Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 17  |  Issue : 2  |  Page : 60-64

Review of 5 year mortality trend at federal medical center, Umuahia Nigeria using the global burden of disease classification


1 Department of Medicine, Federal Medical Centre, Umuahia, Nigeria
2 Department of Medicine, Federal Medical Centre, Umuahia; Department of Medicine, Cardiology Unit, University of Calabar Teaching Hospital, Calabar, Nigeria
3 Department of Ophthalmology, Federal Medical Centre, Umuahia, Abia State, Nigeria

Date of Web Publication5-Aug-2015

Correspondence Address:
Kelechukwu Uwanuruochi
Department of Medicine, Federal Medical Centre, Umuahia, PMB 7001
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2276-7096.162272

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  Abstract 

Background: There have been few systematic studies of the causes of death in Nigeria. However, the causes of death as well as the average age at death are important statistics in the public health policy formulation. The global burden of disease (GBD) classification is very useful in describing relative etiologies of mortality, as well as the epidemiologic transition.
Objective: The aim of this study was to describe the causes of mortality in the Federal Medical Centre, Umuahia with respect to causes, gender, age at death, and duration of hospital stay using the GBD classification.
Methods: We retrospectively reviewed records of mortalities seen between February 2003 and December 2008 at the Federal Medical Centre, Umuahia using the deaths register at our records department.
Results: There were 3444 cases of mortality over the period, comprising 58.2% males and 41.4% females.
Mean age at death was 40.92 ± 26.12 years communicable, maternal, neonatal, and nutritional disorders comprised 39.91%, noncommunicable diseases made up 48.76%, while Injuries comprised 11.33%.
Conclusion: Public health attention should be sustained at reducing morbidity and mortality of noncommunicable diseases.

Keywords: Federal Medical Centre Nigeria, GBD classification, mortality trend


How to cite this article:
Oghale OM, Uwanuruochi K, Odigwe CO, Chuku A. Review of 5 year mortality trend at federal medical center, Umuahia Nigeria using the global burden of disease classification. J Med Trop 2015;17:60-4

How to cite this URL:
Oghale OM, Uwanuruochi K, Odigwe CO, Chuku A. Review of 5 year mortality trend at federal medical center, Umuahia Nigeria using the global burden of disease classification. J Med Trop [serial online] 2015 [cited 2022 Oct 4];17:60-4. Available from: https://www.jmedtropics.org/text.asp?2015/17/2/60/162272


  Introduction Top


A number of workers have undertaken to describe the mortality pattern in Nigerian hospitals in recent years. Adeolu and co-workers [1] have described the pattern of death at the Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC), Ile-Ife, Osun State in Southwest Nigeria from 1978 to 2006. Iliyasu et al. [2] also described the pattern of death at Aminu Kano Teaching Hospital, Kano, northern Nigeria, prospectively over a 4-year analysis but their study was limited to in-patients. Dahiru et al. [3] reviewed the causes of death between 1999 and 2005 in Ahmadu Bello University Teaching Hospital, Zaria. However, as the disease spectrum in the developing world is currently undergoing transition, there is a need for ongoing studies in patterns of disease morbidity and mortality. These data are vital in public health policy formulations.

The global burden of disease (GBD) classification followed the GBD study in 1993, and it has been a useful method to assess the relative contribution of different disease conditions. [4] It has been described as the most comprehensive and consistent set of estimates of mortality and morbidity yet produced. [5] It classifies diseases, on the 1 st level as either Group 1 consisting of communicable diseases, maternal, perinatal, and nutritional disorders, Group 2 consisting of noncommunicable diseases, and Group 3 consisting of all intentional or unintentional injuries. On a 2 nd level, Group 1 includes disease conditions that predominate in less developed countries. Group 2 includes various categories of noncommunicable diseases. Group 3 comprises war and disaster, classes of injuries. It also has higher levels of classification that identifies specific disease entities.

In this study, we describe the mortality in the Federal Medical Centre, Umuahia using the GBD classification. We also describe such characteristics as gender distribution, age at death, and duration of hospital stay.


