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Combined SEP was the measure with the second-greatest differences between the highest and a lowest SEP level.
There were significant differences in predicted probabilities of the outcomes by SEP level among dentate, but not among edentate, participants.
After adjusting for demographic characteristics, geographical location and general health, analyses showed significant differences in the predicted probabilities of oral health outcomes by SEP level among dentate participants.
In the analyses examining effect modification by area-level SEP, the SEP level was tertiled as previous studies used trichotomized categories of regional SEP [ 23, 25].
To obtain the index for all census blocks of Rome, we assigned a SEP level to census blocks with fewer than 50 inhabitants (0.4% of the population) according to the levels of contiguous blocks.
Generally, the five groups of MCH outcomes showed a consistent positive gradient for most (23/25) of the health outcomes across one or more SEP measures; the higher the SEP level, the better the MCH outcome.
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In general, mothers with lower education, lower household income (at or below the LICO), residing in lower SEP neighborhoods and having low individual-high neighborhood combined SEP had poorer MCH health outcomes than mothers at the higher SEP levels.
To analyse permutations of SEP levels at the two time points, a binary indicator of SEP was created by dichotomizing the standardized SLI by the median, and assigning values 1/0 for high/low SEP.
We included all the available variables in the logistic regression model: age, sex, initial observed EEG and SEPs levels, each dichotomised decrease of EEG and SEP levels, ICP, available treatment and clinical variables during hospitalisation, and the extent of the observation time.
Results of age-standardized prevalence of oral health outcomes by SEP showed consistent and significant social gradients in subjective oral health by all SEP measures; namely, a higher prevalence of the outcomes at successively lower SEP levels (results not shown).
From the regression coefficients we then estimated predictive margins and conditional marginal effects to compare predicted probabilities of the outcome across different SEP levels while accounting for all other variables in the model [ 40, 41].
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