ABSTRACT
BACKGROUND: Predictive modelling using pre-epidemic data have long been used to guide public health responses to communicable disease outbreaks and other health disruptions. In this study, cancer registry and related health data available 2-3 months from diagnosis were used to predict changes in cancer detection that otherwise would not have been identified until full registry processing was completed about 18-24 months later. A key question was whether these earlier data could be used to predict cancer incidence ahead of full processing by the cancer registry as a guide to more timely health responses. The setting was the Australian State of New South Wales, covering 31â¯% of the Australian population. The study year was 2020, the year of emergence of the COVID-19 pandemic. METHODS: Cancer detection in 2020 was modelled using data available 2-3 months after diagnosis. This was compared with data from full registry processing available from 2022. Data from pre-pandemic 2018 were used for exploratory model building. Models were tested using pre-pandemic 2019 data. Candidate predictor variables included pathology, surgery and radiation therapy reports, numbers of breast screens, colonoscopies, PSA tests, and melanoma excisions recorded by the universal Medical Benefits Schedule (MBS). Data were analysed for all cancers collectively and 5 leading types. RESULTS: Compared with full registry processing, modelled data for 2020 had a >95â¯% accuracy overall, indicating key points of inflexion of cancer detection over the COVID-disrupted 2020 period. These findings highlight the potential of predictive modelling of cancer-related data soon after diagnosis to reveal changes in cancer detection during epidemics and other health disruptions. CONCLUSIONS: Data available 2-3 months from diagnosis in the pandemic year indicated changes in cancer detection that were ultimately confirmed by fully-processed cancer registry data about 24 months later. This indicates the potential utility of using these early data in an early-warning system.
Subject(s)
COVID-19 , Early Detection of Cancer , Neoplasms , Pandemics , Registries , Humans , COVID-19/epidemiology , COVID-19/diagnosis , Neoplasms/epidemiology , Neoplasms/diagnosis , Incidence , Early Detection of Cancer/statistics & numerical data , Early Detection of Cancer/methods , Female , Male , SARS-CoV-2/isolation & purification , Australia/epidemiology , New South Wales/epidemiology , Epidemics , Coronavirus Infections/epidemiology , Coronavirus Infections/diagnosisABSTRACT
There were no pediatric oncology centers in southwest Ethiopia prior to 2016. This study aims to describe presenting diagnoses and initial outcomes at Jimma University Medical Center (JUMC), the first pediatric oncology unit (POU) in southwest Ethiopia, provide initial insights into regional pediatric cancer epidemiology, illustrate the rapid growth of pediatric cancer services, and highlight ongoing challenges. We used a retrospective descriptive approach to assess the epidemiologic pattern and initial treatment outcomes of pediatric cancer at JUMC POU from August 2016 through December 2022. During the study period, 749 children were diagnosed with cancer at JUMC. The mean age was 7.2 years (20 days-18 years). Acute lymphoblastic leukemia was the most common diagnosis (16.4%), followed by non-Hodgkin lymphoma (12.4%), Wilms tumor (11.1%), soft tissue sarcoma (8.8%), Hodgkin lymphoma (8.4%), and retinoblastoma (8.3%). Brain tumors accounted for only 2.7% of the diagnoses. Of the 703 patients that were not referred elsewhere, 42% of the patients abandoned treatment, 29% died, 17% completed treatment, and 7% remained on treatment at the time of this assessment. The findings emphasize the growth in the diagnosis and treatment of children with cancer in the southwest region of Ethiopia. The data suggests a different epidemiologic profile of childhood cancer cases diagnosed at the JUMC POU compared to high-income countries and neighbouring countries in Africa. Treatment abandonment remains a barrier to care. Ongoing areas of focus include establishment of a hospital-based cancer registry, reduction of treatment abandonment, improvement of diagnostic capacity, and increased access to advanced supportive care.
