Falls and fracture risk screening in primary care: update and validation of a postal screening tool for community dwelling older adults recruited to UK Prevention of Falls Injury Trial (PreFIT)

Table 3 Logistic regression models for prediction of fall outcomes in control group (development) at 12 months

Predictors	Control group (model 1): Any fall n = 2329			Control group (model 1): Recurrent falls n = 2259
Predictors	Coefficient	95% CI	p-value	Coefficient	95% CI	p-value
Age	-0.011	-0.029, 0.007	0.244	-0.002	-0.023, 0.019	0.831
Female gender	-0.019	-0.204, 0.167	0.844	-0.236	-0.464, -0.008	0.042
Lives alone	-0.034	-0.237, 0.169	0.745	-0.043	-0.288, 0.202	0.731
BMI	-0.020	-0.039, 0.001	0.044	-0.004	-0.026, 0.018	0.733
Practice deprivation 4 -7	0.099	-0.143, 0.340	0.424	0.367	0.064, 0.670	0.018
Practice deprivation 8 -10	-0.019	-0.275, 0.238	0.887	0.201	-0.119, 0.520	0.219
Clock Draw Test	-0.055	-0.171, 0.062	0.357	-0.099	-0.235, 0.038	0.156
SFI frail	0.333	0.080, 0.586	0.010	0.501	0.227, 0.774	< 0.001
SF-12 PCS	-0.019	-0.030, -0.009	< 0.001	-0.026	-0.039, -0.014	< 0.001
SF-12 MCS	-0.017	-0.027, -0.007	0.001	-0.027	-0.039, -0.016	< 0.001
High risk of falling	1.072	0.876, 1.267	< 0.001	1.293	1.053, 1.533	< 0.001
Intercept	2.592	0.521, 4.662	0.014	1.420	-1.004, 3.843	0.251

Equation ¹:\(logit\left[P\left(faller=1\right)\right]={\beta }_{0}+{\beta }_{1}age+{\beta }_{2} sex+{\beta }_{3}Living {+{\beta }_{4}BMI+\beta }_{5}Dep cat+{\beta }_{6}CDT+{\beta }_{7}SFI+{\beta }_{8}High risk+{\beta }_{9}PCS+{\beta }_{10}MCS\)
¹For recurrent falls model, replace with \(\left[P\left(recurrent faller=1\right)\right]\). Reference values: SFI frail vs. non-frail; GP deprivation score vs. 1–3; female vs. male; lives alone vs. lives with others; baseline high vs. low risk. The equation gives log odds. Probability can be calculated by taking the antilogit of the log odds

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