Abstract

BackgroundThere is growing interest in passively-generated online search data for health sciences research, but limited use to address musculoskeletal illness. Questions/purposes(1) To determine geographic and seasonal patterns in Google queries for shoulder, knee, hip, and neck pain across the United States, and (2) to quantify the state-level correlation of the volume of online symptom searches with rates of various population health indicators. MethodsUsing Google trends, we identified queries for shoulder, knee, hip, and neck pain in every state of the United States during 2018. We assessed the correlation of state-level Google search volumes with 9 population health indicators extracted from the 2018 Behavioral Risk Factor Surveillance System survey: tobacco use, obesity, diabetes, hyperlipidemia, depression, arthritis, cardiovascular disease, participation in physical activities, and college education. ResultsNeck and shoulder pain were the most common queries in most Southern states, while knee pain was generally the top query elsewhere. Queries for neck and shoulder pain peaked during the late fall and winter, while searches for knee and hip pain peaked in the spring. State-level search volumes for shoulder and neck pain correlated closely with all health indicators––particularly with tobacco use, obesity, cardiovascular disease, hyperlipidemia, participation in physical activities and college education. The only strong correlation of hip pain queries was with self-reported prevalence of arthritis. Knee pain queries were not associated with any of the studied health indicators. ConclusionThis study highlights the potential of search engine data to be utilized as population-level health indicators. The state-level correlation of psychosocial and behavioral health indicators with online search volumes for neck and shoulder pain may reflect the influence of mental and social health on the experience of pain.

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