General and age-specific fertility rates in non-affective psychosis : population-based analysis of Scottish women

MacBeth, Angus and McSkimming, Paula and Bhattacharya, Sohinee and Park, John and Gumley, Andrew and St Clair, David and Barry, Sarah J. E. (2022) General and age-specific fertility rates in non-affective psychosis : population-based analysis of Scottish women. Social Psychiatry and Psychiatric Epidemiology, 58 (1). pp. 105-112. ISSN 0933-7954 (https://doi.org/10.1007/s00127-022-02313-y)

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Abstract

Purpose: Women diagnosed with non-affective psychosis have a lower general fertility rate (GFR) and age-specific fertility rate (ASFR) than women in the general population. Contemporary data on GFR in this group remain limited, despite substantive changes in prescribing and management. We calculated contemporary estimates of the GFR and ASFR for women diagnosed with non-affective psychosis compared with the general population of women without this diagnosis. Methods: A population-based design combined routinely collected historical maternity and psychiatric data from two representative areas of Scotland. Women were included from the NHS Grampian or Greater Glasgow and Clyde areas and were aged 15–44 between 2005 and 2013 inclusive. The ‘exposed’ group had a diagnosis of non-affective psychosis (ICD-10 F20–F29) and was compared to the general population of 'unexposed' women in the same geographical areas. Results: Annual GFR between 2005 and 2013 for women with non-affective psychosis varied from 9.6 to 21.3 live births/1000 women per year in the exposed cohort and 52.7 to 57.8 live births/1000 women per year in the unexposed cohort, a rate ratio (RR) of 0.28 [p < 0.001; 95% CI (0.24, 0.32)]. ASFR for all 5-year age groups was lower in the exposed cohort than amongst unexposed women. Conclusion: We highlight continued low fertility rates in women with a diagnosis of non-affective psychosis, despite widespread availability of prolactin-sparing atypical antipsychotics. Accurate estimation of fertility rates remains crucial in developing needs-matched perinatal care for these women. Methodological improvements using routine datasets to investigate perinatal mental health are also urgently needed.

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