| Literature DB >> 31639123 |
Lerong Wang1, Huimei Shi2, Yanbo Zhu1, Yanni Li1, Xiaohan Yu2, Muran Shi1, Hui Yan1, Tong Li1, Jia Lu1, Yanfeng Suo1, Kun Zheng1, Ooh Chye Tan1.
Abstract
OBJECTIVE: The relationship among blood donation, cognition in blood donation and health condition of blood donors remains unclear. Based on our hypothesis, this study aimed to explore the mediating effect of cognition in blood donation on the relationship between blood donation and blood donors' health status.Entities:
Mesh:
Year: 2019 PMID: 31639123 PMCID: PMC6804979 DOI: 10.1371/journal.pone.0223657
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
SF-36 outcomes and cognition in blood donation of blood donors with different characteristics.
| Variable | N (%) | PCS | MCS | Cognition in blood donation | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean±SD | T/F | P | Cohen’s d/ ηp2 | Mean± D | T/F | P | Cohen’s d/ ηp2 | Mean± D | T/F | P | Cohen’s d/ ηp2 | ||
| Male | 546(65.2) | 91.6±8.8 | 3.25 | <0.001 | 0.24 | 83.9±13.8 | 2.45 | 0.015 | 0.19 | 73.8±10.4 | 1.22 | 0.223 | 0.08 |
| Female | 291(34.8) | 89.3±10.5 | 81.2±15.3 | 72.9±11.2 | |||||||||
| ≤30 | 490(58.5) | 89.9±9.8 | -3.13 | <0.001 | 0.22 | 80.6±15.1 | -6.00 | <0.001 | 0.41 | 72.8±11.3 | -2.48 | 0.013 | 0.17 |
| >30 | 347(41.5) | 92.0±9.0 | 86.3±12.6 | 74.6±9.8 | |||||||||
| Single | 417(49.8) | 90.0±9.4 | -2.27 | 0.024 | 0.16 | 80.1±15.2 | -5.79 | <0.001 | 0.40 | 72.5±11.1 | -2.80 | 0.005 | 0.20 |
| Married | 407(48.6) | 91.5±9.5 | 85.7±12.8 | 74.6±10.2 | |||||||||
| Below high school | 159(19.0) | 92.5±9.2 | 8.33 | <0.001 | 0.02 | 87.0±13.0 | 16.36 | <0.001 | 0.04 | 72.6±9.0 | 0.84 | 0.432 | 0.00 |
| High school or junior college | 217(25.9) | 92.1±7.7 | 85.2±12.5 | 73.5±9.5 | |||||||||
| Bachelor’s degree or above | 461(55.1) | 89.6±10.2 | 80.5±15.1 | 73.8±11.7 | |||||||||
PCS: physical component summary; MCS: mental component summary; SD: standard deviation. Nonparametric Test and Cohen’s d were used to analyze the differences between groups of gender, age or marital status and their effect size, respectively. Kruskal-Wallis Test and ηp2 were used to analyze the differences between groups of education and its effect size. Individuals of other marital status (13) were excluded in analysis.
Correlation matrix of model variables.
| 2 | 3 | 4 | |
|---|---|---|---|
| 0.22 | 0.14 | 0.19 | |
| - | 0.17 | 0.19 | |
| - | - | 0.58 | |
| - | - | - |
PCS: physical component summary; MCS: mental component summary.
** p<0.01 (both sides).
- indicates no correlation coefficient or repeated calculations.
The goodness of fit and judgment of mediating effects.
| Model and standard | CFI | TLI | RMSEA | SRMR | WRMR |
|---|---|---|---|---|---|
| correction model | 0.993 | 0.950 | 0.043 | 0.013 | 0.494 |
| criterion for judging | >0.90 | >0.90 | <0.08 | <0.08 | <1.00 |
CFI: comparative fit index; TLI: Tucker-Lewis index; RMSEA: root mean square error of approximation; SRMR: standardized root mean square residual; WRMR: weighted residual root mean residual.
Fig 1Path diagram for the mediating effect of cognition in blood donation.
Values represent standardized path coefficients by a path analysis using Mplus 8.0 employing the S-B robust estimation method. Path coefficients are presented. P value for the path: ** p <0.01 (both sides).
Decomposition of effects of blood donation on PCS and MCS.
| Model path | Direct effect | Indirect effect | Total effect | Mediating effect quantity (%) |
|---|---|---|---|---|
| Cumulative times of blood donation | 0.101 | 0.033 | 0.134 | 24.63 |
| Cumulative times of blood donation | 0.096 | 0.035 | 0.131 | 26.72 |
PCS: physical component summary; MCS: mental component summary.
** p<0.01 (both sides).