Estimating the prevalence of COPD in an African country:evidence from southern Nigeria

# BACKGROUND: Though several environmental and demographic factors would suggest a high burden of chronic obstructive pulmonary disease (COPD) in most African countries, there is insufficient country-level synthesis to guide public health policy. # METHODS: A systematic search of MEDLINE, EMBASE, Global Health and African Journals Online identified studies reporting the prevalence of COPD in Nigeria. We provided a detailed synthesis of study characteristics, and overall median and interquartile range (IQR) of COPD prevalence in Nigeria by case definitions (spirometry or non-spirometry). # RESULTS: Of 187 potential studies, eight studies (6 spirometry and 2 non-spirometry) including 4,234 Nigerians met the criteria. From spirometry assessment, which is relatively internally consistent, the median prevalence of COPD in Nigeria was 9.2% (interquartile range, IQR: 7.6–10.0), compared to a lower prevalence (5.1%, IQR: 2.2–15.4) from studies based on British Medical Research Council (BMRC) criteria or doctor’s diagnosis. The median prevalence of COPD was almost the same among rural (9.5%, IQR: 7.6–10.3) and urban dwellers (9.0%, IQR: 5.3–9.3) from spirometry studies. # CONCLUSIONS: A limited number of studies on COPD introduces imprecision in prevalence estimates and presents concerns on the level of response available across different parts of Nigeria, and indeed across many countries in sub-Saharan Africa

Assessing readiness to implement routine immunization among patent and proprietary medicine vendors in Kano, Nigeria : a theory-informed cross-sectional study

Background: Patent and proprietary medicine vendors (PPMVs) are widespread in communities and can potentially be used to expand access to routine immunization especially in underserved areas. In this study, we aimed to assess their readiness to implement routine immunization in Kano, Nigeria and identify factors associated with it. Methods: We conducted a cross-sectional survey of PPMVs aged 18 years and above in Kano metropolis, Nigeria, using cluster sampling technique. A 10-item Likert scale-based measure was used to estimate readiness score. The relationship between selected factors and readiness score was examined using multilevel linear modeling technique. Results: A total of 455 PPMVs with median age of 36 years participated in the study. The median raw score for readiness was 4.7 (IQR: 4.3 – 4-8) (maximum obtainable was 5). The mean readiness score (obtained through factor analysis) was 5.28 (SD: 0.58). Readiness score was associated with factors such as knowledge of immunization and task demand, engagement by other public health programs among others. Conclusion: This study demonstrated the feasibility of measuring the level of readiness for implementing routine immunization among PPMVs. Given the high level of readiness, policy makers should consider the possibility of expanding access to immunization through PPMVs

The Conundrum of Low COVID-19 Mortality Burden in sub-Saharan Africa: Myth or Reality?

The burden of coronavirus disease (COVID-19) in sub-Saharan Africa (SSA) has been substantially lower compared to other regions of the world. Extensive morbidity and mortality were not observed among countries in SSA during the first wave of the COVID-19 pandemic. To explain this phenomenon, several hypotheses have been formulated, including the low median age of the population in most SSA countries, lack of long-term care facilities, cross-protection from other local coronaviruses, insufficient testing and reporting resulting in an undercounting of COVID-related deaths, genetic risk factors, or the benefit of early lockdowns that were extensive in many SSA countries. Early lockdowns in SSA have been some of the strictest and resulted in devastating economic and social consequences and increased mortality from other health-related problems including maternal deaths. We review the literature and rationale supporting the various hypotheses that have been put forward to account for relatively low hospitalization and death rates for COVID-19 in SSA. We conclude that the strongest evidence would support the demographic age structure with a very low median age as the primary factor in leading to the low mortality seen in the first wave of the pandemic. The impact of new variants of concern in SSA raises the risk of more severe waves. Nevertheless, furthering the understanding of the underlying explanations for the low morbidity and mortality seen across SSA countries may allow the adoption of unique strategies for limiting the spread of COVID-19 without the need for stringent lockdowns

Deaths during tuberculosis treatment among paediatric patients in a large tertiary hospital in Nigeria.

