BMC Public Health (May 2020)

Multilevel analysis of factors associated with unmet need for family planning among Malawian women

  • Owen Nkoka,
  • Watanja M. Mphande,
  • Peter A. M. Ntenda,
  • Edith B. Milanzi,
  • Victor Kanje,
  • Shiaau J. G. Guo

DOI
https://doi.org/10.1186/s12889-020-08885-1
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 12

Abstract

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Abstract Background Malawi has a high fertility rate which is also characterized by a relatively high prevalence of unmet need for contraception. However, little is known about the influence of individual- and community- level characteristics on unmet need in Malawi. This study examined the individual- and community- level factors associated with unmet need for family planning (FP) among Malawian women. Methods Data from the 2015–16 Malawi demographic and health survey were used to analyze 15, 931 women. The association between individual- and community- level factors and unmet need was assessed using multilevel binary logistic regression models. Results The prevalence of total unmet need was 21.0%. Women aged ≥35 years were more likely to have total unmet need [adjusted odds ratio (aOR) = 1.19, 95% confidence interval (CI) = 1.04–1.35] compared with those aged 15–24 years. Women who were married [aOR = 0.41, 95% CI = 0.35–0.48], and those employed [aOR = 0.78, 95% CI = 0.71–0.85] were associated with less likelihood of having total unmet need compared with unmarried, and unemployed women, respectively. At community-level, women from communities with a high percentage of women from rich households [aOR = 0.81, 95% CI = 0.67–0.96], and those from communities with a middle and high percentage of educated women [aOR = 0.86, 95% CI = 0.76–0.96 and aOR = 0.81, 95% CI = 0.70–0.93, respectively] were less likely to have total unmet need for FP compared with those from communities with low percentages of rich and educated women, respectively. The proportional change in variance showed that about 36.0% of total variations in the odds of unmet need across the communities were explained by both individual- and community-level factors. Moreover, the intraclass correlation showed that about 3.0% of the total variation remained unexplained even after controlling for both individual- and community-level factors. Conclusion Both individual- and community- level factors influenced unmet need for FP in Malawi. Public health practitioners should conduct community profiling and consider individual and community factors when designing FP programs.

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