ANarrative Review of the Impacts of Income, Education, and Ethnicity on Arterial Hypertension, Diabetes Mellitus, and Chronic Kidney Disease in the World : Saudi Journal of Kidney Diseases and Transplantation

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Original Article

ANarrative Review of the Impacts of Income, Education, and Ethnicity on Arterial Hypertension, Diabetes Mellitus, and Chronic Kidney Disease in the World

Tirapani, Luciana dos Santos1; da Fernandes, Natália Maria2,

Author Information

1Department of Health, Institute for Studies and Research in Nephrology from Minas Gerais (IMEPEN Foundation), Juiz de Fora, Minas Gerais, Brazil

2Department of Medicine, Federal University of Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil

Correspondence to: Dr. Natália Maria da Silva Fernandes, Department of Medicine, Federal University of Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil. E-mail: [email protected]

Received June 30, 2018

Accepted August 06, 2018

Saudi Journal of Kidney Diseases and Transplantation 30(5):p 1084-1096, Sep–Oct 2019. | DOI: 10.4103/1319-2442.270264
  • Open

Abstract

Introduction

Nontransmissible chronic diseases (NTCDs) are the major causes of death worldwide, responsible for the death of nearly 15 million women and men aged between 30 and 70 every year.[1] This causes serious social and economic consequences in all societies and economies, especially in poor and vulnerable populations, emerging as a serious public health problem throughout the world.[2] There is strong evidence that correlates socioeconomic factors such as education, occupation, income, gender, and ethnicity to a higher prevalence and to risk factors of cardiovascular disease (CVD), chronic kidney disease (CKD), and diabetes mellitus (DM).[345]

In 2011, the Heads of State and Governments, at a meeting of the United Nations, recognized that the NTCDs constitute a major threat to economies and societies and placed them at the top of the agenda for development.[2] Developing countries, with low and middle income, are the most affected, due to the fact that NTCDs are more frequent in more vulnerable populations, with low income and education.[6]

Numerous studies, especially in high-income countries, show that people with low socioeconomic level or those who live in the poorest regions have a higher risk of dying of NTCDs, being higher in people with low education, income, or economic status; those from excluded ethnic groups; and those living in poor and deprived communities.[7]

One of the ways of coping with the social and economic impact caused by the NTCDs is the development of effective public policies, understanding that social policies have been and are determined by a range of historical facts, not stagnant, but dynamic, accompanying the constant changes in the society.[8] One of the instruments used for the elaboration of public policies is social indicators. The emergence and development of social indicators is related to the consolidation of public sector planning activities throughout the 20th century. In order to develop public planning activities and formulate social policies, social indicators are an essential tool because they enable the public and civil societies to monitor the living conditions of the population and allow one to comprehend the social changes in a given society.[9]

The most popular second-generation indicator at present is the Human Development Index (HDI), which covers the dimensions of longevity, education, and income. It is an index capable of measuring the level of development of a country by a perspective beyond gross domestie product (GDP). In 2010, the inequality-adjusted HDI (IHDI) was implemented, which quantifies the effects of inequality in development, measured in terms of HDI.[10]

The objective of this study was to analyze, through the narrative review of the literature, the impact of income, education, and ethnicity on the presentation of systemic arterial hypertension (AH), DM, and CKD in the world, also analyzing the social indicators HDI and IHDI in the countries analyzed.

Methodology

A review of the literature was performed from January 2012 to December 2017, in the PubMed database with the following keywords in the Mesh search: Educational Status and Renal Insufficiency Chronic, Educational Status and Diabetes Mellitus, Educational Status and Hypertension, Income and Renal Insufficiency Chronic, Income and Diabetes Mellitus, and Income and Hypertension; for color, the Mesh terms used were Continental Population Groups and Renal Chronic Insufficiency, Continental Population Groups and Diabetes Mellitus, and Continental Population Groups and Hypertension.

Articles in Portuguese, English, and Spanish were included. Articles in other languages, which did not have an abstract, and articles that did not encompass the search scope were excluded.

