• Users Online: 147
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 41  |  Issue : 1  |  Page : 26-31

Global inequality in the incidence and mortality rate of melanoma skin cancer according to human development index: a country-level analysis


1 Gastroenterology and Hepatology Diseases Research Center, Qom University of Medical Sciences, Qom, Iran
2 Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamedan, Iran
3 Psychosocial Injuries Research Cente, Iran
4 Department of Clinical Epidemiology, Ilam University of Medical Sciences, Ilam, Iran
5 Autism Spectrum Disorders Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

Date of Submission17-Feb-2020
Date of Acceptance16-May-2020
Date of Web Publication23-Dec-2020

Correspondence Address:
Yousef Veisani
Psychosocial Injuries Research Center, Ilam University of Medical Sciences, Ilam
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejdv.ejdv_10_20

Rights and Permissions
  Abstract 


Objective The present study aimed to quantify existing inequalities in melanoma skin cancer (MSC) incidence and mortality between countries with different level of human development index (HDI).
Methods A descriptive study was conducted based on GLOBOCAN project of the WHO for most countries in the world. Inequality in the age-specific incidence and mortality rates of MC was calculated according to the HDI by using the concentration index (CI) and decomposition of the CI was conducted.
Results The CI for incidence and mortality rates of MSC was 0.44 (95% CI: 0.38, 0.54) and 0.11 (95% CI: 0.04, 0.21), respectively, which showed that MSC was more concentrated in countries with higher HDI. Expected years of schooling (0.44), mean year of schooling (0.38), and gross national income per 1000 capita (0.17) were the most important contributors of inequality in MSC incidence.
Conclusion Disparity in melanoma rates was observed across diverse HDI components in different countries. The risk of MCS increased with higher life expectancy at birth, higher mean year of schooling, more expected years of schooling, and higher gross national income per 1000 capita according to the decomposing analysis.

Keywords: decomposition, human development index, incidence, melanoma skin cancer, mortality


How to cite this article:
Mohammadbeigi A, Khazaei S, Veisani Y, Delpisheh A, Jenabi E. Global inequality in the incidence and mortality rate of melanoma skin cancer according to human development index: a country-level analysis. Egypt J Dermatol Venerol 2021;41:26-31

How to cite this URL:
Mohammadbeigi A, Khazaei S, Veisani Y, Delpisheh A, Jenabi E. Global inequality in the incidence and mortality rate of melanoma skin cancer according to human development index: a country-level analysis. Egypt J Dermatol Venerol [serial online] 2021 [cited 2022 Oct 1];41:26-31. Available from: http://www.ejdv.eg.net/text.asp?2021/41/1/26/304320


  Introduction Top


Skin cancer is the most common type of cancer around the world. This cancer is divided into melanoma and nonmelanoma skin cancer (non-MSC) [1]. Melanoma skin cancer (MSC) represents only ∼3% of all skin cancers, but it causes a large majority of skin cancer deaths [2].

Studies in different parts of the world have shown a steady increase in the incidence of MSC over the past 50 years [3],[4]. Skin phenotype, a family history of melanoma, actinic damage, a history of sunburns, and exposure to ultraviolet radiation are known as important risk factors in the development of MSC [5],[6].

Cancer incidence and mortality are not equally distributed across countries, as more than half of all new cancer cases and two-thirds of all cancer deaths occur in less-developed countries [7]. Although some factors like demographic structure, population size, and stages of epidemiologic transition can party justify this inequality, many of these disparities are unexplained [7]. It seems that further studies are needed to find out the unknown aspects of the causes of these disparities.

One of the 17 sustainable development goals is reducing inequalities across societies, and understanding and reducing this inequality in incidence and mortality of cancers is a strategic priority in global policy making [7]. It is widely accepted that countries’ per capita income, literacy, life expectancy, and other indicators conceal widespread human deprivation and inequality [8]. As has been reported the link between social and economic status and cancer incidence and mortality [9], and also as the human development index (HDI) as an indicator reflects the socioeconomic development [10], therefore the probable role of HDI in changing the incidence and mortality rate of MSC should be investigate, owing to the lack of knowledge in this case worldwide. This study aimed to assess inequalities in incidence and mortality of MSC across the world by linking the HDI.


