Error bars indicate 95% CIs. For prevalence, awareness, control, and treatment, there is a significant trend by education overall (P < .001). Younger and older describe age categories (<50 years and ≥50 years). A, P values were significant in men and women (P < .001), older and younger participants (P < .001), urban communities (P < .001), rural communities (P = .004), high-income communities (HICs, P < .001), upper–middle-income communities (UMICs, P < .001), lower–middle-income communities (LMICs, P = .048), and low-income communities (LICs, P < .001). There were significant interactions of sex × education (P < .001), age × education (P = .008), urban and rural location × education (P < .001), and economic status of countries × education (P < .001).
B, P values were significant in men (P < .001), older participants (P < .001), urban and rural communities (P < .001), LICs (P < .001), but not in other groups. There were significant interactions of sex × education (P < .001), urban and rural location × education (P = .001), and economic status of countries × education (P < .001).
C, P values were significant in men (P < .001), older participants (P < .001), urban and rural communities (P < .001), in LICs (P < .001), but not in other groups. There were significant interactions of sex × education (P < .001), age × education (P < .001), urban and rural location × education (P = .001), and economic status of countries × education (P < .001).
D, P values were significant in women and men (P < .001), older participants (P < .001), urban and rural communities (P < .001), HICs (P = .01), LICs (P < .001), but not in other groups. There were significant interactions of age × education (P < .001), urban and rural location × education (P = .005), and economic status of countries × education (P < .001).
Error bars indicate 95% CIs. ACE indicates angiotensin-converting enzyme; ARB, angiotensin II receptor blocker; HIC, high-income country; LIC, low-income country; LMIC, low–middle-income country; UMIC, upper–middle-income country.
eTable 1. Prevalence of Different Stages of Hypertension (Defined by Blood Pressure Measurements at Time of Survey Only) by Country Income, Gender, and Region
Table 1. Adjusted Mean BP and Prevalence of Hypertension (Adjusted for Age, Sex, Urban/Rural Location)
eTable 2. Prevalence of Hypertension by Age Group, Income Status, Sex, and Geographic Region (Unadjusted)
eTable 3. Prevalence of Different Stages of Hypertension Stratified by Education (Age, Gender, Location, and Education Adjusted as Relevant)
eTable 4. Use of 2 or More BP-Lowering Medications as a Percentage of Those With Hypertension and as a Percentage of Those on Treatments for Hypertension by Economic Status of Country
eTable 5. Use of 2 or More BP-Lowering Medications by Education (Age, Gender, Location, and Economic Status Adjusted as Relevant Among All Hypertensive Participants)
eTable 6. Prevalence of Hypertension, Awareness, Treatment, and Control in PURE—Absolute Numbers and Percentages (See Also Table 3 in Main Paper for Adjusted Proportions)
eTable 7. PURE Study—Location of Communities and Methodology of Household Sampling
eTable 9. Prevalence of Hypertension Stratified by Education (Age, Gender, Location, and Country Economic Status Adjusted as Relevant) (Figure 1A)
eTable 10. Awareness of Hypertension Stratified by Education (Age, Gender, Location, and Country Economic Status Adjusted As Relevant) (Figure 1B)
eTable 11. Treated Hypertension Stratified by Education (Age, Gender, Location, and Country Economic Status Adjusted as Relevant) (Figure 1C)
eTable 12. Controlled Hypertension Stratified by Education (Age, Gender, Location, and Country Economic Status Adjusted as Relevant) (Figure 1D)
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Chow CK, Teo KK, Rangarajan S, Islam S, Gupta R, Avezum A, Bahonar A, Chifamba J, Dagenais G, Diaz R, Kazmi K, Lanas F, Wei L, Lopez-Jaramillo P, Fanghong L, Ismail NH, Puoane T, Rosengren A, Szuba A, Temizhan A, Wielgosz A, Yusuf R, Yusufali A, McKee M, Liu L, Mony P, Yusuf S, . Prevalence, Awareness, Treatment, and Control of Hypertension in Rural and Urban Communities in High-, Middle-, and Low-Income Countries. JAMA. 2013;310(9):959–968. doi:10.1001/jama.2013.184182
Copyright 2013 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
Hypertension is the most important preventable cause of morbidity and mortality globally, yet there are relatively few data collected using standardized methods.
