Literature DB >> 30262990

Tuberculosis disease burden and attributable risk factors in Nigeria, 1990-2016.

Felix Akpojene Ogbo1,2, Pascal Ogeleka2, Anselm Okoro3, Bolajoko O Olusanya4, Jacob Olusanya4, Ifegwu K Ifegwu2, Akorede O Awosemo2, John Eastwood5,6,7,8,9, Andrew Page1.   

Abstract

BACKGROUND: According to the World Health Organization, Nigeria is one of the countries with a high burden of tuberculosis (TB) worldwide. Improving the burden of TB among HIV-negative people would require comprehensive and up-to-date data to inform targeted policy actions in Nigeria. The study aimed to describe the incidence, prevalence, mortality, disability-adjusted life years (DALYs) and risk factors of tuberculosis in Nigeria between 1990 and 2016.
METHODS: This study used the most recent data from the global burden of disease study 2016. TB deaths were estimated using the Cause of Death Ensemble model, while TB incidence, prevalence and DALYs, as well as years of life lost and years of life lived with disability were calculated in the DisMod-MR 2.1, a Bayesian meta-regression tool. Using a comparative risk assessment approach, TB burden attributable to risk factors was estimated in a spatial-temporal Gaussian Process Regression tool.
RESULTS: In 2016, the prevalence of TB among HIV-negative people was 27% (95% uncertainty interval [95% UI] 23-31%) in Nigeria. TB incidence rate (new and relapse cases) was 158 per 100,000 people (95% UI; 128-193), while the total number of TB mortality was 39,933 deaths (95% UI; 30,488-55,039) in 2016. Between 2000 and 2016, the age-standardised prevalence and incidence rates of TB-HIV negative decreased by 20.0 and 87.6%, respectively. The age-standardised mortality rate also dropped by 191.6% over the same period. DALYs due to TB among HIV-negative Nigerians was high but varied across the age groups. Of the risk factors studied, alcohol use accounted for the highest number of TB deaths and DALYs, followed by diabetes and smoking in 2016.
CONCLUSION: The study shows an improving trend in TB disease burden among HIV-negative individuals in Nigeria from 1990 to 2016. Despite this progress, this study suggests that additional efforts are still needed to ensure that Nigeria is not left behind in the current global strategy to end TB disease. Reducing TB disease burden in the country will require a multipronged approach that includes increased funding, health system strengthening and improved TB surveillance, as well as preventive efforts for alcohol use, smoking and diabetes.

Entities:  

Keywords:  Burden; Global burden of disease; Mortality; Nigeria; Tuberculosis

Year:  2018        PMID: 30262990      PMCID: PMC6156953          DOI: 10.1186/s41182-018-0114-9

Source DB:  PubMed          Journal:  Trop Med Health        ISSN: 1348-8945


Background

Tuberculosis (TB) remains a significant public health issue in low-income and middle-income countries and is the leading cause of deaths as a single infectious disease, ranking above human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) [1]. The World Health Organization’s (WHO) Global Tuberculosis Report 2017 reported 6.3 million new cases of TB among HIV-negative people in 2016 [1], compared to 6.1 million in 2015 [2]. Similarly, the Global Burden of Diseases, Injuries and Risk Factors (GBD) Study 2016 estimated 9.0 million TB-HIV-negative incident cases (new and relapse cases) compared to 8.8 million in 2015 [3]. These reports highlighted the considerable burden of TB globally. For example, the WHO African region accounted for 25% of the total number of incident cases (i.e., TB-HIV-negative and TB-HIV infection) globally, where Nigeria accounted for 8% or 407 cases per 100,000 population in 2016 [1], up from 322 cases per 100,000 population in 2015 [2]. These estimates may be lower than the actual number of TB cases in Nigeria because only less than a quarter of TB cases (15%) were notified in 2015 [2]. In the past two decades, the WHO has listed Nigeria as one of the countries with a high burden of TB in order to stimulate targeted interventions and advocacy for funding and policies to improve TB control [4]. This initiative has led to focused and practical actions for TB control worldwide [1]. Recently, the Nigeria National TB Control Programme and its donor partners have commenced the scale-up of availability and accessibility to improved methods for TB diagnosis and effective treatment regimen [5, 6]. While those efforts are needed and well deserved in Nigeria, there are limited pragmatic policy actions to tackle emerging risk factors for TB at the population level, including diabetes [7, 8], alcohol intake [8-11] and tobacco smoking [8, 12]. Country-specific epidemiologic studies which investigate trends in TB disease burden and the attributable risk factors for TB would be useful for public health experts and policy-makers to strengthen TB control and preventive efforts. Evidence shows that TB mortality among HIV-negative people has declined in many developing countries (including Nigeria); but that TB incidence has remained unchanged in many communities [1, 3]. To ensure a continued reduction in TB disease burden in Nigeria, it is essential to understand not only the trends in TB burden but also the extent to which risk factors contribute to TB disease burden to inform targeted and high-priority TB programmes. We have provided a detailed exposition of TB disease burden in Nigeria from the GBD findings because this is not practicable in the GBD capstone publications due to the huge size and scope of the study, which have also led to further characterisation of the results for other health focus areas and locations [3, 13–16]. Additionally, by distilling the findings for TB burden in Nigeria, we aim to increase awareness and understanding of TB estimates for clinicians, national, and international health experts for TB prevention and control programmes, especially that Nigeria is the largest recipient of developmental assistance for health in Sub-Saharan Africa [17]. The present study aimed to highlight the incidence, prevalence, deaths, disability-adjusted life years (DALYs) and risk factors for tuberculosis in Nigeria from 1990 to 2016 using data from the GBD Study 2016.

Methods

Overview of data sources

The GBD study is a systematic and scientific effort that provides comparable estimates of incidence, prevalence, the cause of death and health loss, and risk factors for diseases and injuries by age, sex, year, location, and over time. In the past two decades, the GBD study has been quantifying health loss from diseases and injuries to inform health programmes and policy decision-making worldwide [18, 19]. The GBD 2016 complied with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) statement, a global agreement that ensures transparency, accurate reporting, interpretation and use of health estimates [20]. For this study, the complete information on data sources, the conceptual framework, and the analytical strategy for the calculation of TB incidence, prevalence, mortality, DALYs and attributable risk factors in Nigeria has been described elsewhere [3, 21–25]. Data used for the TB estimation in Nigeria have been extracted from the Global Health Exchange website (GHDx, http://ghdx.healthdata.org/gbd-2016/data-input-sources). GHDx provides researchers and policy-makers access to the most recent GBD input sources and results, and also creates opportunities for discussing population health based on the best available data, as well as acknowledgment of data owners’ contributions [26].

Case definition

TB is an infectious disease caused by the bacterium Mycobacterium tuberculosis, an acid-fast bacillus that is spread mainly via the respiratory pathway. The GBD study provides estimates for all forms of TB, including pulmonary and extrapulmonary TB using the International Classification of Diseases (ICD-10) codes [27]. In this study, we have reported estimates for TB (drug-susceptible TB, extensively drug resistance TB, latent TB infection and multidrug-resistant TB, MDR-TB) among HIV-negative people in Nigeria. Information on TB-HIV is provided elsewhere [3, 28].

