| Literature DB >> 34862431 |
Junhui Jeong1, So Ra Yoon2, Hyunsun Lim2, Jangwon Oh1, Hyun Seung Choi3.
Abstract
The associations between hypertension, diabetes, and dyslipidemia with Bell's palsy have been controversial and only a few studies have assessed risk factors for Bell's palsy based on population-based data. The aim of the present study was to evaluate whether sociodemographic factors such as sex, age, residence, household income, and metabolic diseases such as hypertension, diabetes, and dyslipidemia were risk factors for Bell's palsy using the National Health Insurance Service National Sample Cohort data of Korea. Patients who visited an outpatient clinic twice or more or had one or more admission and received steroid medication under the International Classification of Diseases diagnostic codes for Bell's palsy from 2006 to 2015 were defined as patients with Bell's palsy in this study. The associations between sociodemographic factors and metabolic diseases to Bell's palsy were analyzed with univariate and multivariate Cox proportional hazard regression models. There were 2708 patients with Bell's palsy recorded from 2006 to 2015. Male sex, advanced age, residence in a location other than the capital and metropolitan cities, hypertension, and diabetes were significant risk factors for Bell's palsy. This study is significant for patients and providers because we analyzed the relationships using a population-based database over a long-term follow-up period.Entities:
Mesh:
Year: 2021 PMID: 34862431 PMCID: PMC8642421 DOI: 10.1038/s41598-021-02816-9
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
The number of patients and incidence of Bell’s palsy from 2006 to 2015 based on the National Sample Cohort data of Korea.
| Year | Number of patients with Bell's palsy | Total number of people in the National Sample Cohort | Incidence (per 100,000) |
|---|---|---|---|
| 2006 | 215 | 1,021,208 | 21.1 |
| 2007 | 213 | 1,031,653 | 20.6 |
| 2008 | 257 | 1,035,089 | 24.8 |
| 2009 | 263 | 1,038,462 | 25.3 |
| 2010 | 260 | 1,042,706 | 24.9 |
| 2011 | 279 | 1,046,465 | 26.7 |
| 2012 | 332 | 1,050,743 | 31.6 |
| 2013 | 276 | 1,053,952 | 26.2 |
| 2014 | 301 | 1,057,454 | 28.5 |
| 2015 | 312 | 1,061,141 | 29.4 |
| Total | 2708 | 10,438,873 | 25.9 |
Sociodemographic distribution of patients with Bell’s palsy. †The sum of patients in household income is less than the total due to missing values.
| Bell’s palsy (n = 2708) | ||
|---|---|---|
| n | % | |
| Male | 1422 | 52.5 |
| Female | 1286 | 47.5 |
| ≤ 29 | 617 | 22.8 |
| 30–49 | 1035 | 38.2 |
| 50–69 | 840 | 31.0 |
| ≥ 70 | 216 | 8.0 |
| Seoul (capital) | 508 | 18.8 |
| Metropolitan cities | 674 | 24.9 |
| Other | 1526 | 56.4 |
| 1st quintile (lowest) | 380 | 14.7 |
| 2nd quintile | 426 | 16.5 |
| 3rd quintile | 472 | 18.3 |
| 4th quintile | 604 | 23.4 |
| 5th quintile (highest) | 697 | 27.0 |
Risk factors for Bell’s palsy based on univariate and multivariate Cox proportional hazard regression analyses.