ABSTRACT
BACKGROUND: Cohort studies linking greenspace exposure to a lower risk of obesity-related cancer (ORC) are scarce. Existing evidence on site-specific cancers has predominantly relied on non-specific greenspace measures, including vegetation indices. We examined the associations of total greenspace, private residential gardens, and other greenspace types with the risk of being diagnosed with overall and site-specific ORC. METHODS: We used data from the participants in the UK Biobank recruited between 2006 and 2010 and censored until December 31, 2016. We defined greenspace variables using Ordnance Survey MasterMap™ greenspace categories. The incidence of ORC was ascertained through data linkage to cancer registries. Hazard ratios (HRs) and 95 % confidence intervals (CIs) were estimated using Cox proportional hazard models and adjusted for covariates. We conducted mediation and modification analysis by physical activity, serum 25-hydroxyvitamin D [25(OH)D], and particulate matter air pollution with an aerodynamic diameter ≤ 2.5 (PM2.5) and nitrogen dioxide (NO2), as well as subgroup analysis by covariates. RESULTS: Among 279,326 participants, 9550 developed ORC over a median follow-up period of 7.82 years. An increase in private residential gardens within a 100 m buffer was associated with a decreased risk of overall ORC (HR:0.92; 95 % CI: 0.88, 0.96), breast cancer (HR: 0.91; 95 % CI: 0.84, 0.98), and uterine cancer (HR:0.80; 95 % CI: 0.67, 0.96). There was no association between other greenspace types and ORC, except for uterine cancer. The association for ORC was partly mediated by NO2 and modified by physical activity levels, 25(OH)D, PM2.5, and NO2, and sociodemographic factors, including sex and neighbourhood socioeconomic status. CONCLUSION: Increased exposure to private residential gardens may lower the risk of being diagnosed with obesity-related cancer, particularly breast and uterine cancer. Future studies might move beyond considering greenspace quantity to explore functional types of greenspace exposure that should be prioritized for targeted health intervention and cancer prevention.
Subject(s)
Gardens , Neoplasms , Obesity , Adult , Aged , Female , Humans , Male , Middle Aged , Cohort Studies , Environmental Exposure/statistics & numerical data , Neoplasms/epidemiology , Obesity/epidemiology , Risk Factors , UK Biobank , United Kingdom/epidemiologyABSTRACT
BACKGROUND: In 2015, the World Health Organization introduced the concept of intrinsic capacity (IC) to define the individual-level characteristics that enable an older person to be and do the things they value. This study developed an intrinsic capacity score for UK Biobank study participants and validated its use as a tool for health outcome prediction, understanding healthy aging trajectories, and genetic research. METHODS: Our analysis included data from 45,208 UK biobank participants who had a complete record of the ten variables included in the analysis. Factor adequacy was tested using Kaiser-Meyer-Olkin, Barthelt's, and the determinant of matrix tests, and the number of factors was determined by the parallel analysis method. Exploratory and confirmatory factor analyses were employed to determine the structure and dimensionality of indicators. Finally, the intrinsic capacity score was generated, and its construct and predictive validities as well as reliability were assessed. RESULTS: The factor analysis identified a multidimensional construct comprising one general factor (intrinsic capacity) and five specific factors (locomotor, vitality, cognitive, psychological, and sensory). The bifactor structure showed a better fit (comparative fit index = 0.995, Tucker Lewis index = 0.976, root mean square error of approximation = 0.025, root mean square residual = 0.009) than the conventional five-factor structure. The intrinsic capacity score generated using the bifactor confirmatory factor analysis has good construct validity, as demonstrated by an inverse association with age (lower intrinsic capacity in older age; (ß) =-0.035 (95%CI: -0.036, -0.034)), frailty (lower intrinsic capacity score in prefrail participants, ß = -0.104 (95%CI: (-0.114, -0.094)) and frail participants, ß = -0.227 (95%CI: -0.267, -0.186) than robust participants), and comorbidity (a lower intrinsic capacity score associated with increased Charlson's comorbidity index, ß =-0.019 (95%CI: -0.022, -0.015)). The intrinsic capacity score also predicted comorbidity (a one-unit increase in baseline intrinsic capacity score led to a lower Charlson's comorbidity index, ß = 0.147 (95%CI: -0.173, -0.121)) and mortality (a one-unit increase in baseline intrinsic capacity score led to 25 % lower risk of death, odds ratio = 0.75(95%CI: 0.663, 0.848)). CONCLUSION: The bifactor structure showed a better fit in all goodness of fit tests. The intrinsic capacity construct has strong structural, construct, and predictive validities and is a promising tool for monitoring aging trajectories.