To examine hypertension prevalence, awareness, treatment, and control in participants at baseline in the Prospective Urban Rural Epidemiology (PURE) study.
Design, Setting, and Participants
A cross-sectional study of 153 996 adults (complete data for this analysis on 142 042) aged 35 to 70 years, recruited between January 2003 and December 2009. Participants were from 628 communities in 3 high-income countries (HIC), 10 upper–middle-income and low–middle-income countries (UMIC and LMIC), and 4 low-income countries (LIC).
Main Outcomes and Measures
Hypertension was defined as individuals with self-reported treated hypertension or with an average of 2 blood pressure measurements of at least 140/90 mm Hg using an automated digital device. Awareness was based on self-reports, treatment was based on the regular use of blood pressure–lowering medications, and control was defined as individuals with blood pressure lower than 140/90 mm Hg.
Among the 142 042 participants, 57 840 (40.8%; 95% CI, 40.5%-41.0%) had hypertension and 26 877 (46.5%; 95% CI, 46.1%-46.9%) were aware of the diagnosis. Of those who were aware of the diagnosis, the majority (23 510 [87.5%; 95% CI, 87.1%-87.9%] of those who were aware) were receiving pharmacological treatments, but only a minority of those receiving treatment were controlled (7634 [32.5%; 95% CI, 31.9%-33.1%]). Overall, 30.8%, 95% CI, 30.2%-31.4% of treated patients were taking 2 or more types of blood pressure–lowering medications. The percentages aware (49.0% [95% CI, 47.8%-50.3%] in HICs, 52.5% [95% CI, 51.8%-53.2%] in UMICs, 43.6% [95% CI, 42.9%-44.2%] in LMICs, and 40.8% [95% CI, 39.9%-41.8%] in LICs) and treated (46.7% [95% CI, 45.5%-47.9%] in HICs, 48.3%, [95% CI, 47.6%-49.1%] in UMICs, 36.9%, [95% CI, 36.3%-37.6%] in LMICs, and 31.7% [95% CI, 30.8%-32.6%] in LICs) were lower in LICs compared with all other countries for awareness (P <.001) and treatment (P <.001). Awareness, treatment, and control of hypertension were higher in urban communities compared with rural ones in LICs (urban vs rural, P <.001) and LMICs (urban vs rural, P <.001), but similar for other countries. Low education was associated with lower rates of awareness, treatment, and control in LICs, but not in other countries.
Conclusions and Relevance
Among a multinational study population, 46.5% of participants with hypertension were aware of the diagnosis, with blood pressure control among 32.5% of those being treated. These findings suggest substantial room for improvement in hypertension diagnosis and treatment.
High blood pressure is the leading cause of cardiovascular disease (CVD) and deaths globally. It is associated with at least 7.6 million deaths per year worldwide (13.5% of all deaths), making it the leading risk factor for CVD.1 The majority of CVD occurs in low-, low–middle-, and upper–middle-income countries (LIC, LMIC, and UMIC).1,2 The importance of blood pressure as a modifiable risk factor for CVD is well-recognized and many effective and inexpensive blood pressure–lowering treatments are available. Therefore, hypertension control and prevention of subsequent morbidity and mortality clearly should be achievable.
Information on hypertension prevalence, awareness, treatment, and control in multiple countries and different types of communities is necessary to provide a baseline for monitoring and also to inform the development of new strategies for improving hypertension control. A number of initiatives from the World Health Organization (WHO) have documented prevalence of hypertension and some have recorded treatment rates.3- 5 The largest systematic analysis of health surveys from 199 countries for individuals aged 25 years and older was conducted in 2008 and reported the prevalence and mean of hypertension.6 However, most studies were limited to few countries and were conducted at least 2 decades ago, few reported awareness, and none reported on variations between urban vs rural settings, economic status and other variables, rates of blood pressure control, or the types of treatments used. Such information is key to developing strategies for better detection and control of hypertension globally.
The overall Prospective Urban Rural Epidemiology (PURE) study is a prospective, standardized collaborative study7,8 in which we report a cross-sectional analysis of baseline data to assess the prevalence, awareness, treatment, and control of hypertension by the economic status of countries and by sex, age group, location (urban vs rural), and education of the participants.