| Univariate analysis | Multivariate analysis† | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Bell's palsy (n = 2,708) | % | Control (n = 1,028,953) | % | HR | 95% CI | HR | 95% CI | |||||
| Male | 1422 | 52.5 | 515,709 | 50.1 | 1.105 | 1.025 | 1.191 | 0.0096* | 1.169 | 1.081 | 1.263 | < 0.0001* |
| Female | 1286 | 47.5 | 513,244 | 49.9 | 1 | 1 | ||||||
| ≤ 29 | 617 | 22.8 | 421,388 | 41 | 1 | 1 | ||||||
| 30–39 | 467 | 17.3 | 181,785 | 17.7 | 1.759 | 1.560 | 1.984 | < 0.0001* | 1.730 | 1.530 | 1.955 | < 0.0001* |
| 40–49 | 568 | 21 | 175,350 | 17 | 2.231 | 1.991 | 2.500 | < 0.0001* | 2.153 | 1.915 | 2.420 | < 0.0001* |
| 50–59 | 472 | 17.4 | 115,309 | 11.2 | 2.853 | 2.531 | 3.217 | < 0.0001* | 2.554 | 2.248 | 2.901 | < 0.0001* |
| 60–69 | 368 | 13.6 | 77,278 | 7.5 | 3.447 | 3.029 | 3.922 | < 0.0001* | 2.801 | 2.422 | 3.238 | < 0.0001* |
| 70–79 | 178 | 6.6 | 43,229 | 4.2 | 3.33 | 2.818 | 3.935 | < 0.0001* | 2.663 | 2.204 | 3.217 | < 0.0001* |
| ≥ 80 | 38 | 1.4 | 14,614 | 1.4 | 2.886 | 2.079 | 4.006 | < 0.0001* | 2.278 | 1.576 | 3.293 | < 0.0001* |
| Seoul (capital) | 508 | 18.8 | 213,921 | 20.8 | 1 | 1 | ||||||
| Metropolitan cities | 674 | 24.9 | 267,152 | 26 | 1.064 | 0.849 | 1.194 | 0.2884 | 1.068 | 0.948 | 1.201 | 0.2733 |
| Others | 1526 | 56.4 | 547,880 | 53.3 | 1.181 | 1.068 | 1.306 | 0.0011* | 1.182 | 1.067 | 1.309 | 0.0014* |
| 1st quintile (lowest) | 380 | 14.7 | 144,996 | 14.8 | 1 | 1 | ||||||
| 2nd quintile | 426 | 16.5 | 160,304 | 16.3 | 1.009 | 0.879 | 1.158 | 0.9009 | 1.061 | 0.924 | 1.219 | 0.4021 |
| 3rd quintile | 472 | 18.3 | 178,183 | 18.2 | 1.004 | 0.877 | 1.149 | 0.9588 | 1.056 | 0.922 | 1.209 | 0.4286 |
| 4th quintile | 604 | 23.4 | 239,254 | 24.3 | 0.958 | 0.843 | 1.089 | 0.5137 | 0.990 | 0.871 | 1.126 | 0.8833 |
| 5th quintile highest) | 697 | 27 | 258,850 | 26.4 | 1.026 | 0.905 | 1.162 | 0.6891 | 1.009 | 0.890 | 1.144 | 0.8919 |
| No | 2205 | 81.4 | 928,701 | 90.3 | 1 | 1 | ||||||
| Yes | 503 | 18.6 | 100,252 | 9.7 | 2.286 | 2.075 | 2.519 | < 0.0001* | 1.362 | 1.208 | 1.535 | < 0.0001* |
| No | 2504 | 92.5 | 996,728 | 96.9 | 1 | 1 | ||||||
| Yes | 204 | 7.5 | 32,225 | 3.1 | 2.743 | 2.378 | 3.164 | < 0.0001* | 1.579 | 1.347 | 1.851 | < 0.0001* |
| No | 2502 | 92.4 | 981,281 | 95.4 | 1 | 1 | ||||||
| Yes | 206 | 7.6 | 47,672 | 4.6 | 1.875 | 1.570 | 2.239 | < 0.0001* | 1.017 | 0.842 | 1.229 | 0.8614 |
HR hazard ratio, CI confidence interval.
*p value < 0.05.
†All factors were adjusted in the multivariate Cox proportional hazard regression analysis. ‡The sum of patients in household income is less than the total due to missing values.