Epidemiology of Cancers in Zambia: A significant variation in Cancer incidence and prevalence across the nation

BackgroundCancer is one of the leading causes of death worldwide. More than two-thirds of deaths due to cancers occur in low- and middle-income countries where Zambia belongs. This study, therefore, sought to assess the epidemiology of various types of cancers in Zambia.MethodsWe conducted a retrospective observational study using the Zambia National Cancer Registry (ZNCR) population based data from 2007 to 2014. Zambia Central Statistics Office (CSO) demographic data were used to determine catchment area denominator used to calculate prevalence and incidence rates of cancers. Age-adjusted rates and case fatality rates were estimated using standard methods. We used a Poisson Approximation for calculating 95% confidence intervals (CI). ResultsThe seven most cancer prevalent districts in Zambia were Luangwa, Kabwe, Lusaka, Monze, Mongu, Katete and Chipata. Cervical cancer, prostate cancer, breast cancer and Kaposi’s sarcoma were the four most prevalent cancers as well as major causes of cancer related deaths in Zambia. Age adjusted rates and 95% CI for these cancers were: cervix uteri (186.3; CI = 181.77 – 190.83), prostate (60.03; CI = 57.03 – 63.03), breast (38.08; CI = 36.0 – 40.16) and Kaposi’s sarcoma (26.18; CI = 25.14 – 27.22). CFR were: Leukaemia (38.1%); pancreatic cancer (36.3%); lung cancer (33.3%); and brain, nervous system (30.2%). The cancer population was associated with HIV with p- value of 0.000 and a Pearson correlation coefficient of 0.818.ConclusionsThe widespread distribution of cancers with high prevalence observed in the southern zone may have been perpetrated by lifestyle and sexual culture (traditional male circumcision known to prevent STIs is practiced in the northern belt) as well as geography. Intensifying cancer screening and early detection countrywide as well as changing the lifestyle and sexual culture would greatly help in the reduction of cancer cases in Zambia

Digitalisation for water sustainability: Barriers to implementing circular economy in smart water management

“Clean water and sanitation” is listed as one of the 17 United Nations’ Sustainable Development Goals and implementing circular economy principles in the water sector has been widely regarded as an important approach in achieving this goal. In the era of Industry 4.0, research and practice in the digitalisation of the water sector to create a smart water system have attracted increasing attention. Despite the growing interest, limited research has been devoted to how digital technologies might enhance circularity. In practice, smart water systems often fail to promote circularity in such aspects as water reuse and resources recovery. This paper aims to identify the main barriers to implementing circularity in the smart water management system in Zhejiang, China. The research adopts a mixed research method that includes a literature review to identify the potential barriers from the existing studies, a case study to determine the most critical barriers in practice, and a fuzzy Delphi method to reach a consensus on the crucial barriers. The research identified 22 main barriers to implementing circular economy in smart water management. The barriers are divided into three categories: infrastructure and economic, technology, and institution and governance. The results show that the barriers related to recycling technologies, digital technology know-how, and the lack of CE awareness raise the most concern. Our findings also indicate that experts are interested in the decentralized wastewater treatment system. This research provides significant insights that practitioners, researchers, and policymakers can use in developing and implementing digital-based CE strategies to reduce water scarcity and pollution

Establishment of Prognostic Models for Astrocytic and Oligodendroglial Brain Tumors with Standardized Quantification of Marker Gene Expression and Clinical Variables

Background Prognosis models established using multiple molecular markers in cancer along with clinical variables should enable prediction of natural disease progression and residual risk faced by patients. In this study, multivariate Cox proportional hazards analyses were done based on overall survival (OS) of 100 glioblastoma multiformes (GBMs, 92 events), 49 anaplastic astrocytomas (AAs, 33 events), 45 gliomas with oligodendroglial features, including anaplastic oligodendroglioma (AO, 13 events) and oligodendraglioma (O, 9 events). The modeling included two clinical variables (patient age and recurrence at the time of sample collection) and the expression variables of 13 genes selected based on their proven biological and/or prognosis functions in gliomas ( ABCG2, BMI1, MELK, MSI1, PROM1, CDK4, EGFR, MMP2, VEGFA, PAX6, PTEN, RPS9, and IGFBP2 ). Gene expression data was a log-transformed ratio of marker and reference ( ACTB ) mRNA levels quantified using absolute real-time qRT-PCR. Results Age is positively associated with overall grade (4 for GBM, 3 for AA, 2_1 for AO_O), but lacks significant prognostic value in each grade. Recurrence is an unfavorable prognostic factor for AA, but lacks significant prognostic values for GBM and AO_O. Univariate models revealed opposing prognostic effects of ABCG2, MELK, BMI1, PROM1, IGFBP2, PAX6, RPS9 , and MSI1 expressions for astrocytic (GBM and AA) and oligodendroglial tumors (AO_O). Multivariate models revealed independent prognostic values for the expressions of MSI1 (unfavorable) in GBM, CDK4 (unfavorable) and MMP2 (favorable) in AA, while IGFBP2 and MELK (unfavorable) in AO_O. With all 13 genes and 2 clinical variables, the model R 2 was 14.2% ( P = 0.358) for GBM, 45.2% ( P = 0.029) for AA, and 62.2% ( P = 0.008) for AO_O. Conclusion The study signifies the challenge in establishing a significant prognosis model for GBM. Our success in establishing prognosis models for AA and AO_O was largely based on identification of a set of genes with independent prognostic values and application of standardized gene expression quantification to allow formation of a large cohort in analysis

