Smoking patterns by birth cohort in Argentina: an age-period-cohort population-based modeling study.

Background: Argentina's smoking rates remain high. We aim to estimate Argentina age-specific histories of smoking initiation, cessation, prevalence, and intensity by birth-cohort to inform policy interventions. Methods: Modeling study. Data from three Argentinian nationally representative surveys conducted from 2004 to 2018 (n = 268,193) were used to generate smoking histories. The Cancer Intervention and Surveillance Modeling (CISNET) Network Lung Working Group age, period, and cohort modeling approach was used to calculate smoking initiation and cessation probabilities, ever and current smoking prevalence, and intensity (cigarettes per day, CPD) by age, sex, and birth cohort from 1950 to 2018. Findings: Ever smoking prevalence increases with age up to 25 and decreases with birth cohorts after 1990. Smoking initiation peaks between 15 and 18 years of age. Among females, initiation probabilities increased until the 1955 cohort, reaching a second peak in 1980-85 cohorts and declining thereafter. Males have higher initiation probabilities than females. Among males, initiation has decreased since the 1950 birth cohort, with a slight increase around the 1985 cohort. Current smoking prevalence has been decreasing since the 1960 birth cohort, except for a peak in 1980-85 cohorts. Cessation increases with age. Mean CPD increases with age and peaks around age 40, appearing flat in females since the 1985 cohort. Interpretation: Recent birth cohorts seem to be experiencing lower rates of initiation, stable rates of quitting and lower current and ever smoking prevalence. The stabilization of cessation probabilities and mean CPD indicate the need to strengthen existing tobacco control measures and advance new ones. Funding: NIH/NCI U01CA253858 grant.

The burden of premature coronary heart disease among adults with low socioeconomic status in Argentina: A modeling study.

BACKGROUND: The well-established inverse relationship between socioeconomic status (SES) and risk of developing coronary heart disease (CHD) cannot be explained solely by differences in traditional risk factors. OBJECTIVE: To model the role SES plays in the burden of premature CHD in Argentina. MATERIALS AND METHODS: We used the Cardiovascular Disease Policy Model-Argentina to project incident CHD events and mortality in low and high-SES Argentinean adults 35 to 64 years of age from 2015 to 2024. Using data from the 2018 National Risk Factor Survey, we defined low SES as not finishing high-school and/or reporting a household income in quintiles 1 or 2. We designed simulations to apportion CHD outcomes in low SES adults to: (1) differences in the prevalence of traditional risk factors between low and high SES adults; (2) nontraditional risk associated with low SES status; (3) preventable events if risk factors were improved to ideal levels; and (4) underlying age- and sex-based risk. RESULTS: 56% of Argentina´s 35- to 64-year-old population has low SES. Both high and low SES groups have poor control of traditional risk factors. Compared with high SES population, low SES population had nearly 2-fold higher rates of incident CHD and CHD deaths per 10 000 person-years (incident CHD: men 80.8 [95%CI 76.6-84.9] vs 42.9 [95%CI 37.4-48.1], women 39.0 [95%CI 36.-41.2] vs 18.6 [95%CI 16.3-20.9]; CHD deaths: men 10.0 [95%CI 9.5-10.5] vs 6.0 [95%CI 5.6-6.4], women 3.2 [95%CI 3.0-3.4] vs 1.8 [95%CI 1.7-1.9]). Nontraditional low SES risk accounts for 73.5% and 70.4% of the event rate gap between SES levels for incident CHD and CHD mortality rates, respectively. DISCUSSION: CHD prevention policies in Argentina should address contextual aspects linked to SES, such as access to education or healthcare, and should also aim to implement known clinical strategies to achieve better control of CHD risk factors in all socioeconomic levels.

Disparities in regional obesity rates in argentina by socioeconomic status / Disparidades en prevalencia de obesidad por región y estatus socioeconómico en Argentina

Abstract Background : Obesity rates in Latin America are increasing overall and among people with low socio economic status (SES). Obesity and SES disparities can vary by region-a valuable indicator of local drivers. The objective of this study was to examine regional and SES differences in obesity in Argentina. Methods : We used data from Argentina's 4th Na tional Risk Factors Survey (n = 29226) 2018 and defined obesity as BMI ≥ 30. Low SES was defined as not fin ished high school or having a household income in the lowest two quintiles. Descriptive analysis stratified by sex compared obesity rates by SES, province, and re gion. Age-adjusted logistic regression models explored the association between obesity, socioeconomic status, and region. Results : Obesity rates varied more by SES among women (39% for low SES vs. 26% for middle/high SES; p < 0.001) than among men (33% low SES vs. 29% middle/ high SES; p = 0.027). The Patagonian region had the high est obesity prevalence for both men (36%) and women (37%). A gender-stratified age-adjusted analysis with region and SES showed that low SES (OR 1.72, 95% CI 1.45, 2.03) and the Patagonian region (OR 1.29, 95% CI 1.02, 1.62) were the only significant predictors for women. Conclusions : SES associated disparities in obesity in Argentina were pronounced for women but not men. Disparities were particularly high in Patagonia. Further research is needed to understand the drivers behind these SES, regional, and gender disparities.

