Nigerian doctors’ willingness to work at COVID-19 treatment center: How does Abraham Maslow’s motivation theory explain this finding?

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Design and Preliminary Evaluation of a Dry Cowpea Dehuller

Cowpea dehulling is an important operation in the processing of cowpea. Traditional cowpea dehulling methods recognize the soaking of cowpea in water for a significant amount of time before manual abrasion is carried out either through the use of mortar and pestle, hands, or legs. Existing mechanical alternatives also require prolonged soaking of cowpea before dehulling occurs in addition to being expensive and beyond the reach of many rural populations. This study designed and fabricated a dry cowpea dehulling machine using engineering principles and with locally available materials. Components of the machine include the hopper, power transmission drive, dehulling chamber, polishing chamber, sieves, discharge chute, and agitator. Dry cowpea varieties of Brown Drum (15%Mc dB) and Oloyin (17.5%Mc dB) cowpea weighing 500 g each were fed into the machine at a constant speed of 358 rpm. Preliminary tests showed the “Brown Drum” cowpea variety recorded a maximum dehulling efficiency of 97.44% in 7 minutes while the Oloyin variety was completely dehulled in 7 minutes at 98.75% efficiency. The throughput capacity recorded was 450kg/hr and this machine raises the possibility of producing dry dehulled cowpea for domestic and industrial end-users

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.publishedVersio

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100:a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.FundingBill & Melinda Gates Foundation

Global, regional, and national mortality due to unintentional carbon monoxide poisoning, 2000–2021: results from the Global Burden of Disease Study 2021

Background Unintentional carbon monoxide poisoning is a largely preventable cause of death that has received insufficient attention. We aimed to conduct a comprehensive global analysis of the demographic, temporal, and geographical patterns of fatal unintentional carbon monoxide poisoning from 2000 to 2021. Methods As part of the latest Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), unintentional carbon monoxide poisoning mortality was quantified using the GBD cause of death ensemble modelling strategy. Vital registration data and covariates with an epidemiological link to unintentional carbon monoxide poisoning informed the estimates of death counts and mortality rates for all locations, sexes, ages, and years included in the GBD. Years of life lost (YLLs) were estimated by multiplying deaths by remaining standard life expectancy at age of death. Population attributable fractions (PAFs) for unintentional carbon monoxide poisoning deaths due to occupational injuries and high alcohol use were estimated. Findings In 2021, the global mortality rate due to unintentional carbon monoxide poisoning was 0·366 per 100 000 (95% uncertainty interval 0·276–0·415), with 28 900 deaths (21 700–32 800) and 1·18 million YLLs (0·886–1·35) across all ages. Nearly 70% of deaths occurred in males (20 100 [15 800–24 000]), and the 50–54-year age group had the largest number of deaths (2210 [1660–2590]). The highest mortality rate was in those aged 85 years or older with 1·96 deaths (1·38–2·32) per 100 000. Eastern Europe had the highest age-standardised mortality rate at 2·12 deaths (1·98–2·30) per 100 000. Globally, there was a 53·5% (46·2–63·7) decrease in the age-standardised mortality rate from 2000 to 2021, although this decline was not uniform across regions. The overall PAFs for occupational injuries and high alcohol use were 13·6% (11·9–16·0) and 3·5% (1·4–6·2), respectively. Interpretation Improvements in unintentional carbon monoxide poisoning mortality rates have been inconsistent across regions and over time since 2000. Given that unintentional carbon monoxide poisoning is almost entirely preventable, policy-level interventions that lower the risk of carbon monoxide poisoning events should be prioritised, such as those that increase access to improved heating and cooking devices, reduce carbon monoxide emissions from generators, and mandate use of carbon monoxide alarms.publishedVersio

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Rethinking Public Private Mix (PPM) Performance in the Tuberculosis Program: How Is Care Seeking Impacting This Model in High TB Burden Countries?

