The Treatment of Sludge from the Rubber Processing Industry with Chitosan

Composite sludge samples were collected from a Rubber Processing industry. The collected sludge samples were characterized according to standard procedures. The values of some of the parameters were found to be 996.55 ± 5.85 NTU, 229.00 ± 7.80 mg/L and 1921.20 ± 6.50 mg/L for Turbidity, BOD and COD respectively. The Total Solids (TS) and Suspended Solids (SS) were 6217.00 ± 7.00 and 2733.00 ± 5.80 mg/L respectively. This portends pollution. Locally sourced coagulant, chitosan was obtained and the optimum dosage determined. It was found to be 2.10cm3 of 1% chitosan solution per 100 cm3 sludge at pH of 7.9. On the basis of this, the sludge was treated and the treated sludge sample, characterized. Triplicate determinations were done in each case and the mean values and standard deviations obtained from statistical evaluation using the Tukey-Kramer multiple comparison tests. From the results obtained, there were significant reductions (p 0.05) in pollution in measured parameters of the treated sludge samples with 74.69 %, 77.67 % and 81.70 % reduction in the COD, BOD and Turbidity respectively, thus improving the quality of the sludge in terms of toxins. The total and suspended solids increased expectedly, by 30.58 % and 12.92 % respectively. The coagulant was quite effective at low levels. It also showed other characteristics of locally sourced coagulants, which include less pH dependence, readily available, cheap and easy to handle, more biodegradable, therefore more environmentally friendly. The use of the coagulant for the treatment of sludge and indeed where coagulation and flocculation is desirous can be so recommended.Keywords: Biodegradable, Chitosan, Exoskeleton, Pollution, Sludge,

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

Background Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (−28·4 to −2·9) for all diabetes, and by 21·0% (–33·0 to −5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (−13·6% [–28·4 to 3·4]) and for type 1 diabetes (−13·6% [–29·3 to 8·9]). Interpretation Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations.publishedVersio

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990-2019, for 204 countries and territories: the Global Burden of Diseases Study 2019.

BACKGROUND: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. METHODS: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). FINDINGS: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1-38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78-0·91) per female living with HIV in 2019, 0·99 male infections (0·91-1·10) for every female infection, and 1·02 male deaths (0·95-1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58-35·43, and a 39·66% decrease in deaths, 36·49-42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05-0·06) and the global incidence-to-mortality ratio was 1·94 (1·76-2·12). No regions met suggested thresholds for progress. INTERPRETATION: Sub-Saharan Africa had both the highest HIV burden and the greatest progress between 1990 and 2019. The number of incident cases and deaths in males and females approached parity in 2019, although there remained more females with HIV than males with HIV. Globally, the HIV epidemic is far from the UNAIDS benchmarks on progress metrics. FUNDING: The Bill & Melinda Gates Foundation, the National Institute of Mental Health of the US National Institutes of Health (NIH), and the National Institute on Aging of the NIH

Identifying the Gaps in HIV Prevention and Treatment During the COVID-19 Pandemic in Nigeria

Context: To manage the COVID-19 pandemic, the Nigerian government has introduced travel restrictions to reduce the spread of the virus. However, this measure has caused numerous challenges in the accessibility and availability of HIV services (testing, prevention, and treatment) for patients. This study aimed to examine the delivery of HIV care services during the COVID-19 pandemic in Nigeria by analyzing the barriers to HIV care in recent years, weighing the impact of these barriers, and bridging the existing gaps by proposing practical solutions to maintain the patients’ uninterrupted access to HIV services throughout the pandemic. Evidence Acquisition: We searched Google Scholar, PubMed, and Science Direct databases, using the following MESH headings: “HIV”, “COVID-19”, and “Nigeria”. The reviewed articles provided information on gaps and solutions for maintaining HIV services during the COVID-19 pandemic in Nigeria. The selected papers were all written in English, with no time restrictions. Also, further publications were identified from the reference lists of articles and reports via snowball sampling. Results: The collected data in 2018 revealed that 67% of people living with HIV were aware of their disease status. Based on the results, 53% of people living with HIV were on antiretroviral treatment, and 42% of people living with HIV had viral suppression, based on the global 90-90-90 HIV targets. Ten barriers and gaps were identified in different aspects of HIV care delivery (prevention, testing, and treatment), and practical solutions were proposed to provide a more effective approach for ensuring the availability and accessibility of services during pandemics. Conclusions: A unique and inter-sectoral approach is generally needed to address different barriers to the delivery of HIV care services during the COVID-19 pandemic. Also, funding of HIV care services is critical at this time. Based on the findings, HIV care services (prevention, testing, and treatment programs) cannot be postponed due to the COVID-19 outbreak, otherwise Nigeria may face a double pandemic

In-person vs mobile app facilitated life skills education to improve the mental health of internally displaced persons in Nigeria: protocol for the RESETTLE-IDPs cluster randomized hybrid type 2 effectiveness-implementation trial.

Background: Internally displaced persons (IDPs) in Nigeria face a high burden of mental health disorders, with limited access to evidence-based, culturally relevant interventions. Life skills education (LSE) is a promising approach to promote mental health and psychosocial well-being in humanitarian settings. This study aims to evaluate the effectiveness and implementation of a culturally adapted LSE program delivered through in-person and mobile platforms among IDPs in Northern Nigeria. Methods: This cluster-randomized hybrid type 2 effectiveness-implementation trial will be conducted in 20 IDP camps or host communities in Maiduguri, Nigeria. Sites will be randomly assigned to receive a 12-week LSE program delivered either through in-person peer support groups or WhatsApp-facilitated mobile groups. The study will recruit 500 participants aged 13 years and older. Intervention effectiveness outcomes include the primary outcome of change in post-traumatic stress disorder (PTSD) symptoms assessed using the PCL-5 scale, and secondary outcomes of depression, anxiety, well-being, and life skills acquisition. Implementation outcomes will be assessed using the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM). Both sets of outcomes will be compared between the in-person and mobile delivery groups. Quantitative data will be analyzed using mixed-effects linear regression models, while qualitative data will be examined through reflexive thematic analysis. The study will be guided by the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) framework. Discussion: The RESETTLE-IDPs study addresses key gaps in the evidence base on mental health interventions for conflict-affected populations. It focuses on underserved IDP populations, evaluates the comparative effectiveness of in-person and mobile-delivered LSE, and incorporates implementation science frameworks to assess contextual factors influencing adoption, fidelity, and sustainability. The study employs a community-based participatory approach to enhance cultural relevance, acceptability, and ownership. Findings will inform the development and scale-up of evidence-based, sustainable mental health interventions for IDPs in Nigeria and other humanitarian contexts. Trial sponsor: Dalhousie University, 6299 South St, Halifax, NS B3H 4R2, Canada. Trial registration: ClinicalTrials.gov, NCT06412679  Registered 15 May 2024

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Note: Not all authors listed; please see article (last page) for full list of Contributors).Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys