OBJECTIVES: Despite several investigations, the association between adolescent pregnancy and gynecological cancers has yet to be conclusively established. To further explore this association, we conducted a meta-analysis of observational studies. METHODS: We conducted a comprehensive search of databases such as PubMed, Web of Science, and Scopus to identify studies investigating the link between adolescent pregnancy and gynecologic cancers. This search continued until February 20, 2023. To assess the heterogeneity among the studies, we used the I2-statistics. We also explored the potential presence of publication bias using the Begg and Egger tests. The overall effect sizes were reported as either risk ratio or odds ratio, accompanied by a 95% confidence interval (CI), using a random-effects model. RESULTS: From an initial pool of 25,436 studies, a total of 76 studies involving 13,991,683 participants met the predefined eligibility criteria. The analysis indicated that the overall effect size for individuals having their first pregnancy at age 20 or older, compared to those having it before age 20, was 0.54 (95% CI, 0.50 to 0.59) for cervical cancer, 0.82 (95% CI, 0.77 to 0.88) for ovarian cancer, and 0.96 (95% CI, 0.89 to 1.04) for uterine cancer. CONCLUSIONS Our findings suggest that experiencing one’s initial pregnancy at the age of 20 or above is associated with a significantly reduced risk of cervical and ovarian cancer. However, no significant association was found between first pregnancy at this age and uterine cancer.

OBJECTIVES: Despite several investigations, the association between adolescent pregnancy and gynecological cancers has yet to be conclusively established. To further explore this association, we conducted a meta-analysis of observational studies. METHODS: We conducted a comprehensive search of databases such as PubMed, Web of Science, and Scopus to identify studies investigating the link between adolescent pregnancy and gynecologic cancers. This search continued until February 20, 2023. To assess the heterogeneity among the studies, we used the I2-statistics. We also explored the potential presence of publication bias using the Begg and Egger tests. The overall effect sizes were reported as either risk ratio or odds ratio, accompanied by a 95% confidence interval (CI), using a random-effects model. RESULTS: From an initial pool of 25,436 studies, a total of 76 studies involving 13,991,683 participants met the predefined eligibility criteria. The analysis indicated that the overall effect size for individuals having their first pregnancy at age 20 or older, compared to those having it before age 20, was 0.54 (95% CI, 0.50 to 0.59) for cervical cancer, 0.82 (95% CI, 0.77 to 0.88) for ovarian cancer, and 0.96 (95% CI, 0.89 to 1.04) for uterine cancer. CONCLUSIONS Our findings suggest that experiencing one’s initial pregnancy at the age of 20 or above is associated with a significantly reduced risk of cervical and ovarian cancer. However, no significant association was found between first pregnancy at this age and uterine cancer.

OBJECTIVES: Despite several investigations, the association between adolescent pregnancy and gynecological cancers has yet to be conclusively established. To further explore this association, we conducted a meta-analysis of observational studies. METHODS: We conducted a comprehensive search of databases such as PubMed, Web of Science, and Scopus to identify studies investigating the link between adolescent pregnancy and gynecologic cancers. This search continued until February 20, 2023. To assess the heterogeneity among the studies, we used the I2-statistics. We also explored the potential presence of publication bias using the Begg and Egger tests. The overall effect sizes were reported as either risk ratio or odds ratio, accompanied by a 95% confidence interval (CI), using a random-effects model. RESULTS: From an initial pool of 25,436 studies, a total of 76 studies involving 13,991,683 participants met the predefined eligibility criteria. The analysis indicated that the overall effect size for individuals having their first pregnancy at age 20 or older, compared to those having it before age 20, was 0.54 (95% CI, 0.50 to 0.59) for cervical cancer, 0.82 (95% CI, 0.77 to 0.88) for ovarian cancer, and 0.96 (95% CI, 0.89 to 1.04) for uterine cancer. CONCLUSIONS Our findings suggest that experiencing one’s initial pregnancy at the age of 20 or above is associated with a significantly reduced risk of cervical and ovarian cancer. However, no significant association was found between first pregnancy at this age and uterine cancer.

OBJECTIVES: Despite several investigations, the association between adolescent pregnancy and gynecological cancers has yet to be conclusively established. To further explore this association, we conducted a meta-analysis of observational studies. METHODS: We conducted a comprehensive search of databases such as PubMed, Web of Science, and Scopus to identify studies investigating the link between adolescent pregnancy and gynecologic cancers. This search continued until February 20, 2023. To assess the heterogeneity among the studies, we used the I2-statistics. We also explored the potential presence of publication bias using the Begg and Egger tests. The overall effect sizes were reported as either risk ratio or odds ratio, accompanied by a 95% confidence interval (CI), using a random-effects model. RESULTS: From an initial pool of 25,436 studies, a total of 76 studies involving 13,991,683 participants met the predefined eligibility criteria. The analysis indicated that the overall effect size for individuals having their first pregnancy at age 20 or older, compared to those having it before age 20, was 0.54 (95% CI, 0.50 to 0.59) for cervical cancer, 0.82 (95% CI, 0.77 to 0.88) for ovarian cancer, and 0.96 (95% CI, 0.89 to 1.04) for uterine cancer. CONCLUSIONS Our findings suggest that experiencing one’s initial pregnancy at the age of 20 or above is associated with a significantly reduced risk of cervical and ovarian cancer. However, no significant association was found between first pregnancy at this age and uterine cancer.

