Potential factors that may affect acceptance of routine prenatal HIV testing

Can J Public Health. 2005 Jan-Feb;96(1):60-4. doi: 10.1007/BF03404020.

Abstract

Background: Despite increasing advocacy for an "opt-out" strategy in routine prenatal HIV screening programs in Canada, no published studies have examined factors that may affect acceptance of prenatal HIV testing.

Methods: We included all pregnant women in Alberta who received prenatal care (N = 38,712) and their caregivers (N = 2,007) between January 1 and November 30, 2000. Factors associated with non-acceptance of HIV testing in both pregnant women and their caregivers were assessed using multivariate logistic regression.

Results: Overall, 1.5% of women declined HIV testing. First Nations women were about twice as likely to decline the test (adjusted odds ratio [OR(adj)] 1.91, 95% CI [1.42-2.58]) compared to non-First Nations women (p < 0.001). The proportion also increased with age (chi2 trend p < 0.001) in the general population. In First Nations women, however, most (3.2%) declined in the 20-24 year age group. No significant effect was seen for a socio-economic status marker or for the place of residence. The caregivers of women who declined HIV testing were more likely to be female (OR(adj) 1.56 [1.28-1.89]), midwives (OR(adj) 140.65 [58.61-337.49]), other non-obstetrical medical specialties (OR(adj) 4.92 [1.94-12.47]), and general practitioners (OR(adj) 3.44 [1.87-6.33]).

Conclusion: In an "opt-out" routine prenatal HIV screening program, the characteristics of both the pregnant women and their caregivers may contribute to the non-acceptance of HIV testing. A higher likelihood of declining HIV testing among First Nations pregnant women and other pregnant women under the care of midwives and female physicians warrants further study.

MeSH terms

  • AIDS Serodiagnosis / statistics & numerical data*
  • Adolescent
  • Adult
  • Alberta
  • American Indian or Alaska Native / psychology
  • Caregivers / psychology
  • Diagnostic Tests, Routine / statistics & numerical data
  • Female
  • HIV Infections / ethnology
  • HIV Infections / prevention & control*
  • Humans
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Patient Acceptance of Health Care* / ethnology
  • Pregnancy
  • Pregnant Women / psychology
  • Prenatal Care*
  • Sex Factors