Overview of the estimation of incidence, prevalence, mortality, disability-adjusted life years and risk factors for tuberculosis

TB mortality was modelled in the GBD Cause of Death Ensemble model (CODEm), a Bayesian, hierarchical, ensemble modelling tool, which has been used to estimate cause-specific mortality for a range of diseases and injuries globally [21, 29]. CODEm modelling strategy used data from the WHO Global Project on Anti-Tuberculosis Drug Resistance Surveillance data (1988–2015) and community-based surveillance data for Nigeria and applied different functional forms (mixed-effects models and spatiotemporal Gaussian process regression models) to mortality rates with varying combinations of predictive models [21]. TB incidence was estimated based on age-specific and sex-specific notification data from the WHO and was defined as new and relapse cases diagnosed within a given calendar year [25]. Categorised notification data (i.e. new pulmonary smear-positive, new pulmonary smear-negative, new extrapulmonary and relapse) were combined to represent all forms of TB [3]. The GBD study estimated point prevalence of TB, defined as the people in the population who at any point within a calendar year with active TB [25]. DALYs are a summary metric of disease or injuries, defined as the number of years lost due to ill-health, disability or premature death, and were computed as the sum of years of life lost (YLLs) and years lived with disability (YLDs) for each year and age in Nigeria [24]. YLLs were calculated by multiplying TB deaths by normative standard life birth (86.9 years), measured as the lowest observed death rates for each 5-year age group in populations higher than five million [30]. In the estimation of YLDs, TB epidemiologic data from the WHO and the Nigeria National Tuberculosis Prevalence Survey 2012 were multiplied by a TB-specific disability weight. The disability weight was obtained from population-based surveys, where respondents rated their health status, from ‘perfect health’ to ‘death’ to quantify the severity of the health loss due to a given disease or injury [24]. TB mortality and DALYs attributable to risk factors were computed as the proportion of deaths and DALYs that could be attributed to risk factors (alcohol use, diabetes and tobacco smoking) as a counterfactual relative to the theoretical minimum level of exposure had the population not been exposed to the given risk factor previously. Based on the available evidence on the causal relationship between risk factors and TB, GBD 2016 estimated the attributable burden of diabetes, alcohol use and tobacco smoking for TB in Nigeria using the comparative risk assessment (CRA) strategy developed by Murray and Lopez [31]. Estimates of the attributable number of deaths or DALYs were calculated by multiplying the number of deaths, or DALYs for the outcome by the population attributable fraction (PAF) for the risk-outcome pair for a given age and year in Nigeria [3]. The analyses were conducted in DisMod-MR 2.1, the GBD meta-regression tool that adjusts for variations in epidemiologic data sources and other parameters, including model predictions, as well as propagates uncertainty around the estimates. DisMod-MR 2.1 also estimated 95% corresponding uncertainty intervals for TB incidence, prevalence, deaths and DALYs. A full description of the analytical strategy for the estimation of TB epidemiology in Nigeria is provided in respective GBD study publications [21-25].

Results

Levels and trends of tuberculosis prevalence, incidence, mortality and DALYs

In 2016, age-standardised prevalence rate of TB among HIV-negative people was 31,643.5 per 100,000 population (95% uncertainty interval [95% UI] 27,316-36,249) (Table 1), while the absolute prevalence was 27% (95% UI; 23–31%), highest in people aged 50–69 years and lowest in children under 5 years (Fig. 1). Absolute TB incidence rate (new and relapse cases) was 158 per 100,000 people (95% UI; 128-193) (Table 2).
Table 1

Age-standardised cases of tuberculosis, drug-susceptible tuberculosis, multidrug-resistant tuberculosis and extensively drug-resistant tuberculosis among HIV-negative individuals in Nigeria, 2000–2016

PrevalenceIncidence
20002016% change, 2000–201620002016% change, 2000–2016
Rate/100,000 (95% UI)Rate/100,000 (95% UI)Rate/100,000 (95% UI)Rate/100,000 (95% UI)
Tuberculosis37,964.1 (32,963.3–43,057.0)31,643.5 (27,316.3–36,249.3)−20.0%373.9 (300.2–455.4)199.2 (162.0–238.5)−87.6%
Drug-susceptible tuberculosis269.9 (217.2–329.6)147.3 (119.4–180.2)−83.3%362.8 (292.3–442.1)192.9 (157.3–231.8)−88.0%
Multidrug-resistant tuberculosis8.2 (2.7–18.5)4.8 (2.0–9.5)−72.5%11.1 (3.8–25.2)6.3 (2.7–12.8)−76.6%
Latent tuberculosis infection37,685.9 (32,701.1–42,774.3)31,491.4 (27,161.1–36,074.3)−19.7%
DeathsDALYs
Tuberculosis131.3 (101.7–177.9)45.0 (35.2–59.3)−191.6%3524.8 (2696.8–4867.8)1159.3 (897.4–1557.6)−204.1%
Drug-susceptible tuberculosis120.0 (92.0–163.4)40.9 (31.6–54.2)−193.2%3228.3 (2414.1–4569.2)1056.5 (808.5–1427.6)−205.6%
Multidrug-resistant tuberculosis11.3 (3.8–25.0)4.0 (1.7–7.9)−179.1%295.7 (98.2–640.7)101.1 (43.0–199.7)− 192.5%
Extensively drug-resistant tuberculosis0.9 (0.3–1.9)1.7 (0.7–3.4)48.1%

- indicate less than one per 100,000 population

Fig. 1

Prevalence of tuberculosis in Nigeria by age, 1990–2016

Table 2

Incidence rate of tuberculosis (with 95% uncertainty interval, UI) by age in Nigeria, 1990–2016 (per 100,000 population)

Age199019952000200520102016% change (1990–2016)
N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)
Under 5 years218 (153–306)226 (156–323)220 (150–317)179 (122–264)136 (91–199)102 (71–148)− 53.3
5–14 years68 (43–100)71 (45–106)78 (48–117)77 (47–117)65 (38–102)56 (34–85)− 16.9
15–49 years356 (273–461)377 (273–497)358 (254–487)290 (201–400)228 (161–312)210 (155–274)− 41.1
50–69 years536 (399–699)558 (398–742)557 (377–773)474 (321–669)354 (235–506)276 (182–396)− 48.6
70+ years799 (591–1045)807 (601–1073)759 (543–1007)607 (428–821)425 (304–574)342 (244–464)− 57.2
All ages277 (233–329)292 (240–356)285 (228–352)236 (188–293)182 (146–231)158 (128–193)− 42.9
Age-standardised cases of tuberculosis, drug-susceptible tuberculosis, multidrug-resistant tuberculosis and extensively drug-resistant tuberculosis among HIV-negative individuals in Nigeria, 2000–2016 - indicate less than one per 100,000 population Prevalence of tuberculosis in Nigeria by age, 1990–2016 Incidence rate of tuberculosis (with 95% uncertainty interval, UI) by age in Nigeria, 1990–2016 (per 100,000 population) In the same year, the total number of TB mortality was 39,933 deaths (95% UI; 30,488-55,039), highest in people aged 15–49 years (13,916, 95% UI; 9311-20,530) but lowest in those aged between 5 and 14 years (875, 95% UI; 600-1,211) (Table 3). A similar pattern in the prevalence of TB mortality was observed (Fig. 2). Between 2000 and 2016, the age-standardised prevalence and incidence rates of TB-HIV negative decreased by 20.0 and 87.6%, respectively. The age-standardised mortality rate also dropped by 191.6% over the same period. Drug-susceptible TB was the most common variant, followed by multidrug- resistance TB in 2016 (Table 1).
Table 3