Resumen Introducción : Las tasas de obesidad en América La tina están aumentando, tanto en la población general como entre las personas con bajo nivel socioeconómi co (NSE). Las disparidades en obesidad y NSE pueden variar ampliamente según la región, un indicador po tencialmente valioso de fenómenos causales locales. El objetivo de este estudio fue examinar las diferencias en la prevalencia de obesidad a nivel regional y según el NSE en Argentina. Métodos : Utilizamos datos de la 4ª Encuesta Nacio nal de Factores de Riesgo realizada en Argentina en 2018 (n = 29226). Definimos obesidad como índice de masa corporal ≥ 30, y bajo NSE como no haber termi nado la escuela secundaria o tener un ingreso familiar en los dos quintiles más bajos. El análisis descriptivo estratificado por sexo comparó la prevalencia de obe sidad por NSE, provincia y región. Además, utilizamos modelos de regresión logística ajustados por edad para explorar la asociación entre obesidad, nivel socioeconó mico y región, tanto globalmente como estratificando por sexo.367 Resultados : Las tasas de obesidad variaron más por NSE entre las mujeres (39% NSE bajo vs. 26% NSE medio/ alto; p < 0.001) que entre los hombres (33% NSE bajo vs. 29% NSE medio/alto; p = 0.027). La región patagónica tuvo la mayor prevalencia de obesidad tanto para hom bres (36%) como para mujeres (37%). Un análisis estra tificado por género, con región y NSE como covariables, mostró que el bajo NSE (OR 1.72, IC 95% 1.45, 2.03) y la región patagónica (OR 1.29, IC 95% 1.02, 1.62) fueron los únicos predictores significativos para las mujeres; nin guno se asoció significativamente con un mayor riesgo de obesidad para los hombres. Conclusiones : Las disparidades asociadas al NSE en la obesidad en Argentina fueron pronunciadas entre mujeres, pero no entre hombres. Las disparidades fueron particularmente altas en la Patagonia. Se necesita más estudios para comprender los factores detrás de estas disparidades de NSE, regionales y de género.

[Disparities in regional obesity rates in Argentina by socioeconomic status]. / Disparidades en prevalencia de obesidad por región y estatus socioeconómico en Argentina.

BACKGROUND: Obesity rates in Latin America are increasing overall and among people with low socioeconomic status (SES). Obesity and SES disparities can vary by region-a valuable indicator of local drivers. The objective of this study was to examine regional and SES differences in obesity in Argentina. METHODS: We used data from Argentina's 4th National Risk Factors Survey (n = 29226) 2018 and defined obesity as BMI = 30. Low SES was defined as not finished high school or having a household income in the lowest two quintiles. Descriptive analysis stratified by sex compared obesity rates by SES, province, and region. Age-adjusted logistic regression models explored the association between obesity, socioeconomic status, and region. RESULTS: Obesity rates varied more by SES among women (39% for low SES vs. 26% for middle/high SES; p < 0.001) than among men (33% low SES vs. 29% middle/ high SES; p = 0.027). The Patagonian region had the highest obesity prevalence for both men (36%) and women (37%). A gender-stratified age-adjusted analysis with region and SES showed that low SES (OR 1.72, 95% CI 1.45, 2.03) and the Patagonian region (OR 1.29, 95% CI 1.02, 1.62) were the only significant predictors for women. CONCLUSIONS: SES associated disparities in obesity in Argentina were pronounced for women but not men. Disparities were particularly high in Patagonia. Further research is needed to understand the drivers behind these SES, regional, and gender disparities.

Introducción: Las tasas de obesidad en América Latina están aumentando, tanto en la población general como entre las personas con bajo nivel socioeconómico (NSE). Las disparidades en obesidad y NSE pueden variar ampliamente según la región, un indicador potencialmente valioso de fenómenos causales locales. El objetivo de este estudio fue examinar las diferencias en la prevalencia de obesidad a nivel regional y según el NSE en Argentina. Métodos: Utilizamos datos de la 4° Encuesta Nacional de Factores de Riesgo realizada en Argentina en 2018 (n = 29226). Definimos obesidad como índice de masa corporal = 30, y bajo NSE como no haber terminado la escuela secundaria o tener un ingreso familiar en los dos quintiles más bajos. El análisis descriptivo estratificado por sexo comparó la prevalencia de obesidad por NSE, provincia y región. Además, utilizamos modelos de regresión logística ajustados por edad para explorar la asociación entre obesidad, nivel socioeconómico y región, tanto globalmente como estratificando por sexo.Resultados: Las tasas de obesidad variaron más por NSE entre las mujeres (39% NSE bajo vs. 26% NSE medio/alto; p < 0.001) que entre los hombres (33% NSE bajo vs. 29% NSE medio/alto; p = 0.027). La región patagónica tuvo la mayor prevalencia de obesidad tanto para hombres (36%) como para mujeres (37%). Un análisis estratificado por género, con región y NSE como covariables, mostró que el bajo NSE (OR 1.72, IC 95% 1.45, 2.03) y la región patagónica (OR 1.29, IC 95% 1.02, 1.62) fueron los únicos predictores significativos para las mujeres; ninguno se asoció significativamente con un mayor riesgo de obesidad para los hombres. Conclusiones: Las disparidades asociadas al NSE en la obesidad en Argentina fueron pronunciadas entre mujeres, pero no entre hombres. Las disparidades fueron particularmente altas en la Patagonia. Se necesita más estudios para comprender los factores detrás de estas disparidades de NSE, regionales y de género.

Modelling the impact of plain packaging of tobacco products on cardiovascular disease in Argentina.

