2.1: Study Design
In order to respond to the research question (study hypothesis), the study employed an analytic ecological study design. Based on the study’s purpose, data was collected in order to determine possible associations between diabetes prevalence (dependent variable) and health expenditure for diabetes plus other health indicators (independent variables) across the globe.
2.1.1: Ecological study
Ecological studies are studies which deal with aggregated or grouped data measured on groups of people rather than on individuals19. They describe and analyze correlations between variates measured on populations in groups or regions. Thus, ecological analyses employ aggregated data as the basic sampling unit of analysis. In such studies, the grouping variate could be geographical region, ethnicity, socioeconomic class, time period, etc19. Types of ecological study designs include explorative vs analytic study (where the primary group is measured); and multi-group study, time-trend study, or mixed study (where subjects are grouped by place, by time, or by place and time, respectively)20. Although ecological studies have several practical advantages, they also have many methodological problems that severely limit causal inference. These include cross-level bias, problems of confounder control, within-group misclassification, lack of adequate data, temporal ambiguity, collinearity, and migration across groups20. Due to the above limitations of ecological studies which could result in the “ecological fallacy”1, ecological studies are sometimes regarded as inadequate and unreliable. But, such studies are highly relevant because even when studying individual risk factors, population level studies play a vital role in defining the most important public health problems to be tackled, and in generating hypothesis as to their potential causes21. Furthermore, it is increasingly being recognized that some risk factors for disease
1 An error in the interpretation of statistical data in an ecological study that results when concludions are made about individuals from the aggregated data inappropriately.
Page | 6 genuinely operate at the population level22-24. Ecological studies are particularly advantageous because they permit the study of very large populations, and are often relatively easy to conduct using existing databases in a fairly short period of time19. They are also useful in describing differences between groups and identifying questions for further investigations25. The ecological approach has proven to be quite useful in public health/epidemiologic research for centuries26. For example Chadwick employed this approach in his famous report on the sanitary condition of the laboring population of Great Britain in 184227.
2.2: Study Population
The study population comprised of 183 Member States of WHO which are grouped into 4 country income groups based on their Gross National Income (GNI) per capita, namely: low-, lower middle-, upper middle-, and high-income groups28 (Appendix A). But the upper middle- and lower middle-income groups both comprise the middle-income countries29. My reason for employing the above grouping of income in this study, was based on another study conducted in the WHO African region which grouped African countries into income groups based on their GNI per capita, in order to estimate the economic burden associated with diabetes mellitus in the countries in the African region30.
2.3: Independent variables
The main independent variable was health expenditure for diabetes. The other independent variables include: life expectancy at birth, prevalence of tuberculosis, population living in urban areas, out-of-pocket health expenditure, adults aged ≥ 20 years who are obese, and alcohol consumption among adults aged ≥ 15 years. All of these independent variables were included based on their relevance to global public health; possible association with diabetes;
availability and quality of the data; and reliability and comparability of the resulting estimates.
Page | 7 2.4: Dependent variable
The dependent variable was the prevalence of diabetes mellitus.
2.4.1: Diagnostic criteria for diabetes mellitus
According to WHO and IDF, the following criteria are recommended for the diagnosis of diabetes mellitus: fasting plasma glucose ≥ 7.0mmol/l (126mg/dl) or 2-h plasma glucose (venous plasma glucose 2 hours after ingestion of 75g oral glucose load) ≥ 11.1mmol/l (200mg/dl). They further recommend that the oral glucose tolerance test is the most preferred diagnostic test for diabetes mellitus31. The test should be performed in the morning after an overnight fast of between 8 and 14 hours and after at least 3 days of unrestricted diet (≥ 150g carbohydrate per day) and unlimited physical activity. More so, the subject should remain seated and not smoke throughout the test32. In recent times, glycated haemoglobin has also been recommended for the diagnosis of diabetes, with a threshold of ≥ 6.5%33,34.
2.5: Data Collection
The study included data from 183 Member States of the World Health Organization. This data was included based on its relevance, availability, quality, reliability, and comparability of the resulting estimates. Particular details related to the collection of data pertaining to the various variables considered in this study are explained below.
2.5.1: Data for dependent variable: prevalence of diabetes mellitus
Diabetes mellitus is one of the most common chronic diseases in nearly all countries, and continues to increase in numbers and significance, as urbanization and economic development lead to changing lifestyles characterized by reduced physical activity, and increased obesity35,36. Amongst the several previous estimates of the number of persons with diabetes which have been made37-40, of particular interest is the publication of the fourth edition of the IDF Atlas41 as seen in the table below.