Number of deaths from tuberculosis (with 95% uncertainty interval, UI) by age in Nigeria, 1990–2016

Age199019952000200520102016% change (1990–2016)
N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)
Under 5 years9313 (5939–13,651)9557 (6136–14,356)8577 (5421–13,213)5868 (3733–8747)3519 (2148–5743)4720 (3030–7196)− 49.3
5–14 years1382 (964–1926)1517 (1055–2095)1447 (981–1975)1113 (756–1572)746 (503–1060)875 (600–1211)− 36.7
15–49 years21,542 (16,162–31,474)24,437 (17,214–34,397)25,107 (16,951–37,381)20,300 (13,190–30,585)12,187 (8543–17,420)13,916 (9311–20,530)− 35.4
50–69 years18,723 (14,227–27,847)21,405 (15,544–31,463)22,178 (15,703–32,747)17,871 (12,701–26,285)10,573 (7688–1,4845)12,357 (8797–17,817)− 34
70+ years11,553 (9091–15,539)13,613 (10,740–17,887)14,034 (10,930–18,725)11,274 (8711–14,819)7377 (5655–9722)8065 (6129–10,550)− 30.2
All ages62,513 (50,969–85,245)70,530 (54664–94,278)71,343 (54,497–98,715)56,427 (42,423–77,678)34,403 (26,533–46,550)39,933 (30,488–55,039− 36.1
Fig. 2

Prevalence of deaths from tuberculosis in Nigeria by age, 1990–2016

Number of deaths from tuberculosis (with 95% uncertainty interval, UI) by age in Nigeria, 1990–2016 Prevalence of deaths from tuberculosis in Nigeria by age, 1990–2016 In Nigeria, the burden of TB among HIV-negative people was highest in those aged 15–49 years (660,942 DALYs [477,430-921,111]), followed by people aged 50–69 years (312,294, 95% UI; 227,215-440,406) (Table 4).
Table 4

Numbers of disability-adjusted life years (with 95% uncertainty interval, UI) due to tuberculosis in Nigeria, 1990–2016

Age199019952000200520102016% change (1990–2016)
N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)N (95% UI)
Under 5 years796,326 (509,536–1,167,425)818,094 (526,989–1,225,994)735,514 (466,850–1,131,697)504,739 (325,725–750,223)406,505 (263,324–617,181)303,628 (186,059–490,830)− 61.9
5–14 years109,450 (77,440–151,691)120,172 (84,493–165,691)115,521 (78,775–155,780)90,261 (62,470–125,194)71,786 (50,534–99,023)61,720 (43,117–86,028)− 43.6
15–49 years1,144,635 (872,156–1,633,936)1,308,897 (930,238–1,818,531)1,349,558 (922,957–1,973,510)1,089,776 (723,744–1,636,032)755,490 (520,518–1,080,864)660,942 (477,430–921,111)− 42.3
50–69 years541,198 (411,353–813,917)619,595 (449,209–901,830)643,310 (455,098–948,833)519,960 (372,897–763,299)363,631 (259,050–524,544)312,294 (227,215–440,406)− 42.3
70+ years162,936 (127,597–221,855)191,308 (149,138–256,179)196,198 (150,260–266,630)156,696 (119,232–207,194)111,538 (84,317–148,261)101,646 (77,262–134,947)− 37.6
All ages2,754,545 (2,222,630–3,625,684)3,058,066 (2,396,218–3,929,792)3,040,101 (2,347,459–4,075,851)2,361,431 (1,801,039–3,192,772)1,708,950 (1,321,347–2,300,534)1,440,229 (1,127,285–1,921,654)− 47.7
Numbers of disability-adjusted life years (with 95% uncertainty interval, UI) due to tuberculosis in Nigeria, 1990–2016 In 2016, YLLs were highest among people aged 15–49 years (623,955, 95% UI; 442,103-888,510), followed by those aged 50–69 years (301,086, 95% UI; 216,478-428,083) (Additional file 1: Table S1). YLDs were highest in those aged 15–49 years (36,987, 95% UI; 22,578-55,926) and adults between 50 and 69 years (11,208, 95% UI; 6263-17,761]) (Additional file 1: Table S2). Between 1990 and 2016, DALYs and YLLs decreased in all age group over time, while there were variations in the YLDs across the age groups.

TB mortality and DALYs attributable to individual risk factors

In Nigeria, alcohol use accounted for 13,196 (95% UI; 7277-20,605) TB deaths among HIV-negative people in 2016, followed by diabetes (1486 deaths [818-2493]) and smoking (942 deaths [349-1756]) (Additional file 1: Table S3). Proportionally, TB deaths that could be attributed to alcohol use was 38%, (95% UI; 23–52%), diabetes (4%, 95% UI; 3–6%) and smoking (3%, 95% UI; 1–5%) in 2016. The number of DALYs from TB due to alcohol use was 496,147 (95% UI; 283,342-777,331), followed by diabetes at 45,926 (95% UI; 26,297-75,452) and smoking at 32,369 (95% UI; 11,417-60,737) in 2016 (Additional file 1: Table S3).

