Presentaci

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Evaluation of a health promotion intervention to
improve maternal health in rural Nepal PhD
Mixedmethods evaluation of a maternity care
intervention in rural Nepal
S Sharma, E Sicuri, J Belizan, E van Teijlingen,
Padam Simkhada, Jane Stephens
Spanish Stata Users Group meeting, Barcelona
September 2012
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• Overview of talk
• Nepal and intervention background
• Maternal and Rural Health Care Issues
• Evaluation of the intervention project in Nepal
• Methodology
• Some early findings
• Next steps

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Objective of the PhD

• To evaluate using mixed-methods
• 1. Improved knowledge and increased uptake of
  reproductive health, antenatal and postnatal care
  services
• 2. Improved capacity of community to identify,
  negotiate and solve health related problems
  relating to maternal and child health
• 3. What are the range of barriers to accessing
  care
• 4. To determine if the intervention is
  cost-effective we first measure the efficacy of
  the intervention

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• Nepal
• Large rural population, majority Hindu (80.6)
• Land-locked between India China 240 peaks
  over 6,096 m
• GDP about 1,200 per person per year
• Nepal's MMR better than India, Pakistan and
  Bangladesh with 415 deaths in 2000 to 170 in 2010
  per 100,000 live births.

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Green Tara Nepal (GTN) Health promotion
intervention Improving maternity care in rural
Nepal
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2007 Green Tara Nepal Intervention 2012
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Health Promotion Cycle
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Results of Needs assessment

• High burden of preventable disease, most is
  avoidable through health promotion
• Over 70 deliveries take place at home
• Lack of knowledge/information
• ANC uptake is low, only 28 have 4 visits
• Uptake of ANC strongly influenced by
  socio-cultural factors
• The family is very influential the
  mother-in-law and daughter-in-law relationship
  influences ANC uptake

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Health Promotion Groups

• Total Participants n1100 (mostly women aged
  15-49 with children less than 2 years old but
  also Male56 Mother-in-law138Dalit7)
• Groups n40, covering all villages
• 22 mothers-in-law groups
• Visited 134 households to support women most in
  need
• Mobile phone given to several groups
• - emergency call ambulance
• - communicate with GTN staff

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Health Promotion (HP) Groups

• The project supported in 64 governments clinics
• 145 warm-baby blankets
• Monitoring of Pregnant women and under 2 years
  Children

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Before after study with controls
Preparatory work
2006
Control community
Intervention community
2007 2008 2010 2012
Baseline information
Baseline information
Intervent ion
Mid-term evaluation
Mid-term evaluation
Final evaluation
Final evaluation
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Study design

• controlled before and after
• - repeated cross-sections
• - non-randomised study
• - 833 women of childbearing age (either
  participating to health promotion activities or
  not) were interviewed in 4 village development
  communities included in two surveys in 2008
  (baseline) and 2010 (mid-term evaluation)

N 2008 2010
INT 208 217
CON 204 204
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Control
Intervention area
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Control and Intervention areas selection

• Visited 6 different communities, two were
  selected
• Access
• Health problems/needs
• Political commitment of local leaders
• Advice District Public Health office
• Distance to Kathmandu 20 km
• No statistically significant differences between
  individuals in treatment and control groups

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Demographics of respondentswomen 15-49, last
childlt2years of age
N833 (intervention control) Age at marriage Age at first pregnancy
up to 14 years 15-19 years     20-24 years 25-29 years         30 and above years 3 53.12 37.75 5.53 0.60 0.84 40.26 48.67 9.03 0.84
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The efficacy of the GTN intervention?
In order to ascertain the impact of the
intervention a. we used Difference in Difference
approach b. we control for factors such as
socio-economic factors, age, number of children
in the household and education
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Efficacy is determined by the change in ANC
uptake due to the intervention

• Difference in Difference analysis whereby
  intervention has had an impact on health uptake
  behaviour (i.e. ANC visits)
• i.e. E (TA-TB) (CA-CB)

Treatment Before (TB) Control Before (CB)
Treatment After (TA) Control After (CA)
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Data base structure for diff-in-diff analysis
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PCA to construct SES variable