Using multivariate quantile regression analysis to explore cardiovascular risk differences in subjects with chronic kidney disease by race and ethnicity: Findings from the U.S. Chronic Renal Insufficiency Cohort Study

Background and Aims: Adults with chronic kidney disease (CKD) carry an extraordinarily high risk for cardiovascular disease (CVD). The present study aimed to test two hypotheses that: (1) CVD risk factors disproportionately affect non-Hispanic black (NHB) with CKD compared to non-Hispanic white (NHW). (2) This difference significantly contributes to an excess risk of CVD in NHB versus NHW. Methods: A total of 3,939 aged 21-74 years old participating in the Chronic Renal Insufficiency Cohort Study was analyzed. A sum weighted CVDRisk score was constructed from well-established CVD risk factors. Differences in CVD Risk score by race/ethnicity were tested using quantile regression (Qreg) analysis. Results: The prevalence of CVD was 30.7% in NHW and 38.2% in NHB (p<0.001). The means (SD) of CVD Risk score were 12.6 (5.7) in NHW and 14.6 (6.4) in NHB (p<0.001). Qreg analysis indicated that NHB with estimate glomerular filtration rate (eGFR) 30-59.9 ml/min/1.73m2 had significantly higher (worse) CVD Risk scores across all quantiles (Qs) than NHW. This race differences in CVD Risk were also significantly higher in NHB with eGFR 60-70 ml/min/1.73m2 in Qs 1 and 2 as compared to their NHW counterparts. An estimated 35.8% of the excess prevalent CVD could be attributable to the difference in CVD Risk for NHB versus NHW. Conclusion: NHB have a significantly higher CVD risk factor score in those with moderate and mild CKD than NHW

Geographic Variation in Heart Failure Mortality and Its Association With Hypertension, Diabetes, and Behavioral-Related Risk Factors in 1,723 Counties of the United States

Background and objectives Studies that examined geographic variation in heart failure (HF) and its association with risk factors at county and state levels were limited. This study aimed to test a hypothesis that HF mortality is disproportionately distributed across the United States, and this variation is significantly associated with the county- and state-level prevalence of high blood pressure (HBP), diabetes, obesity and physical inactivity. Methods: Data from 1,723 counties in 51 states (including District of Columbia as a state) on the age-adjusted prevalence of obesity, physical inactivity, HBP and diabetes in 2010, and age-adjusted HF mortality in 2013–2015 are examined. Geographic variations in risk factors and HF mortality are analyzed using spatial autocorrelation analysis and mapped using Geographic Information System techniques. The associations between county-level HF mortality and risk factors (level 1) are examined using multilevel hierarchical regression models, taking into consideration of their variations accounted for by states (level 2). Results: There are significant variations in HF mortality, ranging from the lowest 11.7 (the state of Vermont) to highest 85.0 (Mississippi) per 100,000 population among the 51 states. Age-adjusted prevalence of obesity, physical inactivity, HBP, and diabetes are positively and significantly associated with HF mortality. Multilevel analysis indicates that county-level HF mortality rates remain significantly associated with diabetes (β = 2.7, 95% CI: 1.7–3.7, p < 0.0001), HBP (β = 3.6, 2.1–5.0, p < 0.0001), obesity (β = 0.9, 0.6–1.3, p < 0.0001), and physical inactivity (β = 1.2, 0.8–1.5, p < 0.0001) after controlling for gender, race/ethnicity, and poverty index. After further controlling obesity and physical inactivity in diabetes and HBP models, the effects of diabetes (β = 1.0, −0.3 to 2.3, p = 0.12) and HBP (β = 2.4, 0.9–3.9, p = 0.003) on HF mortality had a considerable reduction. Conclusion: HF mortality disproportionately affects the counties and states across the nation. The geographic variations in HF morality are significantly explained by the variations in the prevalence of obesity, physical inactivity, diabetes, and HBP

Population based studies of fibrinogen in relation to other coronary heart disease risk factors, coronary heart disease and diabetesmellitus in Hong Kong

published_or_final_versionCommunity MedicineDoctoralDoctor of Philosoph

Does VAT retention rate affect firms’ capacity utilization? Evidence from China

Value-added tax (VAT) is shared between central and local governments, and is levied based on firms' production location, which provides incentives for local governments to intervene in firms' production. This paper investigates how local governments' VAT retention rate affect firms' capacity utilization theoretically and empirically. We find that the more VAT retained by local governments', the lower the firm's capacity utilization. Our findings suggest the fiscal and taxation system reform should correct local governments' improper incentives and eliminate the negative effects of the distorted intergovernmental fiscal relationships on firms