Discussion

In Nigeria, the prevalence of TB among HIV-negative people was 27%, the TB incidence rate was 158 per 100,000 population, and the total number of TB mortality was 39,933 in 2016. From 2000 to 2016, the age-standardised prevalence, incidence and mortality rates dropped considerably, with variations across the age groups. The number DALYs due to TB among HIV-negative Nigerians varied across the age groups; highest in those aged 15–49 years, followed by people aged 50–69 years and children under 5 years in 2016. Alcohol use accounted for the highest number of deaths and DALYs that could be attributed to TB in 2016, followed by diabetes and smoking, probably reflecting the high burden of TB among older adults. Consistent with previous studies [1, 32, 33], this study showed that the prevalence and incidence of TB among HIV-negative people were higher in adults compared to children in Nigeria. Evidence has shown that not all individuals who are exposed to the Mycobacterium tuberculosis progress to having active TB infections. Studies from high burden TB environments suggest that approximately 20% of people maintain negative tuberculin skin tests throughout their lifespan despite repeated exposure to the mycobacteria [34]. In young children, active TB disease usually results from the haematogenous spread of the mycobacterium after primary infection, associated with subsequent pulmonary and extrapulmonary infections in some cases. In adults, however, TB infection is usually pulmonary and may reflect the reactivation of the latent TB infection (LTBI) from a primary site, which may partly be responsible for the increased prevalence and incidence observed in adults [35]. While only a limited number of individuals with LTBI progress to active TB disease, it is worth noting that one untreated infected person can transmit the disease to many healthy people, with broader implications for population health and TB control programmes [36, 37]. Early treatment of advanced LTBI in high TB-endemic countries like Nigeria is been advocated [38], and if the intervention is well implemented, it would reduce TB incidence and improve survival and productivity. The present study showed that the number of deaths from TB mortality had dropped substantially over time in Nigeria, consistent with other reports [1, 2]. Similarly, between 2000 and 2016, this study indicated that TB incidence has declined. This improvement could be attributed to the scale-up of strategic policies and interventions, socioeconomic growth and a stable political environment [33, 39, 40], as well as increased developmental assistance for health and impact of the Millennium Development Goal agenda [17]. However, the WHO Tuberculosis Report 2017 indicated that TB incident cases have remained stagnant in Nigeria since the year 2000 [1]. The variation in the findings may be due to the data sources and methodological approach used wherein the WHO estimated TB incidence based on WHO notification [1]. The GBD study, however, employed a statistical triangulation method that utilised all data sources (including data from the WHO global TB database and surveillance data) in Nigeria for TB estimation [3, 41]. A recent systemic review conducted in Nigeria reported higher levels of MDR-TB compared to the WHO estimate [42]. Despite the differences in data sources and methodology, both the WHO and GBD study reported similar estimates for global TB incidence and mortality in 2016 [1, 28]. Globally, delayed TB diagnosis and treatment has been shown to increase the transmission of the mycobacterium, exacerbate the disease, increase the likelihood of mortality [43-45] and may be a reason for why TB incident cases have not reduced considerably compared to TB mortality [1, 3]. Evidence from regional areas of Nigeria found that delayed diagnosis and treatment of TB was due to factors such as a lack of awareness of TB symptoms by primary health professionals, older age, distance to the public health facility, male gender, and first clinic visit to a non-tuberculosis control programme providers [43, 46–48]. Additional studies have suggested that a lack of knowledge about TB in the community and patients preference for private health practitioners are the major reasons for why patients delay TB treatment [44, 45]. However, Lambert and Van der Stuyft argued that the failed health care system should be blamed and not the patient because there is limited evidence to indicate that health education about TB could reduce treatment delays [49]. Improving timely diagnosis and treatment of TB in Nigeria will require improved human resources, better coordination and decentralisation of TB control programmes [6], as well as increased and monitoring of public health financing [50]. The estimation of the population attributable risk for a specific disease or injury is crucial for health and other relevant agencies to identify opportunities for preventive efforts and policy priorities [22, 51, 52]. In the current study, we found that alcohol use, tobacco smoking and diabetes were essential contributors to the burden of TB in Nigeria. Studies have shown that the association between alcohol use [53, 54], smoking [55] and tuberculosis is due to impairment of the host immune system (innate and adaptive response), which increases vulnerability to TB infection, or reactivation of latent TB infection. Diabetes leads to increased susceptibility to tuberculosis through direct effects of hyperglycaemia and inadequate secretion of insulin at the cellular level, as well as indirect effects on specialised anti-TB immune cells (macrophages and lymphocytes), where chemotaxis, phagocytosis, activation and antigen presentation by macrophages are impaired [7, 56]. Evidence from regional areas of Nigeria has suggested that the lifetime prevalence of alcohol use was 57.9% [57], while the overall prevalence of current alcohol use ranged from 15 to 24% [57-60]. In Nigeria, there are some policy initiatives (excise tax on beer, wine and spirits, the national legal minimum age for on/off-premise sales of alcoholic beverages and regulations on alcohol advertising) to limit alcohol use. However, there is currently no written national action plan, nor is there a national monitoring system or enforcement of relevant policies to reduce alcohol use [61]. For tobacco smoking, an estimated 5.6% Nigerian adults aged over 15 years smoked tobacco products in 2017 [62]. Similar to alcohol use initiatives, strategic policies to support Nigerians to quit smoking [62], as well as efforts to prevent diabetes, are weak [63, 64]. Our finding implies that efforts must not only be made to strengthen the health system and its human resources for TB control but also calls for collaborative, targeted and measurable socioeconomic reforms that address issues of alcohol use, tobacco, smoking and vulnerabilities, galvanised with strong political support to reduce TB burden in Nigeria. The current study has policy implications for national health agencies and development partners aiming to reduce the high burden of TB and improve the quality of life in Nigeria because it provides relevant country-specific epidemiologic data for TB disease. The World Health Organization End TB Strategy highlights priority areas for attention to end the global TB epidemic, with targets to reduce TB deaths by 95% and to cut incidence by 90% between 2015 and 2035 [65, 66]. The WHO domains include integrated, patient-centred TB care and prevention; bold policies and supportive systems; and intensified research and innovation. For Nigeria to achieve the WHO goal of ending TB, a multipronged approach will be needed. Those strategic measures will include closing the funding gaps for TB control programmes and reducing the reliance on international donors; scaling up the national immunisation schedule (including the anti-TB vaccine, bacillus calmette–guérin) in underserved areas; improving the political commitment at all levels of government; and strengthening the healthcare system and TB diagnosis and surveillance [3, 42], including improving coordination, integration and consistency in the primary health care structure through the National Primary Care Health Development Agency [6]. Additional measures to reduce the high burden of TB in Nigeria should also include initiatives to limit alcohol use and prevent tobacco smoking and diabetes [3]. The study has several methodological limitations, and they have been described in detail elsewhere [3, 21, 22]. Briefly, caution should be exercised when interpreting the study findings especially that vital registration and other high-quality data for TB are sparse at the subnational and national levels in Nigeria. Importantly, the availability of high-quality TB data at the subnational level is essential given differences in the socioeconomic and political situation in Nigeria which have been shown to influence healthcare and social policies [67, 68]. In the present study, the assessment of TB mortality was based on various modelling strategies of WHO notification and other published data. Consequently, the TB estimates for Nigeria with limited high-quality data are reflected in the wide uncertainty intervals. Efforts at improving both subnational and national research, surveys and vital statistics on TB disease burden are warranted in Nigeria to guide strategic policy interventions. While there is biological plausibility for the association between malnutrition and TB, the attributable burden of malnutrition due to TB was not examined in GBD 2016 because of limited evidence of a casual association. The limitations related to the estimation of TB incidence, YLLs, YLDs and DALYs using the GBD Bayesian meta-regression tool also applied to this study [24, 25]. Publication bias relating to the use of the GBD data may also be a limitation. Despite these limitations, this study provides comprehensive country-level epidemiologic data on TB disease burden and attributable risk factors to inform better TB prevention and control programmes in Nigeria, a country with Africa’s largest population of over 186 million people [40]. Future studies which investigate the rate of decline of TB incidence and mortality at the subnational level and whether those declines are fast enough to meet the WHO End TB Strategy may be warranted.