The articles were organized in a spreadsheet, in decreasing publication date order, containing the list of authors, country of study, the values and classifications of the HDI and IHDI, title, objective, sample, conclusion, key social scope, social factors included (income, color, and/or education), and pathologies studied (AH, DM, and CKD). The values for the HDI and IHDI were those described in the Human Development Report – Human Development for Everyone published by the United Nations Development Program.

Results

Altogether, 918 articles were analyzed. Of these, 161 encompassed the objectives of the present study. The studies were performed in 96 countries, covering a total sample of 11,008,970 participants. Of the 96 countries, 15 were of low (HDI <0.549): Burkina Faso, Cameroon, Chad, Comoros, Congo, Ivory Coast, Ethiopia, Malawi, Mali, Mauritania, Nigeria, the Democratic Republic of the Congo, Senegal, Swaziland, and Zimbabwe; 20 of medium (HDI 0.550–0.699): South Africa, Bangladesh, Cambodia, the Philippines, Ghana, Guatemala, India, Indonesia, Morocco, Myanmar, Namibia, Nepal, Nicaragua, Pakistan, Paraguay, Kenya, Lao People's Democratic Republic, Singapore, Vietnam, and Zambia; 27 of high (HDI 0.700–0.799): Albania, Armenia, Azerbaijan, Barbados, Bosnia and Herzegovina, Brazil, Kazakhstan, China, Colombia, Costa Rica, Cuba, Ecuador, Georgia, Iran, Jamaica, Malaysia, Mauritius, Mexico, Peru, Dominican Republic, Sri Lanka, Thailand, Taiwan, Tunisia, Turkey, Ukraine, and Uruguay; and 34 of are very high (HDI >0.800): Germany, Saudi Arabia, Argentina, Australia, Austria, Belgium, Canada, Chile, Korea, Croatia, Denmark, Slovakia, Spain, the United States of America, Estonia, Finland, France, Greece, the Netherlands, Hungary, Ireland, Italy, Japan, Latvia, Lithuania, Norway, New Zealand, Poland, Portugal, the United Kingdom, the Czech Republic, Russia, Sweden, and Switzerland. The distribution of the countries and the HDI ranking are depicted in Figure 1.

F1-11
Figure 1:
Distribution of the studies analyzed by country and human development index rank.

After adjusting for inequality, the change in HDI values in all countries was analyzed that contained data from IHDI. Of the 96 countries, 52 fell from the HDI rating level after adjustment; of these, four fell two levels of classification (Argentina, Chile, Colombia, and Iran); despite changes in values, 35 countries managed to maintain the same classification, and nine countries did not present any data regarding their inequalities, as shown in Figure 2.

F2-11
Figure 2:
Distribution of the studies analyzed by country and classification of human development index adjusted for inequality.

The selected studies sometimes addressed more than one social factor and more than one pathology. Studies of race/ethnicity did not occur alone because most of the studies that deal exclusively with this theme deal with race in the genetic aspect, out of the scope of the present study. The quantitative analysis of studies by pathology and socioeconomic factors is presented in Figure 3.

F3-11
Figure 3:
Studies by social factors and pathology.

The countries organized by pathology and topics covered are shown in Figures 456.

F4-11
Figure 4:
Map of social factors discussed related to arterial hypertension.
F5-11
Figure 5:
Map of social factors discussed related to diabetes mellitus.
F6-11
Figure 6:
Map of social factors discussed related to chronic kidney disease.

Discussion

The four major chronic diseases of greater global impact are CVDs, DM, cancer, and chronic respiratory diseases. These affect 15 million individuals every year. Premature deaths by NTCD scan be avoided or delayed by implementing a number of actions.[11] The World Health Organization reports that the population with lower income is more exposed to risk factors for NTCDs and has less access to health services, and illness creates a vicious circle that further increases the poverty situation.[67] As with income, another important factor to be evaluated is the educational level, which can also be considered a risk factor for chronic diseases.

Ethnicity is another factor to be considered, not dealing here of race or genetic and biological issues, but the social implications associated with ethnicity. Ethnic differences are associated with the risk of exposure to gradients of inequality.