INTRODUCTION: Tobacco packaging design is conceived to be attractive. Plain packaging of tobacco products reduces this attractiveness by standardising their shape, size, font and colours. METHODS: To evaluate the effect of applying plain packaging to tobacco products on cardiovascular events and mortality in Argentina, we used the Cardiovascular Disease Policy Model-Argentina, a local adaptation of a well-established computer simulation model that projects cardiovascular and mortality events for the population 35-94 years old using local demographic and consumption data, during the period 2015-2024. After a literature review, we estimated that the implementation of plain packaging of tobacco products would result in an absolute decrease in tobacco prevalence of 0.55% (base-case scenario) and performed a sensitivity analysis assuming a higher and lower decrease of 1.01% and 0.095%, respectively. RESULTS: Over the 2015-2024 period, the decrease in smoking prevalence associated with plain packaging (0.55%) is projected to avert 1880 myocardial infarctions (MI), 820 strokes and 4320 total deaths in Argentina. The higher estimate of smoking prevalence reduction (1.01%) would translate into 3450 fewer MIs, 1490 fewer strokes and 7920 fewer deaths, while the lower estimate of smoking prevalence reduction (0.095%) would result in 330 fewer MIs, 140 fewer strokes and 750 fewer deaths. CONCLUSIONS: The implementation of plain packaging of tobacco products could reduce cardiovascular events in Argentina, even in the absence of other tobacco control measures. Actual health benefits are likely higher than those presented here, since plain packaging may be most impactful by preventing young people from initiating smoking.

Manejo farmacológico del sangrado irregular no menstrual asociado al uso de implantes anticonceptivos subdérmicos / Pharmacological management of irregular non-menstrual bleeding associated with the use of subdermal contraceptive implants

El spottingo sangrado irregular no menstrual es uno de los principales efectos secundarios de los implantes anticonceptivos, situación que se recomienda discutir con la usuaria previo a la colocación, para evitar falsas expectativas o temores que lleven a la extracción temprana del dispositivo. A propósito de una paciente sin antecedentes relevantes que consultó al centro de salud por spotting desde la colocación del implante cuatro meses antes, decidimos revisar la evidencia sobre la efectividad de los distintos esquemas farmacológicos disponibles para el manejo de este evento adverso. Luego de realizar una búsqueda bibliográfica concluimos que, si bien existe sustento para indicar algunos de los esquemas farmacológicos, este es aún débil y son necesarios estudios clínicos adicionales que brinden evidencia sólida sobre qué esquema en particular utilizar, evaluando sus riesgos y beneficios. (AU)

Spotting or irregular non-menstrual bleeding is one of the main side effects of contraceptive implants, a situation that health professionals must discuss with the user prior to its placement in order to avoid false expectations or fears that lead to early removal of the implant. Regarding a patient with no relevant history who consulted the health center due to spotting four months after implant placement, we decided to review the evidence onthe effectiveness on different pharmacological schemes available for the management of this adverse event. After performing a literature search, we concluded that, although there is support for indicating some of the pharmacological schemes, this is still weak, and further clinical studies are needed to provide solid evidence on which particular scheme touse, assessing its risks and benefits. (AU)

Telmisartan for treatment of Covid-19 patients: An open multicenter randomized clinical trial.

Background: Angiotensin receptor blockers (ARBs), such as telmisartan, have been postulated to treat Covid-19-induced lung inflammation. Methods: This is a parallel-group, randomized, two-arm, open-label, adaptive, multicenter superiority trial with 1:1 allocation ratio. Participants included patients from 18 years of age hospitalized with Covid-19 with 4 or fewer days since symptom onset enrolled at a university and a community hospital in Buenos Aires, Argentina. Exclusion criteria included prior intensive care unit (ICU) admission and use of ARBs/angiotensin converting enzyme inhibitors at randomization. Control arm received standard care alone and treatment arm telmisartan 80 mg twice daily for 14 days. Primary outcomes were C-reactive protein (CRP) plasma levels at day 5 and 8 after randomization. Secondary outcomes included time to discharge within 15 days, admission to ICU and death at 15- and 30-days. NCT04355936 (Completed). Findings: A pragmatic decision to end the study before the third interim analysis was made on Oct. 30th due to sharp reduction in recruitment. A total of 162 patients were randomized. 158 patients enrolled between May 14 and October 30 2020, were included in the analysis, 80 in the standard care and 78 in the telmisartan added to standard care group. Baseline absolute CRP serum levels were 5.53 ± 6.19 mg/dL (95% CI 6.91 to 4.15, n = 80) and 9.04 ± 7.69 (95% CI 9.04 to 10.82, n = 74) in the standard care and telmisartan added to standard care groups, respectively. Day 5 control-group CRP levels were 6.06 ± 6.95 mg/dL (95% CI 7.79-4.35, n = 66) while telmisartan group were 3.83 ± 5.08 mg/dL (95% CI 5.08-2.59, n = 66, p = 0.038). Day 8 CRP levels were 6.30 ± 8.19 mg/dL (95% CI 8.79-3.81, n = 44) and 2.37 ± 3.47 mg/dL (95% CI 3.44-1.30, n = 43, p = 0.0098) in the control and telmisartan groups, respectively (all values expressed as mean ± SD). Kaplan-Meier analysis showed that telmisartan-treated patients had a lower median time-to-discharge (control=15 days; telmisartan=9 days). Death by day 30 was reduced in the telmisartan-treated group (control 22.54%, 16/71; telmisartan 4.29%, 3/70 participants; p = 0.0023). Composite ICU, mechanical ventilation or death was reduced by telmisartan treatment at days 15 and 30. No adverse events were reported. Interpretation: Our study suggests that the ARB telmisartan, a widely used antihypertensive drug, is safe and could reduce morbidity and mortality in hospitalized patients infected with SARS -CoV-2 by anti-inflammatory effects. Further studies employing telmisartan are needed for confirmation of our results and to define its true therapeutic value as a tool against Covid-19.