Conclusion

Between 1990 and 2016, the present study showed a decreasing trend in TB disease burden among HIV-negative people in Nigeria. Despite this progress, TB disease remains a significant public health issue in the country. Efforts to ensure a further reduction in TB disease burden, as well as improve the health and well-being of Nigerians, will require a multipronged approach that includes increased funding and appropriate monitoring, health system strengthening and enhanced national and subnational surveillance for TB disease. Table S1. Number of years of life lost (with 95% uncertainty interval, UI) due to tuberculosis in Nigeria, 1990–2016. Table S2. Number of years of life lived with disability (with 95% uncertainty interval, UI) due to tuberculosis in Nigeria, 1990–2016. Table S3. Numbers of deaths and disability-adjusted life years (with 95% uncertainty interval, UI) from tuberculosis due to attributable risk factors in Nigeria, 1990–2016. (DOCX 25 kb)
  46 in total

Review 1.  Latent Mycobacterium tuberculosis infection.

Authors:  Haileyesus Getahun; Alberto Matteelli; Richard E Chaisson; Mario Raviglione
Journal:  N Engl J Med       Date:  2015-05-28       Impact factor: 91.245

2.  Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study.

Authors:  C J Murray; A D Lopez
Journal:  Lancet       Date:  1997-05-24       Impact factor: 79.321

3.  Tuberculosis and excess alcohol use in the United States, 1997-2012.

Authors:  T Volkmann; P K Moonan; R Miramontes; J E Oeltmann
Journal:  Int J Tuberc Lung Dis       Date:  2015-01       Impact factor: 2.373

Review 4.  Prevalence of drug-resistant tuberculosis in Nigeria: A systematic review and meta-analysis.

Authors:  Cajetan C Onyedum; Isaac Alobu; Kingsley Nnanna Ukwaja
Journal:  PLoS One       Date:  2017-07-13       Impact factor: 3.240

Review 5.  Barriers to initiating tuberculosis treatment in sub-Saharan Africa: a systematic review focused on children and youth.

Authors:  Brittney J Sullivan; B Emily Esmaili; Coleen K Cunningham
Journal:  Glob Health Action       Date:  2017       Impact factor: 2.640

6.  Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016.