The social cost with the management of these pathologies is significant, the treatments of a chronic disease impose some aggregate costs and, because they have a long course, impact the financial life of individuals and their families, leading to the weakening of the economy of a country, generating a chain of circumstances that produces and perpetuates inequities and increases poverty.[6] It should be emphasized that inequalities in NTCDs can be both a cause and a consequence of socioeconomic inequalities.[7]

Inequality-adjusted Human Development Index, the inequality-adjusted Human Development Index

The IHDI in the countries analyzed demonstrated that when the HDIs are adjusted for inequality, almost all countries showed a fall in the indicators, underlining that in fact, the degree of development is not synonymous with the degree of social protection such that there is an imbalance between economic growth and improvement of social conditions of the population. The emergence of social policies and models of patterns of social protection occurs gradually and dissimilarly between countries, due to the influence of three important factors for the analysis of social policies, which are the nature of capitalism, its degree of development and accumulation strategies, and the role of the state in the regulation and implementation of social policies and the role of social classes.[8]

In fact, the HDI represented a step forward in terms of social indicators, from the observation that economic growth alone does not alter the conditions of life of a given population, expanding quite restricted indicators of economic factors, such as the GDP and GDP per capita. Nevertheless, we need to have a clear view of the limitations of the HDI index, especially in the context of public policies, in view of the overestimation of this index and not forgetting that an indicator is nothing more than the operational measure of the concept. An assessment of the changes of life exclusively through an alteration of indicators sometimes conceals changes through the deployment of social policies in dimensions not covered by the index.[9]

Besides the above factors, the HDI has a broader perspective coupled with the developmental policy. We cannot ignore the importance of international relations of power in the production of unequal access to wealth among the poor countries, with consequences on international inequalities. Another important factor to be considered regarding the index is the fact that it establishes minimum standards of quality of life for all countries, without considering the particularities of each territory and culture.[9]

What moves the current model of global economic policy is the pursuit of profits, extracting the maximum added value, configuring a rigid state regarding social and economic issues, or flexible, with a certain degree of openness.[8] This threshold of action cannot be perceived through the HDI or IHDI, and intentionally such indexes are not adjusted for such perception.

Countries with low and medium human development

The studies related to social factors addressed in the present study indicate that income and education are associated with SAH and DM in countries of low and medium human development. Nevertheless, there are differences between the countries. In Bangladesh, some studies demonstrate associations between higher level of education and income with AH and DM, in contrast to the majority of existing publications on health inequalities throughout the world.[1213] In the most frequent findings, education has a protective effect. In some countries such as South Africa, India, and Pakistan, a high prevalence of high cardiovascular risk was observed, but those with more education had lower prevalence (23%).[14] A study conducted in India shows that the increase in the level of education presents a tendency for a reduction of systolic blood pressure (BP), plasma glucose, and body mass index (BMI).[15] However, although the rates of mortality related to CVD appear to be higher among groups with low socioeconomic level, the proportion of deaths was greater among groups with higher socioeconomic level.[16]

Several studies highlight the impact of high cardiovascular risk in low- and middle-income countries. The social epidemiology of hypertension in these countries seems to be correlated with the increase in the prevalence of obesity.[17] Besides obesity, in Bangladesh, the risk of hypertension was significantly associated with more advanced age, sex, education, place of residence, occupation, wealth index, and DM.[18]

Unfavorable socioeconomic and cultural settings are determinants of the conditions of clinical risk and mortality.[19] The condition related to a health plan and income was also associated with the diagnosis and the probability of treatment.[17] It was observed that the territory is an important factor related to hypertension and CVDs.[15] Several studies discuss the lack of treatment and difficulty of access for populations living in rural areas or poor and vulnerable regions. [1218192021]

Socioeconomic level, unemployment, place of residence, overweight and obesity and hypertension, all have a significant association with type 2 DM.[1222] One of the studies analyzed showed a positive association between high BMI and DM at each level of education, being more prominent among women in countries such as South Africa, Bangladesh, Burkina Faso, Chad, Comoros, Congo, Ivory Coast, Ethiopia, the Philippines, Ghana, Guatemala, India, Malawi, Mali, Morocco, Mauritania, Myanmar, Namibia, Nepal, Pakistan, Paraguay, Kenya, Lao People's Democratic Republic, Senegal, Swaziland, Vietnam, Zambia, and Zimbabwe.[23]

