| Literature DB >> 30486273 |
Seung Ju Kim1,2, Kyu-Tae Han3,4, Suk-Yong Jang5, Ki-Bong Yoo6, Sun Jung Kim7.
Abstract
Background: Migraines gradually increase year by year, as does its burden. Management and prevention are needed to reduce such burdens. Previous studies have suggested that daily health behaviors can cause migraines. Sleep is a substantial part of daily life, and in South Korea, the average sleep duration is shorter than in other countries. Thus, this study focused on the increase of both diseases, and analyzed sleep disorders as a risk factor for migraines.Entities:
Keywords: accessibility; headache; migraine; sleep disorder; sleep disturbance
Mesh:
Year: 2018 PMID: 30486273 PMCID: PMC6313424 DOI: 10.3390/ijerph15122648
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
General characteristics of the study population.
| Variables | Total | Migraine | |||||
|---|---|---|---|---|---|---|---|
| Diagnosed | None | ||||||
| % | % | % | |||||
| Sleep disorder | |||||||
| Yes | 66,631 | 50.00 | 8025 | 12.04 | 58,606 | 87.96 | 0.0002 |
| No | 66,631 | 50.00 | 7591 | 11.39 | 59,040 | 88.61 | |
| Sex | |||||||
| Male | 55,614 | 41.73 | 4293 | 7.72 | 51,321 | 92.28 | <0.0001 |
| Female | 77,648 | 58.27 | 11,323 | 14.58 | 66,325 | 85.42 | |
| Age (Years) | |||||||
| ~29 | 6199 | 4.65 | 471 | 7.60 | 5728 | 92.40 | <0.0001 |
| 30–39 | 12,124 | 9.10 | 1290 | 10.64 | 10,834 | 89.36 | |
| 40–49 | 18,563 | 13.93 | 2148 | 11.57 | 16,415 | 88.43 | |
| 50–59 | 26,726 | 20.06 | 3374 | 12.62 | 23,352 | 87.38 | |
| 60–69 | 25,794 | 19.36 | 3059 | 11.86 | 22,735 | 88.14 | |
| 70–79 | 23,717 | 17.80 | 3182 | 13.42 | 20,535 | 86.58 | |
| 80~ | 20,139 | 15.11 | 2092 | 10.39 | 18,047 | 89.61 | |
| Economic level | |||||||
| ~30% (low) | 36,151 | 27.13 | 4408 | 12.19 | 31,743 | 87.81 | 0.0001 |
| 31–60% | 33,177 | 24.90 | 3919 | 11.81 | 29,258 | 88.19 | |
| 61–90% | 44,898 | 33.69 | 5215 | 11.62 | 39,683 | 88.38 | |
| +91% (high) | 19,036 | 14.28 | 2074 | 10.90 | 16,962 | 89.10 | |
| Types of insurance coverage | |||||||
| Medical aid | 6733 | 5.05 | 932 | 13.84 | 5801 | 86.16 | <0.0001 |
| NHI, self-employed insured | 54,054 | 40.56 | 6492 | 12.01 | 47,562 | 87.99 | |
| NHI, employee insured | 72,475 | 54.39 | 8192 | 11.30 | 64,283 | 88.70 | |
| Charlson comorbidity index | |||||||
| 0 | 109,022 | 81.81 | 12,596 | 11.55 | 96,426 | 88.45 | <0.0001 |
| 1 | 15,257 | 11.45 | 1994 | 13.07 | 13,263 | 86.93 | |
| 2 | 6015 | 4.51 | 693 | 11.52 | 5322 | 88.48 | |
| 3 | 1165 | 0.87 | 130 | 11.16 | 1035 | 88.84 | |
| 4+ | 1803 | 1.35 | 203 | 11.26 | 1600 | 88.74 | |
| Region | |||||||
| Capital area | 55,652 | 41.76 | 5971 | 10.73 | 49,681 | 89.27 | <0.0001 |
| Metropolitan | 33,888 | 25.43 | 3848 | 11.36 | 30,040 | 88.64 | |
| Others | 43,722 | 32.81 | 5797 | 13.26 | 37,925 | 86.74 | |
| Total | 133,262 | 58.24 | 15,616 | 11.72 | 117,646 | 88.28 | |
Figure 1Kaplan–Meier survival curve for the incidence of migraine. The results of the log-rank test for time to migraine by the diagnosis of sleep disorder were statistically significant.