Authors: 
Journal:  Lancet       Date:  2017-09-16       Impact factor: 79.321

7.  Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Authors:  Christopher J L Murray; Ryan M Barber; Kyle J Foreman; Ayse Abbasoglu Ozgoren; Foad Abd-Allah; Semaw F Abera; Victor Aboyans; Jerry P Abraham; Ibrahim Abubakar; Laith J Abu-Raddad; Niveen M Abu-Rmeileh; Tom Achoki; Ilana N Ackerman; Zanfina Ademi; Arsène K Adou; José C Adsuar; Ashkan Afshin; Emilie E Agardh; Sayed Saidul Alam; Deena Alasfoor; Mohammed I Albittar; Miguel A Alegretti; Zewdie A Alemu; Rafael Alfonso-Cristancho; Samia Alhabib; Raghib Ali; François Alla; Peter Allebeck; Mohammad A Almazroa; Ubai Alsharif; Elena Alvarez; Nelson Alvis-Guzman; Azmeraw T Amare; Emmanuel A Ameh; Heresh Amini; Walid Ammar; H Ross Anderson; Benjamin O Anderson; Carl Abelardo T Antonio; Palwasha Anwari; Johan Arnlöv; Valentina S Arsic Arsenijevic; Al Artaman; Rana J Asghar; Reza Assadi; Lydia S Atkins; Marco A Avila; Baffour Awuah; Victoria F Bachman; Alaa Badawi; Maria C Bahit; Kalpana Balakrishnan; Amitava Banerjee; Suzanne L Barker-Collo; Simon Barquera; Lars Barregard; Lope H Barrero; Arindam Basu; Sanjay Basu; Mohammed O Basulaiman; Justin Beardsley; Neeraj Bedi; Ettore Beghi; Tolesa Bekele; Michelle L Bell; Corina Benjet; Derrick A Bennett; Isabela M Bensenor; Habib Benzian; Eduardo Bernabé; Amelia Bertozzi-Villa; Tariku J Beyene; Neeraj Bhala; Ashish Bhalla; Zulfiqar A Bhutta; Kelly Bienhoff; Boris Bikbov; Stan Biryukov; Jed D Blore; Christopher D Blosser; Fiona M Blyth; Megan A Bohensky; Ian W Bolliger; Berrak Bora Başara; Natan M Bornstein; Dipan Bose; Soufiane Boufous; Rupert R A Bourne; Lindsay N Boyers; Michael Brainin; Carol E Brayne; Alexandra Brazinova; Nicholas J K Breitborde; Hermann Brenner; Adam D Briggs; Peter M Brooks; Jonathan C Brown; Traolach S Brugha; Rachelle Buchbinder; Geoffrey C Buckle; Christine M Budke; Anne Bulchis; Andrew G Bulloch; Ismael R Campos-Nonato; Hélène Carabin; Jonathan R Carapetis; Rosario Cárdenas; David O Carpenter; Valeria Caso; Carlos A Castañeda-Orjuela; Ruben E Castro; Ferrán Catalá-López; Fiorella Cavalleri; Alanur Çavlin; Vineet K Chadha; Jung-Chen Chang; Fiona J Charlson; Honglei Chen; Wanqing Chen; Peggy P Chiang; Odgerel Chimed-Ochir; Rajiv Chowdhury; Hanne Christensen; Costas A Christophi; Massimo Cirillo; Matthew M Coates; Luc E Coffeng; Megan S Coggeshall; Valentina Colistro; Samantha M Colquhoun; Graham S Cooke; Cyrus Cooper; Leslie T Cooper; Luis M Coppola; Monica Cortinovis; Michael H Criqui; John A Crump; Lucia Cuevas-Nasu; Hadi Danawi; Lalit Dandona; Rakhi Dandona; Emily Dansereau; Paul I Dargan; Gail Davey; Adrian Davis; Dragos V Davitoiu; Anand Dayama; Diego De Leo; Louisa Degenhardt; Borja Del Pozo-Cruz; Robert P Dellavalle; Kebede Deribe; Sarah Derrett; Don C Des Jarlais; Muluken Dessalegn; Samath D Dharmaratne; Mukesh K Dherani; Cesar Diaz-Torné; Daniel Dicker; Eric L Ding; Klara Dokova; E Ray Dorsey; Tim R Driscoll; Leilei Duan; Herbert C Duber; Beth E Ebel; Karen M Edmond; Yousef M Elshrek; Matthias Endres; Sergey P Ermakov; Holly E Erskine; Babak Eshrati; Alireza Esteghamati; Kara Estep; Emerito Jose A Faraon; Farshad Farzadfar; Derek F Fay; Valery L Feigin; David T Felson; Seyed-Mohammad Fereshtehnejad; Jefferson G Fernandes; Alize J Ferrari; Christina Fitzmaurice; Abraham D Flaxman; Thomas D Fleming; Nataliya Foigt; Mohammad H Forouzanfar; F Gerry R Fowkes; Urbano Fra Paleo; Richard C Franklin; Thomas Fürst; Belinda Gabbe; Lynne Gaffikin; Fortuné G Gankpé; Johanna M Geleijnse; Bradford D Gessner; Peter Gething; Katherine B Gibney; Maurice Giroud; Giorgia Giussani; Hector Gomez Dantes; Philimon Gona; Diego González-Medina; Richard A Gosselin; Carolyn C Gotay; Atsushi Goto; Hebe N Gouda; Nicholas Graetz; Harish C Gugnani; Rahul Gupta; Rajeev Gupta; Reyna A Gutiérrez; Juanita Haagsma; Nima Hafezi-Nejad; Holly Hagan; Yara A Halasa; Randah R Hamadeh; Hannah Hamavid; Mouhanad Hammami; Jamie Hancock; Graeme J Hankey; Gillian M Hansen; Yuantao Hao; Hilda L Harb; Josep Maria Haro; Rasmus Havmoeller; Simon I Hay; Roderick J Hay; Ileana B Heredia-Pi; Kyle R Heuton; Pouria Heydarpour; Hideki Higashi; Martha Hijar; Hans W Hoek; Howard J Hoffman; H Dean Hosgood; Mazeda Hossain; Peter J Hotez; Damian G Hoy; Mohamed Hsairi; Guoqing Hu; Cheng Huang; John J Huang; Abdullatif Husseini; Chantal Huynh; Marissa L Iannarone; Kim M Iburg; Kaire Innos; Manami Inoue; Farhad Islami; Kathryn H Jacobsen; Deborah L Jarvis; Simerjot K Jassal; Sun Ha Jee; Panniyammakal Jeemon; Paul N Jensen; Vivekanand Jha; Guohong Jiang; Ying Jiang; Jost B Jonas; Knud Juel; Haidong Kan; André Karch; Corine K Karema; Chante Karimkhani; Ganesan Karthikeyan; Nicholas J Kassebaum; Anil Kaul; Norito Kawakami; Konstantin Kazanjan; Andrew H Kemp; Andre P Kengne; Andre Keren; Yousef S Khader; Shams Eldin A Khalifa; Ejaz A Khan; Gulfaraz Khan; Young-Ho Khang; Christian Kieling; Daniel Kim; Sungroul Kim; Yunjin Kim; Yohannes Kinfu; Jonas M Kinge; Miia Kivipelto; Luke D Knibbs; Ann Kristin Knudsen; Yoshihiro Kokubo; Soewarta Kosen; Sanjay Krishnaswami; Barthelemy Kuate Defo; Burcu Kucuk Bicer; Ernst J Kuipers; Chanda Kulkarni; Veena S Kulkarni; G Anil Kumar; Hmwe H Kyu; Taavi Lai; Ratilal Lalloo; Tea Lallukka; Hilton Lam; Qing Lan; Van C Lansingh; Anders Larsson; Alicia E B Lawrynowicz; Janet L Leasher; James Leigh; Ricky Leung; Carly E Levitz; Bin Li; Yichong Li; Yongmei Li; Stephen S Lim; Maggie Lind; Steven E Lipshultz; Shiwei Liu; Yang Liu; Belinda K Lloyd; Katherine T Lofgren; Giancarlo Logroscino; Katharine J Looker; Joannie Lortet-Tieulent; Paulo A Lotufo; Rafael Lozano; Robyn M Lucas; Raimundas Lunevicius; Ronan A Lyons; Stefan Ma; Michael F Macintyre; Mark T Mackay; Marek Majdan; Reza Malekzadeh; Wagner Marcenes; David J Margolis; Christopher Margono; Melvin B Marzan; Joseph R Masci; Mohammad T Mashal; Richard Matzopoulos; Bongani M Mayosi; Tasara T Mazorodze; Neil W Mcgill; John J Mcgrath; Martin Mckee; Abigail Mclain; Peter A Meaney; Catalina Medina; Man Mohan Mehndiratta; Wubegzier Mekonnen; Yohannes A Melaku; Michele Meltzer; Ziad A Memish; George A Mensah; Atte Meretoja; Francis A Mhimbira; Renata Micha; Ted R Miller; Edward J Mills; Philip B Mitchell; Charles N Mock; Norlinah Mohamed Ibrahim; Karzan A Mohammad; Ali H Mokdad; Glen L D Mola; Lorenzo Monasta; Julio C Montañez Hernandez; Marcella Montico; Thomas J Montine; Meghan D Mooney; Ami R Moore; Maziar Moradi-Lakeh; Andrew E Moran; Rintaro Mori; Joanna Moschandreas; Wilkister N Moturi; Madeline L Moyer; Dariush Mozaffarian; William T Msemburi; Ulrich O Mueller; Mitsuru Mukaigawara; Erin C Mullany; Michele E Murdoch; Joseph Murray; Kinnari S Murthy; Mohsen Naghavi; Aliya Naheed; Kovin S Naidoo; Luigi Naldi; Devina Nand; Vinay Nangia; K M Venkat Narayan; Chakib Nejjari; Sudan P Neupane; Charles R Newton; Marie Ng; Frida N Ngalesoni; Grant Nguyen; Muhammad I Nisar; Sandra Nolte; Ole F Norheim; Rosana E Norman; Bo Norrving; Luke Nyakarahuka; In-Hwan Oh; Takayoshi Ohkubo; Summer L Ohno; Bolajoko O Olusanya; John Nelson Opio; Katrina Ortblad; Alberto Ortiz; Amanda W Pain; Jeyaraj D Pandian; Carlo Irwin A Panelo; Christina Papachristou; Eun-Kee Park; Jae-Hyun Park; Scott B Patten; George C Patton; Vinod K Paul; Boris I Pavlin; Neil Pearce; David M Pereira; Rogelio Perez-Padilla; Fernando Perez-Ruiz; Norberto Perico; Aslam Pervaiz; Konrad Pesudovs; Carrie B Peterson; Max Petzold; Michael R Phillips; Bryan K Phillips; David E Phillips; Frédéric B Piel; Dietrich Plass; Dan Poenaru; Suzanne Polinder; Daniel Pope; Svetlana Popova; Richie G Poulton; Farshad Pourmalek; Dorairaj Prabhakaran; Noela M Prasad; Rachel L Pullan; Dima M Qato; D Alex Quistberg; Anwar Rafay; Kazem Rahimi; Sajjad U Rahman; Murugesan Raju; Saleem M Rana; Homie Razavi; K Srinath Reddy; Amany Refaat; Giuseppe Remuzzi; Serge Resnikoff; Antonio L Ribeiro; Lee Richardson; Jan Hendrik Richardus; D Allen Roberts; David Rojas-Rueda; Luca Ronfani; Gregory A Roth; Dietrich Rothenbacher; David H Rothstein; Jane T Rowley; Nobhojit Roy; George M Ruhago; Mohammad Y Saeedi; Sukanta Saha; Mohammad Ali Sahraian; Uchechukwu K A Sampson; Juan R Sanabria; Logan Sandar; Itamar S Santos; Maheswar Satpathy; Monika Sawhney; Peter Scarborough; Ione J Schneider; Ben Schöttker; Austin E Schumacher; David C Schwebel; James G Scott; Soraya Seedat; Sadaf G Sepanlou; Peter T Serina; Edson E Servan-Mori; Katya A Shackelford; Amira Shaheen; Saeid Shahraz; Teresa Shamah Levy; Siyi Shangguan; Jun She; Sara Sheikhbahaei; Peilin Shi; Kenji Shibuya; Yukito Shinohara; Rahman Shiri; Kawkab Shishani; Ivy Shiue; Mark G Shrime; Inga D Sigfusdottir; Donald H Silberberg; Edgar P Simard; Shireen Sindi; Abhishek Singh; Jasvinder A Singh; Lavanya Singh; Vegard Skirbekk; Erica Leigh Slepak; Karen Sliwa; Samir Soneji; Kjetil Søreide; Sergey Soshnikov; Luciano A Sposato; Chandrashekhar T Sreeramareddy; Jeffrey D Stanaway; Vasiliki Stathopoulou; Dan J Stein; Murray B Stein; Caitlyn Steiner; Timothy J Steiner; Antony Stevens; Andrea Stewart; Lars J Stovner; Konstantinos Stroumpoulis; Bruno F Sunguya; Soumya Swaminathan; Mamta Swaroop; Bryan L Sykes; Karen M Tabb; Ken Takahashi; Nikhil Tandon; David Tanne; Marcel Tanner; Mohammad Tavakkoli; Hugh R Taylor; Braden J Te Ao; Fabrizio Tediosi; Awoke M Temesgen; Tara Templin; Margreet Ten Have; Eric Y Tenkorang; Abdullah S Terkawi; Blake Thomson; Andrew L Thorne-Lyman; Amanda G Thrift; George D Thurston; Taavi Tillmann; Marcello Tonelli; Fotis Topouzis; Hideaki Toyoshima; Jefferson Traebert; Bach X Tran; Matias Trillini; Thomas Truelsen; Miltiadis Tsilimbaris; Emin M Tuzcu; Uche S Uchendu; Kingsley N Ukwaja; Eduardo A Undurraga; Selen B Uzun; Wim H Van Brakel; Steven Van De Vijver; Coen H van Gool; Jim Van Os; Tommi J Vasankari; N Venketasubramanian; Francesco S Violante; Vasiliy V Vlassov; Stein Emil Vollset; Gregory R Wagner; Joseph Wagner; Stephen G Waller; Xia Wan; Haidong Wang; Jianli Wang; Linhong Wang; Tati S Warouw; Scott Weichenthal; Elisabete Weiderpass; Robert G Weintraub; Wang Wenzhi; Andrea Werdecker; Ronny Westerman; Harvey A Whiteford; James D Wilkinson; Thomas N Williams; Charles D Wolfe; Timothy M Wolock; Anthony D Woolf; Sarah Wulf; Brittany Wurtz; Gelin Xu; Lijing L Yan; Yuichiro Yano; Pengpeng Ye; Gökalp K Yentür; Paul Yip; Naohiro Yonemoto; Seok-Jun Yoon; Mustafa Z Younis; Chuanhua Yu; Maysaa E Zaki; Yong Zhao; Yingfeng Zheng; David Zonies; Xiaonong Zou; Joshua A Salomon; Alan D Lopez; Theo Vos
Journal:  Lancet       Date:  2015-08-28       Impact factor: 79.321