Angiotensin Receptor Blockers for COVID-19: Pathophysiological and Pharmacological Considerations About Ongoing and Future Prospective Clinical Trials.

COVID-19 pandemic demands a swift response to find therapeutic tools that effectively reduce morbidity and mortality. Despite initial fears, evidence from retrospective observational studies supports the inhibition of the renin-angiotensin system as an emerging pathway to delay or moderate angiotensin II-driven lung inflammation. This has triggered several prospective clinical trials. In this commentary we provide an overview and analysis of current ongoing clinical trials aimed at evaluating the therapeutic efficacy of angiotensin receptor blocker (ARB) use in COVID-19. The relevance of the results of these trials will have to be interpreted depending on the stage and severity of the disease and in light of the start time of their prescription related to the time of diagnosis of COVID-19 as well as the administered doses.

The role of computer simulation models in the design of public policies / El rol de los modelos de simulación por computadora en el diseño de políticas públicas

Abstract Cardiovascular diseases are the number one cause of death globally, but their optimal prevention remains a challenge. A high-risk approach can only have a limited effect at a population level, while population-based strategies can improve and extend the coverage of a high-risk approach. However, one main problem for promoting cardiovascular diseases prevention public policies is the difficulty to foresee population health benefits of a single policy. Computer simulation models can assist with this problem, due to their ability to estimate intervention effects over different periods, and by scaling up the evidence to a broader, more diverse population. Their applicability to countries with different social, political and economic contexts can assist in the design of public policies. There are several models that assess health and economics scenarios, but regardless which model is chosen, when adequately used, they can provide reasonable estimations of health policies' impact. There is a growing consensus amongst the public health communities about the powerful role of population-level policies. They are more effective, cost saving and more equitable when compared with individual-level interventions. Policy makers and the public health community need to make further progress in changing the focus of prevention, from individuals to populations.

Resumen Las enfermedades cardiovasculares son la principal causa de muerte en el mundo, pero su prevención óptima sigue siendo un desafío. El enfoque prioritario a escala individual en pacientes de alto riesgo solo puede tener un efecto limitado a nivel colectivo, mientras que las estrategias de alcance poblacional pueden mejorar y ampliar la cobertura de estos enfoques de alto riesgo. Sin embargo, uno de los principales problemas para promover políticas públicas de prevención de enfermedades cardiovasculares es la dificultad para prever los beneficios que una política única puede tener en salud. Los modelos de simulación por computadora pueden ayudar con este problema, dada su capacidad para estimar los efectos de una intervención en diferentes períodos, ampliando la evidencia a una población más extensa y diversa. Adicionalmente, su aplicabilidad a países con diferentes contextos sociales, políticos y económicos puede asistir en el diseño de políticas públicas. Existen varios modelos que evalúan escenarios tanto de salud como de economía, pero independientemente de qué modelo se elija, usados adecuadamente pueden proporcionar estimaciones razonables del impacto de las políticas de salud. Existe un consenso creciente en el ámbito de la salud pública sobre el importante rol de las políticas poblacionales. Son más efectivas, económicas, y equitativas en comparación con las intervenciones a nivel individual. En la formulación de políticas públicas en general, y de salud pública en particular, se debe avanzar en cambiar el enfoque de la prevención desde las personas a las comunidades.

The role of computer simulation models in the design of public policies.

Cardiovascular diseases are the number one cause of death globally, but their optimal prevention remains a challenge. A high-risk approach can only have a limited effect at a population level, while population-based strategies can improve and extend the coverage of a high-risk approach. However, one main problem for promoting cardiovascular diseases prevention public policies is the difficulty to foresee population health benefits of a single policy. Computer simulation models can assist with this problem, due to their ability to estimate intervention effects over different periods, and by scaling up the evidence to a broader, more diverse population. Their applicability to countries with different social, political and economic contexts can assist in the design of public policies. There are several models that assess health and economics scenarios, but regardless which model is chosen, when adequately used, they can provide reasonable estimations of health policies' impact. There is a growing consensus amongst the public health communities about the powerful role of population-level policies. They are more effective, cost saving and more equitable when compared with individual-level interventions. Policy makers and the public health community need to make further progress in changing the focus of prevention, from individuals to populations.

Las enfermedades cardiovasculares son la principal causa de muerte en el mundo, pero su prevención óptima sigue siendo un desafío. El enfoque prioritario a escala individual en pacientes de alto riesgo solo puede tener un efecto limitado a nivel colectivo, mientras que las estrategias de alcance poblacional pueden mejorar y ampliar la cobertura de estos enfoques de alto riesgo. Sin embargo, uno de los principales problemas para promover políticas públicas de prevención de enfermedades cardiovasculares es la dificultad para prever los beneficios que una política única puede tener en salud. Los modelos de simulación por computadora pueden ayudar con este problema, dada su capacidad para estimar los efectos de una intervención en diferentes períodos, ampliando la evidencia a una población más extensa y diversa. Adicionalmente, su aplicabilidad a países con diferentes contextos sociales, políticos y económicos puede asistir en el diseño de políticas públicas. Existen varios modelos que evalúan escenarios tanto de salud como de economía, pero independientemente de qué modelo se elija, usados adecuadamente pueden proporcionar estimaciones razonables del impacto de las políticas de salud. Existe un consenso creciente en el ámbito de la salud pública sobre el importante rol de las políticas poblacionales. Son más efectivas, económicas, y equitativas en comparación con las intervenciones a nivel individual. En la formulación de políticas públicas en general, y de salud pública en particular, se debe avanzar en cambiar el enfoque de la prevención desde las personas a las comunidades.

