Diabetes and impaired glucose tolerance
Childhood type 1 diabetes
Complications of diabetes
Economic impacts of diabetes 

Methodology for the estimates on diabetes and impaired glucose tolerance

1. Data search
The search for data was limited to studies published after 1979. This cut-off was chosen as data collected prior to 1980 may no longer reflect the current prevalence of diabetes. Selection of articles was limited to those published pre-March 2006.

The Medline database and internet were used for the literature search. Systematic searches were conducted for each country using the following search formulae:

• Country name (all the countries of the world were entered for separate searches) together with ‘diabetes’ or ‘impaired glucose tolerance’ and ‘prevalence’ or ‘incidence’; and
  
• ‘NIDDM’ or ‘IDDM’ or ‘non-insulin-dependent diabetes mellitus’ or ‘insulin-dependent diabetes mellitus’ or ‘Type 1 diabetes’ or ‘Type 2 diabetes’, combined with ‘prevalence’ or ‘incidence’.

Relevant citations from each article were also obtained. A number of other avenues were explored in the search for relevant data. Diabetes researchers in each major IDF geographical region were contacted and requested to provide information on the prevalence of diabetes for countries within their region. In addition, IDF member associations in each member country were asked about relevant data. In the absence of data for a country, the member association was further asked to comment on the use of data from another country (see section on Extrapolation below).

2. Data selection
The search obtained data in a variety of forms such as prevalence studies, registry reports, hospital statistics, government estimates, etc. Studies for a particular country were included based on their level of reliability. The following factors were taken into account when assessing a study’s level of reliability: 

• The year of the study — more recent studies were preferred.
• The screening method used — the oral glucose tolerance test (OGTT) was the preferred method of screening, followed by two-hour blood glucose (2hBG) alone, then the fasting blood glucose (FBG) alone, and then self-report (SR).
• Sample size — studies with larger sample sizes and higher response rates were preferred.

When more than one study was available for a country, and there was no clear superiority of one over the other, the results from the available studies were averaged, and then applied to the national population.

Extrapolation
If there were no data available for a particular country, prevalence rates from a published study from the socio-economically, ethnically, and geographically most similar country were applied to that country’s age and sex-specific (and in the case of low/middle-income countries, urban/rural-specific) population distribution. Socio-economic comparisons were based on gross national product (GNP) per capita. Ethnic comparisons were based on ethnicity data from the CIA World Factbook 2005   1 .

If a dataset did not provide sex-specific data, the data were disaggregated and assigned 50% to females and 50% to males.

Urban: rural prevalence
In countries with low or middle-income economies, differences between urban and rural populations in levels of physical exercise, diet, and socio-economic factors often result in significant differences in diabetes prevalence rates. Therefore, for low- and middle-income economies (except those of the former socialist economies in Europe), the urban and rural rates were calculated and numbers reported separately.

The economies were defined according to the 1997 GNP per capita, calculated using the World Bank Atlas method   2 . Low- and middle-income economies had a GNP per capita of less than USD9,655, and high-income economies had a GNP per capita of USD9,655 or more. If the above conditions for different urban and rural diabetes prevalences applied, then for countries where available studies showed prevalences separately for urban and rural populations, these rates were applied to the national urban and rural populations.

For studies reporting on a mixed urban and rural population, but where no data were provided as to the urban/rural distribution of the survey population, the available age and gender specific data were assigned to the population so as to produce a 2:1 urban:rural ratio in diabetes prevalence.

For countries where only urban or only rural data were available, the 2:1 ratio was used to calculate the prevalence of diabetes in the other segment of the population. No urban:rural difference was used for IGT prevalence, unless the data for that country indicated a prevalence difference to be present.

Known diabetes
Studies from several countries — Canada, France, Germany, Israel, Italy, Netherlands, New Zealand, Norway — only provided data on self-reported diabetes. To account for undiagnosed diabetes, the prevalence of diabetes for Canada was multiplied by a factor of 1.5, in accordance with findings from the USA   3 , and for the other countries doubled, based on data from a number of countries   4    5    6    7    8 .

3. Prevalence calculation
A list of the world’s countries and 2007 and 2025 population distribution estimates was obtained from the United Nations Population Division   9 . The age- and sex-specific prevalence rates (obtained from the logistic regression, see below) were applied to the corresponding age and sex population distribution for the years 2007 and 2025 for each country. This method for estimating figures for 2025 only takes into account changes in age, sex and urban/rural population distributions, and not for the likely changes in lifestyle and obesity, which may tend to increase diabetes prevalence. Thus, the figures may be an underestimate.

The prevalence rate (PR) of diabetes and IGT for each country was then calculated using the formula: 

4. Prevalence reporting
In addition to calculating the national rates, a prevalence for each country and region, adjusted to the world population, was calculated by applying for each country that country’s age- and sex-specific rates to a notional population of that country’s population size, but with the world population age and gender distribution for 20–79 years (for 2007 and 2025). This was done to facilitate comparison of rates between countries and regions, and this adjustment to the world population noted whenever it was used.

For each region the prevalence adjusted to the world population was calculated by the summation of the number of persons for each member country with the condition, if each country’s world population adjusted prevalence were applied to that country, and the sum divided by the total regional population (20-79 years).

5. Logistic Regression
For each country, data for both diabetes and IGT are presented for people in the 20-79 age group. Most of the datasets used did not contain data for all age groups in the 20-79 year age bracket. In order to fill in missing data and to ensure a smooth relationship between prevalence and age, logistic regression was performed on those datasets that contained four or more datapoints.

Observed data were entered into an SPSS spreadsheet under the following columns: age (mid-age of each age group), weight (number of people without or with diabetes, or IGT, for each age group), and diabetes or IGT (0 = no, 1 = yes). The age specific prevalence (or case numbers, when provided) was used to obtain the weighting in the following manner: 

Examples of modelled and published diabetes prevalences 

Figure A1.1 Jordanian males and females combined (urban)

Figure A1.2 Chinese males

Figure A1.3 Bolivian females

Figure A1.4 Indian females