8.  Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study.

Authors:  Christina Fitzmaurice; Christine Allen; Ryan M Barber; Lars Barregard; Zulfiqar A Bhutta; Hermann Brenner; Daniel J Dicker; Odgerel Chimed-Orchir; Rakhi Dandona; Lalit Dandona; Tom Fleming; Mohammad H Forouzanfar; Jamie Hancock; Roderick J Hay; Rachel Hunter-Merrill; Chantal Huynh; H Dean Hosgood; Catherine O Johnson; Jost B Jonas; Jagdish Khubchandani; G Anil Kumar; Michael Kutz; Qing Lan; Heidi J Larson; Xiaofeng Liang; Stephen S Lim; Alan D Lopez; Michael F MacIntyre; Laurie Marczak; Neal Marquez; Ali H Mokdad; Christine Pinho; Farshad Pourmalek; Joshua A Salomon; Juan Ramon Sanabria; Logan Sandar; Benn Sartorius; Stephen M Schwartz; Katya A Shackelford; Kenji Shibuya; Jeff Stanaway; Caitlyn Steiner; Jiandong Sun; Ken Takahashi; Stein Emil Vollset; Theo Vos; Joseph A Wagner; Haidong Wang; Ronny Westerman; Hajo Zeeb; Leo Zoeckler; Foad Abd-Allah; Muktar Beshir Ahmed; Samer Alabed; Noore K Alam; Saleh Fahed Aldhahri; Girma Alem; Mulubirhan Assefa Alemayohu; Raghib Ali; Rajaa Al-Raddadi; Azmeraw Amare; Yaw Amoako; Al Artaman; Hamid Asayesh; Niguse Atnafu; Ashish Awasthi; Huda Ba Saleem; Aleksandra Barac; Neeraj Bedi; Isabela Bensenor; Adugnaw Berhane; Eduardo Bernabé; Balem Betsu; Agnes Binagwaho; Dube Boneya; Ismael Campos-Nonato; Carlos Castañeda-Orjuela; Ferrán Catalá-López; Peggy Chiang; Chioma Chibueze; Abdulaal Chitheer; Jee-Young Choi; Benjamin Cowie; Solomon Damtew; José das Neves; Suhojit Dey; Samath Dharmaratne; Preet Dhillon; Eric Ding; Tim Driscoll; Donatus Ekwueme; Aman Yesuf Endries; Maryam Farvid; Farshad Farzadfar; Joao Fernandes; Florian Fischer; Tsegaye Tewelde G/Hiwot; Alemseged Gebru; Sameer Gopalani; Alemayehu Hailu; Masako Horino; Nobuyuki Horita; Abdullatif Husseini; Inge Huybrechts; Manami Inoue; Farhad Islami; Mihajlo Jakovljevic; Spencer James; Mehdi Javanbakht; Sun Ha Jee; Amir Kasaeian; Muktar Sano Kedir; Yousef S Khader; Young-Ho Khang; Daniel Kim; James Leigh; Shai Linn; Raimundas Lunevicius; Hassan Magdy Abd El Razek; Reza Malekzadeh; Deborah Carvalho Malta; Wagner Marcenes; Desalegn Markos; Yohannes A Melaku; Kidanu G Meles; Walter Mendoza; Desalegn Tadese Mengiste; Tuomo J Meretoja; Ted R Miller; Karzan Abdulmuhsin Mohammad; Alireza Mohammadi; Shafiu Mohammed; Maziar Moradi-Lakeh; Gabriele Nagel; Devina Nand; Quyen Le Nguyen; Sandra Nolte; Felix A Ogbo; Kelechi E Oladimeji; Eyal Oren; Mahesh Pa; Eun-Kee Park; David M Pereira; Dietrich Plass; Mostafa Qorbani; Amir Radfar; Anwar Rafay; Mahfuzar Rahman; Saleem M Rana; Kjetil Søreide; Maheswar Satpathy; Monika Sawhney; Sadaf G Sepanlou; Masood Ali Shaikh; Jun She; Ivy Shiue; Hirbo Roba Shore; Mark G Shrime; Samuel So; Samir Soneji; Vasiliki Stathopoulou; Konstantinos Stroumpoulis; Muawiyyah Babale Sufiyan; Bryan L Sykes; Rafael Tabarés-Seisdedos; Fentaw Tadese; Bemnet Amare Tedla; Gizachew Assefa Tessema; J S Thakur; Bach Xuan Tran; Kingsley Nnanna Ukwaja; Benjamin S Chudi Uzochukwu; Vasiliy Victorovich Vlassov; Elisabete Weiderpass; Mamo Wubshet Terefe; Henock Gebremedhin Yebyo; Hassen Hamid Yimam; Naohiro Yonemoto; Mustafa Z Younis; Chuanhua Yu; Zoubida Zaidi; Maysaa El Sayed Zaki; Zerihun Menlkalew Zenebe; Christopher J L Murray; Mohsen Naghavi
Journal:  JAMA Oncol       Date:  2017-04-01       Impact factor: 31.777