The PURE study was approved by the ethics committees in all participating centers. All participants provided consent (either written or a thumbprint if unable to read). The PURE study involves urban and rural communities within 17 countries including 3 high-income countries (HICs): Canada, Sweden, United Arab Emirates; (7 UMICs) Argentina, Brazil, Chile, Poland, Turkey, Malaysia, South Africa; (3 LMICs) China, Colombia, Iran; and (4 LICs) Bangladesh, India, Pakistan, Zimbabwe (eTable 8 in Supplement). Categorization of economic level of a country was based on information from the World Bank in 2006.9 The overall aim of PURE was to examine the relationship of societal influences on lifestyle behaviors, cardiovascular risk factors, and incidence and mortality of chronic diseases. The methods of the PURE study have been described previously.10,11 Briefly, countries and communities were chosen purposively to participate in PURE. For practical reasons, our goal was not to select strict proportionate sampling, but instead to show economic and sociocultural diversity and inclusion of sites in which investigators were committed to collecting high-quality data at a modest budget and to following up participants for at least 10 years. Within communities, the sampling framework used aimed to recruit an unbiased sample of households.10 Inclusion of a broad sample of several countries of low- and middle-income status, countries in which data on chronic disease are relatively sparse, was a key goal. Within each country, an urban and rural stratified sample of communities was selected with the aim to include a diverse range of communities (eTable 8 in Supplement). In the analysis by region, South Asia includes cohorts from Bangladesh, India, and Pakistan; Africa includes South Africa and Zimbabwe; North America and the European Union includes Canada, Sweden, and Poland; the Middle East includes Iran, Turkey, and the United Arab Emirates; South America includes Argentina, Brazil, Chile, and Colombia; while China and Malaysia included cohorts from their respective countries only.
Households were eligible if 1 or more members of the household was aged between 35 and 70 years and the household members intended to stay at that address for a further 4 years. Medical history and risk factors were recorded and a basic physical examination was conducted on participants between the ages of 35 and 70 years who provided written informed consent.10,11
CVD risk factor history, including smoking, history of hypertension, diabetes, psychosocial factors, alcohol consumption, and physical measures were recorded as described in the INTERHEART study,12 as were sociodemographic characteristics including date of birth. With participants for whom date of birth was unknown, self-reported age was recorded in years. Younger age was defined as less than 50 years, and older was defined as aged 50 years or older. In these analyses, prevalent diabetes and CVD are defined on the basis of self-reported medical diagnoses, which have demonstrated substantial and moderate agreement,13 respectively with data from disease registers in a large Finnish study (κ, 0.58 and 0.75).14 We also verified, during a central adjudication process, medical or hospital records in a sample of 455 events during follow-up with agreement rates of 89%.11 Education was categorized as high (trade school, college or university); medium (secondary school or high school), low (primary education or no education), or unknown.
Sitting blood pressure was measured by trained research assistants at all centers following a standardized procedure using an Omron digital blood pressure measuring device (Omron HEM-757) provided for all sites. The mean of 2 measures was used for all analyses. The main hypertension definition used in this article was individuals who reported having hypertension and receiving blood pressure-lowering treatment or had an average systolic blood pressure (SBP) of at least 140 mm Hg, an average diastolic blood pressure (DBP) of at least 90 mm Hg (categorized as stage 1), or both an SBP and DBP that exceeded the previously shown levels. We also used a similar definition similar to categorize stage 2 participants but included individuals with SBP of at least 160 mm Hg, DBP of at least 100 mm Hg (or both, as previously shown). Categorizing stage 1 vs stage 2 was done to demonstrate the distribution of definite hypertension. All participants were asked whether they had a medical diagnosis of hypertension (awareness), whether they were receiving blood pressure-lowering medications (treatment), and a list of all their medications were recorded. Control was the proportion of participants with hypertension who had an average systolic and diastolic blood pressure of less than 140/90 mm Hg.
