The coronavirus (COVID-19) pandemic and the ensuing sociopolitical measures to control and curb its spread have been affecting people's psychosocial health and well-being through various complex pathways and in unprecedented ways. The present study aims to assess the sociodemographic correlates of psychosocial health situation of Chinese community-dwelling residents. Methods: This was a cross-sectional survey that was carried out online and using a structured questionnaire during April 2020. In total, 4788 men and women with the age range of 11-98 years were included in the analysis. Outcome variables were the change in the experience of hopelessness, loneliness and depression before and during the pandemic, and the explanatory variables included demographic and social capital related variables.Results: Respectively 34.80%, 32.50% and 44.84% of the participants expressed feeling more hopeless, lonely, and depressed during the pandemic. The percentage of all three indicators was comparatively higher among women than among men: hopelessness (50.67% vs 49.33%), loneliness (52.44% vs 47.56%), and depression (56.22% vs 43.78%). Being married was associated lower odds of loneliness among men [Odds ratio= 0.63, 95% CI=0.45,0.90]. Loneliness was negatively associated with smoking [Odds ratio= 0.67, 95% CI=0.45,0.99] and positively with drinking [Odds ratio= 1.45, 95% CI=1.04,2.02]. Compared with those in the lowest income bracket (<10K), men [Odds ratio= 0.34, 95% CI=0.21,0.55] and women [Odds ratio= 0.36, 95% CI=0.23,0.56] in the highest (>40K) had the lowest odds of reporting perceived hopelessness [Odds ratio= 0.35, 95% CI=0.25,0.48]. Smoking also showed negative association with depression only among men [Odds ratio=0.63, 95% CI=0.43,0.91]. Conclusion: More about one-third of the participants reported worsening in the experience of hopelessness and loneliness, with more than two-fifth of worsening depression during the pandemic compared with the time before. Several socioeconomic and lifestyle factors were found to be associated with the outcome variables, most notably participants marital status, household income, smoking, alcohol drinking, existing chronic conditions, and urbanicity.