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ORIGINAL RESEARCH

Quantifying the Adverse Effects of Long COVID on Individuals’ Health After Infection: A Propensity Score Matching Design Study

, , , , , , , , , ORCID Icon, , , , & show all
Pages 701-713 | Received 24 Oct 2023, Accepted 28 Feb 2024, Published online: 23 Mar 2024

Figures & data

Figure 1 The flowchart of participants selection of this study.

Figure 1 The flowchart of participants selection of this study.

Table 1 The Characteristics, Lifestyles and Health Status Scores of the Study Participants

Figure 2 Factors influencing the health status of long COVID and non-long COVID cases.

Notes: 95% CI, confidence interval. CNY, China Yuan, The exchange rate,1 dollar=7.055 CNY. β, Adjusted for sex, age, ethnic, marriage, religion, BMI, Annual household income, education level, wearing masks, smoking, drinking, sufficient sleeping, mental decompression.
Figure 2 Factors influencing the health status of long COVID and non-long COVID cases.

Figure 3 The mediating effect of lifestyle scores.

Notes: a long COVID predicts lifestyle scores. b lifestyle scores predict health status scores. c long COVID predicts health status scores. c’ long COVID and lifestyle scores co-predict health status scores.
Figure 3 The mediating effect of lifestyle scores.

Figure 4 The health status scores between long COVID and non-long COVID cases pre- and post-PSM.

Notes: 95% CI, confidence interval. PSM, Propensity Score Matching.
Figure 4 The health status scores between long COVID and non-long COVID cases pre- and post-PSM.

Figure 5 The possible mechanistic pathway for the findings of this study. 95% CI, confidence interval.

Figure 5 The possible mechanistic pathway for the findings of this study. 95% CI, confidence interval.