Results are presented as the numbers (and corresponding percentages) for categorical variables and mean (SD) for continuous variables. To enable comparison with other global estimates of hypertension, we conducted age and sex direct standardization15 using the WHO world population.16 To enable comparison between subgroups and to control for clustering, results were adjusted using a generalized linear mixed-effect model. Specifically, we used the GLIMMIX procedure in SAS assuming community as a random effect and other factors such as age, sex, location, education and income status of the country as fixed effects in the model. For binary outcomes, we used the binomial distribution option with the logit link function.
Interaction between variables was also tested by including an appropriate term in the model. When interactions were found to be significant, strata-specific models were used for adjusted rates. Means were compared using t tests or medians and/or proportion compared with appropriate nonparametric tests. To ensure that all tests took into account the effect of clustering, different groups were compared based on the P values obtained from the mixed-effect model and the linear test of trend was performed using model coefficients from mixed models and an appropriate contrast statement. A P value of less than .01 was considered to be statistically significant with a 2-sided alternative. All statistical analyses were calculated using SAS software version 9.2 (SAS Institute Inc) and all figures were drawn using S-PLUS software version 6.2 (TIBCO Software Inc).
The PURE study enumerated 382 341 individuals from 107 599 households in 628 communities (348 urban and 280 rural) in 17 countries on 5 continents. Recruitment started in Karnataka, India in January 2003; however, most communities were recruited between January 2005, and December 2009. Among the enumerated individuals, 197 332 (52%) were between 35 and 70 years of age and 153 996 (78%) of these adults consented to participate in both the interview and physical examination. Response rates were calculated as the numbers enrolled or recruited participants divided by the eligible number of individuals in all of the households approached for the study. Rates of response were similar in HIC (84%), UMIC (87%), and LMIC (82%), but lower in LIC (55%). The average age of participants and the percent with primary or less education were similar, but the percentage of women was higher among those enrolled compared with those who were eligible. This pattern was similar in HIC, UMIC, LMIC, and LIC. At the analysis stage, we excluded individuals who were outside the age criteria, leaving 151 966 participants. Those with incomplete systolic and diastolic blood pressure measures were also excluded, leaving 142 042 to constitute the population used in this report.17
Table 1 summarizes the characteristics of the cohort and the prevalence of hypertension according to different definitions. Overall, 57 840 of the participants enrolled in PURE had hypertension (40.8%; 95% CI, 40.5-41.0) and the mean blood pressure was 131/82 mm Hg. The age and sex prevalence standardized to the WHO world population was 27.7%. The distribution, based on different definitions, is detailed online (eTables 1-4 in Supplement).
Among participants with hypertension, 26 877 were aware of their condition (46.5%; 95% CI, 46.1%-46.9%), 23 510 were receiving treatment (40.6%; 95% CI, 40.2%-41.0% [87.5%; 95% CI, 87.1%-87.9% of those who were aware]), and 7634 had their blood pressure controlled (13.2%; 95% CI, 12.9%-13.5% [32.5%; 95% CI, 31.9%-33.1% of those receiving medical treatment]). Awareness, treatment, and control of hypertension were lowest in LICs, particularly in Africa (Table 2).
Awareness and treatment rates of hypertension were similar in urban and rural communities of HICs and UMICs, but were significantly lower in rural areas vs urban areas in LICs (awareness in urban LICs, 48.4% [95% CI, 41.0%-55.8%] vs awareness in rural LICs, 31.2% [95% CI, 25.2%-38.0%]; and treatment in urban LICs, 36.1% [95% CI, 29.0%-43.9%] vs treatment in rural LICs, 19.9% [95% CI, 15.2%-25.7%]). The proportion of participants with controlled blood pressure was consistently lower in rural areas vs urban areas in all countries (Table 3).
Participants aged 50 years and older consistently had greater awareness of their hypertension compared with younger participants and had higher rates of treatment and control when compared with younger participants. Women consistently had greater awareness of their hypertension and higher rates of treatment and control than men (Table 3).
In models mutually adjusted by age, sex, and urban/rural setting, greater education was associated with greater awareness and treatment in men but not women, and greater control in both men and women (Figure 1). Greater education was associated with greater awareness and treatment in LICs only and greater rates of control in HICs and LICs. Greater education was associated with greater awareness, treatment, and control in older, but not younger participants (eTables 9, 10, 11, and 12 in Supplement).
