Public support for tobacco endgame policies in South Korea: Findings from the 2020 International Tobacco Control Korea Survey.

BACKGROUND: Strong public support can increase the likelihood of adopting tobacco control policies. We assessed support for six commercial tobacco endgame policies in South Korea: limiting the nicotine in cigarettes, banning all additives in cigarettes, restricting the number of places where cigarettes are sold, and banning the manufacture and sales of cigarettes (unconditionally, with the provision of cessation support and with alternative tobacco products available). METHODS: Data were obtained from 4740 adults who completed the 2020 International Tobacco Control Korea Survey. Participants were categorised based on their nicotine use: (1) did not use any products, (2) vaped and/or used heated tobacco products (HTPs) but did not smoke cigarettes, (3) smoked cigarettes only and (4) smoked cigarettes and vaped and/or used HTPs. Attitudes towards the policies were classified as supportive, undecided or opposed. Weighted multinomial logistic regression models assessed support levels according to nicotine use. RESULTS: Support was highest for limiting the nicotine content in cigarettes (68.4%; 95% CI 64.6% to 72.3%) and restricting the number of retailers (68.1%; 95% CI 64.5% to 71.7%), and lowest for banning cigarette sales if alternative products are made available (45.0%; 95% CI 40.9% to 49.1%). People who did not use any products were most likely to support endgame policies, except for banning cigarette sales with alternatives available. The proportion of undecided participants exceeded 10% (range 13%-25%) for all policies. CONCLUSION: There is a strong public support for tobacco endgame policies in South Korea. Further research should prioritise the development of strategies to ensure the effective implementation of highly supported policies.

Longitudinal Evaluation of Reproductive Endocrine Function in Men with ACTH-Dependent Cushing Syndrome.

CONTEXT: Hypogonadism may be caused by Cushing syndrome (CS) and may intensify its adverse consequences. OBJECTIVE: To determine the frequency of male hypogonadism before and after curative surgery for CS, and its cause. DESIGN: Post-hoc analyses of prospective cohort studies. SETTING: Clinical research center. PATIENTS: Men with ACTH-dependent CS. Cohort 1 (C1) (n=8, age 32.5±12 y; studied 1985-1989); Cohort 2 (C2) (n=44, 42.7 ± 15.1 y; studied 1989-2021). INTERVENTIONS: C1: Every 20-minute blood sampling for 24h before and 1-40 months after surgical cure. Three subjects underwent GnRH stimulation tests pre- and post-surgery. C2: Hormone measurements at baseline and 6 and 12 months (M) post-cure. MAIN OUTCOME MEASURES: C1: LH, FSH, LH pulse frequency and LH response to GnRH. C2: LH, FSH, testosterone (T), free T, fT4, T3, TSH and UFC levels and frequency of hypogonadism pre- and post-surgery. RESULTS: C1: mean LH and LH pulse frequency increased after surgery (p < 0.05) without changes in LH pulse amplitude, mean FSH, or peak gonadotropin response to GnRH. C2: 82% had baseline hypogonadism (total T 205 ± 28 ng/dL). Thyroid hormone levels varied inversely with UFC and cortisol. LH, total and free T, and SHBG increased at 6M and 12M post surgery, but hypogonadism persisted in 51% at 6M and in 26% at 12M. CONCLUSION: Hypogonadism in men with CS is widely prevalent but reversible in ∼75% of patients one year after surgical cure and appears to be mediated through suppression of hypothalamic GnRH secretion, and modulated by thyroid hormones.

Contributions of common genetic variants to constitutional delay of puberty and idiopathic hypogonadotropic hypogonadism.

CONTEXT: Constitutional delay of puberty (CDP) is highly heritable, but the genetic basis for CDP is largely unknown. Idiopathic hypogonadotropic hypogonadism (IHH) can be caused by rare genetic variants, but in about half of cases, no rare-variant cause is found. OBJECTIVE: To determine whether common genetic variants that influence pubertal timing contribute to CDP and IHH. DESIGN: Case-control study. PARTICIPANTS: 80 individuals with CDP; 301 with normosmic IHH, and 348 with Kallmann syndrome; control genotyping data from unrelated studies. MAIN OUTCOME MEASURES: Polygenic scores (PGS) based on genome-wide association studies for timing of male pubertal hallmarks and age at menarche (AAM). RESULTS: The CDP cohort had higher PGS for male pubertal hallmarks and for AAM compared to controls (for male hallmarks, Cohen's d = 0.85, p = 1 × 10-16; for AAM, d = 0.67, p = 1 × 10-10). The normosmic IHH cohort also had higher PGS for male hallmarks compared to controls, but the difference was smaller (male hallmarks d = 0.20, p = 0.003; AAM d = 0.10, p = 0.055). No differences were seen for the KS cohort compared to controls (male hallmarks d = 0.04, p = 0.45; AAM d = -0.03, p = 0.86). CONCLUSIONS: Common genetic variants that influence pubertal timing in the general population contribute strongly to the genetics of CDP, weakly to normosmic IHH, and potentially not at all to KS. These findings demonstrate that the common-variant genetics of CDP and normosmic IHH are largely but not entirely distinct.

Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study.

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests.

OBJECTIVE: Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (for example, endometriosis, ovarian cyst, and uterine fibroids). MATERIALS AND METHODS: We harmonized survey data from the Personalized Environment and Genes Study (PEGS) on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. RESULTS: Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant or suggestive predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. DISCUSSION: Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal but can support hypothesis generation. CONCLUSION: This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.