OBJECTIVE: This study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study.
METHODS: Using publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell\'s C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years).
RESULTS: For the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method with PT = 0.05 and R2 = 0.2) derived from Japanese-ancestry GWAS, the Harrell\'s C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64-3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell\'s C-statistics 0.598 versus 0.586).
CONCLUSIONS: This study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.

A secular trend can be observed throughout the world with an increase in childhood obesity and a decrease in fitness. The research aimed to examine the results of tests measuring the conditional abilities of young boys aged 14-18 in fitness tests and their correlations with body composition indicators. That was supported by research that has been prepared in Hungary so far. This research focuses on the results of fitness tests conducted on 14- to 18-year-old boys, presented along with body composition data. The authors sought to describe the development of the fitness profiles of males at a Budapest secondary school participating in the research, based on the results of the Hungarian National Student Fitness Test (NETFIT®), and also how their physical characteristics affect the results of NETFIT® tests in the sample measured. A total of 735 male high school students at a Budapest secondary school (14-18 years old) (mean ± SD, 16.05 ± 1.18 years) participated in the survey. The data were collected in the 2018/2019 academic year, and it was compared with the national data. The correlation between the performance indicators of the NETFIT® tests and the physical characteristic indicators was analyzed using the two-block Partial Least Squares method. In the resulting groups, Kruskal-Wallis variance analysis was performed to investigate the differences in performance. In contrast, pairs of group differences were tested with the Mann-Whitney test. Boys with a short physique were at some advantage in trunk-lifts and push-ups, compared to taller boys. It was also obvious that being overweight is a hindrance regarding the PACER test or the standing broad jump. The handgrip in the left and right hand was mostly of similar strength or weakness. Tall-heavy children performed better in this test. The grip strength of tall-thin students was also strong, but not as strong as in the tall-heavy group. Reducing the percentage of body fat (PBF) and creating the optimal BMI index is important for the younger age group, as our results have clearly demonstrated that overweight is a hindrance in the PACER, VO2 max, standing broad jump, back-saver sit-and-reach, and push-up tests.

BACKGROUND: The recent Austrian Primary Care Act established new primary health care units (PHCUs) and obliged them to draw up a \"care strategy\" specifying their focal care tasks and objectives and emphasizing the health care needs of the population in their catchment area with its specific local health and epidemiological profile. The main purpose of these care strategies is thus to ensure that care-providers meet the local needs, but they also provide a rationale for evaluation and organizational development. To assist new PHCUs in establishing care strategies it was necessary to develop a method for automatically generating comprehensive local case studies for any freely definable location in Austria.
RESULTS: We designed an interactive report generator capable of producing location-specific regional health care profiles for a PHCU located in any of Austria\'s 2122 municipalities and of calculating the radius of its catchment area (defined by different levels of maximum car-travelling times). The reports so generated, called \"regional health care profiles for primary health care\" (RHCPs/PHC), are in comprehensive PDF report format. The core of each report is a set of 35 indicators, classified under five health and health service domains. The reports include an introductory text, definitions, a map, a graphic and tabular presentation of all indicator values, including information on local, supra-regional and national value distribution, a ranking, and numbers of service providers (e.g. pharmacies, surgeries, nursing homes) located within the catchment area.
CONCLUSIONS: The RHCPs/PHC support primary health care planning, efforts to improve care-effectiveness, and strategic organizational development by providing comprehensive information on the health of the population, the utilization of health services and the health care structures within the catchment area. In addition to revealing the scope and nature of the health care needed, they also provide information on what public health approaches are necessary. RHCPs/PHC for different locations have already been distributed to numerous stakeholders and primary health care providers in Austria.

To investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally.
Publicly available register-based ecological study.
Two hundred and nine countries/territories in the world.
Aggregated data including 10 445 656 confirmed COVID-19 cases.
COVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website.
The average of country/territory-specific COVID-19 CFR is about 2%-3% worldwide and higher than previously reported at 0.7%-1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR.
The association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.