Contrast-induced acute kidney injury (CI-AKI) is a frequent challenge following the injection of contrast media and its subsequent oxidative stress. The aim of the present study was to evaluate the preventive effects of coenzyme Q10 (Q10), as a mitochondrial-targeted antioxidant in CI-AKI in diabetic patients, who account for a large proportion of angiographic cases. A total of 118 diabetic patients were randomly assigned to receive 120 mg of oral coenzyme Q10 (Q10 group) or placebo (Placebo group) for four days, starting 24 hours before contrast media injection. Blood urea nitrogen (BUN), serum and urinary creatinine, estimated glomerular filtration rate (eGFR), urinary malondialdehyde (UMDA), urinary total antioxidant capacity (UTAC), and urinary mitochondrial to nuclearDNA ratios (mtDNADNA ratio) were evaluated before and after the treatment period. Urine sediments were also evaluated to report the urine microscopy score (UMS).The levels of BUN, serum and urine creatinine, and UMS were similar in the Q10 and placebo groups. EGFR was lower in the Q10 group before the treatment (p=0.013) but not after. The urinary mtDNADNA ratio was 3.05±1.68 and 3.69±2.58 in placebo and Q10 groups, but UTAC was found to be lower in Q10 both before (p=0.006) and after the treatment (p＜0.001). The incidence of CI-AKI was 14.40% and the mtDNANDA ratio was similar between CI-AKI and non-CI-AKI patients. In conclusion, Q10 treatment shows no favorable effect on prevention of CI-AKI or a urinary mtDNADNA ratio among diabetic patients.

OBJECTIVES: Chronic kidney disease (CKD) is a major public health problem worldwide. Predicting CKD incidence rates and case numbers at the national and global levels is vital for planning CKD prevention programs. METHODS: Data on CKD incidence rates and case numbers in Iran from 1990 to 2019 were extracted from the Global Burden of Disease online database. The average annual percentage change was computed to determine the temporal trends in CKD age-standardized incidence rates from 1990 to 2019. A Bayesian age-period-cohort model was used to predict the CKD incidence rate and case numbers through 2030. RESULTS: Nationally, CKD cases increased from 97,300 in 1990 to 315,500 in 2019. The age-specific CKD incidence rate increased from 168.52 per 100,000 to 382.98 per 100,000 during the same period. Between 2020 and 2030, the number of CKD cases is projected to rise to 423,300. The age-specific CKD incidence rate is projected to increase to 469.04 in 2030 (95% credible interval, 399.20 to 538.87). In all age groups and etiological categories, the CKD incidence rate is forecasted to increase by 2030. CONCLUSIONS CKD case numbers and incidence rates are anticipated to increase in Iran through 2030. The high level of CKD incidence in people with diabetes mellitus, hypertension, and glomerulonephritis, as well as in older people, suggests a deficiency of attention to these populations in current prevention plans and highlights their importance in future programs for the national control of CKD.

Although several causal models relevant to epidemiology have been proposed, a key question that has remained unanswered is why some people at high-risk for a particular disease do not develop the disease while some people at low-risk do develop it. The equivalence model, proposed herein, addresses this dilemma. The equivalence model provides a graphical description of the overall effect of risk and protective factors at the individual level. Risk factors facilitate the occurrence of the outcome (the development of disease), whereas protective factors inhibit that occurrence. The equivalence model explains how the overall effect relates to the occurrence of the outcome. When a balance exists between risk and protective factors, neither can overcome the other; therefore, the outcome will not occur. Similarly, the outcome will not occur when the units of the risk factor(s) are less than or equal to the units of the protective factor(s). In contrast, the outcome will occur when the units of the risk factor(s) are greater than the units of the protective factor(s). This model can be used to describe, in simple terms, causal inferences in complex situations with multiple known and unknown risk and protective factors. It can also justify how people with a low level of exposure to one or more risk factor(s) may be affected by a certain disease while others with a higher level of exposure to the same risk factor(s) may remain unaffected.

