Environmental Engineering Reference
In-Depth Information
in this setting. Subsequently, we discuss the primary outcome in the context of other
study findings, and explain why we hypothesize that the true effect—if there is any—
might be smaller.
First, the estimate for the longitudinal prevalence of diarrhea was substantially
smaller (OR = 0.92, 95% CI 0.66-1.29) than the estimate for incidence and there is
some evidence that prevalence is a better predictor in terms of mortality and weight
gain than incidence [23]. The absence of a time-intervention interaction in our time-
dependent analysis suggested no increased health benefi ts with the ongoing interven-
tion. Furthermore, within the intervention arm, there was no evidence that increased
compliance was associated with a lower incidence of diarrhea (Figure 4). However,
we interpret this post hoc subgroup analysis cautiously because compliant SODIS us-
ers might differ in important ways from noncompliant users. A compliant SODIS user
might be more accurately keeping morbidity diaries, whereas less compliant families
may tend to underreport diarrheal illness. Or, households with a high burden of mor-
bidity might be more likely to be compliant with the intervention. Both of these sce-
narios could lead to an underestimation of the effectiveness of SODIS.
Further, analyzing the laboratory results from 197 randomly selected stool speci-
mens also did not provide convincing evidence for an intervention effect: the propor-
tion of
C. parvum
was lower in the intervention children (5/94 vs. 2/103), but other
pathogens were found at similar proportions in intervention and control children (
G.
lamblia
, 39/94 vs. 40/103;
Salmonella
sp., 2/94 vs. 3/104;
Shigella
sp., 3/94 vs. 3/104).
In further exploring the occurrence of other illness symptoms we found the prevalence
of eye irritations and cough to be lower in the intervention group compared to the
control group. This difference could be the result of the hygiene component in the
intervention that increased hygiene awareness among the treatment communities. An
alternative explanation is that the lack of blinding led to biased (increased) health out-
come reporting in the intervention group.
Due to the nature of the intervention neither participants nor personnel were
blinded to treatment assignment. Ideally, blinding to the intervention allocation should
apply to the NGO staff administering the SODIS intervention and our enumerators
assessing outcomes [30]. Although the former could not be blinded in our study (for
obvious reasons), the latter would inevitably be able to identify the intervention status
of the cluster through the visible display of bottles to sunlight in the village or directly
at the study home during home visits. These problems are consistent with nearly all
household water treatment interventions [5] and other public health cluster random-
ized trials [31, 32]. Schmidt and Cairncross [33] recently argued that reporting bias
may have been the dominant problem in unblinded studies included in a meta-analysis
reporting a pooled estimate of a 49% reduction of diarrhea in trials investigating the
effects of drinking water quality interventions [5]. However, their review of only four
available blinded trials showing no effect demonstrates weak support for contrast. In
addition, all of the blinded trials exhibited analytical shortcomings or had very broad
CIs suggesting very low power. In the absence of blinding—unavoidable in many
behavioral change interventions or household water treatment studies—we believe
that data collection independent from the implementation is a crucial factor. Future
reviews should include reporting on such additional quality parameters.
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