In recent years, an elevated concentration of nitrate in groundwater has been a growing problem on a global scale. It directly shows the adverse effects on human health via various intake pathways. Herein, the aim of the present study was to evaluate the nitrate concentration in groundwater and its associated human health risk in various age groups (females, males and children) in the investigated region. For this purposes, thirty groundwater samples were collected and analyzed physico-chemical parameters including nitrate concentration. The results showed that, the concentration of nitrate ranges from 14 to 82 mg/L and about 43.3% of these groundwater samples beyond the safe level of 45 mg/L according to Indian guidelines. The higher nitrate contamination is observed in the vicinity of Sarvepalli and Timmapur villages where groundwater chemistry is majorly influenced by anthropogenic sources. Health risks were assessed through oral/ingestion and dermal contact exposure routes for females, males and children population in the study region. Oral exposure was much higher than dermal contacts. For the non-carcinogenic risk, the HITotal values of groundwater in the investigated region varied from 0.313 to 1.976 (mean of 0.941) for males, 0.370 to 2.336 (mean of 1.112) for females and 0.443 to 2.694 (mean of 1.314) for children. The health risk assessment for nitrate divulged that 60%, 57% and 50% of groundwater samples pose a non-carcinogenic health risk for children, females and males, respectively.

Coronavirus disease 2019, i.e. COVID-19, started as an outbreak in a district of China and has engulfed the world in a matter of 3 months. It is posing a serious health and economic challenge worldwide. However, case fatality rates (CFRs) have varied amongst various countries ranging from 0 to 8.91%. We have evaluated the effect of selected socio-economic and health indicators to explain this variation in CFR. Countries reporting a minimum of 50 cases as on 14th March 2020, were selected for this analysis. Data about the socio-economic indicators of each country was accessed from the World bank database and data about the health indicators were accessed from the World Health Organisation (WHO) database. Various socioeconomic indicators and health indicators were selected for this analysis. After selecting from univariate analysis, the indicators with the maximum correlation were used to build a model using multiple variable linear regression with a forward selection of variables and using adjusted R-squared score as the metric. We found univariate regression results were significant for GDP (Gross Domestic Product) per capita, POD 30/70 (Probability Of Dying Between Age 30 And Exact Age 70 From Any of Cardiovascular Disease, Cancer, Diabetes or Chronic Respiratory Disease), HCI (Human Capital Index), GNI(Gross National Income) per capita, life expectancy, medical doctors per 10000 population, as these parameters negatively corelated with CFR (rho = -0.48 to -0.38 , p<0.05). Case fatality rate was regressed using ordinary least squares (OLS) against the socio-economic and health indicators. The indicators in the final model were GDP per capita, POD 30/70, HCI, life expectancy, medical doctors per 10,000, median age, current health expenditure per capita, number of confirmed cases and population in millions. The adjusted R-squared score was 0.306. Developing countries with a poor economy are especially vulnerable in terms of COVID-19 mortality and underscore the need to have a global policy to deal with this on-going pandemic. These trends largely confirm that the toll from COVID-19 will be worse in countries ill-equipped to deal with it. These analyses of epidemiological data are need of time as apart from increasing situational awareness, it guides us in taking informed interventions and helps policy-making to tackle this pandemic.

Osteosarcopenia (loss of skeletal muscle and bone mass and/or function usually associated with aging) shares pathophysiological mechanisms with polycystic ovary syndrome (PCOS). However, the relationship between osteosarcopenia and PCOS remains unclear.
We evaluated skeletal muscle index% (SMI% = [appendicular muscle mass/weight (kg)] × 100) and bone mineral density (BMD) in PCOS (hyperandrogenism + oligoamenorrhea), and contrasted these musculoskeletal markers against 3 reproductive phenotypes (i): HA (hyperandrogenism + eumenorrhea) (ii); OA (normoandrogenic + oligoamenorrhea) and (iii), controls (normoandrogenic + eumenorrhea). Endocrine predictors of SMI% and BMD were evaluated across the groups.
Multicenter case-control study of 203 women (18-48 years old) in New York State.
PCOS group exhibited reduced SMI% (mean [95% confidence interval (CI)]; 26.2% [25.1,27.3] vs 28.8% [27.7,29.8]), lower-extremity SMI% (57.6% [56.7,60.0] vs 62.5% [60.3,64.6]), and BMD (1.11 [1.08,1.14] vs 1.17 [1.14,1.20] g/cm2) compared to controls. PCOS group also had decreased upper (0.72 [0.70,0.74] vs 0.77 [0.75,0.79] g/cm2) and lower (1.13 [1.10,1.16] vs 1.19 [1.16,1.22] g/cm2) limb BMD compared to HA. Matsuda index was lower in PCOS vs controls and positively associated with SMI% in all groups (all Ps ≤ 0.05). Only controls showed associations between insulin-like growth factor (IGF) 1 and upper (r = 0.84) and lower (r = 0.72) limb BMD (all Ps < 0.01). Unlike in PCOS, IGF-binding protein 2 was associated with SMI% in controls (r = 0.45) and HA (r = 0.67), and with upper limb BMD (r = 0.98) in HA (all Ps < 0.05).
Women with PCOS exhibit early signs of osteosarcopenia when compared to controls likely attributed to disrupted insulin function. Understanding the degree of musculoskeletal deterioration in PCOS is critical for implementing targeted interventions that prevent and delay osteosarcopenia in this clinical population.