Projected impact of a reduction in sugar-sweetened beverage consumption on diabetes and cardiovascular disease in Argentina: A modeling study.

BACKGROUND: Sugar-sweetened beverage (SSB) consumption is associated with obesity, diabetes, and hypertension. Argentina is one of the major consumers of SSBs per capita worldwide. Determining the impact of SSB reduction on health will inform policy debates. METHODS AND FINDINGS: We used the Cardiovascular Disease Policy Model-Argentina (CVD Policy Model-Argentina), a local adaptation of a well-established computer simulation model that projects cardiovascular and mortality events for the population 35-94 years old, to estimate the impact of reducing SSB consumption on diabetes incidence, cardiovascular events, and mortality in Argentina during the period 2015-2024, using local demographic and consumption data. Given uncertainty regarding the exact amount of SSBs consumed by different age groups, we modeled 2 estimates of baseline consumption (low and high) under 2 different scenarios: a 10% and a 20% decrease in SSB consumption. We also included a range of caloric compensation in the model (0%, 39%, and 100%). We used Monte Carlo simulations to generate 95% uncertainty intervals (UIs) around our primary outcome measures for each intervention scenario. Over the 2015-2024 period, a 10% reduction in SSBs with a caloric compensation of 39% is projected to reduce incident diabetes cases by 13,300 (95% UI 10,800-15,600 [low SSB consumption estimate]) to 27,700 cases (95% UI 22,400-32,400 [high SSB consumption estimate]), i.e., 1.7% and 3.6% fewer cases, respectively, compared to a scenario of no change in SSB consumption. It would also reduce myocardial infarctions by 2,500 (95% UI 2,200-2,800) to 5,100 (95% UI 4,500-5,700) events and all-cause deaths by 2,700 (95% UI 2,200-3,200) to 5,600 (95% UI 4,600-6,600) for "low" and "high" estimates of SSB intake, respectively. A 20% reduction in SSB consumption with 39% caloric compensation is projected to result in 26,200 (95% UI 21,200-30,600) to 53,800 (95% UI 43,900-62,700) fewer cases of diabetes, 4,800 (95% UI 4,200-5,300) to 10,000 (95% UI 8,800-11,200) fewer myocardial infarctions, and 5,200 (95% UI 4,300-6,200) to 11,000 (95% UI 9,100-13,100) fewer deaths. The largest reductions in diabetes and cardiovascular events were observed in the youngest age group modeled (35-44 years) for both men and women; additionally, more events could be avoided in men compared to women in all age groups. The main limitations of our study are the limited availability of SSB consumption data in Argentina and the fact that we were only able to model the possible benefits of the interventions for the population older than 34 years. CONCLUSIONS: Our study finds that, even under conservative assumptions, a relatively small reduction in SSB consumption could lead to a substantial decrease in diabetes incidence, cardiovascular events, and mortality in Argentina.

Update of the cardiovascular disease policy model to predict cardiovascular events in Argentina.

Cardiovascular disease (CVD) is the leading cause of death in Argentina. Computer simulation models allow to extrapolate evidence to broader populations than the originally studied, over longer timeframes, and to compare different subpopulations. The Cardiovascular Disease Policy Model (CVDPM) is a computer simulation state transition model used to represent and project future CVD mortality and morbidity in the population 35 years-old and older. The objective of this study was to update Argentina's version of the CVDPM. For this purpose, information from the 2010 National Census, the 2013 National Risk Factor Survey, CESCAS I study, and PrEViSTA study were used to update the dynamics of population size, demographics, and CVD risk factor distributions over time. Model projections were later calibrated by comparing them to actual data on CVD events and mortality in the year 2010 (baseline year) in Argentina. Country statistics for people 35 years-old and older reported for 2010 a total of 41 219 myocardial infarctions (MIs), 58 658 strokes, and 281 710 total deaths. The CVDPM, in turn, predicted 41 265 MIs (difference: 0.11%), 58 584 strokes (difference: 0.13%), and 280 707 total deaths (difference: 0.36%) in the same population. In all cases, the final version of the model predicted the actual number of events with an accuracy superior to 99.5%, and could be used to forecast the changes in CVD incidence and mortality after the implementation of public policies.

La enfermedad cardiovascular (ECV) es la principal causa de muerte en Argentina. Los modelos de simulación por computadora permiten extrapolar evidencia a poblaciones más amplias que las originalmente estudiadas, a lo largo de períodos prolongados, y comparar diferentes subpoblaciones. El Cardiovascular Disease Policy Model (CVDPM, por sus siglas en inglés) es un modelo de simulación utilizado para representar y proyectar la mortalidad y morbilidad por ECV en la población de 35 o más años. El objetivo de este trabajo fue actualizar la versión argentina del CVDPM. Para esto, se utilizó información del Censo Nacional 2010, la Encuesta Nacional de Factores de Riesgo 2013, el estudio CESCAS I, y el estudio PrEViSTA, para actualizar la dinámica del tamaño de la población, sus características demográficas, y la distribución de factores de riesgo cardiovasculares a lo largo del tiempo. Las proyecciones del modelo se calibraron comparándolas con información sobre eventos de ECV y mortalidad en el año 2010 (año de referencia) en Argentina. Las estadísticas argentinas informaron que en 2010 la población de 35 o más años sufrió un total de 41 219 infartos de miocardio (IM), 58 658 accidentes cerebrovasculares y 281 710 muertes totales. El CVDPM predijo 41 265 IM (diferencia: 0.11%), 58 584 accidentes cerebrovasculares (diferencia: 0.13%) y 280 707 muertes totales (diferencia: 0.36%). En todos los casos, la versión final del modelo predijo el número real de eventos cardiovasculares con una precisión superior al 99.5%, pudiendo ser utilizado para pronosticar cambios en la incidencia y mortalidad de ECV debidos de la implementación de políticas públicas.

