Sex, Residency, and Occupation May Influence Gout Prevalence

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A binary logistic regression analysis recognized factors significantly linked to an increased prevalence of gout, including sex, a history of renal disease or diabetes mellitus, and podagra.

Sex, Residency, and Occupation May Influence Gout Prevalence

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A cross-sectional analysis of patients with gout revealed significant associations between gout prevalence and a number of factors, including sex, residency, biochemical markers, clinical presentations, and occupational status, according to a study published in Cureus.1

Gout, one of the most common inflammatory joint diseases, can lead to impaired mobility, debilitating pain, increased risk of complications such as kidney stones and tophi, and significantly lower a patient’s quality of life. Over the course of the disease, chronic gout can cause irreversible damage and joint deformities, and severely impact functional abilities.2

“Despite the considerable burden imposed by gout, there are notable gaps in our understanding of the disease's epidemiology, particularly in regions outside the Western world,” wrote a team of investigators led by Jaber Abdullah Alshahrani, MBBS, associated with Family Medicine and Medical Education, Armed Forces Hospital Southern Region, Khamis Mushait, SAU. “This knowledge gap hinders the development of targeted interventions and healthcare strategies tailored to the needs of populations in these regions.”

The analysis, performed at King Fahad Hospital, Al-Baha, Saudi Arabia, enrolled 116 patients who visited the hospital for symptoms of gouty arthritis between March 2016 and November 2017. Information collected through electronic medical records included demographics (age, sex, occupational status, educational level, and residency), clinical presentations, clinical history, and relevant biochemical markers (serum uric acid levels and renal function tests).

Among the cohort, 35.3% (n = 41) had clinically diagnosed gout and the mean age was 53.1 years. Of those with gout, males demonstrated a significantly higher prevalence compared with females (43.9% vs 24%, respectively).

Other associations of note included residency, with patients living outside Al-Baha reporting a higher prevalence of gout compared with residents (56.3% vs 32%, respectively). There was also some variation among occupational status in which 44.7% of those in the gout cohort were government employees and 39.3% were private sector workers, compared with 22% of unemployed patients.

A significant association was observed between gout prevalence and education level, with the highest prevalence seen in those with a bachelor’s degree or higher (50%).

Podagra was exhibited in most (85.7%) patients with gout and 58.6% had a combination of arthralgia and arthritis. In 60% of cases, the ankle was the most affected joint, followed by the big toe and the knee (34.9% and 18.6%, respectively).

An analysis of biochemicals demonstrated patients with gout had significantly higher serum uric acid levels, creatinine, and blood urea nitrogen (P <.01).

Ultimately, a binary logistic regression analysis recognized factors significantly linked to an increased prevalence of gout:

  • Male (odds ratio [OR] = .4, P = .02)
  • A history of renal disease (OR = 3.2, P = .03)
  • A family history of gouty arthritis (OR = 0.2, P = .01)
  • A history of diabetes mellitus (OR = 3.4, P = .005)
  • Podagra (OR = 18, P = .01)
  • Combination arthralgia/arthritis (OR = 4.2, P = .002)
  • Big toe reported as the most affected joint (OR = 6.5, P = .01)

Investigators noted limitations including the cross-sectional study design and enrolling a relatively small sample size from a single-center setting, which may have hindered generalizability.

“This study enriches global knowledge by providing localized insights into gout's epidemiology and highlighting demographic influences and clinical presentations specific to the Saudi context,” investigators wrote. “The findings underscore the importance of tailored approaches in gout management, considering regional variations in prevalence, risk factors, and clinical manifestations.”

References

  1. Alshahrani JA, Saleh Alzahrani SA, Ali AlGhamdi OS, et al. Gouty Arthritis Across Ages: Understanding Disease Patterns and Predictors. Cureus. 2024;16(4):e58873. Published 2024 Apr 23. doi:10.7759/cureus.58873
  2. Pascart T, Lioté F: Gout: state of the art after a decade of developments. Rheumatology (Oxford). 2019, 58:27-44. 10.1093/rheumatology/key002
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