Subjective Well-Being Over The Life Course

一生的主观幸福感

• 批准号: 8535369
• 负责人: Martin Knapp
• 金额: $ 5.4万
• 依托单位: LONDON SCHOOL/ECONOMICS/POLITICAL SCI
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8535369
• 关键词: Achievement; Adult; Affect; Age; Attention; Bereavement; Birth; British; Caring; Child; Child Development; Cognitive; Cohort Studies; Collaborations; Complement component C1; Data; Emotional; Employment; Endowment; Epidemiologist; Expenditure; Family; Family Characteristics; Genetic; Health; Health Care Costs; Income; Intervention; Intervention Studies; Life; Life Cycle Stages; Link; Long-Term Effects; Longitudinal Surveys; Malaise; Measures; Modeling; Monozygotic twins; Norway; Personal Satisfaction; Persons; Policies; Policy Maker; Population Policies; Psychiatrist; Psychologist; Research; Retirement; Running; Savings; Shock; Simulate; Social Class; Social Welfare; Social support; Surveys; Sweden; Twin Multiple Birth; cohort; cost effective; evidence base; improved; interest; middle age; model development; physical conditioning; programs; satisfaction; social

DESCRIPTION (provided by applicant): To make evidence-based policy on well-being, policy-makers need information on what causes well- being and on how well-being affects their other objectives (e.g. physical health). Both needs could be satisfied if we had adequate causal models of the development of well-being, physical health etc over the life-course. Policy-makers could then use these models to help evaluate the long-term effects of different types of intervention at different ages - selecting those that gave the biggest improvement to well-being (or other objectives) per net dollar spent. (The model itself helps us to estimate the financial savings resulting from the expenditures.) To take forward this agenda we have four specific aims. Aim 1. Using standard birth cohort surveys, we shall estimate a path-model of well-being over the life course. There will be eight state variables: well-being; conduct/criminality; physical health; cognitive achievement; and (as adults) employment; welfare receipt; income; and family functioning. Each variable at each age will be regressed on previous values of all variables, background variables and on shocks. The British Cohort Study (BCS) and UK National Child Development Study (NCDS) will enable us to estimate these models up to middle age. But these data have the problem that one variable at age t may be related to the same variable at an earlier age (or another variable), without the relationship being causal. The two variables may be determined by a third omitted variable, including most obviously genetic endowment and other unmeasured characteristics of family background. Using identical twins reared together enables us to control for these. Aim 2. Using twin surveys from the UK, Norway and Sweden, we shall estimate similar models to before - once using the data on who is twinned with whom, and once not using it. This will give us a good idea about how far the models in (1) above overestimate the true causal links. (Twin data are not sufficient to replace the earlier data altogether.) Aim 3. Using surveys of ageing, we shall complement (1) with models covering the later years of life. The focus will be especially on how well-being affects physical health and vice versa. Attention will be paid to the moderating effects of social class and social support and to the impact of specific life transitions such as retirement and bereavement. The surveys used will be mainly the English Longitudinal Survey of Ageing, the Whitehall II study and the U.S. Health and Retirement Survey. Aim 4. Using data on well-being interventions, we shall show how these can be used together with the models already estimated to estimate the long-term benefits and savings from these interventions. Policy- makers will be increasingly interested in the long-term benefits from different possible well-being interventions (and in the savings which could result in reduced costs of health care, social care, criminality and so on). But many intervention studies only tell us the short-run effects. Long-term models can be used to simulate longer-term effects. (Where long-term follow-ups are available we can usefully compare the rate at which their effects fade with the rate of fading obtained from the models we estimate.) The measures of well-being used in these surveys vary but most include for adults life-satisfaction and malaise, and for children emotional well-being and conduct. One feature of the research will be the interaction between emotional well-being/malaise and conduct/criminality. The programme will be a fully-integrated collaboration between economists, psychologists, epidemiologists and psychiatrists.

描述（由申请人提供）：为了制定基于证据的福祉政策，决策者需要有关导致福祉以及福祉如何影响其其他目标（例如身体健康）的信息。如果我们在生命过程中有足够的因果，身体健康等的发展，可以满足两种需求。 然后，决策者可以使用这些模型来帮助评估不同年龄段的不同类型干预的长期影响 - 选择那些为每支净美元所花费的福祉（或其他目标）带来最大改善的干预措施。 （该模型本身有助于我们估计支出所产生的财务储蓄。）为了提出这一议程，我们有四个具体的目标。 AIM 1。使用标准的出生队列调查，我们将估计生活过程中幸福感的路径模型。将有八个州变量：幸福感；行为/犯罪；身体健康；认知成就； （成年人）就业；福利收据；收入;和家庭功能。每个年龄段的每个变量都会在所有变量，背景变量和冲击的先前值上进行回归。英国队列研究（BCS）和英国国家儿童发展研究（NCDS）将使我们能够估计这些模型到中年。但是这些数据的问题是，年龄t时的一个变量可能与较早年龄（或其他变量）的相同变量有关，而没有因果关系。这两个变量可以由第三个省略变量确定，包括最明显的遗传捐赠和家族背景的其他未衡量的特征。使用相同的双胞胎一起饲养，使我们能够控制这些。 AIM 2。使用来自英国，挪威和瑞典的双胞胎调查，我们将估计与以前类似的模型 - 一旦使用有关谁与谁进行孪生的数据，曾经使用过的数据。这将使我们有一个很好的了解（1）中的模型高估了真正的因果关系。 （双数据数据不足以完全替代早期的数据。）目标3。使用衰老调查，我们应与涵盖生命后期的模型进行补充（1）。重点将特别放在福祉如何影响身体健康，反之亦然。将注意社会阶层和社会支持的调节作用以及退休和丧亲之类的特定生活转变的影响。所使用的调查将主要是英国对衰老，Whitehall II研究和美国卫生与退休调查的纵向调查。 AIM 4。使用有关福祉干预措施的数据，我们将展示如何将它们与已经估计的模型一起使用，以估算这些干预措施中的长期收益和节省。政策制定者将越来越对来自不同可能的福祉干预措施的长期收益（以及节省的储蓄，这可能导致医疗保健，社会护理，犯罪等）。但是许多干预研究只会告诉我们短期影响。长期模型可用于模拟长期影响。 （如果有长期的随访，我们可以将其效果与从我们估计的模型中获得的褪色率进行比较。）这​​些调查中使用的幸福感测量的措施各不相同，但最适合成人的生活健康和不适，以及儿童的情感幸福感和行为。该研究的一个特征是情绪健康/不适与行为/犯罪性之间的相互作用。该计划将是经济学家，心理学家，流行病学家和精神科医生之间完全融合的合作。