Actualización del modelo de políticas en enfermedad cardiovascular en Argentina / Update of the cardiovascular disease policy model to predict cardiovascular events in Argentina

La enfermedad cardiovascular (ECV) es la principal causa de muerte en Argentina. Los modelos de simulació;n por computadora permiten extrapolar evidencia a poblaciones más amplias que las originalmente estudiadas, a lo largo de períodos prolongados, y comparar diferentes subpoblaciones. El Cardiovascular Disease Policy Model (CVDPM, por sus siglas en ingló;©s) es un modelo de simulació;n utilizado para representar y proyectar la mortalidad y morbilidad por ECV en la població;n de 35 o más aó;±os. El objetivo de este trabajo fue actualizar la versió;n argentina del CVDPM. Para esto, se utilizó; informació;n del Censo Nacional 2010, la Encuesta Nacional de Factores de Riesgo 2013, el estudio CESCAS I, y el estudio PrEViSTA, para actualizar la dinámica del tamaó;±o de la població;n, sus características demográficas, y la distribució;n de factores de riesgo cardiovasculares a lo largo del tiempo. Las proyecciones del modelo se calibraron comparándolas con informació;n sobre eventos de ECV y mortalidad en el aó;±o 2010 (aó;±o de referencia) en Argentina. Las estadísticas argentinas informaron que en 2010 la població;n de 35 o más aó;±os sufrió; un total de 41 219 infartos de miocardio (IM), 58 658 accidentes cerebrovasculares y 281 710 muertes totales. El CVDPM predijo 41 265 IM (diferencia: 0.11%), 58 584 accidentes cerebrovasculares (diferencia: 0.13%) y 280 707 muertes totales (diferencia: 0.36%). En todos los casos, la versió;n final del modelo predijo el nó;ºmero real de eventos cardiovasculares con una precisió;n superior al 99.5%, pudiendo ser utilizado para pronosticar cambios en la incidencia y mortalidad de ECV debidos de la implementació;n de políticas pó;ºblicas.

Cardiovascular disease (CVD) is the leading cause of death in Argentina. Computer simulation models allow to extrapolate evidence to broader populations than the originally studied, over longer timeframes, and to compare different subpopulations. The Cardiovascular Disease Policy Model (CVDPM) is a computer simulation state transition model used to represent and project future CVD mortality and morbidity in the population 35 years-old and older. The objective of this study was to update Argentina’s version of the CVDPM. For this purpose, information from the 2010 National Census, the 2013 National Risk Factor Survey, CESCAS I study, and PrEViSTA study were used to update the dynamics of population size, demographics, and CVD risk factor distributions over time. Model projections were later calibrated by comparing them to actual data on CVD events and mortality in the year 2010 (baseline year) in Argentina. Country statistics for people 35 years-old and older reported for 2010 a total of 41 219 myocardial infarctions (MIs), 58 658 strokes, and 281 710 total deaths. The CVDPM, in turn, predicted 41 265 MIs (difference: 0.11%), 58 584 strokes (difference: 0.13%), and 280 707 total deaths (difference: 0.36%) in the same population. In all cases, the final version of the model predicted the actual number of events with an accuracy superior to 99.5%, and could be used to forecast the changes in CVD incidence and mortality after the implementation of public policies.

Update of the cardiovascular disease policy model to predict cardiovascular events in Argentina

Cardiovascular disease (CVD) is the leading cause of death in Argentina. Computer simulation models allow to extrapolate evidence to broader populations than the originally studied, over longer timeframes, and to compare different subpopulations. The Cardiovascular Disease Policy Model (CVDPM) is a computer simulation state transition model used to represent and project future CVD mortality and morbidity in the population 35 years-old and older. The objective of this study was to update Argentina’s version of the CVDPM. For this purpose, information from the 2010 National Census, the 2013 National Risk Factor Survey, CESCAS I study, and PrEViSTA study were used to update the dynamics of population size, demographics, and CVD risk factor distributions over time. Model projections were later calibrated by comparing them to actual data on CVD events and mortality in the year 2010 (baseline year) in Argentina. Country statistics for people 35 years-old and older reported for 2010 a total of 41 219 myocardial infarctions (MIs), 58 658 strokes, and 281 710 total deaths. The CVDPM, in turn, predicted 41 265 MIs (difference: 0.11%), 58 584 strokes (difference: 0.13%), and 280 707 total deaths (difference: 0.36%) in the same population. In all cases, the final version of the model predicted the actual number of events with an accuracy superior to 99.5%, and could be used to forecast the changes in CVD incidence and mortality after the implementation of public policies.

