The SuRF Report 1
Surveillance of Risk Factors
related to noncommunicable diseases:
Current status of global data
Noncommunicable Diseases and Mental Health
World Health Organization
20 Avenue Appia
1211 Geneva 27
Switzerland
World Health
Organization
WHO Library Cataloguing-in-Publication Data
The SuRF report 1. Surveillance of risk factors related to noncommunicable diseases:
current status of global data.
(SuRF reports)
1.Chronic disease – epidemiology 2.Risk factors 3.Epidemiologic surveillance 4.Databases,
Factual 5.Data collection – methods I.WHO Global NCD InfoBase Team II.Title: Surveillance of risk
factors related to noncommunicable diseases: current status of global data.
ISBN 92 4 158030 5
(NLM Classification: WT 500)
Acknowledgements
The World Health Organization wishes to acknowledge the support from the Governments
of Australia, Canada, the Netherlands, Sweden and the United Kingdom towards the development of
the WHO Global NCD InfoBase. The World Heart Federation provided additional support.
Invaluable contributions towards the development of the InfoBase, from which country
profiles for the Surveillance of Risk Factors (SuRF) report have been drawn, have also
been received from many organizations, institutions and individuals that are listed in
the Acknowledgements section of the accompanying CD-ROM. The authors would like
to acknowledge Dr Andreas Wielgosz and Dr Hongbo Liang at the WHO Collaborating Centre
at the University of Ottawa. Their initial work on the CVD InfoBase was a precursor for the WHO
Global NCD InfoBase. Technical support on internal WHO data bases was provided
by Dr Chizuru Nishida (BMI data base), Emmanuel Guindon and Omar Shafey (NATIONS data base),
and Dr Nina Rehn (Alcohol data base). Dr Sylvia Robles and colleagues in PAHO kindly allowed the use
of the acronym, SuRF.
Dr Kate Strong leads a team at HQ which has included the following: Ms Maria Filimonenko, Dr
Hongbo Liang, Ms Jaclynn Lippe, Ms Carina Marquez, Mr Sean McGrath, Ms Angela Newill, Ms Tomoko
Ono, Ms Rachel Pedersen and Ms Yin Mun Tham. Support and co ordination in the Regional Offices
was provided by Dr Krishnan Anand (SEAR), Dr Maximillian de Courten (WPRO), Dr Djohar Hannoun
(AFRO), Mr John Jabbour (EMRO), Dr Paz Rodriguez (AMRO) and Dr Aushra Shatchkute (EURO).
Copies can be obtained from:
Email: [email protected] – Fax: +41 22 791 4769,
The content of the SuRF report is available on the Internet at:
http://www.who.int/ncd/surveillance/surveillance_publications.htm
Suggested citation: Strong K, Bonita R. The SuRF Report 1. Surveillance of Risk Factors related to
Noncommunicable Diseases: Current status of global data. Geneva, World Health Organization, 2003.
© World Health Organization 2003
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Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters.
2
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
5
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
WHO Global NCD InfoBase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
..................................................................
9
Contents of the SuRF report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Population data and average life expectancy
Statistical methods
Risk factors
WHO’s approach to risk
9
Methods
Risk Factor methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Tobacco use
Alcohol consumption
Physical inactivity
Fruit and vegetable intake
Obesity and overweight
Raised blood pressure
Raised blood lipids
Diabetes
Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Country-level sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
European Region
Region of the Americas
South-East Asia Region and Western Pacific Region
Eastern Mediterranean Region
African Region
Additional survey instruments
Gaps and deficiencies in data
WHO’s response to addressing the gaps in risk factor data . . . . . . . . . . . . . . . . . . . . . . . . 22
The WHO Global NCD Infobase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Structure of the InfoBase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Source
Survey methods
Data entry
Selecting data for display
Displaying data in SuRF report format
Using the country profiles on CD-ROM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Future additions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Vision for the future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
References
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Appendices
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Appendix 1: Acronyms and abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Appendix 2: Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Appendix 3: Six tables for Regional Offices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3
Preface
Until recently, risk factors such as raised blood pressure, cholesterol, tobacco use, excess
alcohol consumption, obesity, and the diseases linked to them, were more commonly associated with developed countries. However, the World Health Report 2002: reducing risks,
promoting healthy life, indicates that they are now becoming more prevalent in developing
nations. These countries are being affected by a double burden of disease, the combination
of long-established infectious diseases and the rapidly growing epidemic of chronic, noncommunicable diseases (NCDs). WHO has responded by giving higher priority to NCD prevention, control and surveillance in its programme of work. Now more than ever, standard
methods and tools are needed to enable countries to build and strengthen their capacity to
conduct surveillance of NCDs and their risk factors.
One such tool is the WHO STEPwise approach to Surveillance (STEPS) of risk factors related to NCDs. It is a simplified, stepwise approach providing standardized materials and
methods to help countries, especially those that lack resources, initiate NCD activities. The
goal is to achieve data comparability between countries over time.
The SuRF Report 1 introduces another tool, the WHO Global NCD InfoBase, which assembles, for the first time in one place, NCD risk factor data collected from WHO Member
States. Data from the InfoBase is presented in the country profiles of the SuRF report and
its associated CD-ROM attachment. Displaying the currently available data is the first step
towards improving NCD risk factor data collections. This is an on-going process. In the next
step (SuRF 2), the available country data will be used to produce comparable estimates for
risk factor prevalence in WHO Member States. This will result in an advocacy tool with the
power to transform health policy by highlighting the need for primary prevention and health
promotion.
Ruth Bonita,
Director Surveillance
Derek Yach,
Executive Director
Noncommunicable Diseases and Mental Health
World Health Organization
4
Summary
High quality health statistics are essential for planning and implementing health policy in
all country settings. In fact noncommunicable disease (NCD) risk factor data are crucial for
predicting the future burden of chronic disease in populations and also for identifying
potential interventions to reduce the future burden. The Surveillance of Risk Factors report
(SuRF) presents, for the first time, country-level NCD risk factor prevalence data from the
WHO Member States.
– The focus of the report is on recent, nationally representative data.
– The risk factors of choice are those that make the greatest contribution to mortality and
morbidity from chronic disease, can be changed through primary intervention and are
easily measured in populations.
– Eight risk factors that relate mainly to cardiovascular disease fit this criteria: tobacco
and alcohol use, patterns of physical inactivity, low fruit/vegetable intake, obesity (as
measured by BMI), blood pressure, cholesterol and diabetes (measured by blood glucose).
– Of principal importance to the data collection is the need to display prevalence data and
(where possible) mean values for these 8 risk factors by age group(s) and sex and with
some measure of the uncertainty of the estimates for each Member State.
NCD risk factor information included in the SuRF report comes from a variety of sources,
ranging from peer-reviewed journal articles to reports and unpublished data from Ministries
of Health. All of this information is held in the WHO Global NCD InfoBase, designed as a
“one stop” resource for data needs. The NCD InfoBase is a timely tool for collecting and
displaying current country-level NCD risk factor data and was used to create the country
profiles of risk factor data displayed on the CD-ROM attachment to this report.
Much of the data gathered for the country profiles has been provided by data focal points
in WHO Regional Offices. Plans are in place to develop Regional NCD InfoBases to improve
the country coverage for data on NCDs and their risk factors.
The format of SuRF 1 consists of a report booklet and CD-ROM attachment. It is the first
step in a series of SuRF reports and presents current country data that are largely non
comparable. The second step will be to produce harmonized prevalence estimates from the
existing country data. These comparable estimates will become a powerful tool in advocating for primary prevention and health promotion. SuRF 1 will be followed by an interactive
website in the autumn of 2003.
5
Introduction
The report on the Surveillance of Risk Factors (SuRF) assembles, for the first time, existing
data on the prevalence of the major risk factors related to noncommunicable diseases
(NCDs) for WHO Member States. It focuses on recent, nationally representative data and
presents the data as they are reported by survey sources. The risk factors included in the
report are those that:
– contribute the most to mortality and morbidity from chronic diseases;
– can be changed through primary intervention; and
– can easily be measured in populations.
The eight risk factors that fit this criteria are tobacco and alcohol use, patterns of physical
inactivity, low fruit/vegetable intake, obesity, raised blood pressure, raised cholesterol and
diabetes. It is important for the data collection to display prevalence and/or mean values
for these eight risk factors by age and sex, and with some measure of the uncertainty for
each estimate.
Knowledge of noncommunicable disease (NCD) risk factors is important for predicting the
burden of chronic disease in populations and for identifying potential interventions to
reduce such burdens. The World Health Report 2002: Reducing risks, promoting healthy
life highlights the importance of risk factors as indicators of future health status (WHO,
2002). Even in the poorest countries, NCD risk factors such as raised blood pressure, cholesterol and tobacco use are responsible for increasing levels of chronic diseases and premature deaths. In fact, the joint effects of these three risk factors account for 65% of all
cardiovascular diseases in those above the age of 30 (WHO, 2002). Furthermore, five of
the top 10 global risks to health are NCD risk factors (Table 1). These include raised blood
pressure, tobacco use, alcohol consumption, cholesterol and obesity/overweight.
Table 1 Leading 10 selected risk factors as selected causes of disease burden (World Health Report 2002).
Indicates major NCD Risk Factors.
