| Literature DB >> 35669361 |
Xueyu Li1,2, Kaushik Chattopadhyay3, Xingjun Qian4, Jingjia Yu1, Miao Xu1, Li Li1, Jing Sun5,6, Jialin Li1.
Abstract
Purpose: Type 2 diabetes mellitus (T2DM) can lead to microvascular complications including diabetic kidney disease. Albuminuria is an important marker to diagnose kidney injury in T2DM patients and healthy sleep duration is important for maintaining good health in patients with T2DM. However, the association between sleep duration and albuminuria in T2DM patients is unclear. Thus, this study aimed to investigate the association between sleep duration and albuminuria in patients with T2DM in Ningbo, China.Entities:
Keywords: China; albuminuria; sleep; type 2 diabetes mellitus
Year: 2022 PMID: 35669361 PMCID: PMC9166454 DOI: 10.2147/DMSO.S366064
Source DB: PubMed Journal: Diabetes Metab Syndr Obes ISSN: 1178-7007 Impact factor: 3.249
Characteristics of T2DM Patients in the Study
| Total (n=2688, 100%) | |
|---|---|
| 18–39 | 499 (18.6%) |
| 40–59 | 1486 (55.3%) |
| ≥60 | 703 (26.2%) |
| Male | 1748 (65.0%) |
| Female | 940 (35.0%) |
| Low | 1182 (44.0%) |
| Medium | 1301 (48.4%) |
| High | 178 (6.6%) |
| Unknown | 27 (1.0%) |
| Yes | 874 (32.5%) |
| No | 1814 (67.5%) |
| Yes | 1189 (44.2%) |
| No | 1498 (55.7%) |
| Unknown | 1 (0.0%) |
| Yes | 1691 (62.9%) |
| No | 997 (37.1%) |
| Yes | 986 (36.7%) |
| No | 1700 (63.2%) |
| Unknown | 2 (0.1%) |
| Yes | 427 (15.9%) |
| No | 2213 (82.3%) |
| Unknown | 48 (1.8%) |
| <5 | 1019 (37.9%) |
| ≥5-<10 | 565 (21.0%) |
| ≥10 | 772 (28.7%) |
| Unknown | 332 (12.4%) |
| <7 | 878 (32.7%) |
| ≥7 | 1761 (65.5%) |
| Unknown | 49 (1.8%) |
| Yes | 987 (36.7%) |
| No | 1701 (63.3%) |
| None | 1322 (49.2%) |
| ≤30 | 474 (17.6%) |
| 31–60 | 553 (20.6%) |
| ≥61 | 339 (12.6%) |
| <7 | 430 (16.0%) |
| ≥7-<8 | 766 (28.5%) |
| ≥8-<9 | 879 (32.7%) |
| ≥9 | 613 (22.8%) |
| No | 1994 (74.2%) |
| Yes | 694 (25.8%) |
Association Between Sleep Duration and Albuminuria in Patients with T2DM
| OR (95% CI) | p-value | |
|---|---|---|
| None | 1 | |
| ≤30 | 1.18 (0.93, 1.51) | 0.180 |
| None | 1 | |
| ≤30 | 1.18 (0.92, 1.50) | 0.193 |
| None | 1 | |
| ≤30 | 1.23 (0.94, 1.60) | 0.128 |
| <7 | 1.02 (0.78, 1.34) | 0.892 |
| ≥7-<8 | 1 | |
| ≥8-<9 | 0.95 (0.76, 1.19) | 0.680 |
| ≥9 | 1.14 (0.90, 1.45) | 0.277 |
| <7 | 1.01 (0.77, 1.32) | 0.972 |
| ≥7-<8 | 1 | |
| ≥8-<9 | 0.95 (0.76, 1.19) | 0.638 |
| ≥9 | 1.12 (0.88, 1.42) | 0.368 |
| <7 | 0.96 (0.72, 1.29) | 0.799 |
| ≥7-<8 | 1 | |
| ≥8-<9 | 0.97 (0.76, 1.23) | 0.773 |
| ≥9 | 1.16 (0.89, 1.51) | 0.263 |
Notes: Model 1 - Unadjusted. Model 2 - Adjusted for age and sex. Model 3 - Adjusted for age, sex, physical activity, smoking, alcohol drinking, overweight/obesity, hypertension, hyperuricaemia, duration of T2DM, HbA1c, ACEI/ARB usage and sleep duration (in the daytime sleep analysis, the nocturnal sleep was adjusted for and vice versa). Italic = statistically significant.