There is a strong link between mental health and physical health, but little is known about the pathways from one to the other. We analyse the direct and indirect effects of past mental health on present physical health and past physical health on present mental health using lifestyle choices and social capital in a mediation framework. We use data on 10,693 individuals aged 50 years and over from six waves (2002-2012) of the English Longitudinal Study of Ageing. Mental health is measured by the Centre for Epidemiological Studies Depression Scale (CES) and physical health by the Activities of Daily Living (ADL). We find significant direct and indirect effects for both forms of health, with indirect effects explaining 10% of the effect of past mental health on physical health and 8% of the effect of past physical health on mental health. Physical activity is the largest contributor to the indirect effects. There are stronger indirect effects for males in mental health (9.9%) and for older age groups in mental health (13.6%) and in physical health (12.6%). Health policies aiming at changing physical and mental health need to consider not only the direct cross-effects but also the indirect cross-effects between mental health and physical health.
Mental and physical aspects are both integral to health but little is known about the dynamic relationship between them. We consider the dynamic relationship between mental and physical health using a sample of 11,203 individuals in six waves (2002–2013) of the English Longitudinal Study of Ageing (ELSA). We estimate conditional linear and non-linear random-effects regression models to identify the effects of past physical health, measured by Activities of Daily Living (ADL), and past mental health, measured by the Centre for Epidemiological Studies Depression (CES-D) scale, on both present physical and mental health. We find that both mental and physical health are moderately state-dependent. Better past mental health increases present physical health significantly. Better past physical health has a larger effect on present mental health. Past mental health has stronger effects on present physical health than physical activity or education. It explains 2.0% of the unobserved heterogeneity in physical health. Past physical health has stronger effects on present mental health than health investments, income or education. It explains 0.4% of the unobserved heterogeneity in mental health. These cross-effects suggest that health policies aimed at specific aspects of health should consider potential spill-over effects.
There is a gap in the literature in understanding how cash transfer programmes affect mental health. We aim to fill this gap by conceptualising and estimating the mediation effects of an unconditional cash transfer programme on mental health. We use a sample of 4,535 adults living below the South African poverty line in four waves (2008–2014) of the South African National Income Dynamics Study. We use information on individual exposure to South Africa's largest unconditional cash transfer programme, the Child Support Grant. Mental health is measured by the 10-item version of the Centre for Epidemiological Depression Scale. We use the product of the coefficient method for the mediation analysis in combination with instrumental variable estimation. We find that physical health and lifestyle factors mediate the relationship of the unconditional cash transfer programme, each explaining about eight percent and 16% of the total positive effect. Our findings show that individuals living in poverty make investment decisions that are positive for their mental health, which has strong implications for policy makers.
Introduction: The Short Form Survey 12-item (SF12) mental and physical health version has been applied in several studies on populations from Sub-Saharan Africa. However, the SF12 has not been computed and validated for these populations. We address in this paper these gaps in the literature and use a health intervention example in Malawi to show the importance of our analysis for health policy. Methods: We firstly compute the weights of the SF12 physical and mental health measure for the Malawian population using principal component analysis on a sample of 2838 adults from wave four (2006) of Malawian Longitudinal Study of Aging (MLSFH). We secondly test the construct validity of our computed and the USpopulation weighted SF12 measures using regression analysis and Fixed Effect estimation on waves four, seven (2012) and eight (2013) of the MLSFH. Finally, we use a Malawian cash transfer programme to exemplify the implications of using US-and Malawi-weighted SF12 mental health measures in policy evaluation. Results: We find that the Malawian SF12 health measure weighted by our computed Malawian population weights is strongly associated with other mental health measures (Depression:-0.501, p = < 0.001; Anxiety:-1.755; p = < 0.001) and shows better construct validity in comparison to the US-weighted SF12 mental health component (rs = 0.675 versus rs = 0.495). None of the SF12 measures shows strong associations with other measures of physical health. The estimated average effect of the cash transfer is significant when using the Malawi-weighted SF12 mental health measure (treatment effect: 1.124; p = < 0.1), but not when using the US-weighted counterpart (treatment effect: 1.129; p > 0.1). The weightings affect the size of the impacts across mental health quantiles suggesting that the weighting scheme matters for empirical health policy analysis. Conclusion: Mental health shows more pronounced associations with the physical health dimension in a Low-Income Country like Malawi compared to the US. This is important for the construct validity of the SF12 health measures and has strong implications in health policy analysis. Further analysis is required for the physical health dimension of the SF12.