La enfermedad cardiovascular (ECV) es la principal causa de muerte en Argentina. Los modelos de simulació;n por computadora permiten extrapolar evidencia a poblaciones más amplias que las originalmente estudiadas, a lo largo de períodos prolongados, y comparar diferentes subpoblaciones. El Cardiovascular Disease Policy Model (CVDPM, por sus siglas en ingló;©s) es un modelo de simulació;n utilizado para representar y proyectar la mortalidad y morbilidad por ECV en la població;n de 35 o más aó;±os. El objetivo de este trabajo fue actualizar la versió;n argentina del CVDPM. Para esto, se utilizó; informació;n del Censo Nacional 2010, la Encuesta Nacional de Factores de Riesgo 2013, el estudio CESCAS I, y el estudio PrEViSTA, para actualizar la dinámica del tamaó;±o de la població;n, sus características demográficas, y la distribució;n de factores de riesgo cardiovasculares a lo largo del tiempo. Las proyecciones del modelo se calibraron comparándolas con informació;n sobre eventos de ECV y mortalidad en el aó;±o 2010 (aó;±o de referencia) en Argentina. Las estadísticas argentinas informaron que en 2010 la població;n de 35 o más aó;±os sufrió; un total de 41 219 infartos de miocardio (IM), 58 658 accidentes cerebrovasculares y 281 710 muertes totales. El CVDPM predijo 41 265 IM (diferencia: 0.11%), 58 584 accidentes cerebrovasculares (diferencia: 0.13%) y 280 707 muertes totales (diferencia: 0.36%). En todos los casos, la versió;n final del modelo predijo el nó;ºmero real de eventos cardiovasculares con una precisió;n superior al 99.5%, pudiendo ser utilizado para pronosticar cambios en la incidencia y mortalidad de ECV debidos de la implementació;n de políticas pó;ºblicas.

Smoking-Related Attitudes and Knowledge Among Medical Students and Recent Graduates in Argentina: A Cross-Sectional Study.

BACKGROUND: Physicians in Argentina smoke at rates similar to the general population, and do not have a clear role in tobacco control strategies. OBJECTIVE: To describe the attitudes and knowledge of medical students and recent graduates towards smoking behavior in Argentina. DESIGN: Cross-sectional self-administered online survey conducted in 2011. PARTICIPANTS: Medical students and recent medical graduates from the University of Buenos Aires. MAIN MEASURES: Attitudes and knowledge were evaluated by responses to 16 statements regarding the effects of smoking cigarettes and the role of physicians in tobacco control. Rates of agreement with a full ban on indoor smoking in different public settings were assessed. KEY RESULTS: The sample included 1659 participants (response rate: 35.1 %), 453 of whom (27.3 %) were current smokers. Only 52 % of participants agreed that doctors should set an example for their patients by not smoking, 30.9 % thought that medical advice had little effect on patients' cessation behavior, and 19.4 % believed that physicians could decline to care for smoking patients who failed to quit. In adjusted logistic regression models, current smokers had less supportive attitudes about tobacco control and were less likely than non-smokers to agree with a full indoor smoking ban in hospitals (OR: 0.30; 95 % CI 0.16-0.58), universities (OR: 0.55; 95 % CI 0.41-0.73), workplaces (OR: 0.67; 95 % CI 0.50-0.88), restaurants (OR: 0.42; 95 % CI 0.33-0.53), cafes (OR: 0.41; 95 % CI 0.33-0.51), nightclubs (OR: 0.32; 95 % CI 0.25-0.40), and bars (0.35; 95 % CI 0.28-0.45). Recent medical graduates had more accurate knowledge about cessation and were more likely to agree with a full smoking ban in recreational venues. CONCLUSIONS: Although most participants reported a strong anti-tobacco attitude, a proportion still failed to recognize the importance of their role as physicians in tobacco control strategies. Current smokers and current students were less likely to support indoor smoking bans. Specific educational curricula could address these factors.

Smoking behavior and use of tobacco industry sponsored websites among medical students and young physicians in Argentina.

BACKGROUND: Internet-based marketing has become an attractive option for promoting tobacco products due to its potential to avoid advertising restrictions. In Argentina, several cigarette brands have designed websites for the local market, which promote user participation. OBJECTIVE: The intent of the study was to report on the use of tobacco company-sponsored websites by medical students and recently graduated physicians. METHODS: An online self-administered survey was conducted among eligible medical students and recent graduates from the University of Buenos Aires (UBA). Sampling was from lists of email addresses of students enrolled in two required courses. Eligibility criteria were ages 18-30 years and reporting on smoking status. Questions on Internet use included accessing a tobacco brand website at least once during their lifetime and any use of tobacco promotional materials. RESULTS: The response rate was 35.08% (1743/4969). The final sample included 1659 participants: 73.06% (1212/1659) were women and mean age was 26.6 years (SD 1.9). The majority were current medical students (55.70%, 924/1659) and 27.31% (453/1659) were current smokers. Men were more likely to report having seen a tobacco advertisement on the Internet (P=.001), to have received a tobacco promotion personally addressed to them (P=.03), to have used that promotion (P=.02), and to have accessed a tobacco-sponsored website (P=.01). Among respondents, 19.35% (321/1659) reported having accessed a tobacco-sponsored website at least once in their lifetime and almost all of them (93.8%, 301/321) accessed these sites only when it was necessary for participating in a marketing promotion. Most people logging on for promotions reported entering once a month or less (58.9%, 189/321), while 25.5% (82/321) reported accessing the tobacco industry Internet sites once a week or more. In adjusted logistic regression models, participants were more likely to have accessed a tobacco brand website if they were former smokers (OR 2.45, 95% CI 1.42-4.22) or current (OR 8.12, 95% CI 4.66-14.16), if they reported having seen a tobacco advertisement on the Internet (OR 2.44, 95% CI 1.77-3.37), received a tobacco promotion personally addressed to them (OR 5.62; 95% CI 4.19-7.55), or used one of these promotions (OR 14.05, 95% CI 9.21-21.43). Respondents were more likely to be current smokers if they received a tobacco promotion (OR 2.64, 95% CI 2.02-3.45) or if they used one of these promotions (OR 1.93, 95% CI 1.31-2.85). CONCLUSIONS: Our study suggests that tobacco industry websites reach medical students and young physicians in a middle-income country with their marketing promotions. Current or proposed legislation to ban tobacco advertising needs to include Internet sites and related social media.