Overall, angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) were the most commonly used blood pressure–lowering agents (13.6%; 95% CI, 13.3%-13.9%) with a similar proportion of participants with hypertension (self-reported on treatment or BP ≥140/90 mm Hg) using other blood pressure–lowering agents (β-blockers, 8.2% [95% CI, 8.0%-8.4%]; diuretics, 7.0% [95% CI, 6.8%-7.2%]; and calcium antagonists, 8.2% [95% CI, 8.0%-8.4%]). However this pattern varied across countries. Medications most commonly used in HICs and UMICs were ACE inhibitors and ARBs, diuretics and calcium channel blockers in LMICs, and β-blockers in LICs (Figure 2).
Among the 23 510 participants who self-reported receiving treatment for hypertension, 7273 reported 2 or more types of blood pressure-lowering medications on their medication lists (30.8% [95% CI, 30.2%-31.4%] or 12.5% of all with hypertension [95% CI, 12.2%-12.8%]). The use of 2 or more medications was significantly lower in LICs compared with HICs, UMICs, or LMICs (combined P = <.001; in HICs, 18.1% [95% CI, 17.2%-19.1%]; in UMICs, 14.5% [95% CI, 14.0%-15.1%]; in LMICs, 14.1% [95% CI, 13.7%-14.6%]; and in LICs, only 1.6% [95% CI, 1.4%-1.8%]; eTable 5 in Supplement).
The use of 2 or more medications among hypertensive patients was slightly higher in women compared with men (8.1% [95% CI, 6.3%-10.4%] and 6.9% [95% CI, 5.3%-9.0%], respectively; P <.001 for comparison), older compared with younger participants (9.5% [95% CI, 7.4%-12.2%] and 4.5% [95% CI, 3.5%-5.9%], respectively; P <.001 for comparison) and urban vs rural areas (8.0% [95% CI, 6.2%-10.3%] and 7.4% [95% CI, 5.7%-9.5%], respectively; P = .005 for comparison). The use of 2 or more medications also was greater with increased education (eTable 6 in Supplement).
This study found a large gap between both detection and control of hypertension across all countries studied. It shows that while initial therapy was started in the large majority of individuals who are detected to have hypertension, control in participants receiving treatment was very poor. The use of combination therapies, generally required to achieve blood pressure control,18 was low. Awareness, treatment, and control were lower in LICs compared with other countries and in rural settings of LMICs and LICs compared with urban ones. Despite men having higher rates of hypertension, women consistently had higher awareness, treatment, and control of their hypertension, consistent with a large body of research on sex and health-seeking behavior.19 Also participants with more education had greater awareness, treatment, and control, particularly in LICs.
The rates of hypertension prevalence, awareness, treatment, and control found in this study are generally consistent with findings in those countries with existing data.6,20 For example, rates of treatment among individuals aware of their hypertension in a 2008/2009 survey in Canada was 82%, which was similar to that from the Canadian cohort in PURE.21 In the China National Nutrition and Health Survey of 2002, awareness of hypertension was lower (28%) but the proportion of those aware on treatment (78%) was similar.22 In a study in India from 2004-2007, a survey of 4608 rural and urban women found 42.8% aware of hypertension, which was similar to PURE, but reported lower rates of treatment (38.6% of those aware).23 The apparently higher prevalence of hypertension measured in this study (40.7%) compared with estimates from the Global Burden of Disease study24 in 2000 of 26.4% (95% CI, 26.0%-26.8%) for 20- to 80-year olds is due to the older age of the participants in PURE (>35 years). When we age-standardized to the WHO world population,15 the overall prevalence of hypertension in the PURE study was 27.7%, which is similar to the Global Burden of Disease estimates24 and to the results of a recent systematic analysis of health surveys from 199 countries for individuals aged 25 years and older in 2008 (SBP ≥140 mm Hg or DBP ≥ 90 mm Hg) of 29% (95% CI, 27%-31%) in men and 25% (95% CI, 23%-27%) in women.6 This suggests that there is unlikely to have been major biases in the selection of communities and individuals in the countries included in this study and therefore, our data can be considered to be reasonably reflective of the prevalence in the urban and rural areas of these diverse countries.
