studies of the relationship of diabetes to COVID-19 beyond few high-income countries will also be essential to limit the burden in low- and middle-income countries where 80% of individuals with diabetes reside and where the COVID-19 pandemic has been so damaging.
Asunto(s)
COVID-19 , Diabetes Mellitus , Cuidados Críticos , Diabetes Mellitus/epidemiología , Hospitalización , Humanos , Pandemias , SARS-CoV-2RESUMEN
The study of infectious disease outbreaks is required to train today's epidemiologists. A typical way to introduce and explain key epidemiological concepts is through the analysis of a historical outbreak. There are, however, few training options that explicitly utilise real-time simulated stochastic outbreaks where the participants themselves comprise the dataset they subsequently analyse. In this paper, we present a teaching exercise in which an infectious disease outbreak is simulated over a five-day period and subsequently analysed. We iteratively developed the teaching exercise to offer additional insight into analysing an outbreak. An R package for visualisation, analysis and simulation of the outbreak data was developed to accompany the practical to reinforce learning outcomes. Computer simulations of the outbreak revealed deviations from observed dynamics, highlighting how simplifying assumptions conventionally made in mathematical models often differ from reality. Here we provide a pedagogical tool for others to use and adapt in their own settings.