Subject(s)
Geriatric Assessment , UK Biobank , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Cognition , Factor Analysis, Statistical , Healthy Aging , Reproducibility of Results , United KingdomSubject(s)
Prostatic Neoplasms , UK Biobank , Male , Humans , Incidence , Biological Specimen Banks , Life Style , Prostatic Neoplasms/epidemiology , Risk Factors , DietABSTRACT
The evolution of microbes in response to conventional antimicrobials leads to antimicrobial resistance (AMR) and multidrug resistance (MDR), and it is a global threat to public health. Natural products are possible solutions to this massive challenge. In this study, the potential of Acanthus polystachyus extracts was investigated for phytochemical composition and biological properties as antimicrobials. Gas chromatography-mass spectra (GC-MS) analysis of methanol extract (ME) and essential oil (EO) detected 79 and 20 compounds, respectively. The major compounds identified in ME and their abundance were ß-sitosterol acetate (16.06%), cholest-5-en-3-yl (9Z)-9-octadecenoate (9.54%), 1-dodecanol (7.57%), (S)-(E)-(-)-4-acetoxy-1-phenyl-2-dodecen-1-one (6.03%), neophytadiene (5.7%), (E)-2-nonadecene (3.9%), hexanol-4-D2 (2.92%), and decane (2.4%). Most compounds have known bioactive functions. In EO, the major compounds were stearyl alcohol (25.38%); cis-9-tetradecenoic acid, isobutyl ester (22.95%); butyl 9-tetradecenoate (10.62%); 11,13-dimethyl-12-tetradecen-1-ol acetate (10.14%); ginsenol (3.48%); and diisooctyl phthalate (2.54%). All compounds are known to be bioactive. The antioxidant activity of ME and EO ranged from 48.3 to 84.2% radical scavenging activity (RSA) and 45.6 to 82% RSA, respectively, with dose dependency. The disc diffusion assay for the antimicrobial activity of ME revealed high inhibition against Acenetobacter baumannii (130.2%), Pseudomonas aeruginosa (100.3%), and Staphylococcus aureus (87.7%). The MIC, MBC/MFC, and MBIC values for ME were 0.5-1.0, 2-4, and 0.5-1.0 mg/mL and for EO were 0.31-0.62, 1.25-2.5, and 0.31-0.62 µL/mL, respectively, indicating inhibition potential as well as inhibition of biofilm formation. The tolerance test values indicated bactericidal activity against most strains and bacteriostatic/fungistatic activity against A. baumannii, E. faecalis, and C. albicans. The antiquorum sensing activity of ME achieved by pyocyanin inhibition assay on P. aeruginosa showed a 51.6% inhibition at 500 µg/mL. These results suggest that ME and EO derived from A. polystachyus leaves are potent, valuable, cost-effective antioxidants and antimicrobials. Both extracts may effectively combat pathogenic and resistant microbes.
