Investigation of the Burden of HIV/AIDS and Cancer in Underdeveloped, Developing and Developed Countries Volume 2 - Issue 2

İlker Etikan*, Akinleye Adewumi Adebayo and Galip Savas İlgi

• Department of Biostatistics, Near East University, Cyprus

Received: January 13, 2020;   Published: January 24, 2020

*Corresponding author: İlkerEtikan, Faculty of Medicine, Department of Biostatistics, Near East University, Nicosia-TRNC, Cyprus

DOI: 10.32474/CTBB.2020.02.000132

Abstract PDF

Abstract

This study aims to examine the most dangerous cause of death in underdeveloped, developing and developed countries. The major diseases considered in this study were HIV/AIDs and Cancer. The causes of this death are selected since the year 2003-2016, the data is extracted from the World Health Organization (WHO). This research shows the level of significant difference between the most common cause of death in the three categories of countries. This test is carried out by the use of ONE-WAY ANOVA. In this case of study, it was concluded that there is a significant difference when comparing the results, except Underdeveloped and Developed countries that are; the case report of the cause of death by HIV/AIDS is low. Similarly, in the case study of the cause of death by CANCER, the results show that there is a significant difference in all when the countries’ categories were compared that is; there is a high rate of the cause of death by cancer in all country categories.

Keywords: Under developed; developing; developed; HIV/AIDs; cancer; death

Introduction

Causes of death are not commonly known in developing countries because autopsy is not believable on account of religious thoughts in most cases. Hence, various means are used to collect the cases and the cause of death of a deceased. Gathering of this information serves as an important tool to detect the major cause(s) of death in a country [1]. Countries that are developing are mostly the ones with a high level of poverty and diseases. Most of these countries with a weak healthcare system often have a problem with genuine information on the cause of death in the population. But such information is so important for policy development, health programs, program monitoring, and assessment and so on. The greatest major sign of detecting the death rate of any population is the health issue or variation of a total population (N). Recorded documentation as relating to cases diagnosis and cause of deaths often caries across a country’s socio-economic level. Most countries in the developed world are well equipped with effective data management record systems which make it effective to capture patients’ profile and status, unlike the poor record systems that are widely available in undeveloped and developing countries.
There are variations in the diseases among the developed, developing and underdeveloped world. In developed countries, studies state that free related causes of death by diseases such as poison and injury are clearly visible [2,3]. Also, the cause of death from self-harm or suicide is stated to be significantly higher in the developed than in developing countries from the population of people with intellectual disability which is connected to the high rates of mental health disorder found in their population study [2- 6]. However, developing countries have been reported to be greatly affected by factors from lack of qualitative health care, low literacy rate, weak infrastructural facilities, and high unemployment rate which have resulted in poor health outcome of these countries [2,7,8].
In a study conducted by [6]. 66% of a sample of 374 adults in the autism spectrum with no intellectual disability, self-reported suicide mission, and suicide plans were reported to be 35%. The survey made it known that death rates, risk factors, and causes of death in developed counties remain rare due to the standard provision of their lifetime needs. The proper clinical record of data may allow data to be studied without the extra time and cost burden attached to primary data gathering. The evaluation of death ratios varies from 200-400 in many of the countries in South America, 1000 in Africa, 500 in many countries in Asia and less than 10 in some European countries, per 100,000 live births [9]. The main objective of the present study is to use datasets to report the significant rates difference of mortality and to detect the major causes of death of people in the underdeveloped, developing and developed countries of the world. It was assumed that those in the underdeveloped and developing countries would experience higher mortality rates than those of the developed countries due to more exposure to hazard and some heavy industrial exhaust inhaled by the people and so on. Furthermore, the assumption is made that the cause of death in most underdeveloped countries is due to some primary factors and some additional factors such as gender, mental health disorders, and medical comorbidities, cause death in most underdeveloped countries. Eventually, the various cause of death in the developed countries would be more noticeable compared to other under developing countries.

Underdeveloped country

Underdeveloped countries are categorized as the countries facing lots of unemployment which is a major problem and the main occupation in these countries is agriculture (Table 1).

Developing country

Developing countries are known to be low and middle-income country, they are less economically developed countries. The term developing describes a currently observed situation and not a changing dynamic or expected direction of progress (Table 2).

Developed countries are economically developed, advanced in technology and infrastructure and also industrialized nations with high per capita income level (Table 3).

Method of Data Collection

The study made use of secondary data. The deaths record in these countries namely; Burundi, Haiti, Nepal, Mali, Bangladesh, Nigeria, Ukraine, Pakistan, Norway, Australia, the United State of America and Singapore are categorized into underdeveloped, developing and developed countries categories. There are different causes of death in the world but for these countries in these categories, two causes of death namely HIV/AIDs and Cancer were considered. These annual number of deaths was extracted only for a period of 14 years ranging from 2003 through 2016. These countries were selected in a manner that each category (underdeveloped, developing and developed) contain four countries from different continents such as Asia, Africa, Europe, and North America.