  Methods Top


This is a retrospective analysis of prospectively collected data. The study was carried out at Federal Medical Centre, Umuahia, Nigeria. Federal Medical Centre, Umuahia is a tertiary health care institution in the capital city of Abia State, Nigeria which was founded on 24 th March, 1956 as a mission hospital, then named Queen Elizabeth hospital and subsequently taken over by the Federal Government in November 1991. This institution is 327-bedded with 58 medical beds. The data reviewed consisted of cases of mortality recorded between February 2003 and December 2008


  Statistics Top


Data management and analysis were performed with SPSS software version 15.0.(SPSS, Inc. Chicago Illinois, USA). Continuous variables were expressed as means, while categorical variables were expressed as proportions.


  Results Top


There were a total of 3444 cases of death, comprising 2004 (58.2%) males and 1425 (41.4%) females. The gender was missing in 15 cases. The age distribution is shown in [Table 1] while the sex distribution of mortalities over the years is as shown in [Table 2]. The mean age at death was 40.92 ± 26.12. There was no significant difference in mortality classes between males and females (X 2 = 0.017).
Table 1: Distribution of deaths according to age groups

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Table 2: Gender distribution of mortalities

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The distribution of causes using the 1 st level GBD classification is shown in [Table 3] while the distribution among the 2 nd level GBM classes, the mean ages at death, as well as the mean duration of hospital stay, is shown in [Table 4]. The duration of hospital stay ranged from 1 to 548 days, with a mean of 5.17 days.
Table 3: Causes of death by first level disease group

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Table 4: Distribution of cases and mean age of death in second level GBM classes

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Four hundred and twenty-five (12.3%) were dead on arrival, while the cause of death was not defined in 102 (3.0%). The trend in mortality from the various classes over the 5 years is shown in [Table 5].
Table 5: Trend in mortality over the years

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The distribution of mortality in the 1 st 24 h is shown in [Table 6]. In 37 cases (2.4%), the cause of death was not defined. The total number of mortalities within the 1 st 24 h was 1463. Specific causes of cardiovascular circulatory mortalities in the 1 st 24 h were shown in [Table 7] while the most common specific causes of death over the study period are shown in [Table 8].
Table 6: Most common causes of death within first 24 h

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Table 7: Specific causes of cardiovascular circulatory mortality within first 24 h

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Table 8: Most common causes of death over the study period

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  Discussion Top


The pattern of mortality has continued to be of immense interest to public health. In this study, we reviewed the distribution of causes of mortality over a 5 year period in the Federal Medical Centre, Umuahia. It is important to observe that noncommunicable diseases, as a 1 st level GBM class were the greatest cause of mortality in this study. This is a pointer to the changing trend in disease profile in sub-Saharan Africa. It will however be noted that when the various infections disorders from various 2 nd level GBM classes were combined, (neglected tropical diseases and malaria, HIV/AIDS and tuberculosis and diarrhea, Lower respiratory infections, Meningitis, and other common infections), they become the highest cause of mortality. This agrees with Adekunle et al., [6] who reported infections as the most common cause of death in a tertiary hospital in South-Western Nigeria over the same period. This calls for proper interpretation of mortality results when GBM classification is being utilized.

The cause of death registered was not specific for any system in as much as 3% of cases. This raises a need for improved record keeping. Health managers should be encouraged to ensure that medical officer certifying patients' dead endeavor to use specific diagnoses. This however may be because physicians were unable to conclude investigations, so as to arrive at a specific cause of the illness before the demise of the patients. A similar figure of 3.4% was not traced to a particular cause in a review of mortality in an accident and emergency department by Ekere et al. [7]

The most common cause of death was Infections (26.61%), followed by cardiovascular disease (19.9%) and Diabetes mellitus (6.24%). Dahiru et al. [3] reporting from Zaria over a similar interval reported HIV Infection (9.9%), Road traffic accident (9.5%), and Cardiovascular diseases (9.1%) as the most common causes. However, between 1997-2006, Adeolu et al. [1] reported renal disease (48.4%), hepatopancreatic disease (46.2%), and Cardiovascular disease (35.1%) as the most common causes of mortality. Factors contributing to these differences will include differences in definitions of these entities as well as variations in facilities at the various centers. OAUTHC, where Adeolu et al. worked, had a specialist gastroenterology service during the interval under review, and this may explain the high prevalence of hepatopancreatic causes at the center. A similar explanation could account for the higher prevalence of renal disease mortalities at the center.

