Abstract

BackgroundThe aims of this study were to explore the health-related quality of life (HRQoL) in a large sample of Australian chronically-ill patients (type 2 diabetes and/or hypertension/ischaemic heart disease), to investigate the impact of characteristics of patients and their general practitioners on their HRQoL and to examine clinically significant differences in HRQoL among males and females.MethodsThis was a cross-sectional study with 193 general practitioners and 2181 of their chronically-ill patients aged 18 years or more using the standard Short Form Health Survey (SF-12) version 2. SF-12 physical component score (PCS-12) and mental component score (MCS-12) were derived using the standard US algorithm. Multilevel regression analysis (patients at level 1 and general practitioners at level 2) was applied to relate PCS-12 and MCS-12 to patient and general practitioner (GP) characteristics.ResultsEmployment was likely to have a clinically significant larger positive effect on HRQoL of males (regression coefficient (B) (PCS-12) = 7.29, P < 0.001, effect size = 1.23 and B (MCS-12) = 3.40, P < 0.01, effect size = 0.55) than that of females (B(PCS-12) = 4.05, P < 0.001, effect size = 0.78 and B (MCS-12) = 1.16, P > 0.05, effect size = 0.16). There was a clinically significant difference in HRQoL among age groups. Younger men (< 39 years) were likely to have better physical health than older men (> 59 years, B = −5.82, P < 0.05, effect size = 0.66); older women tended to have better mental health (B = 5.62, P < 0.001, effect size = 0.77) than younger women. Chronically-ill women smokers reported clinically significant (B = −3.99, P < 0.001, effect size = 0.66) poorer mental health than women who were non-smokers. Female GPs were more likely to examine female patients than male patients (33% vs. 15%, P < 0.001) and female patients attending female GPs reported better physical health (B = 1.59, P < 0.05, effect size = 0.30).ConclusionsSome of the associations between patient characteristics and SF-12 physical and/or mental component scores were different for men and women. This finding underlines the importance of considering these factors in the management of chronically-ill patients in general practice. The results suggest that chronically ill women attempting to quit smoking may need more psychological support. More quantitative studies are needed to determine the association between GP gender and patient gender in relation to HRQoL.

Highlights

  • The aims of this study were to explore the health-related quality of life (HRQoL) in a large sample of Australian chronically-ill patients, to investigate the impact of characteristics of patients and their general practitioners on their HRQoL and to examine clinically significant differences in HRQoL among males and females

  • We investigated the relationship between patient or general practitioner (GP) characteristics and HRQoL in a large sample of chronically-ill Australian adults from two states and the Australian Capital Territory, using social functioning (SF)-12 version 2

  • Female GPs were more likely to have female than male patients (33% vs. 15%, P < 0.001) and the proportions were 37% vs. 18% (P < 0.001) without solo practices

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Summary

Introduction

The aims of this study were to explore the health-related quality of life (HRQoL) in a large sample of Australian chronically-ill patients (type 2 diabetes and/or hypertension/ischaemic heart disease), to investigate the impact of characteristics of patients and their general practitioners on their HRQoL and to examine clinically significant differences in HRQoL among males and females. Investigators from numerous countries representing diverse cultures have determined that both measures are sensitive to differences in a number of socio-demographic and clinical variables, including gender [3,4], age [2,3], income [4,5,6], employment [2,4,5], education [5,6], marital status [2,7], satisfaction with care [2], smoking [8,9,10], and number of chronic conditions [6]. Patient and GP characteristics tended to interact with gender of patients in predicting HRQoL, so we decided to analyse data separately for males and females

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