Effect of illness perception on predicting breast cancer-related lymphedema risk management behaviours among breast cancer patients: A comparison between dimensions and profiles.

AIM: This study aimed to explore the utility of latent profile analysis of illness perception, in comparison to treating illness perception as several dimensions, to predict breast cancer-related lymphedema risk management behaviours among Chinese breast cancer patients. METHODS: This is a 3-month longitudinal study. From August 2019 to January 2021, patients who recently underwent breast cancer surgery including axillary lymphadenectomy were recruited. Illness perception and risk management behaviours were measured by breast cancer-related lymphedema specific questionnaires before discharge following surgery (n = 268) and at 3 months postsurgery (n = 213), respectively. RESULTS: Treating illness perception as several dimensions, 'illness coherence' and 'timeline (cyclical)' dimensions were found to be significantly associated with breast cancer-related lymphedema risk management behaviours. Using the latent profile analysis, two illness perception profiles were identified and significant differences were revealed in breast cancer-related lymphedema risk management behaviours between them. Overall, illness perception profiles explained smaller amounts of variability in breast cancer-related lymphedema risk management behaviours than illness perception dimensions. CONCLUSION: Future studies could combine these two different perspectives of illness perception regarding breast cancer-related lymphedema into the design of interventions to improve breast cancer-related lymphedema risk management behaviours.

Source Identification and Health Risk Assessment of Heavy Metals in Soil: A Case Study of Lintancang Plain, Northeast China.

To investigate the concentration, source, and potential health risk of soil heavy metals (V, Cr, Ni, Cu, Zn, Pb, Hg), this study determined the concentration of these seven metals in 37 soil samples from Linyi City, southeast of Shandong Province, China. The mean concentrations of the investigated heavy metals followed the sequence: Cr (76.2 mg/kg) > V (70.5 mg/kg) > Zn (70.1 mg/kg) > Ni (34.0 mg/kg) > Pb (31.4 mg/kg) > Cu (23.2 mg/kg) > Hg (1.7 mg/kg). The enrichment factor (EF) and geo-accumulation index (Igeo) indicated an extreme enrichment of Hg (EF > 10, Igeo > 4) within the study area, while a slight enrichment of other metals. According to the toxic risk index (TRI), Hg accounted for the strongest soil toxicity (TRI = 8.07, 64.3%). The risk assessment with hazard index (HI) suggested that the health risks of all metals were acceptable, and the HI of adults was generally lower compared with that of the children. In addition, two principal components (PC) calculated by principal component analysis (PCA) were used to identify the sources of these heavy metals, which were 57.73% for PC 1 (Pb, Cr, Zn, Ni, Hg, Cu and V) and 21.63% for PC 2 (Hg, Cu and V), respectively. Moreover, PC 1 was mainly controlled by anthropogenic inputs, while PC 2 was contributed to by natural sources. Combined with the correlation matrix, it was concluded that there were three different sources for all seven heavy metals.

Key factors affecting carbon prices from a time-varying perspective.

For humankind to sustain a livable atmosphere on the planet, many countries have committed to achieving carbon neutralization. Countries mainly reduce carbon emissions by regulations through a carbon tax or by establishing a carbon market using economic stimuli. In this paper, we use the least absolute shrinkage and selection operator (LASSO) method to select the key determinants of a carbon market and then use the Markov switching vector autoregression (MSVAR) model to study the market's driving factors and analyze its time-varying characteristics. The results show that there are perceptible time-varying characteristics and notable differences among markets. During COVID-19, energy factors had a long-term shock on the carbon market, economic factors had a short-term shock on the carbon market, and the economic recession has led to fluctuations in the carbon market. In addition, through MSVAR, the results show that the energy market has a negative effect on the carbon market, and the stock market has a positive effect on the carbon market. In periods of low volatility, compared with the natural gas market and coal market, the oil market has a stronger shock on the carbon market. In periods of high volatility, the coal market has a stronger shock on the carbon market. In terms of emission reduction, countries around the world would be wise to change their energy consumption structure, reduce coal use, and shift to a cleaner energy consumption structure.

Illness perceptions and adherence to breast cancer-related lymphedema risk management behaviours among breast cancer survivors.

PURPOSE: To describe illness perceptions of breast cancer-related lymphedema (BCRL) and adherence to BCRL risk management behaviours and analyse the relationship between these factors in postoperative breast cancer survivors in China. METHODS: A cross-sectional study was conducted in the first half of 2019 using 281 breast cancer survivors. Participants' illness perceptions and adherence to BCRL risk management behaviours at the 3rd month after surgery were investigated using the Revised Illness Perception Questionnaire for BCRL (IPQ-R [BCRL]), Lymphedema Risk Management Behaviour Questionnaire (LRMBQ), and Functional Exercise Adherence Scale (FEAS). The relationship between these variables was studied using correlation analysis and multiple linear regression analysis. RESULTS: Among the four dimensions of the LRMBQ, the mean score of our respondents received in "skin care" was 3.63 (S.D. 0.67), which was the lowest on the dimension, demonstrating the worst performance in this aspect. Regarding the FEAS results, better functional exercise adherence was observed in our sample compared to previous Chinese research. The results also showed that adherence to BCRL risk management behaviours was related to patient age and degree of education. Furthermore, other dimensions of illness perceptions, such as consequence, timeline acute/chronic, illness coherence and identity, follow their multiple linear regression equations with their corresponding BCRL risk management behaviour adherence. CONCLUSIONS: Our findings confirmed the importance of illness perceptions for adherence to BCRL risk management behaviours, suggesting that we need to pay attention to patients' cognition in this respect and supply necessary interventions.