The widespread lack of hypertension awareness (a measure of hypertension case identification) and poor control (a measure of inadequate treatment) in all countries studied, despite the identification and control of blood pressure being prioritized by many national and global organizations and despite the availability of inexpensive and effective medications, is concerning.25,26 The low rates of detection may be because few individuals have their blood pressure checked either through routine health assessment or screening programs and may be due to difficulties or costs in accessing health care.
The lowest rates of use of blood pressure–lowering medications were observed in LICs. Although low-cost generic blood pressure–lowering medications are available in LICs, possible barriers to use of medications are still affordability (as a proportion of local income), lack of drug inventory, distance to clinics, and the costs to see physicians. Hence, models of care that shift the detection and initial treatment of hypertension to nonphysician health workers should be considered.27- 29 Effectiveness of these models of care have been demonstrated in management of other conditions such as HIV in developing countries.30- 32 However, even among individuals who have received treatment, there is poor blood pressure control. This suggests ineffectiveness in our current treatment approach, which is largely based on the use of single drugs. Instead, strategies such as using combination therapy for the initial treatment of hypertension may be required.28
In LICs, awareness, treatment, and control were lower in participants with primary or no education, most likely reflecting a combination of low socioeconomic status, which may influence access to care, lack of knowledge of the sequelae of uncontrolled hypertension, and differing values with respect to the importance of the future.33,34 Education was used as a surrogate for socioeconomic status in this analysis and although this is limited, similar social patterning of hypertension prevalence has been recently reported in some LICs.35
To our knowledge, this is currently the largest multicountry study in which blood pressure was measured using standardized methods across all study centers. It involves a large number of low- and middle-income countries, involves both urban and rural communities, and participants were identified from communities and not from clinics or hospitals. It also recorded data on the number and types of drugs used, which is generally not collected to this detail in other surveys of hypertension.
This study’s major limitation is that the sampling framework in each country was not nationally representative, and therefore caution is needed in extrapolating the information as being representative of the status in each country. Nevertheless, our overall prevalence of hypertension is similar to the global prevalence estimates24 after adjusting for age, and therefore suggests no major biases due to the nonrandom selection of communities or countries included in PURE. Although a random selection of countries from each part of the world that included different economic levels and identification of a random set of communities within them would be ideal from a methodological perspective, such an approach is not practical given the existing poor research infrastructure in many parts of the world. The response rate was lower in LICs, but the characteristics of enrolled to eligible participants were similar in HICs, UMICs, LMICs, and LICs. Diagnosis of hypertension was based on measures and history taken at a single visit; however, multiple visits are impractical for large-scale studies and our approach is similar to that of many epidemiological studies.
In this cross-sectional analysis of a multinational study population, 46.5% of participants with hypertension were aware of the diagnosis, while blood pressure was controlled among 32.5% of those being treated. These findings suggest that substantial improvement in hypertension diagnosis and treatment is needed.
Corresponding Author: Dr Salim Yusuf, PURE Project Office, Population Health Research Institute, Hamilton General Hospital, 237 Barton St East, Hamilton, ON, Canada, L8L 2X2 (firstname.lastname@example.org).
Author Contributions: Mr Islam had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Teo, Yusuf, Chow.
Acquisition of data: Teo, Rangarajan, Gupta, Avezum, Bahonar, Chifamba, Dagenais, Diaz, Kazmi, Lanas, Li, Lopez-Jaramillo, Lu, Noorhassim, Puoane, Rosengren, Szuba, Temizhan, Wielgosz, Yusuf, Yusufali, Liu, Mony, Yusuf, Chow.
Analysis and interpretation of data: Teo, Islam, Gupta, Diaz, Li, Puoane, Rosengren, Temizhan, McKee, Mony, Yusuf, Chow.
Drafting of the manuscript: Teo, Rangarajan, Islam, Yusuf, Chow.
Critical revision of the manuscript for important intellectual content: Teo, Islam, Rangarajan, Gupta, Avezum, Bahonar, Chifamba, Dagenais, Diaz, Kazmi, Lanas, Li, Lopez-Jaramillo, Lu, Noorhassim, Puoane, Rosengren, Szuba, Temizhan, Wielgosz, Yusuf, Yusufali, McKee, Liu, Mony, Chow.
