Risk Factors for Gout Attacks: A Case-crossover Study

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Gout affects over 5.1 million Americans, and recent studies have shown that the prevalence and incidence of gout in the United States (US) are increasing. Gout is characterized by recurrent attacks; these attacks cause pain, disability, and can eventually lead to joint damage. Recurrent gout attacks are often attributed to "triggers," precipitating risk factors that immediately precede an attack. Avoidance of these risk factors is a central preventive strategy for patients with gout. Nevertheless, much of the data identifying risk factors that may trigger recurrent gout attacks are either conjectural or irrelevant to contemporary populations. We propose to conduct an Internet-based case-crossover study to test a set of potential risk factors of gout with great relevance for contemporary adults. We will construct an interactive website for subject recruitment and data collection. We will recruit over 700 individuals who have a diagnosis of gout, confirming their diagnosis by obtaining and reviewing their medical records. Using the Internet, we will systematically collect information on risk factors 48 hours preceding a gout attack (hazard period) and 48 hours preceding a day when no gout attack was experienced (control period). The study duration for each subject will be one year. Risk factors to be assessed include dairy product intake, quantity and type of alcohol consumption; acute infection and immunization, weather factors (i.e., temperature, barometric pressure, and humidity), and medication use (i.e., low-dose aspirin, statins, losartan, and allopurinol). A standardized questionnaire of gout symptoms and signs will be used to ascertain recurrent attacks that occur among participants during the study period. We will examine the relation of each factor to the risk of recurrent attack by comparing its frequency over the hazard period with that over the control period, and calculating odds ratio using the Mantel-Haenszel method. We will perform multiple conditional logistic regression models to examine the relation of each factor to the risk of recurrent attack while adjusting for other potential confounding factors. We will then assess whether the effect of a particular risk factor on the risk of recurrent gout attacks is modified by other risk factors. The findings from this study will have important implications for preventing recurrent gout flares as all risk factors we propose to study are common among patients with gout. If these recurrent flares were prevented, the burden of gout on society would be greatly alleviated. In addition, while focusing on specific risk factors for recurrent gout flares, the current proposal also represents the development of a methodological strategy to better understand why patients with recurrent rheumatic diseases experience disease flares.