Developing Countries
HIGH MORTALITY
LOW MORTALITY
1. Underweight
Alcohol
Tobacco use
2. Unsafe sex
Blood pressure
Blood pressure
3. Unsafe water
Tobacco use
Alcohol
4. Indoor Smoke
Underweight
Cholesterol
5. Zinc deficiency
High body mass index
High body mass index
6. Iron deficiency
Cholesterol
Low fruit and vegetable intake
7. Vitamin A deficiency
Low fruit and vegetable intake
Physical inactivity
8. Blood pressure
Indoor smoke
Illicit drugs
9. Tobacco use
Iron deficiency
Unsafe sex
Unsafe water
Iron deficiency
10. Cholesterol
6
Developed Countries
Unfortunately, country-level data on common, measurable NCD risk factors are scarce. Few
countries have the resources, infrastructure or political commitment to collect this type of
information in a sustainable manner. While some developed countries have regular national
health surveys that include selected NCD risk factors, others gather their information
through small, costly ad hoc surveys. The objective of this report is to promote the sustainable collection of high quality risk factor data and to advocate establishing surveillance
systems for noncommunicable diseases and their risk factors as an alternative to costly ad
hoc surveys.
The risk factor prevalence profiles help to identify a country’s strengths as well as gaps and
deficiencies in its data. Where possible mean values for systolic blood pressure, total cholesterol, blood glucose and body mass index have been included to describe the distribution of the risk factors in specific populations. The World Health Report 2002 demonstrates that NCD risk factors contribute significantly to the burden of disease in both
developed and developing countries. Now is the time to assess the quality of NCD risk factor information at the country-level so that this information can be improved and/or
expanded to provide the impetus for better health policy.
Valid and reliable health statistics are essential for planning and implementing health policy in all settings. The first step is to identify and assess the quality of NCD risk factor data
collected globally. The SuRF report takes this first step and attempts to identify the most
recent prevalence estimates for risk factors related primarily to cardiovascular disease.
Some important country data may be missing by the time this document is published but
country data collection is ongoing and additional information will be reflected in future
SuRF reports.
The risk factor prevalence profiles help to
identify a country’s
strengths as well as
gaps and deficiencies
in its data.
A main objective of the NCD surveillance programme is to use the collected country data
to produce best estimates of country-level risk factor prevalence and trends in standard age
groupings. The resulting comparable risk factor estimates will be published in the SuRF
report 2. To help make country data accessible and comparable, data is being collected
and stored in a data base, the WHO Global NCD InfoBase.
WHO Global NCD InfoBase
The risk factor data displayed by the SuRF report come from the WHO Global NCD
InfoBase. The InfoBase collects all, current country-level data on important NCD risk factors for all WHO Member States. There are many different survey instruments available for
collecting data on health behaviours and physical measurements of risk exposure. Each
instrument has advantages and limitations. For example, some countries have nationally
representative surveys with good sampling frames and well defined methodology. In these
cases, the most recent national survey represents the best estimate of risk factor prevalence for that country.
In other countries, where there is little data, surveys may be non-representative of the
national population, include non-probability sampling frames or have other limitations
reflected in the survey methodology. However, such surveys can still be used, taking into
account their limitations, to help build a model to estimate risk factor prevalence for a
country. Understanding the strengths and deficiencies of the data allows users to maximize
the use of the existing information for health policy and research purposes.
7
The NCD InfoBase displays all the surveys that a country has with information about survey
design and representativeness and gives users the opportunity to select the surveys that
they wish to display. In addition, the InfoBase contains risk factor prevalence data from
other WHO in-house data bases, including the NATIONS tobacco database, the WHO
Global BMI database and the WHO Global Alcohol database. The InfoBase has a flexible
data base structure to allow the inclusion of disease-specific modules in the future. Data
on stroke and respiratory diseases are currently being included, as are measures of oral
health. Indicators of injury and violence will be included in the future. A detailed account
of the structure of the InfoBase is given in Section 4.
Understanding the
strengths and deficiencies of the data
allows users
to maximize the use
of the existing information for health
policy and research
purposes.
8
The NCD InfoBase will be available on the internet towards the end of 2003. This tool for
identifying country-level data and assessing its validity provides a starting point for making
NCD risk factor data comparable. Displaying the available data in one place is the first
step towards developing better quality NCD data collections.
The data presented in this report are by no means complete and require continuing contact
with Ministries of Health and study authors. The SuRF report and the NCD InfoBase will be
up-dated and published regularly with assistance from data focal points in all six WHO
regional offices.
Methods
This section explains some of the concepts that inform the selection and presentation of
NCD risk factors in the SuRF report. The report is made up of a brief text section and a
CD-ROM containing a copy of the text section and complete country profiles of NCD risk
factor data for WHO Member States.
In addition, a list of abbreviations used in the country profiles and throughout the text is provided at the beginning of this report. A glossary is also included to explain frequently used
terms. The CD-ROM includes a complete bibliography of the SuRF report country profiles
and an extensive acknowledgement section to thank all who helped to provide country data.
Contents of the SuRF report
The advantage of the SuRF report is that it displays country risk factor profiles on CD-ROM
to make the data more accessible. The CD-ROM format enables direct access to the data
on a computer instead of a unwieldy paper copy. The format displays the following information for each Member State:
– all recent risk factor data;
– age-specific prevalence rates or mean values;
– survey sample sizes;
– 95% confidence intervals;
– risk factor definitions; and
– complete source information.
In many cases, study authors or Ministries of Health have been contacted for additional,
unpublished information about their risk factor surveys. Notes attached to the source reference indicate where additional information has been provided and identifies the provider.
The SuRF report is a product of the NCD surveillance activities which follow a STEPwise
approach. The first step is an ongoing project to provide up-to-date country data on NCD
risk factors. The second step will use the acquired country data to produce comparable
best estimates of country risk factor prevalence in standard age groupings. The third step is
to use these comparable estimates to advocate for an improved policy response to the
growing global burden of chronic disease.
Population data and average life expectancy
Each country profile is identified by the official name of the Member State, the WHO region to
which it belongs and general information about its population size and average life expectancy
(Figure 1). Estimates of 2002 population size and age structure are based on the 2000
and 2001 demographic assessments prepared by the United Nations Population Division.
Figure 1
Male
Females
2002 Total Population
4,498,305
5,259,387
2020 Projected Population
4,836,000
5,121,000
2001 Average Life Expectancy (years)
71.9
78.8
9
These estimates are for the de facto population (e.g. including guest workers and refugees)
rather than de jure population (e.g. citizens and, in some Member States, permanent residents). As a result, these estimates may differ from official country statistics. WHO uses a
standard method to estimate and project life tables for all Member States (WHO, 2002).
This may lead to minor differences when compared to official life tables prepared by
Member States. A 95 % uncertainty interval is included for the average life expectancy estimates. These intervals take into account the uncertainty in the estimates due to sampling.
Statistical methods
Preventive strategies,
targeting the whole
Age specific rates are used to display the data in the SuRF report. These were calculated
by dividing the number of people exhibiting the risk factor of interest in each specified age
group by the corresponding survey sample in the same age group. This rate is multiplied by
100 to give the per-cent prevalence for particular age and sex groupings.
population, aim to
encourage healthier
behaviour and thus
reduce exposure to
risk.
The age-specific prevalence rates presented in this report also show 95 % confidence intervals. Some surveys and study authors provided the InfoBase team with these values from
their own calculations. Where this was not possible, the InfoBase team estimated the confidence intervals, assuming a binomial distribution for the risk factor of interest in the
specified age range. These estimations were only done for the total age range provided by
the study.
For some countries with national risk factor surveys, the age-specific prevalence rates from
the survey are weighted to the estimates of the national population, either from a recent
population census or from demographic models. If the national survey used a sampling
frame with no systematic biases and good population coverage, these weighted prevalence
values provide a reasonable estimate of national risk factor prevalence. In these cases, the
SuRF report provides the weighted national prevalence estimate along with the actual survey
sample size in the country profiles. This presentation is noted in the accompanying text.
Risk Factors
Risk factors are displayed following the order as outlined in the STEPwise approach to
Surveillance of NCD risk factors (STEPS; Bonita et al., 2001). STEPS is a sequential program that focuses on building and strengthening country capacity for middle and low
income countries to collect, on a periodic basis, small amounts of high quality risk factor
data (Bonita et al. 2001; Figure 2). Step 1 is the collection of self-reported information
about health behaviours, including tobacco use, alcohol consumption (heavy drinkers and
abstainers), diet and physical inactivity. Step 2 focuses on objective standardized physical
measurements to collect data on blood pressure, height and weight. Finally, Step 3 collects
blood samples to measure lipids (cholesterol) and glucose status (for diabetes).
The SuRF report presents risk factors in accordance with the STEPwise approach to
Surveillance of NCD risk factors (STEPS) protocol (Bonita et al., 2001). Key health behaviours collected in Step 1 are reported first, followed by obesity/BMI and raised blood pressure from Step 2, and finally, raised blood lipids and diabetes from Step 3. The order in
specific country profiles depends on data availability. Many countries have limited data
which may not cover all of the NCD risk factors included in this report. As a result, their
risk factor profiles may be incomplete. However, countries with incomplete data have the
opportunity to begin collecting standardized data using STEPS.
10
Figure 2
The WHO STEPs approach to NCD surveillance
The conceptual framework offers a distinction
between different levels of risk-factor
assessment: Information by:
– questionnaire
– physical measerements
– blood samples;
Optional 3
Optional 2
Optional 1
and three modules offering different
quantity of detail of each risk factor:
Expanded
– core
– expanded core, and
– optional
Core
WHO’s approach to risk
Risk of disease generally increases along a continuum of risk factor exposures, resulting in a
continuous population distribution of risk (Rose, 1992). For convenience, clinicians often focus
on interventions for those at the far end of the spectrum, i.e. those considered to be at “high
risk” of disease. This focus creates arbitrary, dichotomous categories for those considered to be
at risk, for example, systolic blood pressures greater than 140 mm Hg or greater than 160 mm
Hg. However, many people with lower risk exposures will develop disease. Furthermore, the
bulk of the disease burden occurs where the greatest proportion of the population is exposed to
risk and this may occur below a particular “high risk” threshold. As a result, preventive strategies that focus on shifting the entire distribution of the risk factor will prevent more disease
than would be the case if only high risk groups were targeted. Preventive strategies, targeting
the whole population, aim to encourage healthier behaviour and thus reduce exposure to risk.
