Background: The increasing rate of excess body weight (EBW) in the global population has led to growing health concerns, including cancer-related EBW. We aimed to estimate the population attributable fraction (PAF) of cancer incidence and deaths linked to EBW in Korean individuals from 2015 to 2030 and to compare its value with various body mass index cutoffs. Methods: Levin’s formula was used to calculate the PAF; the prevalence rates were computed using the Korean National Health and Nutrition Examination Survey data, while the relative risks of specific cancers related to EBW were estimated based on the results of Korean cohort studies. To account for the 15-year latency period when estimating the PAF in 2020, the prevalence rates from 2015 and attributable cases or deaths from 2020 were used. Results: The PAF attributed to EBW was similar for both cancer incidence and deaths using either the World Health Organization (WHO) Asian-Pacific region standard or a modified Asian standard, with the WHO standard yielding the lowest values. In the Korean population, the PAFs of EBW for cancer incidence were 2.96% in men and 3.61% in women, while those for cancer deaths were 0.67% in men and 3.06% in women in 2020. Additionally, PAFs showed a gradual increase in both sexes until 2030. Conclusion The EBW continues to have a significant impact on cancer incidence and deaths in Korea. Effective prevention strategies targeting the reduction of this modifiable risk factor can substantially decrease the cancer burden.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Purpose: This study aimed to assess the impact of metaverse-based content for teaching core nursing skills (CNSC) to undergraduate nursing students. Methods: A non-equivalent control group was selected using a non-synchronized design. A total of 71 participants (34 in the experimental group and 37 in the control group) were recruited between May and June 2023 in Gwangju Metropolitan City. The CNSC included scenarios focused on drain management. Data analysis was conducted using SPSS version 25 for Windows. Results: Upon completing the CNSC, significant differences were observed between the groups in core nursing skills knowledge (t=7.97, p<.001), confidence in performing core nursing skills (t=5.79, p<.001), and clinical competency (t=2.26, p=.003). Conclusion The findings suggest that the CNSC designed for undergraduate nursing students was effective in enhancing their knowledge of core nursing skills, confidence in skill performance, and clinical competency.

Background: The increasing rate of excess body weight (EBW) in the global population has led to growing health concerns, including cancer-related EBW. We aimed to estimate the population attributable fraction (PAF) of cancer incidence and deaths linked to EBW in Korean individuals from 2015 to 2030 and to compare its value with various body mass index cutoffs. Methods: Levin’s formula was used to calculate the PAF; the prevalence rates were computed using the Korean National Health and Nutrition Examination Survey data, while the relative risks of specific cancers related to EBW were estimated based on the results of Korean cohort studies. To account for the 15-year latency period when estimating the PAF in 2020, the prevalence rates from 2015 and attributable cases or deaths from 2020 were used. Results: The PAF attributed to EBW was similar for both cancer incidence and deaths using either the World Health Organization (WHO) Asian-Pacific region standard or a modified Asian standard, with the WHO standard yielding the lowest values. In the Korean population, the PAFs of EBW for cancer incidence were 2.96% in men and 3.61% in women, while those for cancer deaths were 0.67% in men and 3.06% in women in 2020. Additionally, PAFs showed a gradual increase in both sexes until 2030. Conclusion The EBW continues to have a significant impact on cancer incidence and deaths in Korea. Effective prevention strategies targeting the reduction of this modifiable risk factor can substantially decrease the cancer burden.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Background: The increasing rate of excess body weight (EBW) in the global population has led to growing health concerns, including cancer-related EBW. We aimed to estimate the population attributable fraction (PAF) of cancer incidence and deaths linked to EBW in Korean individuals from 2015 to 2030 and to compare its value with various body mass index cutoffs. Methods: Levin’s formula was used to calculate the PAF; the prevalence rates were computed using the Korean National Health and Nutrition Examination Survey data, while the relative risks of specific cancers related to EBW were estimated based on the results of Korean cohort studies. To account for the 15-year latency period when estimating the PAF in 2020, the prevalence rates from 2015 and attributable cases or deaths from 2020 were used. Results: The PAF attributed to EBW was similar for both cancer incidence and deaths using either the World Health Organization (WHO) Asian-Pacific region standard or a modified Asian standard, with the WHO standard yielding the lowest values. In the Korean population, the PAFs of EBW for cancer incidence were 2.96% in men and 3.61% in women, while those for cancer deaths were 0.67% in men and 3.06% in women in 2020. Additionally, PAFs showed a gradual increase in both sexes until 2030. Conclusion The EBW continues to have a significant impact on cancer incidence and deaths in Korea. Effective prevention strategies targeting the reduction of this modifiable risk factor can substantially decrease the cancer burden.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Purpose: This study aimed to assess the impact of metaverse-based content for teaching core nursing skills (CNSC) to undergraduate nursing students. Methods: A non-equivalent control group was selected using a non-synchronized design. A total of 71 participants (34 in the experimental group and 37 in the control group) were recruited between May and June 2023 in Gwangju Metropolitan City. The CNSC included scenarios focused on drain management. Data analysis was conducted using SPSS version 25 for Windows. Results: Upon completing the CNSC, significant differences were observed between the groups in core nursing skills knowledge (t=7.97, p<.001), confidence in performing core nursing skills (t=5.79, p<.001), and clinical competency (t=2.26, p=.003). Conclusion The findings suggest that the CNSC designed for undergraduate nursing students was effective in enhancing their knowledge of core nursing skills, confidence in skill performance, and clinical competency.

Background: The increasing rate of excess body weight (EBW) in the global population has led to growing health concerns, including cancer-related EBW. We aimed to estimate the population attributable fraction (PAF) of cancer incidence and deaths linked to EBW in Korean individuals from 2015 to 2030 and to compare its value with various body mass index cutoffs. Methods: Levin’s formula was used to calculate the PAF; the prevalence rates were computed using the Korean National Health and Nutrition Examination Survey data, while the relative risks of specific cancers related to EBW were estimated based on the results of Korean cohort studies. To account for the 15-year latency period when estimating the PAF in 2020, the prevalence rates from 2015 and attributable cases or deaths from 2020 were used. Results: The PAF attributed to EBW was similar for both cancer incidence and deaths using either the World Health Organization (WHO) Asian-Pacific region standard or a modified Asian standard, with the WHO standard yielding the lowest values. In the Korean population, the PAFs of EBW for cancer incidence were 2.96% in men and 3.61% in women, while those for cancer deaths were 0.67% in men and 3.06% in women in 2020. Additionally, PAFs showed a gradual increase in both sexes until 2030. Conclusion The EBW continues to have a significant impact on cancer incidence and deaths in Korea. Effective prevention strategies targeting the reduction of this modifiable risk factor can substantially decrease the cancer burden.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.