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There is sparse evidence on the impact of health information on mental health as well as on the mechanisms governing this relationship. We estimate the causal impact of health information on mental health via the effect of a diabetes diagnosis on depression. We employ a fuzzy regression discontinuity design (RDD) exploiting the exogenous cut-off value in the diagnosis of type-2 diabetes provided by a biomarker (glycated haemoglobin) and information on diagnosed clinical depression drawn from rich administrative longitudinal data from Spain. We find that overall a type-2 diabetes diagnosis increases the probability of becoming depressed, however this effect appears to be driven mostly by women. Results also appear to differ by changes in lifestyle induced by the diabetes diagnosis: while women who did not lose weight are more likely to develop depression, men who did lose weight present a reduced probability of being depressed. Results are robust to alternative parametric and non-parametric specifications and placebo tests.

We estimate short- and long-term causal impacts of a type-2 diabetes mellitus (T2DM) diagnosis on lifestyle behaviours. We employ a fuzzy regression discontinuity design exploiting the exogenous cut-off value in the diagnosis of T2DM provided by a biomarker (glycated haemoglobin, HbA1c). We make use of unique administrative longitudinal data from Spain and focus on the impact of a diagnosis on clinically measured BMI, smoking and alcohol consumption. We find that, following a T2DM diagnosis, individuals appear to reduce their weight in the short-term. These effects are particularly large among obese individuals and those diagnosed with depression. Patients who are younger, still in the labour market and healthier also present increased short-term probabilities of quitting smoking. In addition, we provide evidence of statistically significant long-term impacts of a T2DM diagnosis on BMI up to three years from the diagnosis. Our results are consistent across parametric and non-parametric estimations with varying bandwidths. Overall, our findings suggest the relevance of health information in affecting changes in key lifestyle behaviours.

We explore the effects of retirement on both physical and mental ill-health and whether these change in the presence of economic shocks. We employ inverse probability weighting regression adjustment to examine the mechanisms influencing the relationship between retirement and health and a difference-in-differences approach combined with matching to investigate whether the health effects of retirement are affected by the Great Recession. We estimate these models on data drawn from the English Longitudinal Study of Ageing (ELSA) and find that retirement leads to a deterioration in both mental and physical health, however there seems to be considerable effect heterogeneity by gender and occupational status. Our findings also suggest that retiring shortly after the Great Recession appears to improve mental and physical health, although only among individuals working in the most affected regions. Overall, our results indicate that the health effects of retirement might be influenced by the presence of economic shocks.

We explore the relationship between high school dropout and pupils' adult crime by accounting for the role of the intergenerational transmission of crime. We employ a human capital model of schooling and crime and show that the intergenerational transmission of crime could have a direct effect on adult crime as well as an indirect effect mediated by high school dropout. We empirically assess the relevance of these relationships using fixed effects linear probability models and inverse probability weighting regression adjustment on US data from the National Longitudinal Study of Adolescent to Adult Health. We find that dropping out from high school and having a convicted father increase the probability of adult crime, with the former presenting a larger effect. Our empirical models also suggest that having a convicted father increases the probability of dropping out from school. This reveals that paternal crime imposes a double penalty on children: it increases their probability of committing crimes later on in life both directly and indirectly via school dropout. When considering the role of the environment, we find that while an early exposure to high levels of crime exacerbates dropping out, it has no direct long-term effect on adult crime. Finally, we show that individual traits may also play a role, as pupils with lower levels of cognitive skills present higher probabilities of adult criminal behaviour and stronger intergenerational effects.

Table S1. Search strategy. (DOCX 14 kb)

Although uncontrolled diabetes (UD) or poor glycaemic control is a widespread condition with potentially life‐threatening consequences, there is sparse evidence of its effects on health care utilisation. We jointly model the propensities to consume health care and UD by employing an innovative bivariate latent Markov model that allows for dynamic unobserved heterogeneity, movements between latent states and the endogeneity of UD. We estimate the effects of UD on primary and secondary health care consumption using a panel dataset of rich administrative records from Spain and measure UD using a biomarker. We find that, conditional on time‐varying unobservables, UD does not have a statistically significant direct effect on health care use (...)

Background Hypertension is the leading driver of cardiovascular disease deaths in Africa. Its prevalence is highest in older populations. Yet, this group has received little attention in many African countries. We conducted a systematic review and meta-analysis (PROSPERO registration: CRD42017056474) to estimate the prevalence of hypertension in older adults living in Africa. Methods We searched grey literature and major electronic databases including PubMed and Embase for population-based studies and published between 1 January 1980 to 28 May 2018 reporting the prevalence of hypertension for adults aged > 50 years living in Africa. We employed a random effects model to estimate the pooled prevalence across included studies. Findings We screened 10,719 articles and retrieved 103 full-text articles to evaluate for inclusion in the review. Thirty-four unique studies providing 37 data points on 43,025 individuals in 15 African countries were analyzed. The prevalence of hypertension ranged from 22.3% to 90.0% from the individual studies while the overall pooled prevalence was 57.0% (95% CI 52%-61%). The prevalence was not statistically significantly different by sex, residence, or African sub-region. In individual studies, older age and overweight/obesity were independently associated with hypertension. Twenty-nine (78%) data points were deemed to be of low- or moderate-risk of bias. Eliminating high-risk bias studies made little difference to the pooled estimate of hypertension. Sensitivity analyses, omitting one study at a time, identified three studies with significant but relatively small impact on the pooled estimate. We observed substantial heterogeneity (I2 = 98.9%) across the studies which was further explored by meta-regression analyses. Overall, the GRADE assessment suggested moderate quality evidence in the results. Conclusion The persistent high prevalence of hypertension among older adults in Africa, even in rural populations warrants more attention to the cardiovascular health of this group by public health authorities