BACKGROUND: Despite availability of effective cure, tuberculosis (TB) remains a leading cause of death in children. In many high-burden countries, childhood TB is underdiagnosed and underreported, and care is often accessed too late, resulting in adverse treatment outcomes. In this study, we examined the time to death and its associated factors among a cohort of children that commenced TB treatment in a large treatment centre in northern Nigeria. METHODS: This is a retrospective cohort study of children that started TB treatment between 2010 and 2014. We determined mortality rates per 100 person-months of treatment, as well as across treatment and calendar periods. We used Cox proportional hazards regression to determine adjusted hazard ratios (aHR) for factors associated with mortality. RESULTS: Among 299 children with a median age 4 years and HIV prevalence of 33.4%; 85 (28.4%) died after 1,383 months of follow-up. Overall mortality rate was 6.1 per 100 person-months. Deaths occurred early during treatment and declined from 42.4 per 100 person-months in the 1st week of treatment to 2.2 per 100 person-months after at the 3rd month of treatment. Mortality was highest between October to December period (9.1 per 100 pm) and lowest between July and September (2.8 per 100 pm). Risk factors for mortality included previous TB treatment (aHR 2.04:95%CI;1.09-3.84); HIV infection (aHR 1.66:95%CI;1.02-2.71), having either extra-pulmonary disease (aHR 2.21:95%CI;1.26-3.89) or both pulmonary and extrapulmonary disease (aHR 3.03:95%CI;1.70-5.40). CONCLUSIONS: Mortality was high and occurred early during treatment in this cohort, likely indicative of poor access to prompt TB diagnosis and treatment. A redoubling of efforts at improving universal health coverage are required to achieve the End TB Strategy target of zero deaths from TB

High mortality among tuberculosis patients on treatment in Nigeria: a retrospective cohort study.

BACKGROUND: Tuberculosis (TB) remains a leading cause of death in much of sub-Saharan Africa despite available effective treatment. Prompt initiation of TB treatment and access to antiretroviral therapy (ART) remains vital to the success of TB control. We assessed time to mortality after treatment onset using data from a large treatment centre in Nigeria. METHODS: We analysed a retrospective cohort of TB patients that commenced treatment between January 2010 and December 2014 in Aminu Kano Teaching Hospital. We estimated mortality rates per person-months at risk (pm). Cox proportional hazards model was used to determine risk factors for mortality. RESULTS: Among 1,424 patients with a median age of 36.6 years, 237 patients (16.6%) died after commencing TB treatment giving a mortality rate of 3.68 per 100 pm of treatment in this cohort. Most deaths occurred soon after treatment onset with a mortality rate of 37.6 per 100 pm in the 1st week of treatment. Risk factors for death were being HIV-positive but not on anti-retroviral treatment (ART) (aHR 1.39(1 · 04-1 · 85)), residence outside the city (aHR 3 · 18(2.28-4.45)), previous TB treatment (aHR 3.48(2.54-4.77)), no microbiological confirmation (aHR 4.96(2.69-9.17)), having both pulmonary and extra-pulmonary TB (aHR 1.45(1.03-2.02), and referral from a non-programme linked clinic/centre (aHR 3.02(2.01-4.53)). CONCLUSIONS: We attribute early deaths in this relatively young cohort to delay in diagnosis and treatment of TB, inadequate treatment of drug-resistant TB, and poor ART access. Considerable expansion and improvement in quality of diagnosis and treatment services for TB and HIV are needed to achieve the sustainable development goal of reducing TB deaths by 95% by 2035

Estimating the prevalence of overweight and obesity in Nigeria in 2020: a systematic review and meta-analysis

Background Targeted public health response to obesity in Nigeria is relatively low due to limited epidemiologic understanding. We aimed to estimate nationwide and sub-national prevalence of overweight and obesity in the adult Nigerian population. Methods MEDLINE, EMBASE, Global Health, and Africa Journals Online were systematically searched for relevant epidemiologic studies in Nigeria published on or after 01 January 1990. We assessed quality of studies and conducted a random-effects meta-analysis on extracted crude prevalence rates. Using a meta-regression model, we estimated the number of overweight and obese persons in Nigeria in the year 2020. Results From 35 studies (n = 52,816), the pooled crude prevalence rates of overweight and obesity in Nigeria were 25.0% (95% confidence interval, CI: 20.4–29.6) and 14.3% (95% CI: 12.0–15.5), respectively. The prevalence in women was higher compared to men at 25.5% (95% CI: 17.1–34.0) versus 25.2% (95% CI: 18.0–32.4) for overweight, and 19.8% (95% CI: 3.9–25.6) versus 12.9% (95% CI: 9.1–16.7) for obesity, respectively. The pooled mean body mass index (BMI) and waist circumference were 25.6 kg/m2 and 86.5 cm, respectively. We estimated that there were 21 million and 12 million overweight and obese persons in the Nigerian population aged 15 years or more in 2020, accounting for an age-adjusted prevalence of 20.3% and 11.6%, respectively. The prevalence rates of overweight and obesity were consistently higher among urban dwellers (27.2% and 14.4%) compared to rural dwellers (16.4% and 12.1%). Conclusions Our findings suggest a high prevalence of overweight and obesity in Nigeria. This is marked in urban Nigeria and among women, which may in part be due to widespread sedentary lifestyles and a surge in processed food outlets, largely reflective of a trend across many African settings

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

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042