Manipulating large data sets is one of the tasks of a project undertaken by the Medical Research Council in which the levels of worker exposure to lead in a South African battery factory was studied. One of the aims of the study was to ascertain the levels of lead in the blood of South African factory workers. Lead poisoning can lead to renal failure and hypertensive diseases. Studies have found that high exposure to lead can adversely affect kidney functions, say MRC researchers.
Esme Jordaan, a researcher on the project, says that the project`s statistical analysis relied heavily on using SAS software because of the lack of consistent data collection in the project that has spanned a number of years and a variety of data sources.
The project methodology included compiling a history of the blood leads for the workers that were compiled from company records. Some of the data dated back from the 1970s but the company took more frequent measurements from 1982 onwards.
Some workers had been with the company since 1951 but measurement was only started 29 years later.
"Extrapolations were made for those years before any measurements were taken using the mean value of the first two months measurements taken, and we assumed a uniform exposure over the years when no measurements were taken. Interpolation were used for the measurements missed in between the workers` occupation years," says Jordaan.
With the programming abilities of SAS Institute software it was quite simple to calculate an index of lead exposure which represented the cumulative burden of lead exposure for each worker. SAS Institute software was found to be the most appropriate software tool to combine data from various sources for analysis. The study was a collaborative effort among a number of organsiations. The various statistical procedures (reg, logistic, test and others) were used for the regression analysis.
The study, which aimed to establish a relationship between inorganic lead exposure, blood pressure and renal function in South African battery factory workers - showed that the workforce in this industry should be the subject of more attention.
"The findings probably reflect a higher cumulative renal burden of lead exposure in this workforce in comparison to those in recent negative studies. The results also confirm the need for strategies to reduce lead exposure among industrial workers in South Africa," says Jordaan.
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