Assessing the association of coffee consumption on the relationship of chronic pain with depression and anxiety

Qin, Xiaoyue; Li, Chune; Wei, Wenming; He, Dan; Zhao, Yijing; Cai, Qingqing; Zhang, Na; Chu, Xiaoge; Shi, Sirong; Zhang, Feng

doi:10.1080/1028415x.2023.2175412

Cited by 5 publications

(5 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, depression, anxiety, and stress were risk factors for treatment refractoriness and migraine chronification in patients with episodic migraine. On the other hand, several studies have shown a protective role for coffee in depression and anxiety 33 – 35 . Results from a meta-analysis showed that coffee consumption was significantly associated with a lower risk of depression 33 .…”

Section: Discussionmentioning

confidence: 99%

Coffee consumption and migraine: a population-based study

Cho,

Kim,

Chu

2024

Sci Rep

View full text Add to dashboard Cite

Although coffee is one of the most consumed caffeinated beverages worldwide, the role of coffee consumption in migraine is controversial. This study examined the relationship between coffee consumption and clinical characteristics in participants with migraine compared to those with non-migraine headache. This cross-sectional study used data from a nationwide survey on headache and sleep. Coffee consumption was classified as no-to-low (< 1 cup/day), moderate (1–2 cups/day), or high (≥ 3 cups/day). Of the 3030 survey participants, 170 (5.6%) and 1,768 (58.3%) were identified as having migraine and non-migraine headache, respectively. Coffee consumption tended to increase in the order of non-headache, non-migraine headache, and migraine (linear-by-linear association, p = 0.011). Although psychiatric comorbidities (depression for migraine and anxiety for non-migraine headache) and stress significantly differed according to coffee consumption, most headache characteristics and accompanying symptoms did not differ among the three groups for participants with migraine and non-migraine headache. Response to acute headache treatment—adjusted for age, sex, depression, anxiety, stress, preventive medication use, and current smoking—was not significantly different by coffee consumption in participants with migraine and non-migraine headache. In conclusion, most headache-related characteristics and acute treatment response did not significantly differ by coffee consumption in migraine and non-migraine headache.

show abstract

Section: Discussionmentioning

confidence: 99%

Coffee consumption and migraine: a population-based study

Cho,

Kim,

Chu

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Using the terms "chronic pain, " "depression, " and "UK Biobank" in PubMed (from the inception to March 1, 2024), we found 13 studies including chronic pain and depression through the analysis of UK Biobank [19,20,[35][36][37][38][39][40][41][42][43][44][45]. Of the 13 studies, five focused on genetic information [35,36,39,41,45], five were association analyses [19,37,38,42,44], one examined the role of coffee in the association between chronic pain and depression [43], one was a clinical prediction model for the development and spread of chronic pain [20], and one assessed risk factors for facial pain [40]. We also extended the search to clinical prediction models based on other datasets and found no other relevant studies.…”

Section: Comparison With Previous Studiesmentioning

confidence: 99%

Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models

Chen,

Ashton-James,

Shi

et al. 2024

BMC Med

View full text Add to dashboard Cite

Background The prevalence of depression among people with chronic pain remains unclear due to the heterogeneity of study samples and definitions of depression. We aimed to identify sources of variation in the prevalence of depression among people with chronic pain and generate clinical prediction models to estimate the probability of depression among individuals with chronic pain. Methods Participants were from the UK Biobank. The primary outcome was a “lifetime” history of depression. The model’s performance was evaluated using discrimination (optimism-corrected C statistic) and calibration (calibration plot). Results Analyses included 24,405 patients with chronic pain (mean age 64.1 years). Among participants with chronic widespread pain, the prevalence of having a “lifetime” history of depression was 45.7% and varied (25.0–66.7%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.66; good calibration on the calibration plot) included age, BMI, smoking status, physical activity, socioeconomic status, gender, history of asthma, history of heart failure, and history of peripheral artery disease. Among participants with chronic regional pain, the prevalence of having a “lifetime” history of depression was 30.2% and varied (21.4–70.6%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.65; good calibration on the calibration plot) included age, gender, nature of pain, smoking status, regular opioid use, history of asthma, pain location that bothers you most, and BMI. Conclusions There was substantial variability in the prevalence of depression among patients with chronic pain. Clinically relevant factors were selected to develop prediction models. Clinicians can use these models to assess patients’ treatment needs. These predictors are convenient to collect during daily practice, making it easy for busy clinicians to use them.

show abstract

“…Further, we conduct the seemingly unrelated estimation test (SUEST) to PLOS ONE compare whether differences in coefficients exist. As SUEST can only compare whether the coefficients differed between two groups [41], we perform pairwise comparisons between the coefficients of coverage, usage, and digitalization. Results in Table 8 indicate that the p values are all significant at 1% level while the coefficients of these three dimensions are 0.0223, 0.0116, and 0.0171 respectively.…”

Section: The Heterogeneity Of Digital Financial Structurementioning

confidence: 99%

Digital finance and M&As: An empirical study and mechanism analysis

et al. 2023

View full text Add to dashboard Cite

With the rapid growth and wide application of digital technology, enterprises have entered the digital era with both opportunities and challenges existing. Mergers and acquisitions are one of the most efficient ways to integrate resources and achieve profit growth, giving enterprises advantages in competing in the new mode of economic growth. Based on this, this research tries to explore whether the development of digital finance will contribute to the emergence of M&As activities through combining M&As data of the Chinese stock market with the digital finance inclusion index between 2012 and 2020. The results show that the development of digital finance largely influences M&As activities through lower acquirers’ financial constraints. We further replace digital finance with three sub-indexes including coverage breadth, usage depth, and digitalization level to explore the impact of different dimensions of digital finance on M&As. Results show that coverage breadth plays a more important role. In addition, heterogeneity tests reveal that the relationship between the development of digital finance and M&As activities varies significantly. The influences of digital finance on private and western and central enterprises are more significant compared with state-owned and eastern enterprises. According to the study, since the development of digital finance can be an efficient way to ease financial constraints and boost M&As activities, the government should promote the development of digital finance while companies strive to make the most use of it.

show abstract

Assessing the association of coffee consumption on the relationship of chronic pain with depression and anxiety

Cited by 5 publications

References 71 publications

Coffee consumption and migraine: a population-based study

Coffee consumption and migraine: a population-based study

Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models

Digital finance and M&As: An empirical study and mechanism analysis

Contact Info

Product

Resources

About