Prediction of metabolic syndrome based on sleep and work-related risk factors using an artificial neural network

BMC Endocrine Disorders

Table 3 Factors associated with metabolic syndrome using hierarchical multivariate logistic regression (n = 351)

Characteristics	Step 1^a	Step 2^b	Step 3^c
Characteristics	OR (95% CI)	OR (95% CI)	OR (95% CI)
Sex	0.25 (0.13–0.49)**	0.09 (0.04–0.20)**	0.10 (0.04–0.23)**
Exercise habit	0.56 (−1.11 - -0.03)*	NS	NS
Smoking habit	3.01 (1.60–6.05)**	NS	NS
Age (years)	3.19 (1.88–5.47)**	NS	NS
STOP-BANG		3.74 (2.41–6.11)**	2.63 (1.57–4.54)**
Control			NS
Managerial support			NS
Peer support			NS
Role			0.55 (0.38–0.78)**
Change			NS
AIC	398.53	358.98	349.64

NS not significant
*p < .05, **p < .01
^acorrected for age, job tenure, sleep time status, marital status, sex, exercise habit, smoker
^balso corrected for STOP-Bang score
^cand also corrected for dimensions of work-related stress

ISSN: 1472-6823