OBJECTIVES: This report provides information on 14 behavioral and nutritional factors that can be addressed in stomach cancer prevention programs. METHODS: PubMed, Web of Science, and Scopus were searched through December 2018. Reference lists were also screened. Observational studies addressing the associations between stomach cancer and behavioral factors were analyzed. Between-study heterogeneity was investigated using the χ2, τ2, and I2 statistics. The likelihood of publication bias was explored using the Begg and Egger tests and trim-and-fill analysis. Effect sizes were expressed as odds ratios (ORs) with 95% confidence intervals (CIs) using a random-effects model. RESULTS: Of 52,916 identified studies, 232 (including 33,831,063 participants) were eligible. The OR (95% CI) of factors associated with stomach cancer were as follows: Helicobacter pylori infection, 2.56 (95% CI, 2.18 to 3.00); current smoking, 1.61 (95% CI, 1.49 to 1.75); former smoking 1.43 (95% CI, 1.29 to 1.59); current drinking, 1.19 (95% CI, 1.10 to 1.29); former drinking, 1.73 (95% CI, 1.17 to 2.56); overweight/obesity, 0.89 (95% CI, 0.74 to 1.08); sufficient physical activity, 0.83 (95% CI, 0.68 to 1.02); consumption of fruits ≥3 times/wk, 0.48 (95% CI, 0.37 to 0.63); consumption of vegetables ≥3 times/wk, 0.62 (95% CI, 0.49 to 0.79); eating pickled vegetables, 1.28 (95% CI, 1.09 to 1.51); drinking black tea, 1.00 (95% CI, 0.84 to 1.20); drinking green tea, 0.88 (95% CI, 0.80 to 0.97); drinking coffee, 0.99 (95% CI, 0.88 to 1.11); eating fish ≥1 time/wk 0.79 (95% CI, 0.61 to 1.03); eating red meat ≥4 times/wk 1.31 (95% CI, 0.87 to 1.96), and high salt intake 3.78 (95% CI, 1.74 to 5.44) and 1.34 (95% CI, 0.88 to 2.03), based on two different studies. CONCLUSIONS This meta-analysis provided a clear picture of the behavioral and nutritional factors associated with the development of stomach cancer. These results may be utilized for ranking and prioritizing preventable risk factors to implement effective prevention programs.

Although several causal models relevant to epidemiology have been proposed, a key question that has remained unanswered is why some people at high-risk for a particular disease do not develop the disease while some people at low-risk do develop it. The equivalence model, proposed herein, addresses this dilemma. The equivalence model provides a graphical description of the overall effect of risk and protective factors at the individual level. Risk factors facilitate the occurrence of the outcome (the development of disease), whereas protective factors inhibit that occurrence. The equivalence model explains how the overall effect relates to the occurrence of the outcome. When a balance exists between risk and protective factors, neither can overcome the other; therefore, the outcome will not occur. Similarly, the outcome will not occur when the units of the risk factor(s) are less than or equal to the units of the protective factor(s). In contrast, the outcome will occur when the units of the risk factor(s) are greater than the units of the protective factor(s). This model can be used to describe, in simple terms, causal inferences in complex situations with multiple known and unknown risk and protective factors. It can also justify how people with a low level of exposure to one or more risk factor(s) may be affected by a certain disease while others with a higher level of exposure to the same risk factor(s) may remain unaffected.

OBJECTIVES: This report provides information on 14 behavioral and nutritional factors that can be addressed in stomach cancer prevention programs. METHODS: PubMed, Web of Science, and Scopus were searched through December 2018. Reference lists were also screened. Observational studies addressing the associations between stomach cancer and behavioral factors were analyzed. Between-study heterogeneity was investigated using the χ2, τ2, and I2 statistics. The likelihood of publication bias was explored using the Begg and Egger tests and trim-and-fill analysis. Effect sizes were expressed as odds ratios (ORs) with 95% confidence intervals (CIs) using a random-effects model. RESULTS: Of 52,916 identified studies, 232 (including 33,831,063 participants) were eligible. The OR (95% CI) of factors associated with stomach cancer were as follows: Helicobacter pylori infection, 2.56 (95% CI, 2.18 to 3.00); current smoking, 1.61 (95% CI, 1.49 to 1.75); former smoking 1.43 (95% CI, 1.29 to 1.59); current drinking, 1.19 (95% CI, 1.10 to 1.29); former drinking, 1.73 (95% CI, 1.17 to 2.56); overweight/obesity, 0.89 (95% CI, 0.74 to 1.08); sufficient physical activity, 0.83 (95% CI, 0.68 to 1.02); consumption of fruits ≥3 times/wk, 0.48 (95% CI, 0.37 to 0.63); consumption of vegetables ≥3 times/wk, 0.62 (95% CI, 0.49 to 0.79); eating pickled vegetables, 1.28 (95% CI, 1.09 to 1.51); drinking black tea, 1.00 (95% CI, 0.84 to 1.20); drinking green tea, 0.88 (95% CI, 0.80 to 0.97); drinking coffee, 0.99 (95% CI, 0.88 to 1.11); eating fish ≥1 time/wk 0.79 (95% CI, 0.61 to 1.03); eating red meat ≥4 times/wk 1.31 (95% CI, 0.87 to 1.96), and high salt intake 3.78 (95% CI, 1.74 to 5.44) and 1.34 (95% CI, 0.88 to 2.03), based on two different studies. CONCLUSIONS This meta-analysis provided a clear picture of the behavioral and nutritional factors associated with the development of stomach cancer. These results may be utilized for ranking and prioritizing preventable risk factors to implement effective prevention programs.