Comparative and Cost-Effectiveness of Population Strategies to Improve Diet and Reduce Cancer
Comparative and Cost-Effectiveness of Population Strategies to Improve Diet and Reduce Cancer
批准号:
9360575
负责人:
Fang Fang Zhang
金额:
$48.03万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-27 至 2020-06-30
关键词:
AddressAdherenceAmericanBehavioralCancer BurdenCancer ModelCardiovascular DiseasesCause of DeathCessation of lifeCommunitiesCost AnalysisCost Effectiveness AnalysisDataDiagnosticDietDiet HabitsDietary FactorsDietary FiberDietary InterventionDietary intakeDisadvantagedEducationEffectivenessEffectiveness of InterventionsEligibility DeterminationEvaluationExpenditureFacilities and Administrative CostsFood LabelingGovernmentGrantHealth PolicyHealthcareIncentivesIncidenceIndividualIndustryInterventionInvestigationKnowledgeMalignant NeoplasmsMeatMedicalMethodsModelingMonte Carlo MethodMorbidity - disease rateOutcomePilot ProjectsPoliciesPolicy MakingPopulationPopulation InterventionPreventable cancer causePreventionPrevention strategyProcessed MeatsProductivityProgram EvaluationProtocols documentationQuality-Adjusted Life YearsRegulationResearchResourcesRisk AssessmentSodiumTaxationTherapeuticTimeWorkbaseburden of illnesscancer carecancer health disparitycancer preventioncomparativecomparative cost effectivenesscomparative effectivenesscompare effectivenesscostcost effectivecost effectivenesscost-effectiveness evaluationdiet and cancerdisability-adjusted life yearsevidence basefruits and vegetablesimplementation trialimprovedincremental cost-effectivenesslow socioeconomic statusmarkov modelmembermodel buildingmortalitynovelnutritionpopulation basedprematurepreventprogramssugarsweetened beveragesystematic reviewyears of life lost
中文摘要
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Project Summary
Cancer is a leading cause of death in the US. Research has demonstrated that poor dietary habits are a
major preventable cause of cancer. Americans are burdened by suboptimal dietary intake. Improving diet is
clearly a priority for reducing burdens of cancer in the US. Unfortunately, the optimal strategies to improve diet
and reduce cancer are not clear. While various individual-level behavioral change approaches can be effective
for some people, overall benefits and long-term adherence may be modest and overall benefits poorly
sustained. In contrast, population-based strategies can be more powerful and sustainable, and achieve
broader impact. We have systematically reviewed and synthesized the evidence-base for effects of various
population interventions on dietary intake and identified several strategies with the strongest evidence-base.
However, the effectiveness of these strategies on reducing cancer burden has not been quantified. In addition,
the cost for implementing these strategies is largely unknown; and the cost-effectiveness of implementing
these interventions has not been established. To address these major gaps in knowledge, we have selected
population-based strategies to improve specific dietary targets that have the strongest evidence for effects on
cancer incidence, in the realms of (1) media/education, (2) food labeling/information, (3) taxation/subsidies,
and (4) regulations/quality standards. We will develop two population-based models: (a) a Comparative Risk
Assessment (CRA) model; and (b) a health policy state transition Markov model with Monte Carlo simulation,
the Diet Cancer Outcome Model (DiCOM), to quantify and compare the effectiveness of these interventions by
estimating the numbers of cancer incidence and deaths reduced, disability-adjusted life years (DALYs)
averted, and quality-adjusted life years (QALYs) gained in the US population, with projections over 5, 10, 15,
and 20 years. Second, we will develop costing protocols to estimate the cost of implementing specific
population-based dietary interventions from a societal perspective, and subsequently assess the cost-
effectiveness of the interventions by calculating the incremental cost-effectiveness ratio (ICER) per QALY
gained. We will further evaluate the impact of implementing population-based dietary interventions to reduce
cancer disparities in disadvantaged groups as exploratory analyses. The robustness of estimates will be
assessed with extensive sensitivity analyses to varying assumptions on model parameters and assumptions.
This study will provide, for the first time, the effectiveness estimates of well-defined population strategies to
improve targeted dietary factors and reduce cancer burden in the US, which are crucial to informing dietary
healthy policy making and evidence-based cancer prevention efforts.
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