Table S2. Evaluation of risk of bias from primary studies on hypertension in older adults in Africa. (DOCX 16 kb)

While uncontrolled diabetes (UD) or poor glycaemic control is a widespread condition with potentially life-threatening consequences, there is sparse evidence of its effects on health care utilisation. We model the propensities to consume health care and UD by employing an innovative bivariate Latent Markov model which allows for dynamic unobserved heterogeneity, movements between latent states and the endogeneity of UD. We estimate the effects of UD on primary and secondary health care consumption using a panel dataset of rich administrative records from Spain and measure UD using a biomarker. We find that UD does not have a statistically significant effect on health care use. Furthermore, individuals appear to move across latent classes and increase their propensities to poor glycaemic control and health care use over time. Our results suggest that by ignoring time-varying unobserved heterogeneity and the endogeneity of UD, the effects of UD on health care utilisation might be overestimated and this could lead to biased findings. Our approach reveals heterogeneity in behaviour beyond standard groupings of frequent versus infrequent users of health care services. We argue that this dynamic latent Markov approach could be used more widely to model the determinants of health care use.

While uncontrolled diabetes (UD) or poor glycaemic control is a widespread condition with potentially life-threatening consequences, there is sparse evidence of its effects on health care utilisation. We model the propensities to consume health care and UD by employing an innovative bivariate Latent Markov model which allows for dynamic unobserved heterogeneity, movements between latent states and the endogeneity of UD. We estimate the effects of UD on primary and secondary Health care consumption using a panel dataset of rich administrative records from Spain and measure UD using a biomarker. We find that UD does not have a statistically significant effect on health care use. Furthermore, individuals appear to move across latent classes and increase their propensities to poor glycaemic control and health care use over time. Our results suggest that by ignoring time-varying unobserved heterogeneity and the endogeneity of UD, the effects of UD on health care utilisation might be overestimated and this could lead to biased findings. Our approach reveals heterogeneity in behaviour beyond standard groupings of frequent versus infreqüent users of health care services. We argue that this dynamic latent Markov approach could be used more widely to model the determinants of health care use.

Data extraction form HTN protocol. Data extraction form for studies on the prevalence of hypertension in older adults in Africa. Contains the data extraction form. (DOCX 38Â kb)

PRISMA-P 2015 checklist 01 08 2017. Description of data: Contains the line numbers for the different items on the PRISMA-P checklist. (DOCX 33Â kb)

Despite size and relevance of non-adherence to health treatments, robust evidence on its effects on health care utilisation is very limited. We focus on non-adherence to diabetes treatments, a widespread problem, and employ longitudinal administrative data from Spain (2004-2010) to identify and quantify the effects of uncontrolled type 2 diabetes on health care utilisation. We use a biomarker (glycated haemoglobin, HbA1c) to detect the presence of uncontrolled diabetes and explore its effects on both primary and secondary health care. We estimate a range of panel count data models, including negative binomials with random effects, dynamic and hurdle specifications to account for unobserved heterogeneity, previous utilisation and selection. We find uncontrolled diabetes in around 30% of patients of both genders. Although women appear to systematically consume more health care compared to men, their consumption levels do not appear to be influenced by uncontrolled diabetes. Conversely, among men uncontrolled diabetes increases the average number of GP visits per year by around 4%, specialist visits by 4.4% and greatly extends hospital length of stay.

Recent studies on the effects of anti-smoking policies on subjective well-being present mixed results and focus mainly on smokers. We contribute to the literature by exploiting the policy experiment provided by the UK public smoking bans and evaluating the impact of smoking bans on the subjective well-being of smokers, non-smokers and couples of different types of smokers. We employ matching techniques combined with flexible difference-in-differences fixed effects panel data models on data from the British Household Panel Survey. We find that the UK public smoking bans appear to have a statistically significant short-term positive impact on the well-being of married individuals, especially among couples with dependent children. These effects appear to be substantial in size, robust to alternative specifications and may be driven by positive externalities due to parental altruism.

High school dropout is an important policy issue and its determinants are a longstanding interest of economics. However, very little is known on the roles of noncognitive traits in influencing school dropout decisions. We employ voluntary forgone health care as a proxy for the underlying noncognitive traits that may induce adolescents to dropout and estimate its effects on early school attrition. We exploit data from the US National Longitudinal Study of Adolescent to Adult Health (Add Health) and employ a series of flexible specifications with school fixed effects and cohort effects. Our models account for well-established determinants of dropout, including individual and parental characteristics, together with personality traits. Forgone health care consistently appears to be a statistically significant and substantial predictor of dropout among adolescents. We suggest that forgone health care could be used as a signaling device for policy makers targeting potential high school dropouts.