9.  Healthcare-seeking behavior, treatment delays and its determinants among pulmonary tuberculosis patients in rural Nigeria: a cross-sectional study.

Authors:  Kingsley N Ukwaja; Isaac Alobu; Chibueze O Nweke; Ephraim C Onyenwe
Journal:  BMC Health Serv Res       Date:  2013-01-17       Impact factor: 2.655

10.  Prevalence and Correlates of Alcohol Use among a Sample of Nigerian Semirural Community Dwellers in Nigeria.

Authors:  Victor Olufolahan Lasebikan; Bolanle Adeyemi Ola
Journal:  J Addict       Date:  2016-04-19
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  9 in total

1.  Common bacteria in sputum or gastric lavage of patients presenting with signs and symptoms of lower respiratory tract infections.

Authors:  Oliver Deberu; Bernard Nkrumah; Augustina Angelina Sylverken; David Sambian; Godfred Acheampong; John Amuasi; Azure Stebleson; Daron Agboyie; Monica Yenbaree; Sylvester Mensah; Abaifa Dombadoh; Dorcas Ohui Owusu; Abass Abdul-Karim; Michael Owusu
Journal:  Pan Afr Med J       Date:  2021-04-20

2.  The Gap Between Global Tuberculosis Incidence and the First Milestone of the WHO End Tuberculosis Strategy: An Analysis Based on the Global Burden of Disease 2017 Database.

Authors:  Zhenyu Pan; Jun Zhang; Qingting Bu; Hairong He; Ling Bai; Jin Yang; Qingqing Liu; Jun Lyu
Journal:  Infect Drug Resist       Date:  2020-05-04       Impact factor: 4.003

3.  The National Tuberculosis Control Programme of Liberia Laboratory Programme Performance.

Authors:  Kassaye Tekie Desta; T E Masango; Zerish Zethu Nkosi
Journal:  J Environ Public Health       Date:  2019-07-07

4.  Effect of a brief motivational interview and text message intervention targeting tobacco smoking, alcohol use and medication adherence to improve tuberculosis treatment outcomes in adult patients with tuberculosis: a multicentre, randomised controlled trial of the ProLife programme in South Africa.

Authors:  Goedele Louwagie; Mona Kanaan; Neo Keitumetse Morojele; Andre Van Zyl; Andrew Stephen Moriarty; Jinshuo Li; Kamran Siddiqi; Astrid Turner; Noreen Dadirai Mdege; Olufemi Babatunde Omole; John Tumbo; Max Bachmann; Steve Parrott; Olalekan A Ayo-Yusuf
Journal:  BMJ Open       Date:  2022-02-14       Impact factor: 2.692

5.  Diarrhoea deaths and disability-adjusted life years attributable to suboptimal breastfeeding practices in Nigeria: findings from the global burden of disease study 2016.

Authors:  Anselm Okoro; Bolajoko O Olusanya; Jacob Olusanya; Felix Akpojene Ogbo; Ifegwu K Ifegwu; Akorede O Awosemo; Pascal Ogeleka; Andrew Page
Journal:  Int Breastfeed J       Date:  2019-01-09       Impact factor: 3.461

6.  Computerised tomography scan in multi-drug-resistant versus extensively drug-resistant tuberculosis.

Authors:  Payam Mehrian; Poopak Farnia; Dina Jalalvand; Mostafa Rezaei Chamani; Mahmood Bakhtiyari
Journal:  Pol J Radiol       Date:  2020-01-23

7.  Nonadherence to tuberculosis treatment and associated factors among patients using directly observed treatment short-course in north-west Nigeria: A cross-sectional study.

Authors:  Cylia Nkechi Iweama; Olaoluwa Samson Agbaje; Prince Christian Ifeanachor Umoke; Chima Charles Igbokwe; Eyuche Lawretta Ozoemena; Nnenna Lois Omaka-Amari; Benjamin Mudi Idache
Journal:  SAGE Open Med       Date:  2021-01-30

8.  An Emerging Syndemic of Smoking and Cardiopulmonary Diseases in People Living with HIV in Africa.

Authors:  Emmanuel Peprah; Mari Armstrong-Hough; Stephanie H Cook; Barbara Mukasa; Jacquelyn Y Taylor; Huichun Xu; Linda Chang; Joyce Gyamfi; Nessa Ryan; Temitope Ojo; Anya Snyder; Juliet Iwelunmor; Oliver Ezechi; Conrad Iyegbe; Paul O'Reilly; Andre Pascal Kengne
Journal:  Int J Environ Res Public Health       Date:  2021-03-18       Impact factor: 3.390

9.  Evaluation of underweight status may improve identification of the highest-risk patients during outpatient evaluation for pulmonary tuberculosis.

Authors:  Peter J Kitonsa; Annet Nalutaaya; James Mukiibi; Olga Nakasolya; David Isooba; Caleb Kamoga; Yeonsoo Baik; Katherine Robsky; David W Dowdy; Achilles Katamba; Emily A Kendall
Journal:  PLoS One       Date:  2020-12-11       Impact factor: 3.752

  9 in total

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