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Journal of Public Health Advance Access originally published online on October 3, 2007
Journal of Public Health 2007 29(4):405-412; doi:10.1093/pubmed/fdm062
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© The Author 2007, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved

An analysis of the link between behavioural, biological and social risk factors and subsequent hospital admission in Scotland



P. Hanlon
, Professor of Public Health1,

R. Lawder
, Statistician2

A. Elders
, Senior Statistician2

D. Clark
, Senior Statistician2

D. Walsh
, Public Health Programme Manager3

B. Whyte
, Public Health Programme Manager3

M. Sutton
, Professor in Health Economics4
1 University of Glasgow, Glasgow, UK
2 Information Services Division, National Services Scotland, Edinburgh, UK
3 Glasgow Centre for Population Health, Glasgow, UK
4 University of Aberdeen, Aberdeen, UK


Address correspondence to P. Hanlon, E-mail: phil.hanlon{at}clinmed.gla.ac.uk


   Abstract

Objective To determine the association between risk factors and hospital admission.

Methods The 1998 Scottish Health Survey was linked to the Scottish hospital admission database.

Findings Smoking was the most important behavioural risk factor (hazard ratio: 1.90, 95% CI: 1.59–2.27). Other behavioural risk factors yielded small but largely anticipated results. Hazard ratios for biological risks increased predictably but with some exceptions (blood pressure and total cholesterol). The top quintile for C-reactive protein showed almost double the risk of admission compared with the bottom quintile (hazard ratio: 1.93, 95% CI: 1.52–2.46). Elevated body mass index (BMI) increased the risk of serious admission (hazard ratio: 1.23, 95% CI: 1.03–1.47) and raised gamma-GT increased this risk by 20% (hazard ratio: 1.20, 95% CI: 1.04–1.38). Forced expiratory volume was the ‘biological’ factor with the largest risk (hazard ratio for lowest category: 1.82, 95% CI: 1.49–2.22). All the measures of social position showed variable effects on the risk of hospital admission. Large effects on risk were associated with self assessed health, longstanding illness and previous admission.

Conclusion The linkage of national surveys with a prospective hospitalization database will develop into an increasingly powerful tool.

Keywords: hospital admission, linked datasets, risk factors, Scottish Health Survey


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