  Methods Top


This descriptive study was performed on the relation of the age-specific incidence and mortality rate (ASR) of MSC and HDI.

HDI data

HDI has several main components including life expectancy at birth, mean years of schooling, and gross national income (GNI) per capita, and also some ancillary indexes such as percent of urbanization and age-standardized obesity (defined as BMI ≥30) in adults (The weighted average of the age-specific obesity rate among adults ages 20 and older). Estimates of HDI and its components (life expectancy, education, and gross domestic product per capita), BMI, and urbanization level for 169 countries were obtained from the United Nations Development Programme database [11]. These countries were categorized into four categories, including first, very high human development (27 countries), second, high human development (37 countries), third, medium human development (89 countries), and fourth, low human development (16 countries).

XXXXMC incidence and mortality data

ASR is a summary measure of the rate when we have a standard age structure and a population distribution, as age has a powerful influence on the risk of cancer. Therefore, age standardization is necessary for comparing several populations with different age distribution. Data about the incidence and mortality rate of MSC for the year 2012 were obtained from the global cancer project for 172 countries [12].

Statistical analysis

Data analysis was restricted to 169 countries for which the epidemiologic data from the GLOBOCAN database and the HDI were available. We defined inequality in the age-specific incidence and mortality rates (ASR) of MSC according to the HDI by using concentration index (CI). The value of CI ranged from −1 to +1. A CI greater than zero indicates that the cancer cases or deaths are disproportionally concentrated in higher HDI countries (the concentration curve lies below the diagonal), whereas a value below zero points toward a higher burden in countries with lower levels of HDI (the concentration curve lies above the diagonal). We decomposed the CI to determine the main contributors to inequality in MSC. In the decomposition process, in the first step, we calculated elasticity for each variable that shows amount of changes in the dependent variable associated with the change in one explanatory variable. By the multiplying the elasticity of each determinant by its CI, we estimated the absolute contribution of each determinant to inequality.

In this study, each of MSCRs was considered as a quantitative outcome in linear regression model. The y=XB+e formula was applied to obtain contributors in MSCRs inequality, where y is the MCRs and also B and e denote constant and error term, respectively. The likelihood ratio and Akaike information criteria measures were used for goodness of fit of model. All P values less than 0.05 were regarded as statistically significant. Distributive Analysis Stata Package was used for estimating CI. Data were analyzed by Stata computer software version 12 (StataCorp, College Station, Texas, USA).


  Results Top


The number of new cases of MSC in 2012 was 232 130 (∼120 649 in males and 111 481 in females) worldwide. Of these, 55 488 cases died in the same year. The incidence rate of MSC was 3.0 per 100 000 in both sexes, whereas the mortality rate was 0.7 per 100 000, based on GLOBOCAN and the United Nations Development Programme data. As shown in [Table 1], the incidence of MSC was more in more developed regions (9.6 per 100 000) compared with less-developed regions (0.8 per 100 000). The incidence rates of MSC were from 0.7 per 100 000 in low human development countries to 9.8 per 100 000 in very high HDI, and the mortality rates ranged from 0.5 per 100 000 in low human development countries to 2.7 per 100 000 in very high HDI ([Table 1]).
Table 1 Incidence and mortality rates of melanoma skin cancer according to socioeconomic component (the most recent national estimates of melanoma skin cancer incidence, mortality, and prevalence worldwide, for 2012)

Click here to view


The CI for incidence and mortality rates of MSC in both sexes according to HDI was 0.44 (CI 95%: 0.38, 0.54) and 0.11 (CI 95%: 0.04, 0.21), respectively. These results showed that incidence rates of MSC were more concentrated in countries with high HDI and developed countries ([Figure 1]).
Figure 1 Incidence and mortality of melanoma skin cancer ranked by human development index (the most recent national estimates of melanoma skin cancer incidence, mortality, and prevalence worldwide, for 2012, and Human Development Report 2015).