ABSTRACT
Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
ABSTRACT
There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study applied different machine learning algorithms on multiple patient characteristics to predict uncontrolled diabetes. Patients with diabetes above the age of 18 from the All of Us Research Program were included. Random forest, extreme gradient boost, logistic regression, and weighted ensemble model algorithms were employed. Patients who had a record of uncontrolled diabetes based on the international classification of diseases code were identified as cases. A set of features including basic demographic, biomarkers and hematological indices were included in the model. The random forest model demonstrated high performance in predicting uncontrolled diabetes, yielding an accuracy of 0.80 (95% CI: 0.79-0.81) as compared to the extreme gradient boost 0.74 (95% CI: 0.73-0.75), the logistic regression 0.64 (95% CI: 0.63-0.65) and the weighted ensemble model 0.77 (95% CI: 0.76-0.79). The maximum area under the receiver characteristics curve value was 0.77 (random forest model), while the minimum value was 0.7 (logistic regression model). Potassium levels, body weight, aspartate aminotransferase, height, and heart rate were important predictors of uncontrolled diabetes. The random forest model demonstrated a high performance in predicting uncontrolled diabetes. Serum electrolytes and physical measurements were important features in predicting uncontrolled diabetes. Machine learning techniques may be used to predict uncontrolled diabetes by incorporating these clinical characteristics.
ABSTRACT
Introduction: The UK Biobank cognitive assessment data has been a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population. Given the diverse nature of this data, researchers use different approaches - from the use of a single test to composing the general intelligence score, g, across the tests. We argue that both approaches are suboptimal - one being too specific and the other one too general - and suggest a novel multifactorial solution to represent cognitive abilities. Methods: Using a combined Exploratory Factor (EFA) and Exploratory Structural Equation Modeling Analyses (ESEM) we developed a three-factor model to characterize an underlying structure of nine cognitive tests selected from the UK Biobank using a Cattell-Horn-Carroll framework. We first estimated a series of probable factor solutions using the maximum likelihood method of extraction. The best solution for the EFA-defined factor structure was then tested using the ESEM approach with the aim of confirming or disconfirming the decisions made. Results: We determined that a three-factor model fits the UK Biobank cognitive assessment data best. Two of the three factors can be assigned to fluid reasoning (Gf) with a clear distinction between visuospatial reasoning and verbal-analytical reasoning. The third factor was identified as a processing speed (Gs) factor. Discussion: This study characterizes cognitive assessment data in the UK Biobank and delivers an alternative view on its underlying structure, suggesting that the three factor model provides a more granular solution than g that can further be applied to study different facets of cognitive functioning in relation to health outcomes and to further progress examination of its biological underpinnings.
ABSTRACT
Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.
ABSTRACT
BACKGROUND: Genetic and lifestyle factors are associated with cancer risk. We investigated the benefits of adhering to lifestyle advice by the World Cancer Research Fund (WCRF) with the risk of 13 types of cancer and whether these associations differ according to genetic risk using data from the UK Biobank. METHODS: In 2006-2010, participants aged 37-73 years had their lifestyle assessed and were followed up for incident cancers until 2015-2019. Analyses were restricted to those of White European ancestry with no prior history of malignant cancer (n = 195â822). Polygenic risk scores (PRSs) were computed for 13 cancer types and these cancers combined ('overall cancer'), and a lifestyle index was calculated from WCRF recommendations. Associations with cancer incidence were estimated using Cox regression, adjusting for relevant confounders. Additive and multiplicative interactions between lifestyle index and PRSs were assessed. RESULTS: There were 15â240 incident cancers during the 1â926â987 person-years of follow-up (median follow-up = 10.2 years). After adjusting for confounders, the lifestyle index was associated with a lower risk of overall cancer [hazard ratio per standard deviation increase (95% CI) = 0.89 (0.87, 0.90)] and of eight specific cancer types. There was no evidence of interactions on the multiplicative scale. There was evidence of additive interactions in risks for colorectal, breast, pancreatic, lung and bladder cancers, such that the recommended lifestyle was associated with greater change in absolute risk for persons at higher genetic risk (P < 0.0003 for all). CONCLUSIONS: The recommended lifestyle has beneficial associations with most cancers. In terms of absolute risk, the protective association is greater for higher genetic risk groups for some cancers. These findings have important implications for persons most genetically predisposed to those cancers and for targeted strategies for cancer prevention.
