Experimental evidence on the relationship between income and health
Experimental evidence on the relationship between income and health
批准号:
10587123
负责人:
Alexander Wickman Bartik
金额:
$60.26万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-15 至 2028-04-30
关键词:
AdultAffectAftercareAnxietyAutomobile DrivingBehaviorBiological MarkersBloodBlood GlucoseBlood PressureC-reactive proteinCOVID-19 pandemicCaringCharacteristicsCholesterolCitiesCommutingConsentControl GroupsCountryDiseaseEconomicsEducationEligibility DeterminationEmergency department visitEnvironmentEnvironmental Risk FactorEvaluationExerciseFoodGlycosylated HemoglobinHealthHealth BenefitHealth Services AccessibilityHealth behaviorHealthcareHeightHospitalizationHousingIncidenceIncomeIndividualInterventionLifeLinkLongterm Follow-upLow incomeMeasuresMedicalMental DepressionMental HealthNational Health Interview SurveyNatureNeighborhoodsNonprofit OrganizationsNutritionalOutcomeOutcome AssessmentOutcome MeasureParticipantPersonal SatisfactionPersonsPhysical activityPoliciesPolicy MakerPreventive careProxyPublic HealthRandom AllocationRandomizedRandomized, Controlled TrialsRecordsReportingResearchResearch SupportRoleSamplingServicesSleepSocial SciencesSpottingsStressSurveysTimeTrainingVariantWeightWorkcoronavirus diseasediabetes riskdiariesfood securityhealth knowledgeimprovedmortalitynutritionpaymentphysical conditioningpopulation healthpoverty alleviationprofessional atmosphereprogramssleep qualitysubstance usetooltreatment group
中文摘要
项目摘要
健康和收入之间的相关性是社会科学中最持久的观察结果之一,
支持跨国家,人口群体和时间段的研究。的关系
收入和健康的影响很大,出现在生命的早期,并且存在于许多被视为代表的指标中
健康尽管这种关联具有惊人的性质,但在美国背景下,
收入是否对健康结果有因果影响,关于可能影响健康的机制的信息较少。
如果存在这种因果关系的话。收入和健康可能相关,因为
收入对健康有直接影响(例如,通过允许个人购买医疗保健),或健康可能
直接影响收入(例如,因为健康状况不佳,工作很困难)。也可能是第三个
教育等因素影响收入和健康,推动了观察到的收入与健康之间的相关性。
变量如果没有能力使收入变化随机化,那么辨别这种关系的真实性质是很困难的。
难我们建议从美国的一项大规模随机干预中提供新的证据,
收入与身心健康之间的关系,通过对一个持续的
两个非营利组织正在实施无条件现金转移方案。此程序将
将参与者随机分配到每月接受1,000美元的治疗组或对照组,
收到50美元。这两个群体将在三年内每月获得转移。我们将研究治疗/控制
差异以估计额外收入对行为和环境因素的影响(例如,
营养、食品安全、锻炼、物质使用、睡眠质量和邻里特征),
影响长期健康结果(目标1)和医疗服务的获得和利用(目标2)。为了
为了了解收入增加对健康的影响,我们将评估治疗/控制差异,
身体和精神健康的主观测量以及血压,身高,体重和血斑,
可以分析以提供胆固醇、A1c(指示糖尿病风险的糖化血红蛋白的量度)和
C-反应蛋白(Aim 3)。我们将结合以下因素来衡量与这些目标相关的成果:
个人和在线调查问题、营养日记(ASA 24)、时间日记和亲自收集的生物标志物
由受过训练的统计员进行。我们还将在付款结束后进行长期跟踪。本研究将
提供关于收入对健康,健康行为,
和幸福
英文摘要
Project Summary
The correlation between health and income is one of the most persistent observations in the social sciences,
supported by research across countries, demographic groups, and time periods. The relationship between
income and health is large, emerges early in life, and is present across many indicators considered proxies for
health. Despite the striking nature of the association, there is relatively little evidence in the U.S. context on
whether income has a causal impact on health outcomes, and less information on what mechanisms may be
responsible for such a causal relationship if one exists. Income and health may be correlated because higher
income has a direct impact on health (e.g., by allowing individuals to purchase medical care), or health may
directly affect income (e.g., because poor health makes it difficult to work). It may also be the case that a third
factor—such as education—influences both income and health, driving the observed correlation between the
variables. Without the ability to randomize variation in income, discerning the true nature of this relationship is
difficult. We propose to provide new evidence from a large-scale, randomized intervention in the U.S. on the
relationship between income and mental and physical health through a randomized evaluation of a sustained
unconditional cash transfer program being implemented by two non-profit organizations. This program will
randomly assign participants to a treatment group that receives $1,000 per month or to a control group that
receives $50. Both groups will receive the transfer monthly for three years. We will examine treatment/control
differences to estimate the effect of the additional income on behaviors and environmental factors (e.g.,
nutrition, food security, exercise, substance use, sleep quality, and neighborhood characteristics) that could
affect longer-term health outcomes (Aim 1) and on medical care access and utilization (Aim 2). In order to
understand the effect of the increase in income on health, we will assess treatment/control differences in
subjective measures of physical and mental health as well as blood pressure, height, weight, and blood spots that
can be analyzed to provide cholesterol, A1c (a measure of glycated hemoglobin that indicates diabetes risk), and
C-reactive protein (Aim 3). We will measure the outcomes associated with these aims using a combination of in
person and online survey questions, nutrition diaries (ASA 24), time diaries, and biomarkers collected in person
by trained enumerators. We will also conduct long term follow up after the end of the payments. This study will
provide groundbreaking, policy-relevant new information on the impact of income on health, healthy behaviors,
and well-being.
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