Re: Lies, damned lies, and health inequality measurements: understanding the value judgments

No abstract available

Leaving the labour market later in life. How does it impact on mechanisms for health?

Objectives: Negative associations between non-employment and health among older people are well established and are potentially important for successful ageing. However, opportunities to improve health through re-employment or extending working lives are limited as later-life exits from employment are often unwanted and permanent. We aim to establish a greater understanding of the psychosocial mechanisms underlying non-employment and health associations in older people to identify modifiable pathways through which the negative impact of non-employment can be ameliorated. Methods: Using multilevel analysis of four waves of repeated panel data from a representative sample of 1551 older men and women reaching state retirement age in the West of Scotland from 1987/1988 to 2000/2004, we explored respondents' strength of agreement with 20 statements relating to their self-defined employment status, covering themes of functioning, social engagement, self-esteem, mental engagement, stress, and control and autonomy. Results: Compared with those in employment, respondents who were retired, unemployed, sick/disabled and home makers were more likely to agree that this resulted in poor social engagement, low self-esteem and, with the possible exception of retirees, reduced mental engagement. Associations were particularly marked among unemployed and sick/disabled respondents who also agreed that their status was a source of worry and prevented them from feeling in control. Conclusion: Older people who are not in employment are at higher risk of poor physical and mental health. Interventions targeting psychosocial mechanisms such as social and mental engagement and self-esteem offer potentially valuable opportunities to improve health outcomes and promote successful ageing

Selecting surface features for accurate multi-camera surface reconstruction

This paper proposes a novel feature detector for selecting local textures that are suitable for accurate multi-camera surface reconstruction, and in particular planar patch fitting techniques. This approach is in contrast to conventional feature detectors, which focus on repeatability under scale and affine transformations rather than suitability for multi-camera reconstruction techniques. The proposed detector selects local textures that are sensitive to affine transformations, which is a fundamental requirement for accurate patch fitting. The proposed detector is evaluated against the SIFT detector on a synthetic dataset and the fitted patches are compared against ground truth. The experiments show that patches originating from the proposed detector are fitted more accurately to the visible surfaces than those originating from SIFT keypoints. In addition, the detector is evaluated on a performance capture studio dataset to show the real-world application of the proposed detector

The impact on health of employment and welfare transitions for those receiving out-of-work disability benefits in the UK

Employment status has a dynamic relationship with health and disability. There has been a striking increase in the working age population receiving out-of-work disability benefits in many countries, including the UK. In response, recent UK welfare reforms have tightened eligibility criteria and introduced new conditions for benefit receipt linked to participation in return-to-work activities. Positive and negative impacts have been suggested but there is a lack of high quality evidence of the health impact when those receiving disability benefits move towards labour market participation. Using four waves of the UK’s Understanding Society panel survey (2009–2013) three different types of employment and welfare transition were analysed in order to identify their impact on health. A difference-in-difference approach was used to compare change between treatment and control groups in mental and physical health using the SF-12. To strengthen causal inference, sensitivity checks for common trends used pre-baseline data and propensity score matching. Transitions from disability benefits to employment (n = 124) were associated on average with an improvement in the SF12 mental health score of 5.94 points (95% CI = 3.52–8.36), and an improvement in the physical health score of 2.83 points (95% CI = 0.85–4.81) compared with those remaining on disability benefits (n = 1545). Transitions to unemployed status (n = 153) were associated with a significant improvement in mental health (3.14, 95% CI = 1.17–5.11) but not physical health. No health differences were detected for those who moved on to the new out-of-work disability benefit. It remains rare for disability benefit recipients to return to the labour market, but our results indicate that for those that do, such transitions may improve health, particularly mental health. Understanding the mechanisms behind this relationship will be important for informing policies to ensure both work and welfare are ‘good for health’ for this group

Multi-frame scene-flow estimation using a patch model and smooth motion prior

This paper addresses the problem of estimating the dense 3D motion of a scene over several frames using a set of calibrated cameras. Most current 3D motion estimation techniques are limited to estimating the motion over a single frame, unless a strong prior model of the scene (such as a skeleton) is introduced. Estimating the 3D motion of a general scene is difficult due to untextured surfaces, complex movements and occlusions. In this paper, we show that it is possible to track the surfaces of a scene over several frames, by introducing an effective prior on the scene motion. Experimental results show that the proposed method estimates the dense scene-flow over multiple frames, without the need for multiple-view reconstructions at every frame. Furthermore, the accuracy of the proposed method is demonstrated by comparing the estimated motion against a ground truth

Trends in population mental health before and after the 2008 recession: a repeat cross-sectional analysis of the 1991-2010 health surveys of England

<p>Objective: To assess short-term differences in population mental health before and after the 2008 recession and explore how and why these changes differ by gender, age and socio-economic position.</p> <p>Design: Repeat cross-sectional analysis of survey data.</p> <p>Setting: England.</p> <p>Participants: Representative samples of the working age (25–64 years) general population participating in the Health Survey for England between 1991 and 2010 inclusive.</p> <p>Main outcome measures: Prevalence of poor mental health (caseness) as measured by the general health questionnaire-12 (GHQ).</p> <p>Results: Age–sex standardised prevalence of GHQ caseness increased from 13.7% (95% CI 12.9% to 14.5%) in 2008 to 16.4% (95% CI 14.9% to 17.9%) in 2009 and 15.5% (95% CI 14.4% to 16.7%) in 2010. Women had a consistently greater prevalence since 1991 until the current recession. However, compared to 2008, men experienced an increase in age-adjusted caseness of 5.1% (95% CI 2.6% to 7.6%, p<0.001) in 2009 and 3% (95% CI 1.2% to 4.9%, p=0.001) in 2010, while no statistically significant changes were seen in women. Adjustment for differences in employment status and education level did not account for the observed increase in men nor did they explain the differential gender patterning. Over the last decade, socio-economic inequalities showed a tendency to increase but no clear evidence for an increase in inequalities associated with the recession was found. Similarly, no evidence was found for a differential effect between age groups.</p> <p>Conclusions: Population mental health in men has deteriorated within 2 years of the onset of the current recession. These changes, and their patterning by gender, could not be accounted for by differences in employment status. Further work is needed to monitor recessionary impacts on health inequalities in response to ongoing labour market and social policy changes.</p&gt

Employment status and income as potential mediators of educational inequalities in population mental health

We assessed whether educational inequalities in mental health may be mediated by employment status and household income. Poor mental health was assessed using General Health Questionnaire ‘caseness’ in working age adult participants (N = 48 654) of the Health Survey for England (2001–10). Relative indices of inequality by education level were calculated. Substantial inequalities were apparent, with adjustment for employment status and household income markedly reducing their magnitude. Educational inequalities in mental health were attenuated by employment status. Policy responses to economic recession (such as active labour market interventions) might reduce mental health inequalities but longitudinal research is needed to exclude reverse causation