Click here to view


The CIs for incidence and mortality rates of MSC in both sexes are shown in [Table 2]. In all of socioeconomic components, CI values for incidence are higher than CI values for mortality rates in favor of advantages countries. Therefore, this indicated that MSC in both incidence and mortality rates was more concentrated in countries with high HDI index.
Table 2 Concentration indexes for inequality of incidence and mortality rates of melanoma skin cancer according to human development index and components (the most recent national estimates of melanoma skin cancer incidence, mortality and prevalence worldwide, for 2012, and Human Development Report 2015)

Click here to view


In this study, CI was decomposed to determine the important contributors to incidence and mortality of MSC. As shown in [Table 3] and [Figure 2], the important contributors in inequality for incidence rates of MSC were expected years of schooling (0.44), mean year of schooling (0.38), and GNI per 1000 capita (0.17). The important contributors in inequality of mortality rates were expected years of schooling (0.31), mean year of schooling (0.29), and GNI per 1000 capita (0.07).
Table 3 Contributors to inequalities in the incidence and mortality rates inequalities of melanoma skin cancer (the most recent national estimates of melanoma skin cancer incidence, mortality and prevalence worldwide, for 2012, and Human Development Report 2015)

Click here to view
Figure 2 Contributors to incidence and mortality rates inequalities of melanoma skin cancer (the most recent national estimates of melanoma skin cancer incidence, mortality and prevalence worldwide, for 2012, and Human Development Report 2015).

Click here to view



  Discussion Top


Investigations of socioeconomic variations in cancer rates are of interest to policy makers for designing and performing health care planning, which ultimately leads to reduction in inequalities in health. The main goals of the current study were to determine inequality in MSC rates according to HDI and components by CI. We have decomposed the inequality index by decomposition approach to detect the main contributors in inequality.

Our findings showed that MSC incidence in developed regions is much higher than less-developed regions (9.6 per 100 000 compared with 0.8 per 100 000 populations), and also mortality is more prevalent in developed countries (1.5 per 100 000 compared with 0.4 per 100 000 populations). According to our findings, the risk of melanoma cancer is 11 and 13 times higher in more developed and countries with high HDI compared with those with a low HDI, respectively. However, the magnitude of this risk was lower in mortality, whereas the risk of dying owing to melanoma was 2.75 and 1.8 times higher in more developed and countries with high a HDI compared with countries with low a HDI, respectively. This observed greater lethality in less-developed countries with low HDI is very likely that the disease is more advanced and/or more aggressive at the time of diagnosis in these countries. It seems the high incidence rates of some cancers in more developed countries reflect the diagnosis methods, through screening and imaging techniques; consequently, early detection reduces the mortality rate in these countries [13]. Therefore, lower survival of cancer in less-developed countries is more related to lack of access to proper quality care, and not biological differences between tumors [14].

Inequality index based on HDI showed a positive inequality in incidence and mortality rates of MSC. Therefore, both incidence and mortality rates of MSC are more concentrated in countries with high HDI and all components [life expectancy at birth, mean year of schooling, expected years of schooling, GNI per 1000 capita, age-standardized obesity in adults, and urbanization level (%)].

According to results of this study, the distribution of MCS varies in different parts of the world, ranging from low in less-developed regions to high in more developed regions. The key response to this international variation can be attributed to exposure to lifestyle or the environment risk factors [15]. Some risk factors in MCS can be changeable, like smoking and excess sun exposure, and some cannot, like family history or age [16]. Previous studies have been shown that these factors increase the risk of MCS in developed countries and are responsible for higher incidence of MCS in these countries [17],[18].

Our analysis according to decomposing approach showed that MCS incidence and mortality rates were associated with socioeconomic components. The risk of MCS increased with higher life expectancy at birth, higher mean year of schooling, more expected years of schooling, and higher GNI per 1000 capita according to decomposing analysis. The findings were similar for both incidence and mortality rates, and sexes. Our findings are consistent with the results from previous studies that shown MCS was more incident in countries with lower unemployment, higher education, higher income, and urbanization [17],[18],[19],[20],[21]. Others based on SEER data showed lower socioeconomic status was associated with later stage at diagnosis of melanoma [22],[23]. Moreover, a poorer outcome was shown in persons with low socioeconomic status quintiles [24].

