Elsevier

Journal of Health Economics

Volume 27, Issue 5, September 2008, Pages 1357-1367
Journal of Health Economics

GP supply and obesity

https://doi.org/10.1016/j.jhealeco.2008.02.012Get rights and content

Abstract

We investigate the relationship between area general practitioner (GP) supply and individual body mass index (BMI) in England. Individual level BMI is regressed against area whole time equivalent GPs per 1000 population plus a large number of individual and area level covariates. We use instrumental variables (area house prices and age weighted capitation) to allow for the endogeneity of GP supply. We find that that a 10% increase in GP supply is associated with a mean reduction in BMI of around 1 kg/m2 (around 4% of mean BMI). The results suggest that reduced list sizes per GP can improve the management of obesity.

Section snippets

Background

A growing proportion of the population of an increasing number of countries is obese (WHO, 1998). In England in 1980 6% of males and 8% of females in England were obese; by 2003 prevalences had trebled to 21% and 24%, respectively (Department of Health, 2003). Obesity is both a debilitating condition and an important risk factor for a number of major diseases including coronary heart disease, type II diabetes, osteoarthritis, hypertension and stroke (NHLBI, 1998).

In the UK the treatment and

Data sources

The main data source is the core sample of the Health Survey for England (HSE) 2000. The HSE is a nationally representative survey of individuals aged 2 years and over living in England. A new sample is drawn each year and respondents are interviewed on a range of core topics including demographic and socio-economic indicators, general health and psychosocial indicators, and use of health services. There is a follow up visit by a nurse at which various physiological measurements are taken,

Regression models

We use two IV methods to allow for the endogeneity of GP supply. The first is the standard two stage least square procedure. We estimate a GP supply equation at the individual level, regressing GP supply in each year against the two instruments plus the individual and area covariates. This yields predicted GP supply for each individual in each year and individuals in each area can have different predicted supplies. In the second stage individual BMI is regressed against individual predicted GP

Descriptive statistics

Table 1 contains population weighted health authority level summary statistics for WTE GPs per 1000 patients over the period 1995–2000. From the top panel, in each year the mean value is similar, with around 0.5 WTE GPs per 1000 registered persons, or one WTE GP for every 2000 people. The similarity in the distributions suggests that GP supply varied little over the period. The bottom panel of Table 1 shows that GP supply in HAs is highly positively correlated over time.

The sample distribution

Concluding remarks

We have investigated the impact of GP supply on BMI in England using multiple regression models with a rich set of individual and area variables. Using IVs to control for endogeneity we found that GP supply has a statistically significant and negative effect on BMI. On average, a 10% increase in GP supply in an area is associated with a reduction in BMI of around 1 kg/m2.

The impact of GP supply in the IV models is more negative than in the OLS models, which suggests that unobserved area factors

Acknowledgements

NPCRDC receives funding from the Department of Health (DH). The views expressed are those of the authors and not necessarily those of the DH. We thank a referee, Martin Roland, Matt Sutton and Frank Windmeijer for their advice and suggestions. We are grateful to the AREA project team for assistance with data.

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