To account for any differential nonresponse that may have produced different distributions between our survey sample and the overall Ipsos KnowledgePanel, all analyses were conducted on a sample weighted to the overall to the geo-demographic distribution of the United States based on US Census data. The magnitude of missing data was < 5% for all variables, so we conducted complete case analyses. We calculated descriptive estimates of the prevalence of depressive symptoms and loneliness, and used chi-square and t tests to assess which categorical and continuous demographic variables differed significantly by depression status. We used log-binomial regression to estimate the associations between each of the nine exposures (frequency of social and sexual connections and relationship tension) and each of the two mental health outcomes (depression and loneliness). We estimated these associations in unadjusted models, and in models adjusted for gender, age, marital status, and income. To examine whether the associations differed by relationship status, we added an interaction term between relationship status and each of the nine exposures, dichotomizing the frequency variables at 1–3 times per week (at or above/below). We estimated stratified results and used the magnitude of differences in point estimates and Wald p values to inform our conclusions around effect measure modification. All analyses were conducted using SAS statistical software, version 9.4.

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