Results of survival analysis for the association between sleep disorder and migraine.
| Variables | Migraine | |||
|---|---|---|---|---|
| HR | 95% CI | |||
| Lower | Upper | |||
| Sleep disorder | ||||
| Yes | 1.591 | 1.543 | 1.641 | <0.0001 |
| No | 1.000 | — | — | — |
| Sex | ||||
| Male | 1.000 | — | — | — |
| Female | 1.833 | 1.780 | 1.887 | <0.0001 |
| Age (Years) | ||||
| ~29 | 1.000 | — | — | — |
| 30–39 | 1.450 | 1.335 | 1.575 | <0.0001 |
| 40–49 | 4.578 | 1.460 | 1.707 | <0.0001 |
| 50–59 | 1.690 | 1.567 | 1.822 | <0.0001 |
| 60–69 | 1.682 | 1.559 | 1.816 | <0.0001 |
| 70–79 | 1.898 | 1.759 | 2.048 | <0.0001 |
| 80~ | 1.625 | 1.500 | 1.761 | <0.0001 |
| Economic level | ||||
| ~30% (low) | 1.000 | — | — | — |
| 31–60% | 1.035 | 0.988 | 1.083 | 0.1447 |
| 61–90% | 1.069 | 1.022 | 1.117 | 0.0035 |
| 91%~ (high) | 1.020 | 0.977 | 1.064 | 0.3727 |
| Types of insurance coverage | ||||
| Medical aid | 1.251 | 1.175 | 1.330 | <0.0001 |
| NHI, self-employed insured | 1.011 | 0.984 | 1.039 | 0.4098 |
| NHI, employee insured | 1.000 | — | — | — |
| Charlson comorbidity index | ||||
| 0 | 1.000 | — | — | — |
| 1 | 1.151 | 1.107 | 1.197 | <0.0001 |
| 2 | 1.111 | 1.047 | 1.179 | 0.0005 |
| 3 | 1.090 | 0.954 | 1.245 | 0.2036 |
| 4+ | 1.164 | 1.049 | 1.291 | 0.0041 |
| Region | ||||
| Capital area | 1.000 | — | — | — |
| Metropolitan | 1.055 | 1.020 | 1.092 | 0.0017 |
| Others | 1.237 | 1.200 | 1.275 | <0.0001 |
Results of survival analysis for association between types of sleep disorder and migraine.
| Variables | Migraine | |||
|---|---|---|---|---|
| HR | 95% CI | |||
| Lower | Upper | |||
| Sleep disorder | ||||
| Insomnia | 1.792 | 1.740 | 1.846 | <0.0001 |
| Sleep apnea | 1.250 | 1.138 | 1.373 | <0.0001 |
| Other sleep disorders | 1.663 | 1.602 | 1.727 | <0.0001 |
| None | 1.000 | — | — | — |
| Sex | ||||
| Male | 1.000 | — | — | — |
| Female | 1.810 | 1.758 | 1.864 | <0.0001 |
| Age (Years) | ||||
| ~29 | 1.000 | — | — | — |
| 30–39 | 1.470 | 1.353 | 1.597 | <0.0001 |
| 40–49 | 1.603 | 1.483 | 1.733 | <0.0001 |
| 50–59 | 1.716 | 1.592 | 1.851 | <0.0001 |
| 60–69 | 1.723 | 1.596 | 1.859 | <0.0001 |
| 70–79 | 1.944 | 1.802 | 2.098 | <0.0001 |
| 80~ | 1.683 | 1.554 | 1.823 | <0.0001 |
| Economic level | ||||
| ~30% (low) | 1.000 | — | — | — |
| 31–60% | 1.032 | 0.986 | 1.080 | 0.1734 |
| 61–90% | 1.071 | 1.024 | 1.120 | 0.0025 |
| 91%~ (high) | 1.025 | 0.982 | 1.070 | 0.2510 |
| Types of insurance coverage | ||||
| Medical aid | 1.228 | 1.154 | 1.306 | <0.0001 |
| NHI, self-employed insured | 0.999 | 0.972 | 1.027 | 0.9436 |
| NHI, employee insured | 1.000 | — | — | — |
| Charlson comorbidity index | ||||
| 0 | 1.000 | — | — | — |
| 1 | 1.125 | 1.082 | 1.170 | <0.0001 |
| 2 | 1.027 | 0.968 | 1.090 | 0.3745 |
| 3 | 1.024 | 0.896 | 1.170 | 0.7254 |
| 4+ | 1.042 | 0.939 | 1.156 | 0.4372 |
| Region | ||||
| Capital area | 1.000 | — | — | — |
| Metropolitan | 1.054 | 1.019 | 1.090 | 0.0021 |
| Others | 1.238 | 1.201 | 1.277 | <0.0001 |
Figure 2The results of sub-group analysis for survival analysis according to sex and age. The HR was calculated by survival analysis to investigate the association between sleep disorder and migraine. Results were considered to be statistically significant if each bar marked to SD did not reach the cut-off line of 1.000.
Figure 3The results of the sub-group analysis for survival analysis according to the economic level and Charlson comorbidity index (CCI). The HR was calculated by survival analysis to investigate the association between sleep disorder and migraine. Results were considered statistically significant if each bar marked to SD did not reach the cut-off line of 1.000.