Page | 8 Table 1: Global burden of diabetes-prevalence and projections, 2010 and 203041.
At a glance
Year 2010 2030
Total world population (billions) 7.0 8.4
Adult population (20-79 years, billions) 4.3 5.6
Diabetes (20-79 years)
Global prevalence (%) 6.6 7.8
Comparative prevalence (%) 6.4 7.7
Number of people with diabetes (millions) 285 438
According to table 1, the global diabetes epidemic continues to grow. This is illustrated by the fact that in the 20-79 years age group, 285 million out of 4.3 billion people had diabetes in 2010, and this will rise to 438 million out of 5.6 billion people in 2030 (an increase from 6.4%
to 7.7%)41. An updated report from IDF shows that as of 2012, more than 371 million people aged 20-79 years have diabetes; resulting in a diabetes comparative prevalence of 8.3%, and 50% of these people do not know they have it (that is, they remain undiagnosed)42.
For this study, the data for the prevalence of diabetes mellitus for each of the WHO Member States was obtained from the IDF Diabetes Atlas website43. IDF reported the prevalence estimates of diabetes mellitus for the year 2010 as a percentage (%), and the principal aspects of the determination of prevalence were44:
1. Studies were identified through a detailed literature search, and contact made with IDF member organizations.
Page | 9 2. The methodology indicated in Appendix B was employed to create smoothed curves
for prevalence (with respect to age).
3. Prevalence rates for a country were applied to the population distribution of that country. But where no data for certain countries were available, their prevalence rates were applied to those of other countries with similar ethnicity and economic circumstances.
4. An urban/rural prevalence ration of 2:1 was assumed for diabetes (but not impaired glucose tolerance), except in those countries classified by WHO38 as market economies or former socialist economies. The urban proportion of the population was derived from United Nations estimates45.
5. The data for diabetes rates include both type 1 and type 2 diabetes.
6. The prevalence of diabetes throughout the Diabetes Atlas includes both undiagnosed and previously diagnosed diabetes.
For every country, IDF calculated the prevalences in two ways namely: national or regional prevalence, and comparative prevalence44. But this study employed the comparative prevalence estimates as explained below. The national or regional prevalence indicates the percentage of each country’s population that has diabetes. Although it is ideal for assessing the burden of diabetes for each country, it cannot be used for comparing prevalences between countries. This is because the prevalence of diabetes increases with age and different countries have different age structures. On the other hand, the comparative prevalence was calculated by assuming that every country has the same age profile (the age profile of the world population was used in this calculation). Thus, eliminating the differences of age between countries and making this figure ideal for making comparisons between countries44.
Page | 10 2.5.2: Data for independent variables
2.5.2.1: Health expenditure for diabetes mellitus
Diabetes is not only a common chronic disease in nearly all countries but it is also costly to health care systems46. Thus, IDF refers to the global health expenditure for diabetes as the amount of money spent by different countries across the globe in treating and preventing diabetes and its complications44. Based on an IDF study46, estimates on health expenditures attributable to diabetes for all WHO Member States for the years 2010 and 2030 are reported in the table below.
Table 2: Global health expenditure for diabetes mellitus, 2010 and 203046.
At a glance
Year 2010 2030
Total world population (billions) 7.0 8.4
Adult population (20-79 years, billions) 4.3 5.6
Global health expenditure for diabetes (’000) with R values of 2 and 3 (20-79 years)
US dollars (USD), R = 2 375,983,944 490,064,566
US dollars (USD), R = 3 672,235,502 893,011,667
International dollars (ID), R = 2 417,817,971 561,334,452
International dollars (ID), R = 3 745,704,963 1,020,410,426
Page | 11 According to table 2, global health expenditure for diabetes mellitus was estimated by employing R values; where R is defined as the age- and sex-specific ratios of health care expenditure for persons with diabetes to persons without diabetes. In most countries, because the average value of R falls between 2 and 3, health expenditure for diabetes was estimated using two alternative average R values, R = 2 and R = 3. More so, since R is sensitive to age and sex, applying age- and sex-specific R should improve health expenditure estimates46. From table 2 as well, we observe that diabetes imposes an increasing economic burden on national health care systems worldwide. This is because the total annual global health expenditure for diabetes falls between USD 376.0 billion (R = 2) and USD 672.2 billion (R = 3), or between ID 417.8 billion and ID 745.7 billion in 2010, as opposed to 2030 where it is estimated to fall between USD 490.1 billion (R = 2) and USD 893.0 billion (R = 3), or between ID 561.3 billion (R = 2) and ID 1020.4 billion (R = 3). This implies that the global health expenditures for diabetes in 2030 will be 30-34% larger than those of 2010; thus, exceeding the assumed global population growth (28.6%) among people aged 20-79 years over the same period. Expenditures will grow more quickly than population because the global prevalence of diabetes is expected to increase due to aging and increasing urbanization46.
