Too Much of a Good Thing? Exploring the Impact of Wealth on Weight.

Obesity, like many health conditions, is more prevalent among the socioeconomically disadvantaged. In our data, very poor women are three times more likely to be obese and five times more likely to be severely obese than rich women. Despite this strong correlation, it remains unclear whether higher wealth causes lower obesity. In this paper, we use nationally representative panel data and exogenous wealth shocks (primarily inheritances and lottery wins) to shed light on this issue. Our estimates show that wealth improvements increase weight for women, but not men. This effect differs by initial wealth and weight-an average-sized wealth shock received by initially poor and obese women is estimated to increase weight by almost 10 lb. Importantly, for some females, the effects appear permanent. We also find that a change in diet is the most likely explanation for the weight gain. Overall, the results suggest that additional wealth may exacerbate rather than alleviate weight problems.

Self-assessed health: what does it mean and what does it hide?

Self-assessed general health (SAH) is one of the most frequently employed health measures in social science research. Its generic nature means it captures elements of health that more guided measures cannot, and its brevity makes it possible for health information to be included in crowded multifaceted surveys. However, a shortcoming of SAH is that it provides little guidance to researchers as to what individuals are thinking of when they assess their health - when a survey respondent reports that their health is "poor", is it because they are in pain, tired, depressed, unable to climb stairs, or something else entirely? This limits the possible inference from empirical research. It also means that important determinants and consequences of health can be missed if they are only weakly reflected in SAH. Given the continued use of SAH, it is important to better understand its structure. In this paper we use household panel data from Australia to answer two related questions: (i) what components of health does SAH most strongly represent? and (ii) does the use of SAH conceal important health effects? To answer the first question, we use a detailed health instrument and take a rigorous econometric approach to identify the health dimensions most strongly reflected in SAH. To answer the second question, we estimate the causal effects of income on SAH and on disaggregated health measures using instrumental-variables models. We find that some health dimensions - especially vitality - are consistently important to an individual when they assess their health, while other dimensions are inconsequential. We demonstrate that this fact provides insight in to why some studies find weak income gradients in SAH. Instrumental-variable regression results show that shocks to household income have no effect on SAH, but strongly improve several dimensions of health that are less commonly measured.

Anchoring vignettes for health comparisons: an analysis of response consistency.

PURPOSE: Self-rated health (SRH) is widely used to measure and compare the health status of different groups of individuals. However, SRH can suffer from heterogeneity in reporting styles, making health comparisons problematic. Anchoring vignettes is a promising technique for improving inter-group comparisons of SRH. A key identifying assumption of the approach is response consistency-that respondents rate themselves using the same underlying response scale that they rate the vignettes. Despite growing research into response consistency, it remains unclear how respondents rate vignettes and why respondents may not assess vignettes and themselves consistently. METHOD: Vignettes for the EQ-5D-5L were developed and included in an online survey. In-depth interviews were conducted with participants following survey completion. Response consistency was examined through qualitative analysis of the interview responses and quantitative coding of participants' thought processes. RESULTS: Our analysis showed that anchoring vignettes for the EQ-5D-5L is feasible, but that response consistency may not hold for some participants. Respondents are more likely to rate their own health and vignettes in the same way if presented with overall health state vignettes than single health dimension vignettes, and if they imagined themselves in the health state of the hypothetical individual. CONCLUSION: This research highlights opportunities to improve the design of anchoring vignettes in order to enhance response consistency. It additionally provides new evidence on the feasibility of employing anchoring vignettes for the EQ-5D-5L, which is promising for future work to address reporting heterogeneity in the EQ-5D-5L.

The health care cost implications of overweight and obesity during childhood.

OBJECTIVE: To investigate whether childhood overweight at age 4-5 increases publicly funded health care costs during childhood, and to explore the role of timing and duration of overweight on health costs. DATA SOURCES: The Longitudinal Study of Australian Children (2004-2008) and linked records from Medicare, Australia's public health insurance provider (2004-2009). STUDY DESIGN: The influence of overweight status on non-hospital Medicare costs incurred by children over a 5-year period was estimated using two-part models and one-part generalized linear models (GLM). All models controlled for demographic, socioeconomic, and parental characteristics. PRINCIPAL FINDINGS: Being overweight at age 4-5 is associated with significantly higher pharmaceutical and medical care costs. The results imply that for all children aged 4 and 5 in 2004-2005, those who were overweight had a combined 5-year Medicare bill that was AUD$9.8 million higher than that of normal weight children. Results from dynamic analyses show that costs of childhood overweight occur contemporaneously, and the duration of overweight is positively associated with medical costs for children who became overweight after age 5. CONCLUSIONS: This study reveals that the financial burden to the public health system of childhood overweight and obesity occurs even during the first 5 years of primary school.

Employment patterns and changes in body weight among young women.

OBJECTIVE: To investigate the influence of employment patterns on weight gain and weight loss in young adult women. METHODS: Study sample is 5164 participants in the Australian Longitudinal Study on Women's Health who completed surveys in 2003 and 2006. Logistic regression was used to estimate odds ratios of weight change. RESULTS: The adjusted odds of gaining weight, compared with women in stable full-time work (49.7%), were lower for women in stable part-time work (47.3%, OR = 0.74, CI: 0.58-0.94), or who transitioned from not in the labour force (NILF) to part-time (42.8%, OR = 0.68, CI: 0.47-0.99) or full-time (37.5%, OR = 0.54, CI: 0.34-0.85) work. Heavy weight gain (>10 kg) was less likely among women in stable part-time work (6.4%, OR=0.59, CI: 0.37-0.93) compared with those in stable full-time work (8.1%). The likelihood of weight loss compared with women in stable full-time employment (22.4%) was higher among stable part-time workers (28.4% OR = 1.34, CI: 1.02-1.75) and those who transitioned from full-time to part-time work (24.8%, OR = 1.30, CI: 1.01-1.67). DISCUSSION: The lower likelihood of heavy weight gain associated with fewer work hours suggests more time spent at work may contribute to weight gain. Young women in full-time employment may benefit from workplace interventions supporting healthier lifestyles.