Background: Mental health and poverty are strongly interlinked. There is a gap in the literature on the effects of poverty alleviation programmes on mental health. We aim to fill this gap by studying the effect of an exogenous income shock generated by the Child Support Grant, South Africa's largest Unconditional Cash Transfer (UCT) programme, on mental health. Methods: We use biennial data on 10,925 individuals from the National Income Dynamics Study between 2008 and 2014. We exploit the programme's eligibility criteria to estimate instrumental variable Fixed Effects models. Results: We find that receiving the Child Support Grant improves adult mental health by 0.822 points (on a 0-30 scale), 4.1% of the sample mean. Conclusion: Our findings show that UCT programmes have strong mental health benefits for the poor adult population.
Poor mental health is a pressing global health problem, with high prevalence among poor populations from low-income countries. Existing studies of conditional cash transfer (CCT) effects on mental health have found positive effects. However, there is a gap in the literature on population-wide effects of cash transfers on mental health and if and how these vary by the severity of mental illness. We use the Malawian Longitudinal Study of Family and Health containing 790 adult participants in the Malawi Incentive Programme, a year-long randomized controlled trial. We estimate average and distributional quantile treatment effects and we examine how these effects vary by gender, HIV status and usage of the cash transfer. We find that the cash transfer improves mental health on average by 0.1 of a standard deviation. The effect varies strongly along the mental health distribution, with a positive effect for individuals with worst mental health of about four times the size of the average effect. These improvements in mental health are associated with increases in consumption expenditures and expenditures related to economic productivity. Our results show that CCTs can improve adult mental health for the poor living in low-income countries, particularly those with the worst mental health.
Background In response to the COVID-19 pandemic, governments across the globe have imposed strict social distancing measures. Public compliance to such measures is essential for their success yet the economic consequences of compliance are unknown. This is the first study to analyse the effects of good compliance compared to poor compliance to a COVID-19 suppression strategy (i.e. lockdown) on work productivity. Methods We estimate the differences in work productivity comparing a scenario of good compliance with one of poor compliance to the UK government COVID-19 suppression strategy. We use projections of the impact of the UK suppression strategy on mortality and morbidity from an individual-based epidemiological model combined with an economic model representative of the labour force in Wales and England. Results We find that productivity effects of good compliance significantly exceed those of poor compliance and increase with the duration of the lockdown. After three months of the lockdown, work productivity in good compliance is £398.58 million higher compared with that of poor compliance. 75% of the differences is explained by productivity effects due to morbidity and non-health reasons and 25% attributed to avoided losses due to pre-mature mortality. Conclusion Good compliance to social distancing measures exceeds positive economic effects, in addition to health benefits. This is an important finding for current economic and health policy. It highlights the importance to set clear guidelines for the public, to build trust and support for the rules and if necessary, to enforce good compliance to social distancing measures.
BackgroundOver the past decade, targeting acute kidney injury (AKI) has become a priority to improve patient safety and health outcomes. Illness complicated by AKI is common and is associated with adverse outcomes including high rates of unplanned hospital readmission. Through national patient safety directives, NHS England has mandated the implementation of an AKI clinical decision support system in hospitals. In order to improve care following AKI, hospitals have also been incentivised to improve discharge summaries and general practices are recommended to establish registers of people who have had an episode of illness complicated by AKI. However, to date, there is limited evidence surrounding the development and impact of interventions following AKI.DesignWe conducted a quality improvement project in primary care aiming to improve the management of patients following an episode of hospital care complicated by AKI. All 31 general practices within a single NHS Clinical Commissioning Group were incentivised by a locally commissioned service to engage in audit and feedback, education training and to develop an action plan at each practice to improve management of AKI.ResultsAKI coding in general practice increased from 28% of cases in 2015/2016 to 50% in 2017/2018. Coding of AKI was associated with significant improvements in downstream patient management in terms of conducting a medication review within 1 month of hospital discharge, monitoring kidney function within 3 months and providing written information about AKI to patients. However, there was no effect on unplanned hospitalisation and mortality.ConclusionThe findings suggest that the quality improvement intervention successfully engaged a primary care workforce in AKI-related care, but that a higher intensity intervention is likely to be required to improve health outcomes. Development of a real-time audit tool is necessary to better understand and minimise the impact of the high mortality rate following AKI.
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