WHO uses a population-based approach to risk and prevention (WHO, 2002). For this reason,
the SuRF report includes, whenever possible, data on the mean values of risk factors that are
distributed in a continuous manner. These are systolic blood pressure, BMI, total blood cholesterol and blood glucose. The addition of these factors means that the profile for a country
with good data collections can include up to 13 risk factor variables (see Figure 3 below).
Figure 3
Health Behaviours
– Tobacco use
– Alcohol consumption (heavy)
Physiological Factors
– Obesity/overweight (& mean BMI)
Disease outcomes
– Raised blood pressure (& mean systolic
blood pressure)
– Heart disease
– Physical inactivity
– Fruit/vegetable intake
– Raised lipids (& mean total cholesterol)
– Alcohol abstainers
– Stroke
– Cancers
– Diabetes (& mean blood glucose)
– Diabetes
The preferred definitions for these risk factors are outlined in the next section.
11
Risk Factor methodology
Tobacco use
The dried leaf of the plant, Nicotiana tabacum, is used globally in many forms including
smoking, chewing or snuff. The product is cultivated in many regions and can be legally
purchased around the world.
The current pattern of
tobacco use predicts
the future burden
of lung cancer and
other smoking related
disease.
In many countries, cigarette smoking is only a small part of actual tobacco use. In fact, in
some places, more people use huqqa, bedi, snuff or some form of chewing tobacco than
manufactured cigarettes. For these situations, the SuRF profiles also include available data
on other forms of tobacco use. The current pattern of tobacco use predicts the future burden of lung cancer and other smoking related disease. Policy makers can use this information to implement prevention strategies to avoid this burden. From this perspective, past
smoking patterns are less important because they relate directly to the current burden of
tobacco use in a country, not the future, preventable burden. The focus is on current, daily
tobacco users therefore data on occasional and former users is not reported here.
Although comparable data on tobacco use are not widely available, most countries report
some population-level statistics on tobacco use. WHO headquarters and Regional Offices
produce regular country profiles for tobacco use and a wide range of other tobacco related
statistics. A joint venture by WHO, the Centres for Disease Control (CDC) and the American
Cancer Society (ACS), known as the NATIONS Tobacco database stores not only tobacco
prevalence data from most countries but a variety of important information about tobacco
control policies and legislation in these countries. In addition to published reports and online databases, WHO has developed, in collaboration with the CDC, the Global Youth
Tobacco Survey (GYTS). The GYTS is now the largest global surveillance system for any
major public health risk. It is operational in 150 countries and has completed questionnaires on over one million young people between the ages of 13 and 15 years in randomly
selected schools. The SuRF report displays data from the published GYTS surveys.
The definitions for tobacco use supplied by the survey sources are used in the country profiles. No attempt has been made to standardize these definitions. The most common designations include:
– Current daily smoker (including definitions of “at least one cigarette per day”);
– Smoker;
– Regular smoker; and
– User of some form of tobacco (including multiple sources).
Most surveys specify the meaning of “smoker” and “regular smoker” but often this is not
recorded. Where additional information is included about a definition, it is recorded in the
NCD InfoBase and it is displayed in the risk factor definition section of the country profile.
Table 2 shows the variety of definitions used to collect tobacco use prevalence data. For
reasons mentioned above, the preferred definition is “current daily smoker”.
12
Table 2 Selected examples of definitions used and age groups included in surveys to collect prevalence
of tobacco use.
Definition
Age groups (years)
Country of origin of the Source
Current daily smoker
various combinations
various
Regular smoker
various combinations
various
smoker
various combinations
various
Smoker; cigarettes
13-15
GYTS for various countries
Uses some form of tobacco (includes
multiple sources)
18+
Afghanistan
Current daily smoker:
> 10 cigarettes per day
20-89
Venezuela
Chew paan masala or tobacco
15+
India
Smoker (includes daily smoker) once a week
at least and less than once a week
25-69
Bangladesh
Regular current smoking
12-45
Paraguay
Smoker; 1 to more than 15 cigarettes per day or
1 to more than 2 pipe fulls of tobacco per day
18+
Haiti
Smoking or chewing tobacco leaf with betel quid
18-75
Bangladesh
Alcohol Consumption
Alcohol consumption has many health and social consequences resulting from intoxication
and dependence. Direct health consequences range from automobile accidents and domestic violence to chronic health and social problems (WHO, 1999). However, there are also
reported beneficial relationships between low to moderate drinking in a non-binge pattern
and coronary heart disease, stroke and diabetes mellitus (Rehm et al., 2001).
The definitions used for population-based data on alcohol consumption vary widely from
country to country. Many countries do not collect this information at all because alcohol
consumption is not permitted in their societies for religious reasons. Other countries collect
and report the information without a standard definition for heavy consumption. The country profiles display the definitions used by the survey source with the aim of providing the
most specific definition possible for high alcohol consumers. Table 3 provides examples of
the variety of definitions for high alcohol consumption that are routinely reported. The
WHO STEPS survey instrument uses 7 day recall of number of standard drinks to quantify
proportion of adults engaged in “at risk levels” of drinking.
Similarly, definitions for alcohol abstainers differ from country to country. Many studies
consider only those who report ‘never drink alcohol’, while others simply report ‘abstainers’.
Often, there is no way to differentiate between those who have tried alcohol but choose not
to drink and those who have never had a drink. However, this distinction is unlikely to
affect the overall risk profile at the population level.
13
Table 3 Selected examples of definitions and age groups included in surveys to collect prevalence of high alcohol
consumption.
Definition
Age groups
Country of origin of the source
reported alcohol dependency
various combinations
Various
drink alcohol
15 +
Cameroon and various
daily drinkers
various combinations
Various
the ingestion of 100 cc of absolute alcohol
at one time (opportunity)
12-45
Paraguay
alcohol consumption at least one time per year
12-49
Mexico
tion or measure of
20+ g of alcohol daily intake
20-49
Czech Republic
physical activity.
0ver 0.2 L of alcohol per day
26-62
Bosnia and Herzegovina
heavy alcohol consumption in the past year;
more than 14 drinks per week for men and more
than 7 drinks per week for women
20+
USA
There is no internationally agreed defini-
Physical inactivity
Regular physical activity has health benefits including regulation of body weight and
strengthening of the cardiovascular system (CDC, 1996). Measuring the levels of activity or
inactivity in a population has proved difficult. There is no internationally agreed definition
or measure of physical activity. To add to the problem, physical activity exists in multiple
domains of a person’s life, from main occupation (especially if the job involves physical
labour), to means of transport, domestic duties and leisure time.
The SuRF report focuses on lack of activity as a risk factor for poor health outcomes, including overweight/obesity and cardiovascular disease. Again, definitions of physical inactivity
vary in different country settings. Often high and middle income countries report activity or
inactivity in “leisure” time, a concept that may not exist in low income situations. Most
available data are for leisure-time activity while little data are available for activity relating to
work, transport or domestic tasks.
The country profiles display the definition provided by the survey source. Sometimes, surveys
choose to provide information related to specific activity levels as well as inactivity. Preference
was given to including data in the country profiles that relate to physical inactivity rather
than physical activity. The most frequently used definitions for physical inactivity are
“sedentary” or “no exercise” categories.
The WHO STEPS survey instrument measures physical activity/inactivity across three domains
of life: work, leisure time and transport. It uses an activity score based on intensity of activity
and time spent in activity to calculate the proportion of inactive adults.
Fruit and Vegetable intake
14
Fruits and vegetables are important components of a healthy diet designed to regulate
weight and provide appropriate nutrients for growth and development. Low fruit and vegetable intake is causally linked to incidence of cancer and heart disease (Ness and Powles,
1997; World Cancer Research Fund and American Institute for Cancer Research, 1997).
Health promotion programmes emphasize the importance of eating five or more servings of
fruit and vegetables combined a day. Some developed countries collect this information in
their national health surveys. Other surveys collect information on presumed average fruit
and vegetable intake per capita. Still others find it easier to report ‘never eats fruit’ or
‘never eats vegetable’ as categories. The country profiles in the SuRF report display the
definitions given by the survey source.
Definitions that designate the part of the population that is not eating enough fruit and
vegetable are preferred because they relate directly to the risk category of low fruit and
vegetable intake. Such definitions include “less than or equal to five fruit and vegetable
servings per day”, “never eats vegetables”, and “never eats fruit”.
Health promotion
The WHO STEPs survey instrument collects information on how many servings of fruit and
vegetable are eaten on a typical day and uses this information to calculate the proportion
of adults who are not eating 5 or more combined servings of fruit and vegetable.
programmes empha-
Obesity and overweight
of eating five or more
The prevalence of obesity and overweight is commonly assessed using body mass index
(BMI, kg/m2). This formula has a strong correlation to body fat content. The WHO criteria
define overweight as BMI greater than or equal to 25 kg/m2 and obesity as BMI greater
than or equal to 30 kg/m2 (WHO, 2000). These criteria provide a benchmark for measuring
overweight and obesity but the risks of disease in a population increase progressively from
BMI levels of 20 to 22 kg/m2.
servings of fruit
size the importance
and vegetables
combined a day.
BMI generally increases with age, peaking in the middle-aged and elderly, who are at greatest risk of health complications. The increase corresponds to higher levels of free sugars
and saturated fats in the diet combined with reduced physical activity.
