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2017 ; 590-591
(ä): 139-153
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Monitoring the aftermath of Flint drinking water contamination crisis: Another
case of sampling bias?
#MMPMID28259435
Goovaerts P
Sci Total Environ
2017[Jul]; 590-591
(ä): 139-153
PMID28259435
show ga
The delay in reporting high levels of lead in Flint drinking water, following the
city's switch to the Flint River as its water supply, was partially caused by the
biased selection of sampling sites away from the lead pipe network. Since Flint
returned to its pre-crisis source of drinking water, the State has been
monitoring water lead levels (WLL) at selected "sentinel" sites. In a first phase
that lasted two months, 739 residences were sampled, most of them bi-weekly, to
determine the general health of the distribution system and to track temporal
changes in lead levels. During the same period, water samples were also collected
through a voluntary program whereby concerned citizens received free testing kits
and conducted sampling on their own. State officials relied on the former data to
demonstrate the steady improvement in water quality. A recent analysis of data
collected by voluntary sampling revealed, however, an opposite trend with lead
levels increasing over time. This paper looks at potential sampling bias to
explain such differences. Although houses with higher WLL were more likely to be
sampled repeatedly, voluntary sampling turned out to reproduce fairly well the
main characteristics (i.e. presence of lead service lines (LSL), construction
year) of Flint housing stock. State-controlled sampling was less representative;
e.g., sentinel sites with LSL were mostly built between 1935 and 1950 in lower
poverty areas, which might hamper our ability to disentangle the effects of LSL
and premise plumbing (lead fixtures and pipes present within old houses) on WLL.
Also, there was no sentinel site with LSL in two of the most impoverished wards,
including where the percentage of children with elevated blood lead levels
tripled following the switch in water supply. Correcting for sampling bias
narrowed the gap between sampling programs, yet overall temporal trends are still
opposite.