16 February 2022>: Clinical Research
Prevalence Trends and Influencing Factors of Post-Stroke Depression: A Study Based on the National Health and Nutrition Examination Survey
Ying Lyu AEF* , Wei Li BCD , Tao Tang BCDDOI: 10.12659/MSM.933367
Med Sci Monit 2022; 28:e933367
Table 2 Analysis of influencing factors of post-stroke depression based on age.
Characteristics | Age <60 | Age ≥60 | ||||
---|---|---|---|---|---|---|
β | OR (95% CI) | P | β | OR (95% CI) | P | |
Gender | ||||||
Male | Ref | Ref | ||||
Female | 0.562 | 1.76 (1.06–2.92) | 0.030 | 0.207 | 1.23 (0.85–1.77) | 0.269 |
Education | ||||||
JMS or below | Ref | Ref | ||||
JHS or GED | −0.492 | 0.61 (0.33–1.15) | 0.127 | −0.247 | 0.78 (0.49–1.24) | 0.290 |
College or above | −0.662 | 0.52 (0.29–0.93) | 0.028 | −0.354 | 0.70 (0.46–1.08) | 0.107 |
Annual household income | ||||||
Ref | Ref | |||||
≥20,000$ | −0.642 | 0.53 (0.32–0.86) | 0.010 | −0.472 | 0.62 (0.43–0.90) | 0.012 |
Sleep disorders | ||||||
No | Ref | Ref | ||||
Yes | 1.839 | 6.29 (3.69–10.71) | 1.185 | 3.27 (2.26–4.73) | ||
JMS – junior middle schools; JHS – senior high schools; OR – odd ratio |