Source of data

The main source of information is vital registration. Sources of data in the undeveloped, developing and developed countries are readily available from national vital registration. Developing and underdeveloped countries also have some vital record but the level of coverage and reliability are generally low due to some factors. For this reason, few data on causes of death are available for underdeveloped and developing countries. The main international sources for this data are the World Health Organization (WHO) Statistics Annual and the United Nations (UN) Demographic Yearbook. In the WHO Statistics Yearly, all of these show the recorded death rates by group and sex. Data are available for several of the Latin American countries, where vital registration systems are well developed. In Africa however, only Mauritius now reports regularly. Among the developing countries of Asia, data are available only for Thailand and Sri Lanka, but the data for Sri Lanka appears to be incomplete. Lack of locally sited offices and the proximity to these offices, shortage of staff in the rural areas, etc. affect where the death certificate has to be completed by a medically qualified person and also affect the low vital registration in the developing and underdeveloped countries results.

Statistical analysis

A one-way ANOVA was conducted on IBM SPSS version 25 to compare the significant difference among the number of deaths that occurs from cancer and HIV/AIDs relative to the development status categories namely underdeveloped, developing and developed.

Analysis of number of deaths from HIV/AIDS relative to development status

The analysis of variance shows that the effect of the categories on the death cases from HIV/AIDS was significant, F (2,165) = 16, 909 , p − value = 0.0001 as indicated by the Table 4. A Post- Hoc analysis using the Tukey method was further used to make a pairwise comparison. The multiple comparisons show that there is a significant difference among the development status categories excluding the developed and underdeveloped countries, as shown in Table 5 (Figure 1).

Analysis of number of deaths from cancer relative to development status

On the other hand, the analysis of variance shows that the effect of the categories of countries on deaths from cancer was significant, F(2,165) =15.556, p-value =0.0001 (Table 6). The multiple comparisons from Tukey Post –Hoc test shows that there is a significant difference in all the categories, as shown in Table 7 (Figure 2).

Conclusion

In the case of the cause of death, two major diseases; HIV/ AIDS and Cancer are selected as the common cause of death that is rampant in the country’s categories (Underdeveloped, Developing and Developed). The test results are carried out with the Oneway Analysis of variance (ANOVA). The result shows that there is a significant difference in the record of deaths by HIV/AIDS. The result posits that deaths from HIV/AIDs are more prevalent in the developing and under developing nations in contrast to nations in the developed countries. However, regarding cancer, high mortality due to cancer was found to be common in developed countries than the underdeveloped and developing nations.

Limitations

Though this study does not take into consideration the respective population sizes of the countries considered in the analysis, however, the HIV/AIDs mortality burden has been reported to be higher in low and medium countries in the world [10-12]. Regarding deaths from cancer, even though the study concluded that developed countries recorded higher cases of mortality [13] in their study indicated that cancer mortality between developed and developing nations is quite similar. However, the significant differences reported in our study could have been a result of other factors such as population size effect, underreporting cases especially in many developing and under developing countries. Thus, it is recommended that subsequent studies could examine more risk factors that could influence significant differences in mortality cases.

References

1. Mondal1 R N, Rani M, Singh R B, Wilson D W (2016) Validity of Verbal Autopsy Methods for Assessment of Causes of Death in Developing Countries. World Heart Journal 8 (3): 219-222.
2. Hirvikoski T, MittendorferRutz E, Boman M, Larsson H, Lichtenstein P, et.al (2015) Premature mortality in autism spectrum disorder. The British Journal of Psychiatry 208(3): 232-238.
3. Schendel DE, Overgaard M, Christensen J, Hjort L, Jorgensen M, etal. (2016) Association of psychiatric and neurologic comorbidity with mortality among persons with autism spectrum disorder in a Danish population. JAMA Pediatrics 170(3): 1-8.
4. Mouridsen S (2013) Mortality and factors associated with death in autism spectrum disorders: A review.American Journal of Autism 1: 17-25.
5. Buck TR, Viskochil J, Farley M, Coon H, McMahon WM etal. (2014) Psychiatric comorbidity and medication use in adults withan autism spectrum disorder. Journal of Autism and Developmental Disorders 44(12): 3063-3071.
6. Cassidy S, Bradley P, Robinson J, Allison C, McHugh M, etal. (2014) Suicidal ideation and suicide plans or attempts in adults with asperger’s syndrome attending a specialist diagnostic clinic: A clinical cohort study. The Lancet Psychiatry1(2): 142-147.
7. Hwang YI, Srasuebkul P, Foley KR, Arnold S, Trollor JN (2019) Mortality and Cause of Death of Australians on the Autism Spectrum. Autism Research 9999: 1-10.
8. Crown L (2015) The health status of adults on the autism spectrum. Autism 19(7): 814-823.
9. WHOWorld health report (2005) Make every mother and child count. Geneva, USA.
10. Gańczak Maria, Szych Zbigniew(2017) HBV, HCV, and HIV infection prevalence among prison staff in the light of occupational risk factors. MedycynaPracy684(4): 507-516.
11. Hacker MA, Malta M, Enriquez M, Bastos FI (2005) Human immunodeficiency virus, AIDS, and drug consumption in South America and the Caribbean: Epidemiological evidence and initiatives to curb the epidemic. RevistaPanamericana de SaludPública18(4-5): 303-313.
12. Shao Y, Williamson C (2012) The HIV-1 epidemic: low- to middle-income countries. Cold Spring Harbor perspectives in medicine 2(3): a007187.
13. Ahmedin Jemal DVM, Freddie Bray, Melissa M Center, Jacques Ferlay, ME et al. (2011) Global Cancer Statistics. A Cancer Journal for Clinicians 61(2):69-90.