In many high TB burden countries with enormous private-sector presence, up to 60–80% of the initial health-seeking behavior occurs in the private sector when people fall sick. Private-sector providers are also perceived to offer poorer-quality health service, and contribute to TB notification gaps and the spread of multidrug-resistant tuberculosis (MDR-TB). Recent efforts have focused on the expansion of TB services among private providers through public–private mix (PPM) initiatives. However, whether such efforts have matched the contribution of the private sector in TB notification, considering its enormous health-seeking volume, is debatable. Here, we argue that evaluating PPM program performance on the basis of the proportion of private-sector health seeking and level of undernotification is an imperfect approach due to differentials in tuberculosis risk profiles and access among patient populations seeking private care when compared with the public sector. We suggest a uniform definition of what constitutes PPM, and the standardization of PPM reporting tools across countries, including the ability to track patients who might initially seek care in the private sector but are ultimately publicly notified. PPM programs continue to gain prominence with rapid urbanization in major global cities. A universal health coverage framework as part of the PPM expansion mandate would go a long way to reduce the catastrophic cost of seeking TB care

A Comparative Analysis of Patient Profiles and Health Service Utilization between Patent Medicine Vendors and Community Pharmacists in Nigeria

Background: This study examined Nigeria’s socio-demographic profiles and health service utilization patterns of Patent Medicine Vendors (PMVs) and Community Pharmacists (CPs). Method: A cross-sectional study using a structured self-administered questionnaire among 405 retail outlets (322 PMVs and 83 CPs) across 16 Lagos and Kebbi Local Government Areas (LGAs) between June 2020 and December 2020. Results: Results showed that 60.4% were male, 76.3% from Lagos, 58.3% had tertiary education, and 74.1% had medical training. Cough and fever were common symptoms. Significant differences were found in the utilization of STD services (PMVs: 9.2%, CPs: 12.3%, p = 0.03), services by age p p = 0.013). The study revealed that men visited PMVs more, while CPs used more STI services and childhood visits. Conclusions: The findings suggest that expanding health services among PMVs could target male-dominant diseases, and capacity building of CPs on syndromic STI management could reduce the STI burden

Stocking Practices of Anti-Tuberculosis Medications among Community Pharmacists and Patent Proprietary Medicine Vendors in Two States in Nigeria

Background: Evidence has shown that non-fixed-dose combination (non-FDC) anti-TB drugs could promote the spread of drug-resistant tuberculosis (DR-TB). We aimed to determine anti-TB medication stocking and dispensing practices among patent medicine vendors (PMVs) and community pharmacists (CPs) and their determinants. Method: This was a cross-sectional study using a structured, self-administered questionnaire among 405 retail outlets (322 PMVs and 83 CPs) across 16 Lagos and Kebbi local government areas (LGAs) between June 2020 and December 2020. Data were analyzed with Statistical Program for Social Sciences (SPSS) for Windows version 17 (IBM Corp., Armonk, NY, USA). Chi-square test and binary logistic regression were used to assess the determinants of anti-TB medication stocking practices at a p-value of 0.05 or less for statistical significance. Results: Overall, 91%, 71%, 49%, 43% and 35% of the respondents reported stocking loose rifampicin, streptomycin, pyrazinamide, isoniazid and ethambutol tablets, respectively. From bivariate analysis, it was observed that being aware of directly observed therapy short course (DOTS) facilities (OR 0.48, CI 0.25–0.89, p p p = 0.004), having 3 or more apprentices (OR 5.31, CI 2.74–10.29, p p = 0.017) increased the odds of stocking loose anti-TB medications. From multivariate analysis, it was observed that only the variable having three or more apprentices (OR 10.23, CI 0.10–0.49, p = 0.001) significantly increased the odds of stocking anti-TB medications. Conclusions: The stocking of non-FDC anti-TB medications was high and largely determined by the number of apprentices among PMVs and CPs in Nigeria, and this may have serious implications for drug resistance development. However, the results linking the stocking of anti-TB to the number of apprentices should be interpreted cautiously as this study did not control for the level of sales in the pharmacies. We recommend that all capacity-building and regulatory efforts for PMVs and CPs in Nigeria should include not just the owners of retail premises but also their apprentices