National Health and Wellness Survey exploratory cluster analysis of males 40‐70 years old focused on erectile dysfunction and associated risk factors across the USA, Italy, Brazil and China. Issue 9 (28th June 2019) - Goldstein, Irwin; Goren, Amir; Liebert, Ryan; Tang, Wing Yu; Hassan, Tarek A.
Summary: Objectives: Prior studies of erectile dysfunction (ED) tend to narrowly focus on relationships with specific comorbidities, rather than evaluating a more comprehensive array of risk factors and assessing naturalistic patterns among them. This study identifies natural clusters of male characteristics from a general population sample per country, quantifies ED dynamics in these profiles and compares profiles across the US, Italy, Brazil and China samples. Methods: National Health and Wellness Survey 2015 and 2016 patient‐reported data on men aged 40‐70 years (USA n = 15, 652; Italy n = 2, 521; Brazil n = 2, 822; China n = 5, 553) were analysed. Hierarchical agglomerative clustering identified clusters where predictors included demographics, health characteristics/behaviours, ED risk factors and provider visits in the past 6 months. Multinomial logistic regression assessed the independent utility of variables in predicting cluster membership, compared with the healthiest control cluster per country. Results: Different natural clusters were found across countries, with four clusters for the USA, Italy and China and three clusters for Brazil. Age, income, employment, health behaviours and ED risk factors predicted different cluster membership across countries. In the USA, Italy and Brazil, younger clusters were predicted by ED, unhealthy behaviours and ED risk factors. Unique cluster profiles were identified in China, with ED and ED risk factors (aside from hypertension) not predicting cluster membership, while socio‐demographics and health behaviours were strongly predictive. Conclusions: Natural cluster profiles revealed notable ED rates among adult males of age 40‐70 in four different countries. Clusters were mainly predicted by unhealthy behaviours, ED risk factors and ED, regardless of level or presence of positive health characteristics and behaviours. This analysis identified meaningful subgroups of men with heightened ED risk factors, which can help healthcare providers to better recognise specific populations with the greatest need for intervention.