BMC Pregnancy and Childbirth (Aug 2020)

Rural-urban differences in the mental health of perinatal women: a UK-based cross-sectional study

  • Samuel Ginja,
  • Katherine Jackson,
  • James J. Newham,
  • Emily J. Henderson,
  • Debbie Smart,
  • Raghu Lingam

DOI
https://doi.org/10.1186/s12884-020-03132-2
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 11

Abstract

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Abstract Background International data suggest that living in a rural area is associated with an increased risk of perinatal mental illness. This study tested the association between rurality and risk for two mental illnesses prevalent in perinatal women - depression and anxiety. Methods Using a cross-sectional design, antenatal and postnatal women were approached by healthcare professionals and through other networks in a county in Northern England (UK). After providing informed consent, women completed a questionnaire where they indicated their postcode (used to determine rural-urban status) and completed three outcome measures: the Edinburgh Postnatal Depression Scale (EPDS), the Whooley questions (depression measure), and the Generalised Anxiety Disorder 2-item (GAD-2). Logistic regression models were developed, both unadjusted and adjusted for potential confounders, including socioeconomic status, social support and perinatal stage. Results Two hundred ninety-five participants provided valid data. Women in rural areas (n = 130) were mostly comparable to their urban counterparts (n = 165). Risk for depression and/or anxiety was found to be higher in the rural group across all models: unadjusted OR 1.67 (0.42) 95% CI 1.03 to 2.72, p = .038. This difference though indicative did not reach statistical significance after adjusting for socioeconomic status and perinatal stage (OR 1.57 (0.40), 95% CI 0.95 to 2.58, p = .078), and for social support (OR 1.65 (0.46), 95% CI 0.96 to 2.84, p = .070). Conclusions Data suggested that women in rural areas were at higher risk of depression and anxiety than their urban counterparts. Further work should be undertaken to corroborate these findings and investigate the underlying factors. This will help inform future interventions and the allocation of perinatal services to where they are most needed.

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