Subject(s)
Life Style , Neoplasms , Humans , Incidence , Prospective Studies , Risk Factors , Neoplasms/epidemiology , Neoplasms/genetics , Neoplasms/prevention & controlABSTRACT
BACKGROUND AND AIMS: Analyses to predict the risk of cancer typically focus on single biomarkers, which do not capture their complex interrelations. We hypothesized that the use of metabolic profiles may provide new insights into cancer prediction. METHODS: We used information from 290,888 UK Biobank participants aged 37 to 73 years at baseline. Metabolic subgroups were defined based on clustering of biochemical data using an artificial neural network approach and examined for their association with incident cancers identified through linkage to cancer registry. In addition, we evaluated associations between 38 individual biomarkers and cancer risk. RESULTS: In total, 21,973 individuals developed cancer during the follow-up (median 3.87 years, interquartile range [IQR] = 2.03-5.58). Compared to the metabolically favorable subgroup (IV), subgroup III (defined as "high BMI, C-reactive protein & cystatin C") was associated with a higher risk of obesity-related cancers (hazard ratio [HR] = 1.26, 95 % CI = 1.21 to 1.32) and hematologic-malignancies (e.g., lymphoid leukemia: HR = 1.83, 95%CI = 1.44 to 2.33). Subgroup II ("high triglycerides & liver enzymes") was strongly associated with liver cancer risk (HR = 5.70, 95%CI = 3.57 to 9.11). Analysis of individual biomarkers showed a positive association between testosterone and greater risks of hormone-sensitive cancers (HR per SD higher = 1.32, 95%CI = 1.23 to 1.44), and liver cancer (HR = 2.49, 95%CI =1.47 to 4.24). Many liver tests were individually associated with a greater risk of liver cancer with the strongest association observed for gamma-glutamyl transferase (HR = 2.40, 95%CI = 2.19 to 2.65). CONCLUSIONS: Metabolic profile in middle-to-older age can predict cancer incidence, in particular risk of obesity-related cancer, hematologic malignancies, and liver cancer. Elevated values from liver tests are strong predictors for later risk of liver cancer.
Subject(s)
Biological Specimen Banks , Liver Neoplasms , Humans , Risk Factors , Obesity/complications , Biomarkers , Metabolome , United Kingdom/epidemiologyABSTRACT
BACKGROUND: Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15-59 years across SSA. METHODS: We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. RESULTS: We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. CONCLUSIONS: As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.
Subject(s)
Acquired Immunodeficiency Syndrome , HIV Infections , Male , Female , Adult , Humans , Pregnancy , Adolescent , Young Adult , Middle Aged , HIV , Acquired Immunodeficiency Syndrome/epidemiology , Prevalence , Seroepidemiologic Studies , HIV Infections/prevention & control , Africa South of the Sahara/epidemiologyABSTRACT
Hormone-related cancers, including cancers of the breast, prostate, ovaries, uterine, and thyroid, globally contribute to the majority of cancer incidence. We hypothesize that hormone-sensitive cancers share common genetic risk factors that have rarely been investigated by previous genomic studies of site-specific cancers. Here, we show that considering hormone-sensitive cancers as a single disease in the UK Biobank reveals shared genetic aetiology. We observe that a significant proportion of variance in disease liability is explained by the genome-wide single nucleotide polymorphisms (SNPs), i.e., SNP-based heritability on the liability scale is estimated as 10.06% (SE 0.70%). Moreover, we find 55 genome-wide significant SNPs for the disease, using a genome-wide association study. Pair-wise analysis also estimates positive genetic correlations between some pairs of hormone-sensitive cancers although they are not statistically significant. Our finding suggests that heritable genetic factors may be a key driver in the mechanism of carcinogenesis shared by hormone-sensitive cancers.
