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Estimating psychiatric morbidity by logistic regression: application to post-natal depression in a community sample

Published online by Cambridge University Press:  09 July 2009

Andrew D. Carothers  and
Lynne Murray
Andrew D. Carothers*
Affiliation:
Medical Research Council Human Genetics Unit, Edinburgh and Child Care and Development Group, University of Cambridge
Lynne Murray
Affiliation:
Medical Research Council Human Genetics Unit, Edinburgh and Child Care and Development Group, University of Cambridge
*
1Address for correspondence: Dr Andrew Carothers, MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh EH4 2XU.
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Synopsis

The use of logistic regression to estimate the prevalence of psychiatric morbidity in community samples is illustrated here with data from a study of post-natal depression in 702 primiparous Cambridge mothers. The method is also used to validate the primary screening instrument (in this case the Edinburgh Postnatal Depression Scale – EPDS), and to estimate the effects of cofactors, such as maternal age, previous psychiatric history and social class.

Type
Original Articles
Information
Psychological Medicine , Volume 20 , Issue 3 , August 1990 , pp. 695 - 702
Copyright
Copyright © Cambridge University Press 1990

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References

Albert, A. & Lesaffre, E. (1986). Multiple group logistic discrimination. Computing and Mathematics with Applications 12A, 209–224.CrossRefGoogle Scholar
Anderson, J. A. (1973). Logistic discrimination with medical applications. In Discriminant Analysis and Applications (ed. Cacoullos, T.), pp. 1–15. Academic Press: New York.Google Scholar
Anderson, J. A. (1974). Diagnosis by logistic discriminant function: further practical problems and results. Applied Statistics 23, 397–404.CrossRefGoogle Scholar
Choi, S. C. (1986). Discrimination and classification: an overview. Computing and Mathematics with Applications 12A, 173–177.CrossRefGoogle Scholar
Cooper, P. J., Campbell, E. A., Day, A., Kennerley, H. & Bond, A. (1988). Non-psychotic psychiatric disorder after childbirth: a prospective study of prevalence, incidence, course and nature. British Journal of Psychiatry 152, 799–806.CrossRefGoogle ScholarPubMed
Cox, A., Rutter, M., Yule, B. & Quinton, D. (1977). Bias resulting from missing information: some epidemiological findings. British Journal of Preventive and Social Medicine 31, 131–136.Google ScholarPubMed
Cox, J. L., Holden, J. M. & Sagovsky, R. (1987). Detection of postnatal depression: development of the 10-item Edinburgh Postnatal Depression Scale. British Journal of Psychiatry 150, 782–786.CrossRefGoogle ScholarPubMed
Dalton, K. (1971). Prospective study into puerperal depression. British Journal of Psychiatry 118, 689–692.CrossRefGoogle ScholarPubMed
Dunn, G. (1981). The role of linear models in psychiatric epidemiology. Psychological Medicine 11, 179–184.CrossRefGoogle ScholarPubMed
Endicott, J. & Spitzer, R. L. (1978). A diagnostic interview. The Schedule for Affective Disorders and Schizophrenia. Archives of General Psychiatry 35, 837–844.CrossRefGoogle ScholarPubMed
Fleiss, J. L., Williams, J. B. W. & Dubro, A. F. (1986). The logistic regression analysis of psychiatric data. Journal of Psychiatric Research 20, 195–209.CrossRefGoogle ScholarPubMed
Goldberg, D. P., Cooper, B., Eastwood, M. R., Kedward, H. B. & Shepherd, M. (1970). A standardised psychiatric interview for use in community surveys. British Journal of Preventive and Social Medicine 24, 18–23.Google ScholarPubMed
Hayworth, J., Little, B. C., Bonham Carter, S., Raptopoulos, P., Priest, R. G. & Sandler, M. (1980). A predictive study of post-partum depression: some predisposing characteristics. British Journal of Medical Psychology, 53, 161–167.CrossRefGoogle ScholarPubMed
Hobbs, P., Ballinger, C. B. & Smith, A. H. W. (1983). Factor analysis and validation of the General Health Questionnaire in women: a general practice survey. British Journal of Psychiatry 142, 257–264.CrossRefGoogle ScholarPubMed
Kumar, R. & Robson, K. M. (1984). A prospective study of emotional disorders in childbearing women. British Journal of Psychiatry 144, 35–47.CrossRefGoogle ScholarPubMed
Murray, L. & Carothers, A. D. (1990). The validation of the Edinburgh Postnatal Depression Scale on a community sample. British Journal of Psychiatry (in the press).CrossRefGoogle Scholar
Neugebauer, R. (1983). Rate of depression in the puerperium. British Journal of Psychiatry 143, 421–422.CrossRefGoogle ScholarPubMed
Oakley, A. (1980). Women Confined: Towards a Sociology of Childbirth. Martin Robertson: Oxford.Google Scholar
Paykel, E. S., Emms, E. M., Fletcher, J. & Rassaby, E. S. (1980). Life events and social support in puerperal depression. British Journal of Psychiatry 136, 339–346.CrossRefGoogle ScholarPubMed
Pitt, B. (1968). ‘Atypical’ depression following childbirth. British Journal of Psychiatry 114, 1325–1335.CrossRefGoogle ScholarPubMed
Spitzer, R., Endicott, J. & Robins, E. (1975). Research Diagnostic Criteria: Instrument No. 58. New York State Psychiatric Institute: New York.Google Scholar
Vázquez-Barquero, J. L., Díez-Manrique, J. F., Peña, C., Quintanal, R. G. & Labrador Lopez, M. (1986). Two stage design in a community survey. British Journal of Psychiatry 149, 88–97.CrossRefGoogle Scholar