However, owing to lack of access to data, we could not assess differences in the distribution of accuracy of cancer registration system (dependent on the quality and availability of the source information), delay in diagnosis, age/age at onset, population density, ethnic variety, etc. on MSC incidence and mortality. For example, when latitude reduced nearly 10°, the incidence of cancer becomes double [25]. According to El Khwsky et al. [26], the incidence of skin cancer in people who have had excessive exposure to sunlight than other people was 4.8 times. Therefore, without adjusting to these variables, the results should be interpreted with caution.

Some limitations should be addressed regarding the current study: first, ecological studies are potentially susceptible to a phenomenon known as ‘ecological fallacy’, biases that may occur when an observed association between aggregated variables differs from the true, and the HDI does not take into account inequalities within countries. Second, difference in reporting quality of cancer diagnosis could lead to under-reporting in cancer registration, especially in less-developed countries. It is recommended that in future studies, other aspects related to MCS should be surveyed.


  Conclusion Top


Our findings showed that the MSC is more concentrated in developed regions; inequality indexes based on HDI and its components were positive for both incidence and mortality rates of MSC. Effects of HDI and its components on these disparities need studies, with a higher level of evidence. Cancer control specialists and health policy makers should be aware of the markedly different cancer profiles observed at each HDI level.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Diepgen T, Mahler V. The epidemiology of skin cancer. Br J Dermatol 2002; 146(s61):1–6.  Back to cited text no. 1
    
2.
Petermann KB, Rozenberg GI, Zedek D, Groben P, McKinnon K, Buehler C et al. CD200 is induced by ERK and is a potential therapeutic target in melanoma. J Clin Invest 2007; 117:3922.  Back to cited text no. 2
    
3.
Tryggvadóttir L, Gislum M, Hakulinen T, Klint Å, Engholm G, Storm HH et al. Trends in the survival of patients diagnosed with malignant melanoma of the skin in the Nordic countries 1964–2003 followed up to the end of 2006. Acta Oncol (Madr) 2010; 49:665–672.  Back to cited text no. 3
    
4.
de Vries E, Bray FI, Coebergh JWW, Parkin DM. Changing epidemiology of malignant cutaneous melanoma in Europe 1953–1997: rising trends in incidence and mortality but recent stabilizations in western Europe and decreases in Scandinavia. Int J Cancer 2003; 107:119–126.  Back to cited text no. 4
    
5.
Gandini S, Sera F, Cattaruzza MS, Pasquini P, Abeni D, Boyle P et al. Meta-analysis of risk factors for cutaneous melanoma: I. Common and atypical naevi. Eur J Cancer 2005; 41:28–44.  Back to cited text no. 5
    
6.
Gandini S, Autier P, Boniol M. Reviews on sun exposure and artificial light and melanoma. Prog Biophys Mol Biol 2011; 107:362–366.  Back to cited text no. 6
    
7.
Jones LA, Chilton JA, Hajek RA, Iammarino NK, Laufman L. Between and within: international perspectives on cancer and health disparities. J Clin Oncol 2006; 24:2204–2208.  Back to cited text no. 7
    
8.
Kovacevic M. Measurement of inequality in human development − a review. Measurement 2010; 35:1–65.  Back to cited text no. 8
    
9.
Krieger N, Chen JT, Waterman PD, Soobader M-J, Subramanian SV, Carson R. Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter? The Public Health Disparities Geocoding Project. Am J Epidemiol 2002; 156:471–482.  Back to cited text no. 9
    
10.
Bray F, Jemal A, Grey N, Ferlay J, Forman D. Global cancer transitions according to the Human Development Index (2008–2030): a population-based study. Lancet Oncol 2012; 13:790–801.  Back to cited text no. 10
    
11.
Human Development Report, Work for Human Development. United Nations Development Programme. 2015. Available at: http://hdr.undp.org/sites/default/files/2015_human_development_report_0.pdf. [Access date: 20/6/2020].  Back to cited text no. 11
    