BACKGROUND: During healthcare guideline development, panel members often have implicit, different definitions of health outcomes that can lead to misunderstandings about how important these outcomes are and how to balance benefits and harms. McMaster GRADE Centre researchers developed \'health outcome descriptors\' for standardizing descriptions of health outcomes and overcoming these problems to support the European Commission Initiative on Breast Cancer (ECIBC) Guideline Development Group (GDG). We aimed to determine which aspects of the development, content, and use of health outcome descriptors were valuable to guideline developers.
METHODS: We developed 24 health outcome descriptors related to breast cancer screening and diagnosis for the European Commission Breast Guideline Development Group (GDG). Eighteen GDG members provided feedback in written format or in interviews. We then evaluated the process and conducted two health utility rating surveys.
RESULTS: Feedback from GDG members revealed that health outcome descriptors are probably useful for developing recommendations and improving transparency of guideline methods. Time commitment, methodology training, and need for multidisciplinary expertise throughout development were considered important determinants of the process. Comparison of the two health utility surveys showed a decrease in standard deviation in the second survey across 21 (88%) of the outcomes.
CONCLUSIONS: Health outcome descriptors are feasible and should be developed prior to the outcome prioritization step in the guideline development process. Guideline developers should involve a subgroup of multidisciplinary experts in all stages of development and ensure all guideline panel members are trained in guideline methodology that includes understanding the importance of defining and understanding the outcomes of interest.

Continuous glucose monitoring (CGM) use is growing rapidly among people with diabetes and beginning to be standard of care for managing glucose levels in insulin therapy. With this increased use, there is a need to standardize CGM data. CGM standardization has been set forth by expert panels. The Glucose Management Indicator is a concept using the CGM-derived mean glucose to provide a value that can be understood similarly to hemoglobin A1c. The times an individual spends in various glucose ranges is emerging as an important set of metrics. Metrics derived from patient CGM data are changing the way diabetes is managed.

Breast cancer is the most common cancer in women globally, and the risk of developing breast cancer is associated with inflammation. The present study aimed to examine the association between the Dietary Inflammatory Index (DII®) and breast cancer in Korean women and investigate whether the tumor\'s hormone receptor status affects this association. In this case-control study, we enrolled 364 breast cancer patients and 364 age-matched controls. DII scores were calculated from dietary intake evaluated by a 106-item food frequency questionnaire. The DII score was significantly higher in cases than in controls. After adjusting for potential confounders, the odds ratio (OR) of breast cancer was higher in the highest DII tertile (OR = 3.68, 95% confidence interval (CI): 2.34-5.80, p for trend < 0.0001) than in the lowest tertile. We found that higher DII scores were related to an increased risk of breast cancer for estrogen receptor (ER)+/progesterone receptor (PR)+ tumors regardless of menopausal status (OR = 2.59, 95% CI: 1.37-4.88 in the highest DII category, p for trend = 0.01 for premenopausal women; OR = 11.00, 95% CI: 2.93-41.30 in the highest DII category, p for trend = 0.0004 for postmenopausal women), but not for ER-/PR- status. Our results suggested that the DII scores are positively associated with breast cancer risk in Korean women and that this relationship is more robust in ER+/PR+ tumors.