The economic burden of unsafe abortion for
women and households in Zambia
Tiziana Leone, LSE
Ernestina Coast, LSE
Divya Parmar, City University
Bellington Vwalika, UTH Lusaka
Safe Unsafe
Background
• Although abortion is legal, unsafe abortion is still high in
Zambia
• Stigma and barriers to access mean that women still use
illegal and unsafe clandestine providers
• Limited evidence globally on economic consequences of
seeking an unsafe abortion compared to a safe abortion
• Studies often fail to account for indirect costs (e.g. loss of
wages, transport, accommodation), actions taken in order to
find money or for the costs for friends and family
Unsafe abortion…
• a large health risk for women because of inadequate skills of
the providers, unsanitary environments, and hazardous
techniques
• increase the rate of complications (e.g.: severe bleeding,
abdominal and genital injury) or death
• can lead to further complications (e.g.: haemorrhage, sepsis,
genital perforation)
• might need complex tertiary care which is only available at
referral public hospitals with the capacity for surgery, blood
transfusion, and intensive care
A relatively liberal abortion law in
Zambia
• Abortion is legally permitted:
⁻ To save the life of a woman
⁻ To preserve physical health
⁻ To preserve mental health
⁻ Foetal impairment
⁻ Socio-economic and welfare of existing children
can be taken into account
Gestational age limits apply
Estimates of abortion for Zambia
Annual estimate
Total induced abortions 114,279
• Unsafe 108,264
& require post-abortion care 45,471
• Safe 6,015
Aims and objectives
• Estimate and compare the costs of safe
abortion and post-abortion care (PAC)
following an unsafe abortion for women and
their households
• Analyse the impact of different pathways to
termination of pregnancy on economic
burdens and their determinants
Primary Data
• 112 interviews with women
– Enough statistical power level of confidence 95% and a
margin of error at 5% given a response level of 80% (87%
response level achieved)
• For each woman medical records linked
• Data collected January-December 2013 for all women
identified as having undergone either a safe abortion or
having received PAC following an unsafe abortion in the study
hospital in Lusaka and discharged Monday to Friday (08:00-
16:00 and 06:00-17:00)
• Interviews conducted privately with women following
treatment and prior to discharge
Research instrument
• Available from: http://www.abortionresearchconsortium.org/
• Covered:
– socio-demographic background
– direct service costs (e.g.: fees per procedure or
intervention)
– indirect costs (e.g.: travel, food, loss of productivity)
– resources used to pay costs (e.g.: credit, asset sale,
borrowing, loss of wages)
– household assets used to calculate the wealth asset
Methods strengths and innovations
• Costs included all attempts and actions prior
to arriving at hospital
• Medical notes used to validate individual
reports of direct hospital costs
• Qualitative and quantitative data collected
simultaneously
Methods for costingTotal patient costs =
Direct medical costs (e.g. pregnancy test costs, charges paid
by women for un/safe abortion, fees)
+Indirect nonmedical costs (e.g. childcare, travel,
accommodation, informal payments)
+Productivity losses (e.g. time away from work/loss of income
for woman and people involved, including housework)
Linear regression of individual costing controlling for medical
procedures (e.g. medical abortion vs manual vacuum aspiration)
and socio-economic determinants
Pathways to study hospital in our
sample
%
N=112
Safe abortion at hospital 59.8
PAC after unsafe abortion:
[Medical abortion self-initiated]
[Other method e.g.: overdose, insert
foreign object]
41.2
[14.7]
[25.5]
Percentage of women by age and
un/safe abortion
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
14-19 20-24 25-29 30-34 35+
Safe
Unsafe
Percentage of women by un/safe
abortion and wealth
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
poorest below average average above average wealthiest
Safe
Unsafe
First attempt
Includes 2 ambiguous
cases
No information
about 3 (7%)
1 attempts third
unsafe attempt
112
women
34 (89%) go to
hospital
Second attempt
Government hospital
4 make a 2nd unsafe attempt
71 (63%) report going
straight to hospital
11 (15%)
receive referral
2 (50%)
receive referral
38 attempt an unsafe abortion4 seek an
alternative
unsafe method
22 (65%)
receive referral
41(37%) visit
different providers
What happens before arriving at hospital?
Breakdown of costs incurred by
women (US$)
Safe
abortion
Unsafe
abortion +
PAC
Direct pre-
hospital2.6 5.8
Indirect pre-
hospital4.7 17.7
Direct at hospital 6.5 4.9
Indirect at
hospital38.3 35.5
Total costs 52.0 64.0
• Medical abortion = $33
• PAC following a failed abortion = $88
• Average minimum monthly salary for a domestic worker is $100 Gross
• $12 is the equivalent of 3 day’s work
Costs for women by un/safe abortion
and wealth quintile
Determinants of costs
Cost
Age
Parity NS
Wealth
Procedure PAC>ToP
Education NS
Ward (High vs low cost) NS
Main activity Business owners pay more
What determines the costs that
women incur?
• Inadequate decentralisation of ToP services
– Referrals from district clinics to tertiary hospital means
further economic burden for women
• Treating the consequences of an unsafe abortion costs up to
70% more for women than a safe medical abortion
• Indirect payments account for the largest part of the burden
• Costs increase with wealth: women asked to pay more
according to their visible wealth status
• More than half had to ask relatives and friends for money
adding further burden on the wider household
Limitations
• Only one site but most of abortion care done there at
the time the data were collected
• Costs accounted for up to the time of the interview but
could be more costs post-hospital (transport back
home included in our calculations)
• School days missed costs not included
• Costs underestimated due to the lack of data for more
serious complications and those women that die
Future work
• This study has looked at the overall experience
– By costing directly the expenses occurred at the last leg of
the journey we would miss a big chunk of burden that the
whole experience is for women. Need to assess
uncertainty beyond CIs (e.g.: Monte Carlo
simulation/sensitivity analysis)
• More in depth study on more serious cases which might have
been missed by our study and account for
underrepresentation with cost unit weighting
More information
http://zambiatop.wordpress.com/
https://twitter.com/ZambiaToP
@ZambiaToP
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