DM imposes a large economic burden to the population and the health-care system, as people with DM have 97-fold more likelihood of having outpatient consultations in any specialty, 11-fold more likelihood of hospitallization, and 83-fold more likelihood of using at least one medication, compared with those without DM, according to the results of a survey conducted in Cameroon.[20] A study in Singapore warns that the considerable increase in the economic burden of DM affects not only individuals and health-care providers, but the entire society.[24]

The health system needs to develop coping strategies, including early diagnosis and awareness through means of communication, and health.[18] In Pakistan, most of the population studied presented adequate knowledge and perception in relation to DM. However, there was a lack of knowledge and perception of the disease among illiterate, poor, and rural inhabitants.[21]

As with studies related to AH in the case of DM, there is an impact of the lack of treatment and difficulty of access of the resident populations in rural areas or poor and vulnerable regions. Studies show that among patients with diabetes, one in 10 patients (9.6%) gets no treatment. This lack of treatment will not only increase the severity of the disease and progression but may also increase the burden of others.[25] A study in Nigeria concluded that the number of complications due to DM, the number of comorbidities, the age of the patient, and education impact on the quality of life of diabetic patients.[26]

The support of primary health care differs between the countries; however, specific programs for the management of these pathologies are essential. The deployment of services and actions to support health for diabetics can play a crucial role in improving the unfavorable epidemic of DM in developing countries.[25] In low- and middle-income countries, it is possible to maintain a DM program with minimal resources, offering self-care assistance and support, as occurred in Cambodia, the Philippines, and the Democratic Republic of Congo after studies of health-care programs. This also illustrates that the health outcomes of people with DM as well as hypertension are also determined by their bio-psychosocial characteristics and behaviors.[27]

Countries of high and very high human development

The countries of high and very high human development display very similar results to the countries of low and medium human development. Education and income are widely discussed factors in the three pathologies and are strongly associated from prevention to mortality in individuals with hypertension, DM, and CKD. Low education and income influence the prevalence, incidence, diagnosis, treatment, progression, perception, and mortality.[28293031323334353637]

Even in countries with free access to health care, educational disparities also have an impact on access to care and in the fulfillment of goals. A study involving eight countries, France, Italy, Spain, the United Kingdom, the Netherlands, Germany, Sweden, and Denmark, with 340,234 participants revealed that participants with low educational level showed a higher risk of DM.[38] Similarly, individuals with higher education have a 23% lower prevalence of high cardiovascular risk, according to data from 40,965 individuals from China, India, Pakistan, Argentina, Chile, Peru, and Uruguay.[14] In Brazil, education appears to be associated with self-reported hypertension.[39] Education is also associated with CKD-related outcomes; the higher the educational level, the lower the risk of cardiovascular outcomes in patients with CKD and the lower the progression of the disease. [3440]

The association between education and the negative outcomes in DM has been demonstrated in several studies.[41424344454647484950] A group of researchers from the United States reported that the effect of genetic risk in HbA1c is lower among people with higher education and higher among those with less education, suggesting that education can be an important source of socioeconomic heterogeneity in the responses to the vulnerabilities to DM.[51]

A study conducted in Sweden, using data from the Sweden National Diabetes Register with 217,364 participants, showed that a low socioeconomic level was associated with a 2-fold higher risk in all causes of cardiovascular mortality and DM.[36] Moreover, just as poverty appears as a predictor of outcomes in NTCDs, the inverse is also true; these same pathologies may lead the individual to a situation of poverty, inherent to the costs associated with it. An Australian study found that men with DM present a risk for the multidimensional poverty of 2.52.[52] In individuals with CKD, poverty appears to be associated with lower predialysis care and increased mortality.[5354]

Another factor almost exclusive in this group of countries is the concern with the impact of diseases at the level of productivity, work absences, early exits from the labor market, and retirements due to disability.[5556] This concern is inherent in the economic system, as under capitalism, the centrality for the production of wealth is at work.