A high percentage (12.3) was brought in dead to the hospital. Ekere et al. [7] reported a smaller percentage (3.6) in their own study at the University Teaching Hospital Port-Harcourt, while Chukuezi and Nwosu [8] from Imo State University Teaching Hospital, Orlu recorded an even higher figure (19.93%). This would likely reflect a number of variables including the enlightenment of the host community, patient's medical access as well as referral culture of physicians. Because of local sentiments about hospital deaths, many local practitioners avoid patients dying in their facilities and therefore, tend to refer them to bigger hospitals when the outcome is predictable.

This study makes a case for a more detailed and prospective assessment of mortality in Sub-Saharan countries using the GBM classification.


  Limitations Top


There are many areas for improvement in future studies. This study was retrospective and so the data were not prepared for this study. There were also many cases of missing or incorrectly recorded data.


  Conclusion Top


Our study shows that noncommunicable diseases, as a 1 st level GBM disease class, were responsible for most cases of mortality at Federal Medical Centre, Umuahia South-Eastern Nigeria between 2002 and 2008. However, on specific, 2 nd level GBM disease classification, infections caused most deaths, followed by cardiovascular diseases, and diabetes mellitus. Public health attention should be sustained at reducing the morbidity and mortality of noncommunicable diseases.


  Acknowledgments Top


We are grateful to the record staff of our hospital for their cordial assistance.

 
  References Top

1.
Adeolu AA, Arowolo OA, Alatise OI, Osasan SA, Bisiriyu LA, Omoniyi EO, et al. Mortality trends in a Nigerian teaching hospital over three decades. Afr Health Sci 2010;10:266-72.  Back to cited text no. 1
    
2.
Iliyasu Z, Abubakar IS, Gajida AU. Magnitude and leading causes of in-hospital mortality at Aminu Kano Teaching Hospital, Kano, northern Nigeria: A 4-year prospective analysis. Niger J Med 2010;19:400-6.  Back to cited text no. 2
    
3.
Dahiru T, Sabitu K, Oyemakinde A, Mande AT, Singha P. Mortality and cause of death in Abuth, Zaria: 1999-2005. Ann Ib Postgrad Med 2010;8:40-6.  Back to cited text no. 3
    
4.
Polinder S, Haagsma JA, Stein C, Havelaar AH. Systematic review of general burden of disease studies using disability-adjusted life years. Popul Health Metr 2012;10:21.  Back to cited text no. 4
    
5.
Murray CJ, Lopez AD. Evidence-based health policy - lessons from the Global Burden of Disease Study. Science 1996;274:740-3.  Back to cited text no. 5
    
6.
Adekunle O, Olatunde IO, Abdullateef RM. Causes and pattern of death in a tertiary health institution in South Western Nigeria. Niger Postgrad Med J 2008;15:247-50.  Back to cited text no. 6
    
7.
Ekere AU, Yellowe BE, Umune S. Mortality patterns in the accident and emergency department of an urban hospital in Nigeria. Niger J Clin Pract 2005;8:14-8.  Back to cited text no. 7
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8.
Chukuezi AB, Nwosu JN. Pattern of deaths in the adult accident and emergency department of a Sub-Urban teaching hospital in Nigeria. Asian J Med Sci 2010;2:66-9.  Back to cited text no. 8
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

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  In this article
Abstract
Introduction
Methods
Statistics
Results
Discussion
Limitations
Conclusion
Acknowledgments
References
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