Many surveys report prevalence of obesity and overweight using the WHO criteria for measured height and weight and this is the preferred definition. However, a variety of other definitions are also displayed in the country profiles, reflecting what is being collected at the
country-level. Table 4 displays examples of the variety of obesity definitions currently in use.
Often the BMI categories reflect self-reported height and weight and this is indicated in
the country profile definitions. Measured data is preferred because self-reported height and
weight may differ significantly from measured height and weight and the deviations will
result in biased BMI estimates (Waters, 1993). Mean values for BMI in specific age groupings are preferred in line with WHO’s population-based approach to distribution of risk
exposures (WHO, 2002).
Table 4 Selected examples of definitions used and age groups included in surveys to report prevalence of obesity.
Definition
Age groups
Country of origin of the source
BMI>=25 (stated to define obese)
various combinations
various
BMI>=30
various combinations
various
BMI greater than or equal to 27.8 for males
and 27. 3 for females
20-70
Argentina
BMI greater than 27 for males and greater
than 25 for females
20+
Cook Islands; Kiribati
15
Raised blood pressure
Studies that measure
blood pressure are
preferred to those that
collect self-reported
raised blood pressure
status.
Blood pressure is a measure of the force that the circulating blood exerts on the walls of the
main arteries. The highest (systolic) pressure is created by the heart contracting and the lowest (diastolic) pressure is measured as the heart fills. Raised blood pressure is almost always
without symptoms but the result is structural damage to the arteries that supply blood to
the major organs of the body. This damage eventually results in stroke, ischaemic heart disease, renal failure and other diseases. It is becoming increasingly clear that the risk of these
conditions is not limited to those with particularly high levels of blood pressure, but also for
those with average or even below average levels of blood pressure (Law and Wald, 2002;
Eastern Stroke and Coronary Heart Disease Collaborative Group, 1998).
Studies that measure blood pressure are preferred to those that collect self-reported raised
blood pressure status. Still, many national health surveys lack the capacity to collect the
measured data for their large survey samples. In the SuRF report, country profile definitions include the status of the data as measured or self-reported. The most common designation for the prevalence of raised blood pressure is ‘systolic blood pressure greater than or
equal to 140 mm Hg and/or diastolic blood pressure greater than or equal to 90 mm Hg’.
Often those on anti-hypertension medication are also included in the definition (Table 5).
Some surveys prefer to use a higher definition for raised blood pressure and include only
those with ‘systolic blood pressure greater than or equal to 160 mm Hg and/or diastolic
blood pressure greater than or equal to 95 mm Hg. This definition may or may not include
those on anti-hypertension medication. It is clear that such a definition is inadequate for
surveillance purposes, especially for a population-based approach to preventing cardiovascular disease.
Recognizing the limitations of the above definitions, many surveys are also starting to report
measured mean systolic blood pressure as a preferred indicator of risk exposure. The country
profiles display age-specific mean systolic blood pressure data as well as prevalence of hypertension where they exist for a country. This is in line with WHO’s preference for a populationbased approach to risk factor exposure, moving away from a focus on “high risk” categories
of exposure (WHO, 2002).
Raised blood lipids
The blood lipid reported in most surveys is raised total blood cholesterol. Cholesterol is a
fat-like substance found in the blood stream, nerve fibres and major body organs. High levels of cholesterol are associated with heredity, diabetes mellitus and a diet high in saturated fats. Raised cholesterol is an important cause of artherosclerosis, the accumulation of
fatty deposits on the walls of the arteries. The result is an increased risk of stroke,
ischaemic heart disease and other vascular diseases. As with raised blood pressure, the
risks of cholesterol are continuous and extend across almost all levels seen in different
populations (Prospective Studies Collaboration, 1995). Ideally, for surveillance purposes,
mean levels of total cholesterol in specified age and sex groups are recommended.
From the SuRF report, it can be seen that surveys describe the prevalence of raised lipids
(cholesterol) using a variety of different definitions. The most common are total cholesterol:
– greater than or equal to 6.5 mmol/l;
– greater than or equal to 5.5 mmol/l; and
– greater than or equal to 5.2 mmol/l.
16
Often cholesterol levels are reported in units of mg/dl. In these cases, 240mg/dl corresponds to 6.5 mmol/l.
Table 5 Selected examples of definitions used and age groups included in surveys to report prevalence of raised
blood pressure.
Definition
Self-report
ever diagnosed
ever diagnosed by a medical practitioner
recent diagnosis of hypertension
on medication for hypertension
For surveillance
Measured blood pressure (mmHg)
systolic blood pressure > 140
purposes, mean levels
systolic blood pressure >= 140 and diastolic blood pressure >=90
of systolic blood
systolic blood pressure >= 140 and/or diastolic blood pressure >=90
pressure in specified
systolic blood pressure >= 140 or diastolic blood pressure >=90
age and sex groups are
systolic blood pressure >= 140 and/or diastolic blood pressure >=90
or being treated with anti-hypertension medication
recommended.
systolic blood pressure > 160
systolic blood pressure >= 160 and diastolic blood pressure >=95
systolic blood pressure >= 160 and/or diastolic blood pressure >=95
systolic blood pressure >= 160 or diastolic blood pressure >=95
systolic blood pressure >= 160 and/or diastolic blood pressure >=95
or being treated with anti-hypertension medication
systolic blood pressure >=160 and/or diastolic blood pressure >=100
As for the other risk factors, the SuRF report country profiles display the definitions, as
available, from the survey source. Mean total blood cholesterol by age group and sex is
sometimes reported by surveys. This is included in the country profiles, where available,
in accordance with WHO’s population-based approach to risk exposure and recognized in
the WHO STEPwise approach to Surveillance of NCD risk factors (WHO, 2002).
Diabetes
Diabetes is a group of disorders resulting from insulin deficiency, impaired effectiveness of
insulin action or both (IDF, 2000). Insulin impairment leads to high levels of glucose in
the blood as the body cannot break down this basic sugar. Diabetes mellitus is a serious
condition in itself, but is also a risk factor for other conditions including blindness, renal
failure, macro-vascular diseases, such as stroke, and ischaemic heart disease. There are
four different types of diabetes based on aetiology and clinical presentation. These are type
1 diabetes, type 2 diabetes, gestational diabetes and other specific types of diabetes. Data
on diabetes prevalence for the SuRF report focuses on type 2 diabetes, which is characterized by insulin resistance and relative insulin deficiency (IDF, 2000). The onset of this
form of diabetes usually occurs after the age of 40 and is often associated with obesity.
17
The SuRF report includes data on the prevalence of diabetes which is presented with welldefined detection methods and diagnostic criteria. Detection methods of choice are a fasting blood glucose measure and/or an oral glucose tolerance test (using a 75 gram glucose
load). The preferred diagnostic criteria are those of WHO from one of the following three
time periods, 1980, 1985 and 1999 (Table 6). Most good quality studies use the WHO criteria that correspond to the period in which the survey was performed.
The cut-off point for fasting blood glucose concentration has been lowered, meaning that
the number of people considered to be diabetic now is different than in the past, based on
this screening test. For the oral glucose tolerance test (OGTT), the diagnostic blood glucose
concentration has remained the same. The OGTT is the preferred measure of diabetes in
the population because it also detects impaired glucose tolerance and it provides a consistent measure of the prevalence of diabetes in populations over time. However, the OGTT
requires a level of resources which is beyond the capacity of most countries for
Surveillance purposes and is not recommended in the WHO STEPwise approach to
Surveillance of NCD risk factors.
Exact definitions, as reported by survey sources, have been provided in the country profile
definitions. Where WHO criteria are used as definitions, this is recorded with the designation “WHO, year”. Many national health surveys collect self-reported information on diabetes status by using a questionnaire that asks whether or not the participants have been
diagnosed with diabetes by a medical professional. While measured, population-level data
are more accurate, self-reported information does provide base line data where none would
otherwise be collected.
Table 6 Diagnostic values for the oral glucose tolerance test for diabetes mellitus: WHO definitions for 1980,
1985 and 1999 compared.
Diagnostic criteria
for diabetes mellitus
compared
Glucose concentration mmol/litre (mg/dl)
W H O L E
B L O O D
P L A S M A
venous
capillary
venous
capillary
1980
>=7.0
>=7.0
>=8.0
–
1985
>= 6.7 (>=120)
>= 6.7 (>=120)
>=7.8 (>=140)
>=7.8 (>=140)
1999
>=6.1 (>=110)
>=6.1 (>=110)
>=7.0 (>=126)
>=7.0 (>=126)
1980
>=10.0
>=11.0
>=11.0
–
1985
>=10.0 (>=180)
>=11.1 (>=200)
>=11.1 (>=200)
>=12.2 (>=200)
1999
>=10.0 (>=180)
>=11.1 (>=200)
>=11.1 (>=200)
>=12.2 (>=200)
Fasting value
OGTT: 2 hours post
glucose load of 75 grams
18
Data sources
Considerable time and effort has gone into deciding the type of information most useful for
surveillance of NCD risk factors. The collection is limited to data that is strictly relevant to
NCD outcomes; i.e. mortality and morbidity from NCDs. As previously mentioned, the risk
factors chosen are those that:
– make the greatest contribution to mortality and morbidity from chronic disease;
– can be changed through primary intervention; and
– can be measured easily in populations.
The NCD InfoBase includes all NCD risk factor data, regardless of sampling frame and representativeness, but allows users to select the survey and data that suit their purposes. The
SuRF report focuses on most recent, most representative surveys for WHO Member States.