12.
Zhang Q, Zeng L, Chen Y, Lian G, Qian C, Chen S et al. Pancreatic cancer epidemiology, detection, and management. Gastroenterol Res Pract 2016; 2016:8962321.  Back to cited text no. 12
    
13.
Jemal A, Center MM, DeSantis C, Ward EM. Global patterns of cancer incidence and mortality rates and trends. Cancer Epidemiol Prev Biomarkers 2010; 19:1893–1907.  Back to cited text no. 13
    
14.
Bradley CJ, Given CW, Roberts C. Disparities in cancer diagnosis and survival. Cancer 2001; 91:178–188.  Back to cited text no. 14
    
15.
Wheeler BW, Kothencz G, Pollard AS. Geography of non-melanoma skin cancer and ecological associations with environmental risk factors in England. Br J Cancer 2013; 109:235–241.  Back to cited text no. 15
    
16.
Apalla Z, Nashan D, Weller RB, Castellsagué X. Skin cancer: epidemiology, disease burden, pathophysiology, diagnosis, and therapeutic approaches. Dermatol Ther 2017; 7(Suppl 1):5–19.  Back to cited text no. 16
    
17.
Doherty VR, Brewster DH, Jensen S, Gorman D. Trends in skin cancer incidence by socioeconomic position in Scotland, 1978–2004. Br J Cancer 2010; 102:1661–1664.  Back to cited text no. 17
    
18.
Idorn LW, Wulf HC. Socioeconomic status and cutaneous malignant melanoma in Northern Europe. Br J Dermatol 2014; 170:787–793.  Back to cited text no. 18
    
19.
Ramezani Doroh V, Vahedi S, Arefnezhad M, Kavosi Z, Mohammadbeigi A. Decomposition of health inequality determinants in Shiraz, South-west Iran. J Res Health Sci 2015; 15:152–158.  Back to cited text no. 19
    
20.
Mohammadbeigi A, Hassanzadeh J, Eshrati B, Rezaianzadeh A. Socioeconomic inequity in health care utilization, Iran. J Epidemiol Global Health 2013; 3:139–146.  Back to cited text no. 20
    
21.
Hassanzadeh J, Mohammadbeigi A, Eshrati B, Rezaianzadeh A, Rajaeefard A. Determinants of inequity in health care services utilization in Markazi Province of Iran. Iran Red Crescent Med J 2013; 15:363–370.  Back to cited text no. 21
    
22.
Clegg LX, Reichman ME, Miller BA, Hankey BF, Singh GK, Lin YD et al. Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control 2009; 20:417–435.  Back to cited text no. 22
    
23.
Ortiz CA, Goodwin JS, Freeman JL. The effect of socioeconomic factors on incidence, stage at diagnosis and survival of cutaneous melanoma. Med Sci Monit 2005; 11:163–172.  Back to cited text no. 23
    
24.
Linos E, Swetter SM, Cockburn MG, Colditz GA, Clarke CA. Increasing burden of melanoma in the United States. J Investig Dermatol 2009; 129:1666–1674.  Back to cited text no. 24
    
25.
Wakeford R. The cancer epidemiology of radiation. Oncogene 2004; 23:6404.  Back to cited text no. 25
    
26.
El Khwsky F, Bedwani R, D’Avanzo B, Assaad S, Ali AES, Mokhtar S et al. Risk factors for non‐melanomatous skin cancer in Alexandria, Egypt. Int J Cancer 1994; 56:375–378.  Back to cited text no. 26
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]


This article has been cited by
1 Subsidy as An Economic Instrument for Environmental Protection: A Case of Global Fertilizer Use
Mathy Sane,Miroslav Hajek,Chukwudi Nwaogu,Ratna Chrismiari Purwestri
Sustainability. 2021; 13(16): 9408
[Pubmed] | [DOI]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed1081    
    Printed48    
    Emailed0    
    PDF Downloaded180    
    Comments [Add]    
    Cited by others 1    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]