Subject(s)
Genome-Wide Association Study , Neoplasms , Biological Specimen Banks , Genetic Predisposition to Disease , Hormones , Humans , Male , Neoplasms/etiology , Neoplasms/genetics , United Kingdom/epidemiologyABSTRACT
BACKGROUND: Observational and Mendelian randomization (MR) studies link obesity and cancer, but it remains unclear whether these depend upon related metabolic abnormalities. METHODS: We used information from 321,472 participants in the UK biobank, including 30,561 cases of obesity-related cancer. We constructed three genetic instruments reflecting higher adiposity together with either "unfavourable" (82 SNPs), "favourable" (24 SNPs) or "neutral" metabolic profile (25 SNPs). We looked at associations with 14 types of cancer, previously suggested to be associated with obesity. RESULTS: All genetic instruments had a strong association with BMI (p < 1 × 10-300 for all). The instrument reflecting unfavourable adiposity was also associated with higher CRP, HbA1c and adverse lipid profile, while instrument reflecting metabolically favourable adiposity was associated with lower HbA1c and a favourable lipid profile. In MR-inverse-variance weighted analysis unfavourable adiposity was associated with an increased risk of non-hormonal cancers (OR = 1.22, 95% confidence interval [CI]:1.08, 1.38), but a lower risk of hormonal cancers (OR = 0.80, 95%CI: 0.72, 0.89). From individual cancers, MR analyses suggested causal increases in the risk of multiple myeloma (OR = 1.36, 95%CI: 1.09, 1.70) and endometrial cancer (OR = 1.77, 95%CI: 1.16, 2.68) by greater genetically instrumented unfavourable adiposity but lower risks of breast and prostate cancer (OR = 0.72, 95%CI: 0.61, 0.83 and OR = 0.81, 95%CI: 0.68, 0.97, respectively). Favourable or neutral adiposity were not associated with the odds of any individual cancer. CONCLUSIONS: Higher adiposity associated with a higher risk of non-hormonal cancer but a lower risk of some hormone related cancers. Presence of metabolic abnormalities might aggravate the adverse effects of higher adiposity on cancer. Further studies are warranted to investigate whether interventions on adverse metabolic health may help to alleviate obesity-related cancer risk.
Subject(s)
Neoplasms/diagnosis , Overweight/diagnosis , Adolescent , Adult , Cohort Studies , Female , Humans , Male , Mendelian Randomization Analysis/methods , Middle Aged , Neoplasms/epidemiology , Overweight/epidemiology , Retrospective Studies , United Kingdom/epidemiologyABSTRACT
Recent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitability concordant with locations where onchocerciasis has been previously detected. This threshold value was then used to classify IUs (more suitable or less suitable) based on the location within the IU with the largest mean prediction. Mean estimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. The ROC analysis identified a mean environmental suitability index of 0·71 as a threshold to classify based on the location with the largest mean prediction within the IU. Of the IUs considered for mapping surveys, 50·2% exceed this threshold for suitability in at least one 5 × 5-km location. The formidable scale of data collection required to map onchocerciasis endemicity across the African continent presents an opportunity to use spatial data to identify areas likely to be suitable for onchocerciasis transmission. National onchocerciasis elimination programmes may wish to consider prioritising these IUs for mapping surveys as human resources, laboratory capacity, and programmatic schedules may constrain survey implementation, and possibly delaying MDA initiation in areas that would ultimately qualify.
