Prioritizing risk factors to identify preventive interventions for economic assessment

Wilson, Nick; Blakely, Tony; Foster, Rachel H.; Hadorn, David C.; Vos, Theo

doi:10.2471/blt.11.091470

Cited by 11 publications

(8 citation statements)

References 32 publications

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“…Taken together, these criteria help identify the set of risk factors that are responsible for a significant proportion of the preventable burden of adult mental illness. This process is analogous to methods employed by the WHO to prioritise risk factors for global prevention interventions [ 126 ].…”

Section: Methodsmentioning

confidence: 99%

Preventing mental illness: closing the evidence-practice gap through workforce and services planning

Furber

Segal

Leach

et al. 2015

BMC Health Serv Res

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BackgroundMental illness is prevalent across the globe and affects multiple aspects of life. Despite advances in treatment, there is little evidence that prevalence rates of mental illness are falling. While the prevention of cardiovascular disease and cancers are common in the policy dialogue and in service delivery, the prevention of mental illness remains a neglected area. There is accumulating evidence that mental illness is at least partially preventable, with increasing recognition that its antecedents are often found in infancy, childhood, adolescence and youth, creating multiple opportunities into young adulthood for prevention. Developing valid and reproducible methods for translating the evidence base in mental illness prevention into actionable policy recommendations is a crucial step in taking the prevention agenda forward.MethodBuilding on an aetiological model of adult mental illness that emphasizes the importance of intervening during infancy, childhood, adolescence and youth, we adapted a workforce and service planning framework, originally applied to diabetes care, to the analysis of the workforce and service structures required for best-practice prevention of mental illness.ResultsThe resulting framework consists of 6 steps that include identifying priority risk factors, profiling the population in terms of these risk factors to identify at-risk groups, matching these at-risk groups to best-practice interventions, translation of these interventions to competencies, translation of competencies to workforce and service estimates, and finally, exploring the policy implications of these workforce and services estimates. The framework outlines the specific tasks involved in translating the evidence-base in prevention, to clearly actionable workforce, service delivery and funding recommendations.ConclusionsThe framework describes the means to deliver mental illness prevention that the literature indicates is achievable, and is the basis of an ongoing project to model the workforce and service structures required for mental illness prevention.

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Section: Methodsmentioning

confidence: 99%

Preventing mental illness: closing the evidence-practice gap through workforce and services planning

Furber

Segal

Leach

et al. 2015

BMC Health Serv Res

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“…Nutritional risk factors are also likely to be exacerbating health inequalities in some populations. This is the case in New Zealand for the indigenous population of Māori relative to the non-Māori (largely European) population [3].…”

Section: Introductionmentioning

confidence: 97%

Foods and Dietary Patterns That Are Healthy, Low-Cost, and Environmentally Sustainable: A Case Study of Optimization Modeling for New Zealand

et al. 2013

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ObjectiveGlobal health challenges include non-communicable disease burdens, ensuring food security in the context of rising food prices, and environmental constraints around food production, e.g., greenhouse gas [GHG] emissions. We therefore aimed to consider optimized solutions to the mix of food items in daily diets for a developed country population: New Zealand (NZ).MethodsWe conducted scenario development and linear programming to model 16 diets (some with uncertainty). Data inputs included nutrients in foods, food prices, food wastage and food-specific GHG emissions.FindingsThis study identified daily dietary patterns that met key nutrient requirements for as little as a median of NZ$ 3.17 per day (US$ 2.41/d) (95% simulation interval [SI] = NZ$ 2.86 to 3.50/d). Diets that included “more familiar meals” for New Zealanders, increased the cost. The optimized diets also had low GHG emission profiles compared with the estimate for the ‘typical NZ diet’ e.g., 1.62 kg CO2e/d for one scenario (95%SI = 1.39 to 1.85 kg CO2e) compared with 10.1 kg CO2e/d, respectively. All of the optimized low-cost and low-GHG dietary patterns had likely health advantages over the current NZ dietary pattern, i.e., lower cardiovascular disease and cancer risk.ConclusionsWe identified optimal foods and dietary patterns that would lower the risk of non-communicable diseases at low cost and with low greenhouse gas emission profiles. These results could help guide central and local government decisions around which foods to focus policies on. That is which foods are most suitable for: food taxes (additions and exemptions); healthy food vouchers and subsidies; and for increased use by public institutions involved in food preparation.

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“…Estudiar los factores asociados a la depresión en adultos mayores es muy importante desde el punto de vista de salud pública. Una intervención preventiva con alta razón beneficio-costo sólo es posible si se identifican y priorizan, en términos de importancia y modificabilidad, los factores asociados con el trastorno (18) . Numerosos estudios han identificado factores asociados con la depresión en adultos mayores.…”

Section: Introductionunclassified

Depresión y factores asociados en la población peruana adulta mayor según la ENDES 2014-2015

et al. 2018

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Objetivos: Estimar la prevalencia y los factores asociados a la depresión en la población peruana adulta mayor según los resultados de la Encuesta Demográfica y de Salud Familiar (ENDES) 2014-2015. Diseño: Estudio observacional, transversal y analítico. Institucion: UNMSM. Participantes: Adultos mayores. Intervenciones: Muestra probabilística de 11 411 adultos mayores que respondieron a la ENDES 2014-2015. Principales Medidas de Resultados: Prevalencias, promedios, desviaciones estándar y cálculos de OR con un IC 95%. Resultados: La prevalencia estimada fue de 14%. Respecto a los factores de riesgo para la depresión, se identificaron la condición de mujer [OR 1,92 (1,72 - 2,15)]; ser mayor de 75 años [OR 1,56 (1,40 - 1,74)]; el carecer de instrucción [OR 2,63 (2,35 - 2,95)]; el vivir sin pareja [OR 1,32 (1,19 - 1,47)]; el residir en área rural [OR 2,12 (1,91 - 2,36)]; el ser pobre [OR 2,30 (2,06 - 2,56)] y el tener alguna discapacidad [OR 2,63 (2,29 - 3,02)]. Conclusiones: La prevalencia de depresión en adultos mayores es sustancial. Los factores de riesgo identificados para la presencia de depresión en el adulto mayor, fueron la condición de mujer, ser mayor de 75 años, la carencia de instrucción, el vivir sin pareja, vivir en área rural, la pobreza y la discapacidad física.

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Prioritizing risk factors to identify preventive interventions for economic assessment

Cited by 11 publications

References 32 publications

Preventing mental illness: closing the evidence-practice gap through workforce and services planning

Preventing mental illness: closing the evidence-practice gap through workforce and services planning

Foods and Dietary Patterns That Are Healthy, Low-Cost, and Environmentally Sustainable: A Case Study of Optimization Modeling for New Zealand

Depresión y factores asociados en la población peruana adulta mayor según la ENDES 2014-2015

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