Reporting data without
Reporting data without any information on source and survey methods limits its usefulness
for policy decisions or further research. Information about measurement methods, definitions, and age groups is needed to determine if data are comparable to that of other surveys (both within and between countries) or representative of their respective populations.
For these reasons, this report strives to present the data collection for each Member State
with:
– source population information;
– risk factor definitions;
– age group(s);
– sex; and
– some measure of the uncertainty of the estimate (i.e. confidence interval,
standard deviation).
source and survey
any information on
methods limits its
usefulness...
Often this information is missing when data is presented in journal articles. In these cases,
additional steps were taken to complete the information by following up with study authors
or those responsible for the study. These collaborators are acknowledged in the CD-ROM
attachment of this report and on the country profiles displaying the data that they provided.
Country-level sources
The availability of risk factor data varies from country to country. For the NCD InfoBase,
data have been obtained primarily from published sources. For some countries, available
data are restricted to small, ad hoc surveys published in academic journals. WHO Regions
that contain many developed countries have a wider variety of survey instruments available
to them. Examples of data sources for WHO regions are illustrated below.
European Region
Countries in the WHO European Region (EURO) have access to a number of health surveys
and data collection resources. In 1997, the European Commission established a Health
Monitoring Programme (HMP) which has now been superseded by a New Public Health
Programme sponsored by the European Parliament and Council. This programme will start
in January 2003 and run until 2006. The European Health Monitoring Project and the
European Health Interview Surveys are two current projects of the HMP. There are also a
variety of other instruments available that capture some NCD risk factor information including the Eurobarometer and the European Community household panel.
19
The Countrywide Integrated Noncommunicable Diseases Intervention Programme (CINDI)
also collects risk factor information related to evaluation of country programmes. The
CINDI surveys have been implemented in 27 European countries. In addition, many EUR
countries have national health surveys run by their own Ministries of Health. To date, EUR
risk factor data have not been harmonized for use in country comparisons.
Region of the Americas
The WHO Region for the Americas (AMR), in contrast to EUR, has many national health
survey instruments but no co-operating programmes to try to harmonize data collections.
However, the Conjuntos de Accionnes para la Reduccion Multifactorial de Enfermadades
No transmisibles (CARMEN) network seeks to adopt standard data collection for non-communicable disease risk factors.
Several long-term national efforts exist including the national health surveys from the
Instituto Nacional De Salud Publica of Mexico, National Health and Nutrition Examination
Surveys run by the Centers for Disease Control in the USA and the Canadian National
Population Health Survey from Statistics Canada. Other countries rely on academic
research studies to provide base-line data on NCD risk factors.
South-East Asia Region and Western Pacific Region
The South-East Asian Region (SEAR) and the Western Pacific Region (WPR) both contain
some countries that routinely collect NCD risk factor data with national survey instruments.
Other countries in these regions rely on research studies done by cardiovascular research
institutes/ foundations or universities. Both Regional Offices have set up networks to support surveillance and interventions to prevent NCDs and their risk factors. For the WPR,
the network is known as Mobilization of Allies in Noncommunicable Disease Action
(MOANA). For SEAR, the network name is still under consideration.
Eastern Mediterranean Region
The countries in the Eastern Mediterranean Region (EMR) have some NCD risk factor information collected by Ministries of Health. Other studies are specific to institutes and academic departments that focus on cardiovascular diseases (i.e. Tehran Lipid and Glucose
Study from Tehran, Iran and the Dar Al Fatwa Community Household Survey of Beirut,
Lebanon). The Eastern Mediterranean Approach to Non-Communicable Diseases network
(EMAN) is working towards standard collection of NCD risk factor data.
African Region
The African Region (AFR) has the least number of national health surveys that report NCD
risk factors with only a few examples of national collection efforts (South Africa, Tanzania,
Nigeria). Others have national-level surveys done by researchers from outside of the country
(Mauritius). Several national statistical agencies collect health-related information, mainly
on number of providers, maternal and child health status and reportable communicable
diseases. Preferential collection of such indicators reflect the health priorities of these
countries. However, as the World Health Report 2002 warns, rising levels of NCD morbidity
and mortality will occur in the near future in these countries, due to increasing levels of
tobacco use, raised blood pressure and raised cholesterol levels (WHO, 2002). The Africa
Noncommunicable Diseases Intervention network (NANDI) is working to spread the message
that NCD risk factors are a rising problem in the region.
20
Where countries have large, nationally representative surveys, the SuRF country profiles
display their weighted prevalence estimates along with the unweighted sample sizes used
in the survey. This display provides the level of information needed by policy makers to use
the data effectively. If the sampling frame is representative of the national population and
is without systematic bias, the weighted estimates are considered to be the best risk factor
prevalence estimates for that country.
Additional survey instruments
Data for a range of countries are provided by established networks, institutions or commercial companies that focus on collecting health information. One such data source is the
published collections of the WHO Multinational Monitoring of Trends and Determinants
in Cardiovascular Disease, otherwise known as the WHO MONICA project. The MONICA
Project’s objective was to measure the trends and determinants in cardiovascular disease
mortality and morbidity in selected, well-defined populations and to relate these trends to
changes in known risk factors, daily living habits, health care, or major socio-economic features measured at the same time in different countries (Tolonen et al., 2002). Standard
methods for collecting risk factor data were developed and used by the 32 individual collaborating centres that participated in the project (Tunstall-Pedoe, 1988). An emphasis
was placed on training interviewers to use the standard methodology (Tolonen et al.,
2002). Published data are available, mainly for developed countries, by 10 year age and
sex groups starting at age 25 and ending at age 64. The risk factors measured were tobacco use (smoking), (measured) blood pressure, (measured) blood cholesterol, and obesity
(measured height and weight).
Many of the problems
related to validity
of data can be solved
by agreeing to
standardized survey
instruments
Macro International Inc. provides survey and market research information to clients in business and government. They run demographic and health surveys for Ministries of Health in
many low and middle income countries. The surveys generally focus on the health of women
of child bearing age and children only and so have been of limited use for this report. Some
surveys collect data on tobacco use prevalence as well as measured height and weight (in
women of reproductive age). Where relevant, this data is included in the NCD InfoBase.
Gaps and deficiencies in data
Valid, reliable and comparable data are all needed for research and health monitoring. At the
population-level, there is more concern with measurement accuracy (validity) rather than
reliability (i.e. how good the measure is in relation to the “true” population measure). If
the measurement and sampling is without systematic bias and is of adequate size, there
should be an average estimate that approximates the true population estimate with a known
level of confidence. Appropriate health policy decisions can be made on the basis of this
known level of confidence for a prevalence estimate.
Many of the problems related to validity of data can be solved by agreeing to standardized
survey instruments, including standard age categories. Many European countries are now
moving towards a standard data collection format with the European Health Interview
Survey (EUROHIS; Vermeire et al., 2001).
However, valid data need not be comparable data. The major limitation of the data presented in SuRF Report 1 is that it is not comparable between surveys. This is unquestionably
true of survey data from different countries. Even within a country, when trend data are
available, the data may not be comparable. Part of the problem is the use of different survey instruments, different measurement methods and different criteria for a clinical outcome (i.e. diabetic or hypertensive). An additional problem occurs with risk factor variables
21
that change in a consistent way with age. For example, systolic blood pressure increases
with age in most populations (WHR, 2002). As a result, prevalence values for raised blood
pressure can be over or under-reported, depending on the survey start and end ages.
WHO’s response to addressing the gaps in risk factor data
The use of these survey
tools allows for surveillance in a large
number of countries
over a short period
of time. Using the
same definitions
and standard age
groups enhances
comparability.
22
The need for comparable data is being addressed by WHO with four main survey instruments for NCD risk factors. These are the STEPwise approach to NCD risk factor
Surveillance (STEPS), the Global Youth Tobacco Survey (GYTS), the Global School Health
Survey (GSHS), and the World Health Survey (WHS). The World Health Survey risk factor
module and the STEPS survey instrument share a common set of indicators at Step 1
(health behaviours) as well as standardized measurement methods for those indicators.
Valid data are produced by using validated and standard measurements methods, the best
possible sampling strategies and common training of field staff.
The use of these survey tools allows for surveillance in a larger number of countries over a
short period of time. Using the same definitions and standard age groups enhances comparability.
In summary, the NCD InfoBase collects sources and surveys of varying standards. It works
on the premise that all data provide some level of information, provided that the limitations
of the data are understood and taken into account. However, the “best risk factor” selection box in the NCD InfoBase tool has been used for the SuRF report to display preferentially the most recent data from those surveys that are nationally representative, with valid
sampling strategies and specified measurement criteria. Details on the NCD InfoBase tool
are presented in the next section.
The WHO Global NCD InfoBase
The WHO Global NCD InfoBase has, for the first time, assembled in one place, country
level risk factor data stratified by age and sex, with complete source and survey information. The current version of the InfoBase contains over 45,000 data points from more than
1,300 sources. The NCD InfoBase contains data for 166 out of 192 WHO Member States.
A unique feature is that each record can be linked back to all its survey information,
including the primary source. This is important when the collection of such data involves
so many different protocols and definitions.
Identifying country-level data and assessing its validity is the first step in developing better
quality NCD data collections. The second step is producing comparable country estimates
of risk factor prevalence from the country-level data held in the NCD InfoBase.
The NCD InfoBase will become a web-based tool for data users in late 2003. This brief
synopsis of InfoBase features is a preview to the on-line product that will be available to
users. It also describes the process that was involved for the InfoBase team to produce the
CD-ROM containing the data for this report.
Structure of the NCD InfoBase
The Global WHO NCD InfoBase is based on 3 main types of data collections.
These are:
– the source of the data;
– the information about survey methods; and
– the age/sex stratified data.