In Canada, a study on 505,606 workers revealed that DM is associated with several results of occupational health, including work-related injuries and loss of productivity.[57] The same is observed in the Netherlands, in which CVD and DM increase the likelihood of greater benefits for invalidity benefits, early retirement, and unemployment.[56] Dialysis also negatively affects the occupational situation of individuals with CKD.[58] Studies in Sweden, France, and Finland also highlight the increase of early retirements related to DM.[5960] Early retirement affects not only the immediate income of the individual, but reduces the financial capacity over the years, reducing accumulated savings, as demonstrated by an Australian study.[55] Data from the United Kingdom, Austria, Belgium, Czech Republic, Denmark, France, Germany, Greece, Ireland, Italy, the Netherlands, Poland, Spain, Sweden, and Switzerland reveal that individuals diagnosed with DM had a 30% increase in the rate of work cessation, in comparison with those without the disease.[61]

The issue related to the impact of race/ethnicity on the pathologies analyzed is a subject that appears only in this group. In Brazil, women of black and brown ethnicities had a higher prevalence of hypertension, according to a study from the National Health Survey in 2013.[62] A study was carried out in Sweden to identify the effect of ethnicity on glycemic control in a large cohort of patients with DM, with 713,495 participants, and concluded that the impact of ethnicity was greater than the effect of income and education.[63]

Black ethnicity displays a strong association, with preponderance for AH. It is also associated with lower adherence, greater difficulty in accessing health services, with more vulnerable territories, and greater self-reported discrimination events.[646566] In Brazil, a strong association occurs with resistant AH.[67] An important result was evidenced in a study conducted in the United States to evaluate the roles of education and genetic ancestry in the occurrence of hypertension in African-Americans and the association between education and higher BP in racial groups. The researchers observed that education, but not genetic ancestry, was associated with BP among African-Americans. Education was significantly associated with high BP among African-Americans, but not in Whites; one hypothesis is that this is due to stressors related to BP, such as poverty and racial discrimination.[68] Ethnicity is also associated with mortality in CKD; Black individuals present higher mortality compared to Whites.[54]

Territory and demographic disparities are also emerging as risk factors. More vulnerable or rural communities predispose their inhabitants to a higher risk.[53697071] Features associated with the place of birth of the individual, where he/she lives the first stage of life, is associated with the prevalence of future chronic diseases, with a strength of association equivalent to genetic associations, according to a study conducted in the United States.[71] The difficulty of access to health is also present, in countries of low and medium HDI; studies have demonstrated that, among patients with DM, one in every 10 patients did not have any treatment.

Gender associations are also extremely high in recent studies, associated with a worse evolution and mortality in AH.[4162727374] Women are more susceptible to unfavorable outcomes from DM when compared with men.[7576] In contrast, some studies conducted in countries of low and medium HDI indicate that sometimes being female appears as a protective factor.

The great majority of studies suggest the inclusion of socioeconomic factors, so neglected thus far, in the focus of health policies. The models of the health system need to be designed taking into account the new social risk factors, and not only clinical ones. Health professionals need to be enabled to have a sensitive look to these differences. The changes need to occur rapidly, given the degree of involvement planned for the coming years. Not to mention the economic burden, the costs of health care for the treatment are catastrophic, infinitely greater than the cost of prevention.

Conclusion

Health inequalities differ in relation to the stage of and economic and epidemiological development of each country. Nevertheless, even with these economic differences, there is a difference that unites us, the existence of social vulnerability, at whatever level and putting aside regional singularities. The populations deprived of an effective social protection policy are exposed to risks related to NTCDs and present worse evolution and outcomes. The theme related to social factors needs to be a constant in the elaboration of health policies present in professional activity.

This study is part of the doctoral thesis (in progress) of Luciana dos Santos Tirapani, carried out in the Postgraduate Program in Health at the Federal University of Juiz de Fora.

Conflict of interest

None declared.

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