This study obtained the data for the health expenditure for diabetes for each of the WHO Member States from the IDF Diabetes Atlas website43. For every country, IDF reported the health expenditure for the year 2010, and these estimates are represented as mean health expenditure per person with diabetes (R = 2), measured in United States dollars (USD) (the US dollars served as the unit of measurement because they are best used to compare currency prices or expenditures for diabetes care)44.
2.5.2.2: Life expectancy at birth
Life expectancy at birth is defined as the average number of years a person can expect to live, if in the future they experience the current age-specific mortality rates in the population47. It is
Page | 12 also a measure of overall quality of life in a country and reflects the overall mortality level of a population. It summarizes the mortality pattern that prevails across all age groups in a given year - adults and the elderly, children and adolescents48,49. Since 1990 until 2009, life expectancy has increased globally by 4 years49,50, as illustrated in the table below.
Table 3: Life expectancy at birth for both sexes, 1990, 2000, and 200950.
Both sexes
Year 1990 2000 2009
Global life expectancy at birth (years) 64 66 68
Human life expectancy patterns are such that on average humans live 49.42 years in Swaziland51 and 82.6 years in Japan52. But the Japanese life expectancy is attributed to equal opportunities and public health as well as diet53,54. Worth mentioning is the fact that WHO also makes use of the healthy life expectancy, which is a related statistic estimating the equivalent years in full health that a person can expect to live on the basis of the current mortality rates and prevalence distribution of health states in the population47.
The data for life expectancy at birth was obtained from the World Health Statistics 201150. This publication contains health-related data for all WHO Member States, and it was compiled using publications and databases produced and maintained by WHO technical programmes and regional offices50. For this study life expectancy at birth values were reported for the year 2009, represented for both sexes, and measured in years50.
2.5.2.3: Prevalence of tuberculosis
Tuberculosis is an infectious bacterial disease caused by Mycobacterium tuberculosis, which most commonly affects the lungs. It is transmitted from person to person through droplets from the throat and lungs of people with the active respiratory disease. Symptoms of active
Page | 13 TB of the lung include coughing sometimes with sputum or blood, chest pains, weakness, weight loss, fever and night sweats. But TB is treatable with a six-month course of antibiotics55. TB occurs in every part of the world and it remains a major global health problem as it causes ill-health among millions of people each year and ranks as the second after HIV as the leading cause of death from an infectious disease worldwide. In 2011, 8.7 million new TB cases and 1.4 million TB deaths were recorded56,57. Generally, most countries are experiencing a drop in TB cases over the years57, thus, resulting in a decreasing global TB prevalence as illustrated in the table below.
Table 4: Prevalence of TB (per 100 000 population), 2000, 2009, and 201150,56.
Year 2000 2009 2011
Global prevalence of TB (per 100 000 population)
231 201 170
The data for prevalence of TB was obtained from the World Health Statistics 201150. This study reported prevalence of TB for the year 2009, and the unit of measurement was per 100 000 population50.
2.5.2.4: Population living in urban areas
Urbanization is among one of the leading global trends of the 21st century that has a significant impact on health. Certain factors which influence urban health include urban governance; population characteristics; social and economic development; the natural and built environment; services and health emergency management; and food security58. While urban areas bring great opportunities, they also bring challenges for better health. Cities of today and those of tomorrow face a triple threat: infectious diseases; noncommunicable diseases; and violence and injuries58,59. Urban population has increased over the years50 (as
Page | 14 seen in table 5) up to the point where in 2009, for the first time in human history, the majority of the world’s population was living in urban areas59,60.
Table 5: Population living in urban areas (%), 1990, 2000, and 200950.
Year 1990 2000 2009
Global population living in urban areas (%) 43 47 50
The global urban population is expected to grow approximately 1.5% per year between 2025 and 203061. This trend will continue with 6 in 10 people living in towns and cities by 203059, and over 70% of the world’s population living in cities by 205058.
The data for population living in urban areas was obtained from the World Health Statistics 201150. This study reported population living in urban areas for the year 2009, and the unit of measurement was percentage (%)50.