Figure 4
Example: Interviewer method
23
Figure 5
Risk factor data entry form
Source
The source table displays the complete source of the data by country, including the
authors, dates and place of publication. Each source is given a unique reference number
that remains with each piece of data collected from that source. Data cannot be entered
into the InfoBase without an accompanying source.
Survey methods
The second table in the data base is the survey methods table. It contains important epidemiological information about the data source. This information is entered into the survey
entry form (Figure 4) and shares the same unique reference identifier as the source information table. The survey entry form records information on:
– the representativeness of the sample (national or sub-national);
– the sampling frame;
– the publication status (peer-reviewed journal, official government report, etc.;
– the same information for surveys that include different population groups (ethnic, socioeconomic, education level or other demographic strata);
– a contact person for the survey;
– the name of the funding source;
– the response rates for the survey; and
– any additional notes on survey methodology and/or purpose.
Data cannot be entered into the InfoBase without having the above details entered in to
the survey entry form.
Data entry
The data entry table is third part of the InfoBase. Here, the data are entered for each sex
and age group (Figure 5). These data are also connected by the unique source identifier.
The data entry form collects:
– sample sizes;
24
– definitions (which also includes a text box for any unique data definitions);
– prevalence or mean values; and
– confidence intervals or standard deviations (for mean values).
The data entry table for diabetes mellitus includes collection of detection method and criteria
for determining an individual’s diabetes status.
Often small surveys report only limited prevalence data, perhaps for one very broad age group
(i.e. 18+ or 18–64), as publication space is limited or the aim of the study is more specialized than surveillance. Nevertheless, this information can still be useful in surveillance with
the identification and correction of biases, and caveats. Step 2 of the NCD InfoBase project
is to use existing country data to help develop models to harmonize the data and provide
comparable estimates in standard age groupings. These surveys, regardless of limitations, can
help in the harmonization process if they advance our understanding of how risk exposures
are distributed in populations. Alternatively, they may form the basis of future work on risk
factors or trigger acknowledgement of the need for risk factor surveillance in a population.
For these cases, authors and contact people were approached for more detailed age-breakdowns, where possible, for their surveys and they are included in the NCD InfoBase.
The key feature of the NCD InfoBase is that all metadata are available without the
researcher having to refer to the original source publication. This is important because individuals interested in the NCD risk factor data often lack access to necessary journals
and/or other data sources. Thus, the NCD InfoBase is designed to be a “one stop” resource
for these data needs.
Step 2 of the NCD
InfoBase project is to
use existing country
data to help develop
models to harmonize
the data and provide
comparable estimates
in standard age
groupings.
Figure 6
Identifying useful sources
25
Figure 7
Tobacco use
45
40
35
All metadata are avail-
Percent
30
25
20
15
able without the
10
researcher having to
5
refer to the original
0
1974
1979
1983
1985
source publication.
1990
1994
Survey years
1995
1997
1999
2000
male
female
Selecting data for display
In addition to source, survey and data entry forms, the NCD InfoBase has a provision for
selecting specific surveys/studies for display (Figure 6). This feature allows data browsers
to view relevant features of the surveys entered for a country and then select records to display and graph. Features of the survey on display include:
– title;
– start year;
– sub-population;
– urban/rural designation;
– interview response method; and
– sample method.
Data features displayed include risk factor name, data definition, sex, age groups and sample size. Information about whether or not the survey information and risk factor data have
been verified, provided by the “verified” check box, allow the user to have confidence in
the quality assurance practices for the displayed data. A survey’s results can be displayed
by checking the “best survey” box or by checking individual “best records” boxes. There
are also check boxes to display graphs of age-specific rates and/or trend data (where it
exists) for a specific survey (Figure 7).
Displaying data in the SuRF report format
Individual country reports can be generated using the SuRF report selection box (Figure 8).
This feature allows the selection of WHO region and country to generate automatic reports
from the data selected using the “best risk factor survey” box or the “best diabetes survey”
box. The reports generated are the same as those that have been set up for this SuRF report.
26
Figure 8
Generating reports
Example
Using the country profiles on CD-ROM
The CD-ROM contains all of the information included in the written section of this report
as well as risk factor profiles for WHO Member States. It also includes complete references
and an acknowledgement section for data contributors.
Figure 9 gives an example of the lay-out of a Member State risk factor profile as displayed
on the CD-ROM. For each Member State, the report displays official country name, WHO
region, UN population data, including average life expectancy with uncertainty estimates
and the most recent, representative country data available for the risk factors of interest.
Risk factor data are displayed with risk factor name and definition used in the survey at
the top and by:
– age group;
– sample size;
– prevalence estimate (or mean value); and
– 95% confidence interval (or standard deviation for mean values).
In some cases, the 95% confidence intervals are provided by survey authors for all agegroups. In other cases, they are only provided for the total age group for each sex. Survey
year, survey population and a reference for each source are provided at the bottom of each
risk factor data display. The addition of a “notes” section ensures that any additional
important information about a survey can be included. For some studies, where additional
information was provided by study authors, the reported data cannot be found in the cited
source. In these cases, the notation “additional data from personal communication”
27
appears below the source reference.
Sub-national surveys are included with complete information about the populations that
they represent. For national surveys, the weighted prevalence estimates are reported along
with the specified population used to create the weights (i.e. 2000 population census).
The actual sample sizes of the survey are also reported in these cases. The idea behind
this presentation of data is to ensure that data users have all the information that they
need to evaluate the validity of the prevalence values.
The CD-ROM contains
all of the information
included in the written
section of this report
as well as risk factor
profiles for WHO
Member States.
Future additions
It is becoming increasingly apparent that the risks of chronic conditions are cumulative
exposures over a life span. Often the exposure occurs in childhood and adolescence. These
exposures need to be documented using the STEPS framework and included in the NCD
InfoBase. The inclusion of a major risk factor in youth is well advanced with the Global
Youth Tobacco Survey (GYTS). The addition of other risk factors is being started with the
Global School-based Student Health Survey (GSHS), which uses the STEPwise approach to
Surveillance of NCDs as its framework.
While NCD risk factor information is needed to predict future trends in NCD burden, a
country-level source of chronic disease prevalence and incidence data is also needed.
Much of the data collected for diseases are not population-based, but come from hospital
records or registries. Nevertheless, work is currently under way to add the relevant indicators for:
– stroke;
– heart disease;
– oral health;
– injury; and
– respiratory diseases.
The addition of these disease domains will expose the need for population-based diseasespecific collections. Such information will serve as a resource for Member States as they
strive to produce their own estimates of country-level burden of disease from available
country-level data.
28
Figure 9
Tobacco use 1
Sex
2
Age Groups 3
n4
Prevalence 5
95% CI 6
Definition used: Smoker; cigarettes 7
Male
13 – 15
1000
34.4
Female
13 – 15
1200
34.9
Definition used: Uses some form of tobacco (includes multiple sources of tobacco)
Male
13 – 15
1000
35.8
Female
13 – 15
900
33.4
The use of country
data sources to derive
Survey year 8 : 2002
Survey Population 9 : National
the estimates is a
Source 10 : The Global Youth Survey Collaborative Group. Tobacco use among youth: a cross country comparison.
Tobacco Control, 2002, 11:252-270. Additional data from URL; http://www.cdc.gov/tobacco/global/index.htm.
transparent process
11
Notes :
because the data are
freely accessible in the
NCD InfoBase.
Mean Systolic Blood Pressure (mmHg)
n
Mean 5
± SD (95%CI) 6
Sex
Age Groups
Female
25 – 34
265
115.6
13.3
Female
35 – 44
357
121.3
16.1
Female
45 – 54
314
137.2
21
Female
55 – 64
275
147.8
21.4
Female
35 – 64
946
133.8
22.1
Survey year: 1992
Survey Population: National, both urban and rural populations
Source: Tolonen H, Kuulasmaa K, Ruokokoski. MONICA population survey data book. 2000, Available from;
URL:http://www.ktl.fi/publications/monica/surveydb/title.htm, URN:NBN:fi-fe20001206.
Notes:
How to read the tables
1. Risk factor name
2. Sex (male, female, both)
3. Age groups as provided by survey
4. Survey sample sizes by specified age group
5. Prevalence/Mean Values
6. 95%CI- if not published, calculated by InfoBase team assuming a binomial distribution or
standard deviation provided for mean value (or 95% CI displayed in parenthesis)
7. Exact definition of risk factor as presented in survey source
8. Year(s) in which survey was conducted
9. Details of population surveyed
10. Complete source reference, including any personal communication
11. Additional survey information that helps to interpret the data
29
Vision for the future
The WHO Global NCD InfoBase, and the SuRF report that comes from it, represent the first
steps in building better quality NCD risk factor data by displaying the country-level data
that currently exists. The next step is to use this data to develop estimates of national
prevalence for each risk factor and Member State. Member States with national health statistics reporting systems (that include risk factor information) have already produced these
estimates for their countries. For other countries with sub-national surveys, and sometimes
more than one survey, a data harmonization process can be used.
The NCD InfoBase
team is working with
data focal points in
the Regional Offices to
facilitate the development of regional NCD
InfoBases where they
are needed.
For the data harmonization process, the age-specific rates obtained from country-level data
sources will be used to develop models to relate risk factor levels to age and sex. These
models can then be used to derive the best estimate of risk factor prevalence for each
country in standard age groupings. The use of country data sources to derive the estimates
is a transparent process because the data are freely accessible in the NCD InfoBase. The
estimated prevalence values will also be held in the NCD InfoBase, thereby maintaining
the structure of the InfoBase as a “one-stop” source for all data users. This is a major
improvement over previous WHO estimates, which, in the absence of such a relational data
base, relied on studies selected by experts which may have excluded much of the available
data sources and which lacked transparency.
