Table 5 lists the number of facilities in each of ZamCAT’s two groups, the total
population of pregnant women who completed the study, and the proportion of total
facilities in each district that were included in the initial analysis. Out of the 35 facilities
implementing SMGL in Kalomo, ZamCAT operated in 22 (63%), including facilities
from all three phases (7 out of 9 in Phase 2, 9 out of 12 in Phase 2, 6 out of 13 in Phase
3). There were no significant differences in the characteristics of women in the CHX or
DCC groups relevant to this study, so I combined the two groups together (Appendix A).
Since all facilities in Kalomo were part of SMGL, all pregnant women who enrolled in
ZamCAT in Kalomo District were considered part of the intervention group for Objective
1.
Table 5. Number of Facilities and Pregnant Women in ZamCAT, by District District Name Chlorhexi- dine Care Group (CHX) Dry Cord Care Group (DCC) Total # Facilities Selected Total # Women completed study (both groups) Total # Facilities Proportion of Total Facilities in Study Choma 10 8 18 7,487 35 51% Kalomo 9 13 22 9,722 35 63% Livingstone 2 3 5 2,166 14 36% Mazabuka 11 8 19 7,459 46 41% Monze 9 9 18 7,719 26 69% Siavonga 4 4 8 2,912 16 50% TOTAL 45 45 90 37,465 171 53%
The initial analysis was conducted with all six ZamCAT districts. However, to
ensure that characteristics of pregnant women at baseline were comparable between the
intervention (Kalomo District) and comparison groups (other ZamCAT districts), I
examined the characteristics of the five possible comparison districts and purposively
selected those districts that were most similar to Kalomo in respondent-level background
characteristics (mother’s age, education, marital status, parity, household distance to
health facility and mother’s HIV status until I reached the target sample size. The final
districts selected were Choma, Mazabuka and Monze.
Sample Size
To estimate the sample size needed to assess Objective 1, my primary outcome
indicator was FBB, expressed as the proportion of pregnant women delivering at a health
facility. A January 2014 report on the SMGL program by the CDC estimated a baseline
FBB rate of 63% across all four SMGL intervention districts in Zambia (including
Kalomo) and a post-SMGL rate of 84% (Centers for Disease Control and Prevention,
2014). At the time I was establishing the study’s sample size, the estimate from the
Zambia Demographic and Health Survey (ZDHS), 2013–2014 was unavailable.
Therefore, I chose to use the baseline estimate from SMGL, as it was more current than
the change in proportion from pre to post for the comparison group (non-SMGL). Based
on the explanation above, I estimated that the baseline FBB rates for both Kalomo and
the comparison group were approximately 60%. In the comparison districts, this rate
might increase to an estimated 65% due to ZamCAT–related activities. I estimated that
the SMGL intervention districts might increase to approximately 70%, a more
conservative estimate than the one reported from the CDC SMGL evaluation. Therefore,
the difference in post proportion for the intervention and comparison groups was
estimated at five percentage points.
Even though the outcome observations were made at the individual level, the
health facility was the level at which the SMGL program was implemented, therefore
making it important to take clustering into account.(Ukoumunne & Gulliford, 1999)
Therefore, I also included an estimated intra-class correlation coefficient, which is the
proportion of the total variance in the outcome due to between-cluster variation. I used
an estimate of 0.05, based on a recent study on maternal mortality in Brazil (Haddad et
al., 2012). Using the STATA sampsi and sampclus commands (StataCorp., 2009), I
calculated the necessary sample size to declare a difference of 5% in the above
dichotomous outcome to be statistically significant, given the following parameters and
assumptions:
• Alpha = .05, the conventional estimates for a Type I error (two-tailed test) • Power = .80, or the probability of correctly rejecting the null hypothesis of equal
post proportions in the two groups
• Average observations per cluster=100 (estimated number of pregnant women per facility in each time period of the study)
To meet these requirements, the minimum number of facilities needed per group
was 18, and the sample size required per group was 899 pregnancies. The complete
ZamCAT study had 22 clusters in Kalomo, and 68 clusters in the 5 other districts. Table 6
illustrates the number of women in Kalomo and three comparison districts selected for
the final analysis, based on time period of the study.
Table 6. Number of Women in Study Area for Each Study Period for Final Analysis Study area Pre-SMGL
Feb 2011–Jan 2012 Transition: Feb–Aug 2012 During SMGL: Sept 2012–Aug 2013 Total # of Women Kalomo 2,889 3,145 3,694 9,728 Comparison – 3 districts 7,737 7,469 7,689 22,895 TOTAL 10,626 10,614 11,383* 32,196
*1800 women missing information about delivery date
There were a total of 2,889 deliveries in Kalomo in the pre-SMGL period, and
3,694 deliveries in the during-SMGL period. In the comparison group’s three districts,
there were 7,737 pre-SMGL and 7,689 post-SMGL. Thus, using the ZamCAT data I was
able to meet the necessary requirements for sample size even when limiting to only three
of those women living only in Choma, Mazabuka or Monze, excluding a further 5,256
women living in Livingstone and Siavonga Districts (13.3% of the entire ZamCAT
sample). My final sample included all women with FBB outcome data during the pre-
and during- SMGL periods in Kalomo (n=6,477) and comparison districts of Choma,
Monze and Mazabuka (n=15,203). For the health facility analysis, I included all facilities
in Kalomo (n=22), and facilities in the three selected comparison group districts (n=55).