Abstract
Background: Insulin resistance is a phenomenon in which the lowering blood glucose capacity of insulin is decreased, which is a feature of type 2 diabetes mellitus. Some previous studies have found an association between insulin resistance and migraine. The triglyceride glucose (TyG) index is used to assess insulin resistance. However, there is no report on the association between the TyG index and migraine.
Objective: We present a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) to clarify the association between the TyG index and migraine.
Methods: Data was acquired from the NHANES. Migraine was diagnosed based on patient selfreport and prescription medication. Data were analyzed using the weighted linear regression model, weighted chi-square test, logistic regression models, smooth curve fittings, and the twopiecewise linear regression model. Empower software was used for all data analysis.
Results: A total of 18704 participants were enrolled in this study, of which 209 were migraineurs. The rest were set as control. There was a statistically significant difference in mean age (p = 0.0222), gender (p < 0.0001), distribution of race (P < 0.0001), and drug usage between the two groups. However, there were no differences in type 2 diabetes mellitus, type 1 diabetes mellitus, total cholesterol, triglycerides, glucose, and TyG index between the two groups. According to logistic regression models, there was a linear relationship between TyG index and migraine in model 3 (odds ratio (OR = 0.54, p = 0.0165). particularly in female (OR= 0.51, p = 0.0202) or Mexican American (OR= 0.18, p = 0.0203). Moreover, there was no inflection point between the TyG index and migraine.
Conclusion: In conclusion, there was a linear relationship between the TyG index and migraine. A higher TyG index predicts a lower incidence of migraine, particularly in females and Mexican Americans. Meanwhile, there is no inflection point between the TyG index and migraine.
Keywords: Migraine, insulin resistance, triglyceride glucose index, NHANES, logistic regression, smooth curve fittings.
[http://dx.doi.org/10.1186/s12888-021-03275-2] [PMID: 34030657]
[http://dx.doi.org/10.1111/j.1468-2982.2005.00928.x]
[http://dx.doi.org/10.1111/j.1468-1331.2009.02865.x] [PMID: 19930446]
[http://dx.doi.org/10.1007/s10072-012-1047-4]
[http://dx.doi.org/10.1111/ene.12289] [PMID: 24238370]
[http://dx.doi.org/10.1177/0333102413511155]
[http://dx.doi.org/10.1093/pm/pnz055] [PMID: 30938814]
[http://dx.doi.org/10.1089/jmf.2017.0068] [PMID: 28976801]
[http://dx.doi.org/10.1111/jch.14155] [PMID: 33415834]
[http://dx.doi.org/10.1186/s12933-022-01511-x] [PMID: 35524263]
[http://dx.doi.org/10.1186/s12933-021-01268-9] [PMID: 33812373]
[http://dx.doi.org/10.1155/2020/3082318] [PMID: 32676109]
[http://dx.doi.org/10.1007/s12072-013-9457-9] [PMID: 26201928]
[http://dx.doi.org/10.1016/j.endoen.2014.11.006]
[http://dx.doi.org/10.1155/2020/4678526] [PMID: 32256572]
[http://dx.doi.org/10.1016/j.ypmed.2016.01.022] [PMID: 26854766]
[http://dx.doi.org/10.1038/s41598-019-43776-5] [PMID: 31086234]
[http://dx.doi.org/10.1007/s10194-012-0416-y] [PMID: 22278639]
[http://dx.doi.org/10.1111/ene.12732] [PMID: 25981360]
[http://dx.doi.org/10.1111/ijpo.245] [PMID: 24990114]
[http://dx.doi.org/10.1097/EDE.0b013e31827623d0] [PMID: 23211346]
[http://dx.doi.org/10.1111/j.1468-1331.2007.01765.x] [PMID: 17594328]
[http://dx.doi.org/10.1111/head.14039] [PMID: 33398889]
[http://dx.doi.org/10.1080/01616412.2022.2119723] [PMID: 36062535]
[http://dx.doi.org/10.2174/1567202618666210923145635] [PMID: 34561979]