The NCD InfoBase can be adapted to meet the NCD data needs of those in the WHO
Regional Offices. In regions lacking an NCD data management tool, individual NCD
InfoBases that are compatible with the Global NCD InfoBase can be built. These InfoBases
will improve the capacity of WHO Regional Offices to inform policy and advocate for effective interventions to control the burden of NCDs in their regions. They will also improve the
functioning of the Global NCD InfoBase by helping to ensure that no regional NCD risk factor data are missing. The NCD InfoBase team is working with data focal points in the
Regional Offices to facilitate the development of regional NCD InfoBases where they are
needed.
The collection of NCD risk factor data is continuing in many countries and the InfoBase
will need to reflect this new work as it becomes available. In fact, for those countries that
have embarked on a STEPS survey, a method for direct transfer of aggregate, core risk factor data to the NCD InfoBase has been developed. The development of the NCD InfoBase
is meant to support the process of data collection and to hold the collection in a central
place. At the same time, the current collections need to be used to transform the data into
a useful, comparative tool for advocacy, policy and research.
In summary, the NCD InfoBase and the resulting SuRF report are continuing projects,
requiring on-going maintenance and input. The main difficulty with using existing data collections for advocacy, health policy or further research is that the data are not comparable,
either between countries or within countries from different time periods. Future work to
harmonize the current data to produce country-level estimates of risk factor prevalence will
provide the basis for comparisons of risk factor prevalence levels globally. The use of comparable estimates of risk factor prevalence will take advocacy for public health and disease
prevention directly to the policy makers, providing an impetus for early intervention to curb
the rising tide of preventable disease.
30
References
Bonita R, de Courten M, Dwyer T, Jamrozik K, Winkelmann R. Surveillance of risk factors for noncommunicable diseases: The WHO STEPwise approach. Summary. Geneva, World Health Organization, 2001.
Centers for Disease Control. Physical activity and health: a report of the Surgeon General. Atlanta (GA): US
Department of Health and Human Services, Centers for Disease Control and Prevention, 1996.
Eastern Stroke and Coronary Heart Disease Collaboration Group. Blood pressure, cholesterol and stroke in eastern
Asia. Lancet 1998, 352:1801-07.
International Diabetes Federation. Diabetes Atlas 2000. Brussels: International Diabetes Federation, 2000.
Law MR, Wald NJ. Risk factor thresholds: their existence under scrutiny. BMJ 2002, 324: 1570–6.
Ness AR, Powles JW. Fruit and vegetables and cardiovascular disease: a review. International Journal of
Epidemiology 1997, 26: 1–13.
Prospective Studies Collaboration. Cholesterol, diastolic blood pressure, and stroke: 13,000 strokes in 45,000 people in 45 prospective cohorts. Lancet. 1995, 346:1647–53.
Rehm J, Gutjahr E, Gmel G. Alcohol and all-cause mortality: a pooled analysis. Contemporary drug problems 2001,
28:337–61.
Rose G. The strategy of preventive medicine. Oxford: Oxford University Press, 1992.
Tolonen H, Kuulasmaa K, Ruokokoski E, for the WHO MONICA Project. MONICA population survey data book.
(October 2000). Available from URL:http://www.ktl.fi/publications/monica/surveydb/title.htm, URN:NBN:fife20001206.
Tunstall-Pedoe H for WHO MONICA Project Principal Investigators. The World Health Organization MONICA Project
(Monitoring Trends and Determinants in Cardiovascular Disease): a major international collaboration. Journal of
Clinical Epidemiology. 1988, 41: 105–14.
United Nations, Population Division. World Population Prospects- the 2002 revision. New York, 2003.
Vermeire C, Tafforeau J, Hupkens C et al. Database on Health Surveys in EU/EFTA/EEA Member States: Methodology
and content. Annual European Public Health, Association’s meeting, 2001.
Waters, A M. Assessment of self-reported height and weight and their use in the determination of body mass
index. Canberra: Australian Institute of Health and Welfare,1993.
World Cancer Research Fund and American Institute for Cancer Research. Food, nutrition and the prevention of
cancer: a global perspective. Washington (DC): American Institute for Cancer Research, 1997.
World Health Organization. Tobacco or health: a global status report. Geneva: World Health Organization,1997.
World Health Organization. Global Status Report on Alcohol. Geneva: World Health Organization, 1999.
World Health Organization. Obesity: preventing and managing the global epidemic. Geneva: World Health
Organization, 2000. WHO Technical Report Series, No. 894.
World Health Organization. The world health report 2002- Reducing risks, promoting healthy life. Geneva: World
Health Organization, 2002.
31
Appendices
Appendix 1: Acronyms and abbreviations
ACS
American Cancer Society
IDI
International Diabetes Institute
ADA
American Diabetes Association
INCLEN
AFRO
African Regional Office
International Clinical Epidemiology
Network
AIHW
Australian Institute of Health Welfare
kCal
Kilo-calories
BMI
body mass index
MET
metabolic equivalent
CAGE
questionnaire developed by Dr John Ewing
for detecting alcohol dependence
MOANA
Mobilization of allies in noncommunicable
disease action
CARMEN
Conjuntos de Accionnes para la
Reduccion Multifactorial de
Enfermadades No transmisibles
(Region of the Americas)
MOH
Ministry of Health
MONICA
WHO Multinational Monitoring of Trends
and Determinants in Cardiovascular
Disease project
CI
confidence interval
mg/dl
milligrams per deciliter
CINDI
Countrywide Integrated Noncommunicable
Diseases Intervention Programme
(European Region)
mmHg
millimetres of mercury
mmol/l
millimoles per liter
mM
milli-molar
NANDI
Africa Noncommunicable Diseases
Intervention
NCD
noncommunicable disease
NIDDM
non-insulin dependent diabetes mellitus
OECD
Organization for Economic Cooperation
and Development
OGTT
oral glucose tolerance test
CCS
Cross Cluster Surveillance
CDC
Centers for Disease Control and
Prevention (USA)
CHD
coronary heart disease
CVD
cardiovascular disease
DBP
diastolic blood pressure
DIS/DSM-III Diagnostic and statistical manual of
mental health disorders, third edition
(DSM-III)
American psychiatric Association
EBBA
Encuesta breve del bebedor anormal
EFRICARD Estudio factores de riesgo cardiovascular
en la Republica Dominicana
EMAN
32
Eastern Mediterranean Approach to NonCommunicable Diseases
EMRO
Eastern Mediterranean Regional Office
EURO
European Regional Office
EUROHIS
European Health Interview Survey
GSHS
Global School Health Survey
GYTS
Global Youth Tobacco Survey
HMP
Health Monitoring Programme
ICD
international classification of diseases
IDF
International Diabetes Federation
PAHO/AMRO Pan American Health
Organization/Regional Office of the
Americas
SBP
systolic blood pressure
SD
standard deviation
SE
standard error
SEARO
South-East Asian Regional Office
STEPS
Stepwise approach to Surveillance of NCD
risk factors
SuRF
surveillance of risk factors
TFI
Tobacco Free Initiative
WHO
World Health Organization
WHR
World Health Report
WHS
World Health Survey
WPRO
Western Pacific Regional Office
Appendix 2: Glossary
Age-specific rate: A rate for a specified age group. The numerator and denominator refer to the same age group.
Blood pressure: A measure of the force that circulating blood exerts on the walls of the arteries.
Body mass index (BMI): A measure of a person’s weight in relation to their height calculated as weight in kilograms divided by height in metres squared (synonym: Quetelet’s index).
Burden of disease: A systematic and comprehensive assessment of the health consequences of diseases and
injuries in a population using a single summary measure of population health for each cause.
Cholesterol: A fat-like substance found in the bloodstream, in various bodily organs and nerve fibres. Most cholesterol is made in the liver from a variety of foods but particularly from saturated fats. Cholesterol is a key component in the development of artherosclerosis, the accumulation of fatty deposits on the inner lining of the arteries, and as such is a determinant for increased risk of stroke and heart disease.
Confidence interval: The computed interval with a given probability, i.e., 95%, that the true value of a variable
such as a mean, proportion or rate is contained within the interval.
Diabetes mellitus: A group of heterogenous disorders with the common elements of hyperglycaemia and glucose
intolerance, resulting from insulin deficiency, impaired effectiveness of insulin action or both.
Diastolic blood pressure: The blood pressure created when the heart fills with blood.
Health behaviour: The combination of knowledge, practices, and attitudes that together contribute to motivate
the actions that we take regarding health. These behaviours may promote good health or if harmful, be a determinant of disease.
INCLEN: Acronym for International Clinical Epidemiology Network, consisting of clinical epidemiology units in
about 30 countries, mostly developing countries.
Intervention: Any health action, either promotive, preventive, curative or rehabilitative, where the primary intent
is to improve health.
Leisure-time physical activity: Sport and recreational physical activity, including a range of activities conducted
specifically for enjoyment, social, competitive or fitness purposes, and performed during leisure or discretionary
time.
Life Table: A summarizing technique used to describe the pattern of mortality and survival in populations.
Measurement validity: An expression of the degree to which a measurement measures what it purports to measure.
33
Obesity: A measure of how overweight an individual is defined using WHO criteria to be those individuals having
a BMI equal to or greater than 30.
Physical activity: Any bodily movement produced by skeletal muscles that results in energy expenditure.
Physical inactivity: No reported physical activity (in a health survey).
Prevalence: The number of events (disease or other condition), in a given population at a specific time.
Prevalence of risk: The proportion of a population who are exposed to a particular risk.
Prevention: Actions aimed at eradicating, eliminating or minimizing the impact of disease and disability.
