Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

OBJECTIVES: Low handgrip strength (HGS) in children and adolescents might be associated with the risk of metabolic syndrome (MetS) and insulin resistance. This study prospectively evaluated the association between HGS in childhood and MetS in adolescence. METHODS: Based on data from the Ewha Birth and Growth Study, this study analyzed HGS at ages 7 to 9 and metabolic indices at ages 13 to 15. In total, 219 participants were analyzed. The risk of MetS was evaluated using the continuous metabolic syndrome score (cMetS), and insulin resistance was assessed using fasting blood insulin and homeostasis model assessment of insulin resistance (HOMA-IR). Relative HGS in childhood was determined by dividing HGS by body weight and categorized as sex-specific quartiles. RESULTS: This study found an inverse association between relative HGS levels in childhood and MetS and insulin resistance in adolescence. For each 1-group increase in relative HGS quartiles, cMetS (standarard [Std] β=-0.64, p<0.01), HOMA-IR (Std β=-0.21, p<0.01), and fasting blood insulin (Std β=-0.21, p<0.01) all decreased on average. These associations remained significant even after adjusting for confounding factors. CONCLUSIONS Our study showed a prospective association between HGS in childhood and the risk of MetS and insulin resistance in adolescence. It provides significant epidemiological evidence, emphasizing the importance of efforts to increase muscle strength from a young age to mitigate the risk of MetS and insulin resistance in adolescence.

OBJECTIVES: Low handgrip strength (HGS) in children and adolescents might be associated with the risk of metabolic syndrome (MetS) and insulin resistance. This study prospectively evaluated the association between HGS in childhood and MetS in adolescence. METHODS: Based on data from the Ewha Birth and Growth Study, this study analyzed HGS at ages 7 to 9 and metabolic indices at ages 13 to 15. In total, 219 participants were analyzed. The risk of MetS was evaluated using the continuous metabolic syndrome score (cMetS), and insulin resistance was assessed using fasting blood insulin and homeostasis model assessment of insulin resistance (HOMA-IR). Relative HGS in childhood was determined by dividing HGS by body weight and categorized as sex-specific quartiles. RESULTS: This study found an inverse association between relative HGS levels in childhood and MetS and insulin resistance in adolescence. For each 1-group increase in relative HGS quartiles, cMetS (standarard [Std] β=-0.64, p<0.01), HOMA-IR (Std β=-0.21, p<0.01), and fasting blood insulin (Std β=-0.21, p<0.01) all decreased on average. These associations remained significant even after adjusting for confounding factors. CONCLUSIONS Our study showed a prospective association between HGS in childhood and the risk of MetS and insulin resistance in adolescence. It provides significant epidemiological evidence, emphasizing the importance of efforts to increase muscle strength from a young age to mitigate the risk of MetS and insulin resistance in adolescence.

Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

OBJECTIVES: Low handgrip strength (HGS) in children and adolescents might be associated with the risk of metabolic syndrome (MetS) and insulin resistance. This study prospectively evaluated the association between HGS in childhood and MetS in adolescence. METHODS: Based on data from the Ewha Birth and Growth Study, this study analyzed HGS at ages 7 to 9 and metabolic indices at ages 13 to 15. In total, 219 participants were analyzed. The risk of MetS was evaluated using the continuous metabolic syndrome score (cMetS), and insulin resistance was assessed using fasting blood insulin and homeostasis model assessment of insulin resistance (HOMA-IR). Relative HGS in childhood was determined by dividing HGS by body weight and categorized as sex-specific quartiles. RESULTS: This study found an inverse association between relative HGS levels in childhood and MetS and insulin resistance in adolescence. For each 1-group increase in relative HGS quartiles, cMetS (standarard [Std] β=-0.64, p<0.01), HOMA-IR (Std β=-0.21, p<0.01), and fasting blood insulin (Std β=-0.21, p<0.01) all decreased on average. These associations remained significant even after adjusting for confounding factors. CONCLUSIONS Our study showed a prospective association between HGS in childhood and the risk of MetS and insulin resistance in adolescence. It provides significant epidemiological evidence, emphasizing the importance of efforts to increase muscle strength from a young age to mitigate the risk of MetS and insulin resistance in adolescence.

OBJECTIVES: Low handgrip strength (HGS) in children and adolescents might be associated with the risk of metabolic syndrome (MetS) and insulin resistance. This study prospectively evaluated the association between HGS in childhood and MetS in adolescence. METHODS: Based on data from the Ewha Birth and Growth Study, this study analyzed HGS at ages 7 to 9 and metabolic indices at ages 13 to 15. In total, 219 participants were analyzed. The risk of MetS was evaluated using the continuous metabolic syndrome score (cMetS), and insulin resistance was assessed using fasting blood insulin and homeostasis model assessment of insulin resistance (HOMA-IR). Relative HGS in childhood was determined by dividing HGS by body weight and categorized as sex-specific quartiles. RESULTS: This study found an inverse association between relative HGS levels in childhood and MetS and insulin resistance in adolescence. For each 1-group increase in relative HGS quartiles, cMetS (standarard [Std] β=-0.64, p<0.01), HOMA-IR (Std β=-0.21, p<0.01), and fasting blood insulin (Std β=-0.21, p<0.01) all decreased on average. These associations remained significant even after adjusting for confounding factors. CONCLUSIONS Our study showed a prospective association between HGS in childhood and the risk of MetS and insulin resistance in adolescence. It provides significant epidemiological evidence, emphasizing the importance of efforts to increase muscle strength from a young age to mitigate the risk of MetS and insulin resistance in adolescence.

Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

Background: Alcohol consumption is a major risk factor for cancer, and when combined with smoking, the risk increases. Nevertheless, few studies have comprehensively evaluated the combined effects of alcohol consumption and smoking on the risk of various cancer types.Therefore, to assess these effects, we conducted a systematic review and meta-analysis. Methods: We performed a systematic search of five literature databases, focusing on cohort and case-control studies. Considering exposure levels, we quantified the combined effects of alcohol consumption and smoking on cancer risk and assessed multiplicative interaction effects. Results: Of 4,452 studies identified, 24 (4 cohort studies and 20 case-control studies) were included in the meta-analysis. We detected interaction effect of light alcohol and moderate smoking on head and neck cancer risk (relative risk [RR], 4.26; 95% confidence interval [CI], 2.50–7.26; I2 = 65%). A synergistic interaction was observed in heavy alcohol and heavy smoking group (RR, 35.24; 95% CI, 23.17–53.58; I2 = 69%). In more detailed cancer types, the interaction effect of heavy alcohol and heavy smoking was noticeable on oral (RR, 36.42; 95% CI, 24.62–53.87; I2 = 46%) and laryngeal (RR, 38.75; 95% CI, 19.25–78.01; I2 = 69%) cancer risk. Conclusion Our study provided a comprehensive summary of the combined effects of alcohol consumption and smoking on cancers. As their consumption increased, the synergy effect became more pronounced, and the synergy effect was evident especially for head and neck cancer. These findings provide additional evidence for the combined effect of alcohol and smoking in alcohol guidelines for cancer prevention.