2.5.2.5: Out-of-pocket health expenditure
Out-of-pocket health expenditure is a part of private health expenditure, and it refers to any direct outlay by households, including gratuities and in-kind payments, to health practitioners and suppliers of pharmaceuticals, therapeutic appliances, and other goods and services whose primary intent is to contribute to the restoration or enhancement of the health status of individuals or population groups62. Out-of-pocket payments for health can cause households to incur catastrophic expenditures, which can in turn push them into poverty. It can also negatively affect individuals’ health because they cannot afford for health care when they need it63. According to statistics, the global out-of-pocket expenditure as a percentage of private expenditure on health remained at 50.7% in 2000 and 200850.
The data for out-of-pocket health expenditure was obtained from the World Health Statistics 2011, which was generated from information collected by WHO for over 10 years50. This
Page | 15 study reported out-of-pocket health expenditure as a percentage of private health expenditure, for the year 200850.
2.5.2.6: Adults aged ≥ 20 years who are obese
Overweight and obesity are defined as the abnormal or excessive accumulation of fat that presents a risk to health64. Overweight and obesity increase the risk of cardiovascular diseases, cancer, and chronic diseases, including diabetes. Previously, overweight and obesity was considered a problem only in high-income countries, but they are now on the rise in LMIC, particularly in urban settings50,64. Since 1980 obesity has more than doubled worldwide. In 2008, more than 1.4 billion adults aged ≥ 20 years were overweight; among which nearly 300 million women and over 200 million men were obese65.
The data for adults aged ≥ 20 years who are obese was obtained from the World Health Statistics 201150. This study reported values for adults aged ≥ 20 years who are obese for the year 2008, represented for both sexes, and measured in percentage (%)50.
2.5.2.7: Alcohol consumption among adults aged ≥ 15 years
Alcoholic beverages are widely consumed all over the world as a common feature of social gatherings66,67. Chronic diseases, neurological impairments, and social problems are likely to develop in those who drink large amounts of alcohol over a number of years66,68. Worldwide, there exists a large variation in adult per capita consumption (litres of pure alcohol consumed by every person ≥ 15 years), but the trend has remained stable at around 4.3-4.7 litres of pure alcohol since 199067.
The data for alcohol consumption among adults aged ≥ 15 years was obtained from WHO’s publications on World Health Statistics50 and its global status report on alcohol and health67. This study reported values for alcohol consumption among adults aged ≥ 15 years for the year 2005, and the unit of measurement was litres of pure alcohol per person per year50,67.
Page | 16 2.5.3: Data for Gross National Income (GNI) per capita
GNI per capita (formerly GNP per capita) is defined as the gross national income, converted to U.S. dollars (for comparisons across economies) using the World Bank Atlas method, divided by the midyear population69. Since WHO employs the World Bank classification system which classifies economies according to 2004 GNI per capita28 (calculated using the World Bank Atlas method), the 2004 GNI per capita values were obtained from the World Bank website69 and reported in this study. Based on the above classification system, economies are grouped into: low-income, $975 or less; lower middle-income, $976 - $3,855;
upper middle-income, $3,856 - $11,905; and high-income, $11,906 or more69. Furthermore, since the upper middle- and lower middle-income groups both comprise the middle-income countries29, the latter are those countries with GNI per capita ranging from $976 - $11,905. In this study, we had a total of 37 Member States in the low-income group, 51 in the lower middle-income group, 47 in the upper middle-income group, and 48 in the high-income group50. Thus, GNI was classified as a categorical variable, with the 4 country income groups namely: low-, lower middle-, upper middle-, and high-income countries being represented as codes 1, 2, 3, and 4 respectively in the data set.
2.6: Analyses
2.6.1: Descriptive analyses
Microsoft Word 2007 and Microsoft Excel 2007 were used to make tables and charts of the distribution of the study variables in the 4 WHO country income groups.
2.6.2: Statistical analyses
Linear regression analyses were performed to analyze the association between prevalence of diabetes mellitus and health expenditure for diabetes, life expectancy at birth, prevalence of tuberculosis, population living in urban areas, out-of-pocket health expenditure, adults aged ≥ 20 years who are obese, and alcohol consumption among adults aged ≥ 15 years. Two kinds
Page | 17 of linear regression analyses were performed namely: univariate (unadjusted), and multiple (adjusted) analyses. In the univariate linear regression analyses, the impact of each independent variable on the dependent variable was accessed. But in the multiple linear
Page | 17 of linear regression analyses were performed namely: univariate (unadjusted), and multiple (adjusted) analyses. In the univariate linear regression analyses, the impact of each independent variable on the dependent variable was accessed. But in the multiple linear