Subject(s)
Disease Eradication , Onchocerciasis/epidemiology , Africa/epidemiology , Environment , Forecasting , Humans , Ivermectin/administration & dosage , Mass Drug Administration , Onchocerciasis/drug therapy , Onchocerciasis/transmission , ROC CurveABSTRACT
BACKGROUND: Unsuppressed viral load in patients on antiretroviral (ARV) therapy occurs when treatment fails to suppress a patient's viral load, and is associated with decreased survival and increased HIV transmission. Identifying the level of unsuppressed viral load with its associated factors has benefits in controlling transmission and reducing burden. Therefore, this study aimed to assess unsuppressed viral load (>1,000 copies/mL) and associated factors among HIV patients taking first-line antiretroviral treatment at public health facilities in Jimma, Ethiopia. METHODS: A facility-based cross-sectional study was conducted on 669 patients on first-line ARV therapy (at least 6 months) in public health facilities in Jimma. Sociodemographic, treatment, clinical, immunological, and viral load data were extracted from medical records, entered into EpiData 3.1, and analyzed with SPSS 20. Multivariate logistic regression analysis was performed to identify factors independently associated with viral nonsuppression, considering a 95% CI with P<0.05 statistically significant. RESULTS: Among the participants, 258 (38.6%) were aged 25-34 years. Median age was 35 years. Prevalence of unsuppressed viral load was 20.3%. Risk of unsuppressed viral loads was 91% lower among ARV therapy patients who had been taking ARV therapy <2 years (AOR 0.09, 95% CI 0.01-0.83), lower baseline BMI (AOR 4.44, 95% CI 1.56-12.64), lower baseline CD4 (AOR 2.76, 95% CI 1.45-5.29), poor adherence to ARV therapy medication (AOR 3.19, 95% CI 1.29-7.89), and immunological failure (AOR 4.26, 95% CI 2.56-7.09) were the independent predictors of unsuppressed viral load. CONCLUSION: This study revealed that there is a high level of virological failure among adult HIV patients, and confirms the need to develop close follow-up strategies of targeted interventions for patients in care who are at high risk of unsuppressed viral load.
ABSTRACT
BACKGROUND: Sub-Saharan Africa shares a disproportionately large ratio of the global acute disease burden, however epidemiological data specific to the burden of emergency conditions are lacking. This study aimed to determine the morbidity burden of emergency conditions in Jimma city, Southwest Ethiopia. METHODS: A cross-sectional study was conducted using emergency case registries of three years from 2014 to 2017, at Jimma Medical Center and Shenen Gibe Hospital. 39,537 emergency visits were included in the study. The data were exported to SPSS V.23.0 for statistical analysis, descriptive analysis was used to summarize demographic characteristics, causes of visit, and morbidity rates. Findings were integrated with population-based health demographic reports quantifying the morbidity burden. Outcome measures were overall number of emergency visits and morbidity rates for the population groups. RESULTS: From a total of 39,537 visits, those between 15 and 29 years of age accounted for 42.1% (n = 16615), and 50.6% (n = 20004) were females. Communicable, Maternal, Neonatal and Nutritional (CMNNs) conditions accounted for 57.2%(n = 22597), followed by injuries (22.9%, n = 9055). Top five conditions were non-specific trauma (2.3%, n = 4861), complicated labor (8.4%, n = 3320), lower respiratory infections (8.1%, n = 3213), acute febrile illness (6.6%, n = 2600), and neonatal infections (3.7%, n = 1444). CONCLUSION: The burden of acute conditions presented to public hospitals in Jimma city is high. Traumatic injuries, obstetric emergencies, lower respiratory infections, and neonatal emergencies were the most frequent causes of acute visits. An appropriate emergency care system that addresses this high burden of acute emergencies should be established in the study area.
Subject(s)
Emergencies , Emergency Service, Hospital , Cross-Sectional Studies , Ethiopia/epidemiology , Female , Humans , Infant, Newborn , Morbidity , PregnancyABSTRACT
BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
Subject(s)
Global Burden of Disease , Global Health , Wounds and Injuries , Female , Humans , Incidence , Life Expectancy , Male , Morbidity , Quality-Adjusted Life Years , Wounds and Injuries/mortalityABSTRACT
BACKGROUND: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.