• We construct a SES based on assets by using
  Principal Component Analysis PCA,
• PCA assets for SES variable were ownership of
  household assets (goods such as bicycle,
  motorcycle, goat, car), type of access to
  hygienic facilities (sources of drinking water,
  types of toilet), number of rooms, and
  construction materials used in the dwelling
• Stata pca dwelling_roof goat1 landgreater3
  ownpiped commpiped nonpipedopensource pipedshared
  flushtoilet pitlatrine othertoiletor_no_t
  ratioroom_person source_biogas source_lpggas
  cookersource_elec bicy1_28 mob1_23 friz1_23
  com1_23 motorised_veh

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Definition of efficacy in Difference in
difference analysis

• To analyse the efficacy of the intervention on
  different outcomes of health promotion activities
• We expect Measured aspect of health seeking
  behaviour should improve in the intervention area
  relative to the control.
• Non-clinical outcomes chosen ANC uptake
• If they attended ANC at least once
• When? (if during first trimester)
• How many ANC visits?

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Results of Diff in Diff ANC attendance at least
once
ANC attendance Odds Ratio P 95Conf Interval 95Conf Interval
Treatment 1.40 0.27 0.76 2.59
After 1.36 0.34 0.73 2.54
aftertreatment 6.05 0.00 1.98 18.48
SES 2.94 0.00 1.95 4.43
Age 0.90 0.00 0.86 0.94
Education 3.39 0.00 2.09 5.49
N. Of Children 0.77 0.03 0.60 0.98
Logistic regression N830 Plt0.05
STATA logit anc2_5 treat after treatafter SES
age1_2 schle1_9 u10_1_13
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Results of Diff in Diff ANC at least once
during 1st trimester
ANC in the 1st trimester Odds Ratio P 95Conf Interval 95Conf Interval
Treat 0.76 0.21 0.49 1.17
After 1.60 0.03 1.04 2.47
aftertreatment 1.53 0.17 0.83 2.83
SES 2.11 0.00 1.69 2.64
Age 0.98 0.29 0.95 1.01
Education 1.62 0.00 1.34 1.95
N. Of Children 0.76 0.00 0.64 0.89
Logistic regression N830 Plt0.05
STATA logit anc2_8btrimester treat after
treatafter SES age1_2 schle1_9 u10_1_13
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Results of Diff in Diff How many ANC visits?
ANC visits Coef. P 95Conf Interval 95Conf Interval
Treat 0.095 0.05 0.001 0.19
After 0.012 0.81 -0.083 0.11
aftertreatment 0.12 0.05 -0.007 0.25
SES 0.26 0.00 0.21 0.31
Age -0.02 0.00 -0.024 -0.01
Education 3.39 0.00 2.09 5.50
N. Of Children -0.073 0.00 -0.11 -0.036
Cons 1.29 0.00 1.09 1.50
Poisson regression N 830 Plt0.05
STATA poisson anc2_9 treat after treatafter SES
age1_2 schle1_9 u10_1_13
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Summary of diff in diff analysis and further steps

• HP improves the probability of ANC attendance at
  least once and has a positive impact on the
  number of visits
• OR ANC attendance is 6.05 ? 6 times more likely
  to attend ANC
• Coef. N ANC visits 0.12 (ALTHOUGH BORDERLINE) ?
  women receiving the intervention attended 1.13
  times as many ANC visits as women in the control
  group
• But not on going during the 1st trimester
• OR ANC in the 1st trimester 1.53
• Can ANC or a combination of maternal health
  factors be converted in DALYs, i.e. maternal
  deaths averted by ANC attendance? How can we
  translate ANC attendance into health outcome?

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Further analysis of intervention

• Overall effect ? (Direct Indirect) All women
• a) Direct Effect ? Women who attend GTN groups
• b) Indirect (herd) Effect ? Women who did not
• Efficacy ? Health Effectiveness
• The Cost Efficacy Ratio where intervention costs
  are divided by increased probability of ANC
  attendance. Can efficacy be translated into DALYs
  averted due to intervention?
• Cost-efficacy ? Costs effectiveness

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GRÀCIES!