people living in finglas and their health - School of Medicine - Trinity ...
people living in finglas and their health - School of Medicine - Trinity ...
people living in finglas and their health - School of Medicine - Trinity ...
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RESULTS - PART 1<br />
RESULTS - PART 1<br />
Characteristics <strong>and</strong> practices associated with those who have a chronic illness<br />
Bi-variate analysis us<strong>in</strong>g six groups <strong>of</strong> variables (demographic characteristics, socio-economic characteristics,<br />
disability, <strong>health</strong> related behaviours, <strong>health</strong> service utilisation <strong>and</strong> wait<strong>in</strong>g for <strong>health</strong> care) <strong>in</strong>dicated that several<br />
factors were significantly associated with hav<strong>in</strong>g a chronic illness.<br />
Logistic regression models were constructed to clarify the <strong>in</strong>dependent associations between the significant<br />
variables <strong>and</strong> the likelihood <strong>of</strong> hav<strong>in</strong>g a chronic illness (Table 3.13). The relationships presented are those that<br />
rema<strong>in</strong>ed statistically significant or were deemed cl<strong>in</strong>ically important after tak<strong>in</strong>g account <strong>of</strong> confound<strong>in</strong>g. The<br />
associations are expressed as odds ratios (OR) adjusted for confound<strong>in</strong>g.<br />
Table 3.13 Logistic regression model to identify factors associated with hav<strong>in</strong>g a chronic disease <strong>in</strong> the F<strong>in</strong>glas<br />
population (291/963)<br />
Total Reported Prevalence % Adjusted p-value<br />
chronic illness<br />
Odds ratio<br />
(95% CI)<br />
Gender<br />
Male 491 123 25.0 1<br />
Female 471 168 35.7 1.5 (1.1 to 2.0) 0.02<br />
Miss<strong>in</strong>g 0<br />
Age (<strong>in</strong> years)<br />
0 to 49 638 105 16.5 1<br />
50 or over 316 183 57.9 5.1(3.6 to 7.1)