Psychological, social and biological determinants of ill health (pSoBid): Study Protocol of a population-based study
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  • 作者:Yoga N Velupillai (1)
    Chris J Packard (2)
    G David Batty (3)
    Vladimir Bezlyak (4)
    Harry Burns (5)
    Jonathan Cavanagh (6)
    Kevin Deans (7)
    Ian Ford (4)
    Agnes McGinty (8)
    Keith Millar (6)
    Naveed Sattar (9)
    Paul Shiels (10)
    Carol Tannahill (1)
  • 刊名:BMC Public Health
  • 出版年:2008
  • 出版时间:December 2008
  • 年:2008
  • 卷:8
  • 期:1
  • 全文大小:872KB
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  • 作者单位:Yoga N Velupillai (1)
    Chris J Packard (2)
    G David Batty (3)
    Vladimir Bezlyak (4)
    Harry Burns (5)
    Jonathan Cavanagh (6)
    Kevin Deans (7)
    Ian Ford (4)
    Agnes McGinty (8)
    Keith Millar (6)
    Naveed Sattar (9)
    Paul Shiels (10)
    Carol Tannahill (1)

    1. Glasgow Centre for Population Health, Level 6, 39 St Vincent Place, Glasgow, G1 2ER, UK
    2. Dept. Vascular Biochemistry, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, 4th Floor University Block, 10 Alexandra Parade, Glasgow, G31 2ER, UK
    3. MRC Social and Public Health Sciences Unit, 4 Lilybank Gardens, Glasgow, G12 8RZ, UK
    4. Robertson Centre for Biostatistics, University of Glasgow, Level 11, Boyd Orr Building, University Avenue, Glasgow, G12 8QQ, UK
    5. Scottish Executive, St. Andrew's House, Regent Road, Edinburgh, EH1 3DG, UK
    6. Section of Psychological Medicine, Faculty of Medicine, University of Glasgow, Gartnavel Royal Hospital, 1055 Great Western Road, Glasgow, G12 0XH, UK
    7. Dept. of Clinical Biochemistry, Macewen Building, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, 84 Castle Street, Glasgow, G4 0SF, UK
    8. Rosehill, Munros Street, Alexandria, Dunbartonshire, G83 0PU6, UK
    9. Division of Cardiovascular and Medical Sciences based at Vascular Biochemistry, Glasgow Royal Infirmary, University of Glasgow, 4th Floor QEB, 10 Alexandra Parade, Glasgow, G31 2ER, UK
    10. Faculty of Medicine, University Dept. Surgery, Level 2, Q.E.B, Glasgow Royal Infirmary, University of Glasgow, 10 Alexandra Parade, G31 2ER, UK
  • ISSN:1471-2458
文摘
Background Disadvantaged communities suffer higher levels of physical and mental ill health than more advantaged communities. The purpose of the present study was to examine the psychosocial, behavioural and biological determinants of ill health within population groups in Glasgow that differed in socioeconomic status and in their propensity to develop chronic disease especially coronary heart disease and Type 2 diabetes mellitus. Methods Participants were selected at random from areas known to be at the extremes of the socioeconomic continuum in Glasgow. Within the categories of least deprived and most deprived, recruitment was stratified by sex and age to achieve an overall sample containing approximately equal numbers of males and females and an even distribution across the age categories 35-4, 45-4 and 55-4 years. Individuals were invited by letter to attend for assessment of their medical history, risk factor status, cognitive function and psychological profile, morbidity, and carotid intima-media thickness and plaque count as indices of atherosclerosis. Anonymised data on study subjects were collected from the General Practice Administration System for Scotland to analyse characteristics of participants and non-participants. Results 700 subjects were recruited. The response (active participants per 100 invitation letters) in the least deprived group was 35.1% and in the most deprived group was 20.3%. Lowest response was seen in young males (least deprived 22.4% and most deprived 14.1%). Conclusion This cross-sectional study recruited the planned sample of subjects from least deprived and most deprived areas within Glasgow. As evident in other studies response differed between the most and least deprived areas. This study brought together researchers/academics from diverse disciplines to build a more sophisticated understanding of the determinants of health inequalities than can be achieved through unidisciplinary approaches. Future analyses will enable an understanding of the relationships between the different types of measure, and of the pathways that link poverty, biology, behaviour and psychology and lead to health inequalities.

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