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We computed p-for-trend to assess monotonic linear trends in the data using the median exposure value for each quartile.
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We performed a test for linear trend for both exposure metrics by using the median for each exposure category as the quantitative score.
The advantage of using true exposure intervals is that the "spacing" between each group can be plotted accurately using the median of each exposure interval, allowing for the most accurate analysis of the dose response shape.
We tested for linear trend by using the median value of each exposure category.
Tests for linear trend were conducted using the median value for each exposure category analysed as a continuous variable.
Tests for linear trend were conducted using the median value of each exposure category as a continuous variable in the model.
Exposure-response trends were also evaluated in logistic regression models using the median value for each categorical exposure level.
Linear trends were assessed using the p-value of the coefficient of the exposure treated as a continuous value using the median value for each tertile of exposure in the models also adjusting for covariates (Breslow and Day 1987).
Finally, the results were similar when we separately examined fonofos days of use and years of use after categorizing each into none, low, and high categories for exposure, using the median to distinguish between low and high (not shown).
We summarized the distribution of exposures using the median, IQR, and range of urinary paraben concentrations.
To test for significant trends, linear models were fitted using the median values of each category of exposure (e.g., 17.0, 19.0, 28.0, 23.5, 28.0, and 35.0 for BMI at age 18 years).
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