Reliability: The degree of stability exhibited when a measurement is repeated under identical conditions.
Risk: A probability of an adverse outcome, or a factor that raises this probability.
Risk Factor: Any attribute, characteristic or exposure of an individual which increase the likelihood of developing
a disease or injury.
Sedentary: People who report no physical activity in the context of a health survey. This usually refers to people
who report no participation in activities such as walking, moderate or vigorous intensity activity.
Standard deviation: A measure of dispersion or variation. The mean tells where the values for a group are centred
and the standard deviation is a summary of how widely dispersed the values are around this center.
Standard error: The standard deviation of an estimate. It is used to calculate confidence intervals for the estimate.
Surveillance: Systematic, ongoing collection, collation, and analysis of data and the timely dissemination of
information to those who need to know so that action can be taken.
Survey: An investigation in which information is systematically collected not using experimental method but by
using a questionnaire or medical examination.
Systolic blood pressure: The blood pressure that is created by the heart contracting.
Weighted sample: A sample that is not strictly proportional to the distribution of classes in the total population.
A weighted sample has been adjusted to include larger proportions of some other parts of the total population,
because those parts accorded greater “weight” would otherwise not have the sufficient numbers in the sample
to lead to generalizable conclusions.
34
Appendix 3: Six tables for Regional Offices
Quick Reference Check List of Selected Risk Factor Data
African Region
WHO Member State
Tobacco
Algeria
Alcohol**
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
✓
✓
Angola
Benin
✓
Botswana
Burkina Faso
✓
Burundi
✓
Cameroon
✓
✓
✓
✓
✓
✓
Cape Verde
✓
Central African Republic
Chad
✓
Comoros
✓
Congo
Cote d’Ivoire
✓
Democratic Republic of the Congo
Equatorial Guinea
Eritrea
Ethiopia
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Gabon
Gambia
✓
Ghana
✓
Guinea
✓
✓
✓
✓
Guinea-Bissau
Kenya
Lesotho
Liberia
✓
✓
Madagascar
35
WHO Member State
Tobacco
Alcohol**
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
Malawi
✓
✓
Mali
✓
✓
Mauritania
✓
Mauritius
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Mozambique
Namibia
Niger
✓
Nigeria
✓
✓
✓
Rwanda
Sao Tome and Principe
✓
Senegal
✓
Seychelles
✓
✓
Sierra Leone
✓
✓
South Africa
✓
✓
✓
✓
✓
✓
✓
✓
Swaziland
Togo
✓
Uganda
United Republic of Tanzania ✓
Zambia
✓
Zimbabwe
✓
✓
✓
✓
Note:
As at 3 April 2003
Empty box correspond to missing (or no available data)
* Prevalence and/or mean value
** High Alcohol consumer and/or abstainer
36
✓
✓
✓
✓
✓
✓
Quick Reference Check List of Selected Risk Factor Data
Eastern Mediterranean Region
WHO Member State
Tobacco
Afghanistan
✓
Bahrain
✓
Cyprus
✓
Djibouti
✓
Egypt
Alcohol**
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Iran (Islamic Republic of) ✓
✓
✓
✓
✓
✓
✓
Iraq
Jordan
✓
Kuwait
✓
Lebanon
✓
Libyan Arab Jamahiriya
✓
Morocco
✓
Oman
✓
Pakistan
✓
Qatar
✓
Saudi Arabia
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Somalia
Sudan
✓
Syrian Arab Republic
✓
Tunisia
✓
United Arab Emirates
✓
Yemen
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Note:
As at 3 April 2003
Empty box correspond to missing (or no available data)
* Prevalence and/or mean value
** High Alcohol consumer and/or abstainer
37
Quick Reference Check List of Selected Risk Factor Data
European Region
WHO Member State
Tobacco
Albania
✓
Andorra
✓
Armenia
✓
Austria
✓
Azerbaijan
✓
Belarus
✓
Belgium
Alcohol**
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Bosnia and Herzegovina
✓
✓
✓
✓
Bulgaria
✓
✓
✓
✓
Croatia
✓
Czech Republic
✓
✓
Denmark
✓
✓
✓
Estonia
✓
✓
Finland
✓
France
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Georgia
✓
✓
✓
✓
✓
✓
Germany
✓
✓
✓
✓
✓
✓
✓
Greece
✓
✓
✓
✓
✓
✓
✓
Hungary
✓
✓
✓
✓
✓
✓
Iceland
✓
✓
✓
✓
✓
✓
Ireland
✓
✓
✓
✓
✓
Israel
✓
✓
✓
✓
✓
✓
✓
✓
Italy
✓
✓
✓
✓
✓
✓
✓
✓
✓
Kazakhstan
Kyrgyzstan
✓
Latvia
✓
✓
Lithuania
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Luxembourg
✓
Malta
38
✓
WHO Member State
Tobacco
Alcohol**
Netherlands
✓
✓
Norway
✓
✓
Poland
✓
✓
Portugal
✓
Republic of Moldova
✓
Romania
✓
Russian Federation
✓
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
Monaco
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
San Marino
Serbia and Montenegro
✓
Slovakia
✓
Slovenia
✓
Spain
✓
✓
✓
✓
✓
✓
✓
✓
Sweden
✓
✓
✓
✓
✓
✓
✓
✓
Switzerland
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Tajikistan
The former Yugoslav Republic of Macedonia
Turkey
✓
✓
✓
Turkmenistan
Ukraine
✓
United Kingdom
✓
✓
✓
Uzbekistan
✓
✓
✓
✓
✓
✓
✓
Note:
As at 3 April 2003
Empty box correspond to missing (or no available data)
* Prevalence and/or mean value
** High Alcohol consumer and/or abstainer
39
Quick Reference Check List of Selected Risk Factor Data
Region of the Americas
WHO Member State
Tobacco
Alcohol**
Antigua and Barbuda
✓
Argentina
✓
Bahamas
✓
Barbados
✓
✓
Bolivia
✓
✓
Brazil
✓
✓
Canada
✓
Chile
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Colombia
✓
✓
✓
✓
✓
✓
Costa Rica
✓
✓
✓
✓
✓
✓
✓
Cuba
✓
✓
✓
✓
✓
✓
✓
Dominica
✓
✓
Dominican Republic
✓
✓
✓
✓
✓
Ecuador
✓
El Salvador
✓
Grenada
✓
Guatemala
✓
✓
✓
Guyana
✓
Haiti
✓
Honduras
✓
Jamaica
✓
✓
Mexico
✓
✓
Nicaragua
✓
Panama
✓
✓
Paraguay
✓
✓
Peru
✓
✓
Belize
Saint Kitts and Nevis
40
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Saint Lucia
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Saint Vincent and the Grenadines
Suriname
✓
Trinidad and Tobago
✓
✓
United States
✓
✓
✓
✓
✓
✓
✓
✓
Uruguay
✓
✓
✓
✓
✓
✓
✓
✓
Venezuela
✓
✓
✓
✓
✓
✓
✓
Quick Reference Check List of Selected Risk Factor Data
South-East Asia Region
WHO Member State
Bangladesh
Tobacco
Alcohol**
✓
Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
✓
✓
✓
✓
✓
✓
Bhutan
Democratic People’s Republic of Korea
Democratic Republic of Timor-Leste†
India
✓
✓
✓
✓
✓
✓
✓
Indonesia
✓
✓
✓
✓
✓
✓
✓
✓
Maldives
Myanmar
✓
Nepal
✓
Sri Lanka
✓
Thailand
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Note:
As at 3 April 2003
Empty box correspond to missing (or no available data)
† Currently applying for membership with SEARO at the time of publication
* Prevalence and/or mean value
** High Alcohol consumer and/or abstainer
41
Quick Reference Check List of Selected Risk Factor Data
Western Pacific Region
WHO Member State
Australia
Tobacco
Alcohol**
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Diet Physical Inactivity Obesity* Blood Pressure* Cholesterol* Diabetes*
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Brunei Darussalam
Cambodia
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China
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Cook Islands
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Fiji
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Japan
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Kiribati
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Lao People’s Democratic Republic
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Malaysia
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Marshall Islands
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Micronesia, Federated States of
Mongolia
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Nauru
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New Zealand
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Niue
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Palau
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Papua New Guinea
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Philippines
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Republic of Korea
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Samoa
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Singapore
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Solomon Islands
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Tokelau
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Tonga
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Tuvalu
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Vanuatu
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Viet Nam
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The SuRF Report 1
The Surveillance of risk factors report (SuRF 1) brings together country-level noncommunicable disease (NCD) risk factor prevalence data from WHO's Member States for the first
time. The focus of the report is recent, nationally representative data. The focus is on eight
risk factors that relate mainly to cardiovascular disease. They are: tobacco and alcohol
use, patterns of physical inactivity, low fruit/vegetable intake, obesity (as measured by
BMI), blood pressure, cholesterol and diabetes (measured by blood glucose). All of this
information is held in the WHO Global NCD InfoBase, designed as a "one stop" resource
for data needs. The current version of the InfoBase contains data for 166 out of 192 WHO
Member States and over 45,000 data points from more than 1,300 sources.
The format of SuRF 1 consists of a report booklet and CD-ROM attachment. It is the first
step in a series of SuRF reports and presents current country data that are largely non
comparable. The second step will be to produce harmonized prevalence estimates from
the existing country data. SuRF 1 will be followed by an interactive website in 2003.
The InfoBase team is continuing to collect data from countries on these eight risk factors.
Contact us at [email protected] to contribute additional information.
World Health Organization
Noncommunicable Diseases and Mental Health
World Health Organization
20 Avenue Appia
CH-1211 Geneva 27, Switzerland
[email protected]
ISBN 92 4 158030 5