POS1443 IDENTIFYING THE NEW EMERGENCE OF RACIAL DISPARITIES IN GOUT OVER THE PAST 3 DECADES – US NATIONAL SURVEY AND PROSPECTIVE COHORT DATA
Bibliographic record
Abstract
Background Several studies published after 2010 reported a higher frequency of gout and hyperuricemia among US Blacks than Whites.1-4 However, Blacks (in the US and Africa) were previously thought to suffer gout less often than Whites.5 We hypothesized that the racial disparity in Blacks emerged over the past several decades, with flipped prevalence between the two races. Objectives To assess trends in racial differences in gout prevalence in the US using both national survey and cohort study data over the past 3 decades. Methods Using data from the NHANES (National Health and Nutrition Examination Survey) III (1988-1994) and latest decade (2007-2016), and data from 5 examination periods in the ARIC (Atherosclerosis Risk in Communities) Study between 1988 through 2013, we compared age- and sex-adjusted prevalences and odds ratios (OR) to determine the trend of racial differences in gout prevalence between Blacks and Whites. A time-race interaction term was used to assess differences in the rate of change between the two races. Results Among Whites, the sex- and age-standardised prevalence of gout in the NHANES rose from 2.8% (95% CI: 2.4 to 3.2) in 1988-94 to 3.7% (3.2 to 4.1) in 2007/16. Prevalence of gout among Blacks was lower than Whites in 1988-94 (2.6% [2.2 to 3.0]) but rose more sharply over the subsequent decades (p for race-time interaction=0.003), and in 2007/16 came to exceed that of Whites (5.0% [4.4 to 5.6]). Corresponding age-sex-adjusted ORs for gout in Blacks vs. Whites were 0.93 (0.73 to 1.17) in 1988-94, increasing to 1.46 (1.22 to 1.74) in 2007/16 (Table 1). This disproportionate rise in gout prevalence among Blacks tended to be more prominent among women (OR 1.81 [1.29 to 2.53]) than men (OR 1.26 [1.02 to 1.55]; p for race-time interactions of 0.002 and 0.01, respectively). Similar trends were observed in the ARIC cohort, where the OR for gout among Blacks vs. Whites rose progressively from 0.82 (0.65 to 1.02) in 1987-89 to 1.81 (1.49 to 2.19) in 2011-13. Conclusion Gout prevalence tended to be lower in Blacks than Whites until late 80’s, then rose and surpassed that of Whites over the past several decades. These trends closely parallel the worsening obesity epidemic during this period,6 particularly in Blacks, partly due to enhanced Western lifestyle. Gout risk genetic profile change would not contribute to this emergence of racial differences, particularly among the same individuals in ARIC, although it remains to be clarified whether Blacks carry genetic profiles that enhance the effect of lifestyle risk factors for gout. References [1]PMID 22225548 (2012) [2]PMID 24330409 (2013) [3]PMID 24335384 (2014) [4]PMID: 30618180 (2019) [5]NEJM PMID: 15014177 [6]JAMA PMID: 12365955 Disclosure of Interests Natalie McCormick: None declared, Leo Lu: None declared, Chio Yokose: None declared, Amit Joshi: None declared, Yuqing Zhang: None declared, Hyon Choi Consultant of: Ironwood, Selecta, Horizon, Takeda, Kowa, and Vaxart., Grant/research support from: Ironwood and Horizon
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".