Association of media literacy with cigarette smoking among youth in Jujuy, Argentina.

INTRODUCTION: Latin America has the highest prevalence of tobacco use by youth. Higher media literacy, defined as the ability to analyze and evaluate media messages, has been associated with lower smoking among youth in the United States. The objective of this study was to determine whether media literacy related to smoking is independently associated with current smoking and susceptibility to future smoking in a sample of mostly indigenous youth in Jujuy, Argentina. METHODS: In 2006, a self-administered survey was conducted among 10th grade students sampled from 27 randomly selected urban and rural schools in Jujuy. Survey items measured smoking behavior (ever, never, and current), susceptibility to future smoking among never-smokers (definitely not accept a cigarette from a friend or to smoke in the future), 5 items assessing smoking media literacy (SML), and risk factors for smoking. RESULTS: Of the 3,470 respondents, 1,170 (34%) reported having smoked in the previous 30 days (current). Of the 1,430 students who had never smoked, 912 (64%) were susceptible to future smoking. High media literacy was present in 38%. Using multiple logistic regression, fully adjusted models showed that high media literacy was significantly associated as a protective factor of being a current smoker (odds ratio [OR] = 0.81; 95% CI = 0.67-0.97) and of being susceptible to future smoking (OR = 0.73; 95% CI = 0.58-0.92) among those who had never smoked. CONCLUSIONS: Among youth in Jujuy, higher SML was significantly associated with both lower current smoking and susceptibility to future smoking. Teaching SML may be a valuable component in a prevention intervention in this population.

Direct disease-inducing effects of menthol through the eyes of tobacco companies.

OBJECTIVE: Menthol is an important additive in most tobacco products and is an identifying characteristic of many brands. We assessed tobacco companies' research on direct disease-inducing effects of menthol and menthol cigarettes. METHODS: A search was conducted among documents included in the Legacy Tobacco Documents Library. Relevant documents addressed subject areas such as pharmacology, short-term and long-term effects and biomarkers of smoking exposure. RESULTS: The documents contain little internal industry research on the disease-inducing effects of menthol. Most information in the tobacco industry documents are reviews of the published biomedical literature, from which the companies concluded that menthol did not have any direct disease-inducing effects. Evidence that contradicted this conclusion was downplayed. Except for one study, there was no evidence of the companies following up on positive findings in the literature with their own studies. In one case, results were presented at a public scientific meeting concluding that 'There were no effects from addition of menthol to test or reference cigarettes', when a company's internal pathology analysis contradicted this statement. CONCLUSION: The available industry documents suggest that tobacco companies conducted little research on the potential disease-inducing effects of menthol and did not pursue studies that suggested adverse effects.

Language barriers, physician-patient language concordance, and glycemic control among insured Latinos with diabetes: the Diabetes Study of Northern California (DISTANCE).

BACKGROUND: A significant proportion of US Latinos with diabetes have limited English proficiency (LEP). Whether language barriers in health care contribute to poor glycemic control is unknown. OBJECTIVE: To assess the association between limited English proficiency (LEP) and glycemic control and whether this association is modified by having a language-concordant physician. DESIGN: Cross-sectional, observational study using data from the 2005-2006 Diabetes Study of Northern California (DISTANCE). Patients received care in a managed care setting with interpreter services and self-reported their English language ability and the Spanish language ability of their physician. Outcome was poor glycemic control (glycosylated hemoglobin A1c > 9%). KEY RESULTS: The unadjusted percentage of patients with poor glycemic control was similar among Latino patients with LEP (n = 510) and Latino English-speakers (n = 2,683), and higher in both groups than in whites (n = 3,545) (21% vs 18% vs. 10%, p < 0.005). This relationship differed significantly by patient-provider language concordance (p < 0.01 for interaction). LEP patients with language-discordant physicians (n = 115) were more likely than LEP patients with language-concordant physicians (n = 137) to have poor glycemic control (27.8% vs 16.1% p = 0.02). After controlling for potential demographic and clinical confounders, LEP Latinos with language-concordant physicians had similar odds of poor glycemic control as Latino English speakers (OR 0.89; CI 0.53-1.49), whereas LEP Latinos with language-discordant physicians had greater odds of poor control than Latino English speakers (OR 1.76; CI 1.04-2.97). Among LEP Latinos, having a language discordant physician was associated with significantly poorer glycemic control (OR 1.98; CI 1.03-3.80). CONCLUSIONS: Language barriers contribute to health disparities among Latinos with diabetes. Limited English proficiency is an independent predictor for poor glycemic control among insured US Latinos with diabetes, an association not observed when care is provided by language-concordant physicians. Future research should determine if strategies to increase language-concordant care improve glycemic control among US Latinos with LEP.