Statistical analysis: Islam, Yusuf, Chow.
Obtained funding: Avezum, Lanas, Puoane, Rosengren, Yusufali, Mony, Yusuf, Chow.
Administrative, technical, or material support: Teo, Rangarajan, Gupta, Chifamba, Dagenais, Diaz, Kazmi, Li, Lu, Puoane, Rosengren, Szuba, Temizhan, Wielgosz, Yusuf, Mony, Yusuf.
Study supervision: Teo, Rangarajan, Gupta, Avezum, Bahonar, Li, Noorhassim, Puoane, Szuba, Temizhan, Wielgosz, McKee, Liu, Mony, Yusuf.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Chow reports support from a fellowship cofunded by the National Health and Medical Research Council/National Heart Foundation of Australia and the Sydney Medical Foundation; grants or pending grants to her institution from AstraZeneca, Roche, and Abbot; and payment for lectures including service on speakers bureaus from AstraZeneca. Dr Gupta reports receipt of support for travel to meetings for the study or other purposes from the Population Health Research Institute (PHRI), McMaster University. Mr Bahonar reports receipt of funds to his institution from PHRI, McMaster University for study costs. Dr Dagenais reports receipt of consultancy fees and travel/accommodations/meeting expenses from Sanofi. Dr Lanas reports receipt of a grant to his institution from the Universidad de la Frontera and support for travel to meetings for the study or other purposes from PHRI, McMaster University. Dr Lopez-Jaramillo reports support for travel to meetings for the study or other purposes from PHRI, McMaster University and payment for lectures including service on speakers bureaus from Merck, Boehringer Ingelheim, Novartis, and AstraZeneca. Mr Ismail reports support for travel to meetings for the study or other purposes from PHRI, McMaster University. Dr Yusuf reports receiving grants for research from several companies who manufacture antihypertensive drugs including all the multinational pharmaceutical sponsors of PURE and payment for lectures, consulting, and related travel expenses from these companies. No other disclosures were reported.
Funding/Support: The PURE study is an investigator-initiated study that is funded through a variety of sources including the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, grants from several pharmaceutical companies, and grants from various governmental bodies in different countries. Dr S Yusuf is supported by the Mary W Burke endowed chair of the Heart and Stroke Foundation of Ontario. The PURE study is an investigator-initiated study that is funded by the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario and through unrestricted grants from several pharmaceutical companies (with major contributions from AstraZeneca [Sweden and Canada], Novartis, Sanofi [France and Canada], Boehringer Ingelheim [Germany and Canada], Servier, King Pharma, GlaxoSmithKline), and additionally by various national bodies in different countries: Bangladesh: Independent University, Bangladesh, Mitra and Associates; Brazil: Unilever Health Institute, Brazil Canada: Public Health Agency of Canada and Champlain Cardiovascular Disease Prevention Network; Chile: Universidad de la Frontera; China: National Center for Cardiovascular Diseases; Colombia: Colciencias, Grant number:6566-04-18062; India: Indian Council of Medical Research; Malaysia: Ministry of Science, Technology and Innovation of Malaysia:Grant Number 07-05-IFN-MEB010, Universiti Teknologi MARA, Universiti Kebangsaan Malaysia (UKM-Hejim-Komuniti-15-2010); Poland: Polish Ministry of Science and Higher Education grant Nr 290/W-PURE/2008/0, Wroclaw Medical University; South Africa: The North-West University, SANPAD (SA and Netherlands Programme for Alternative Development), National Research Foundation, Medical Research Council of SA, The SA Sugar Association (SASA), Faculty of Community and Health Sciences (UWC); Sweden: Swedish Council for Working Life and Social Research, Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning, Swedish Heart and Lung Foundation, Swedish Research Council, Grant from the Swedish State under LUA Agreement, Grant from the Västra Götaland Region (FOUU); Turkey: Metabolic Syndrome Society, AstraZeneca, Turkey, Sanofi, Turkey; United Arab Emirates: Sheikh Hamdan Bin Rashid Al Maktoum Award For Medical Sciences, Dubai Health Authority, Dubai UAE.
Role of Sponsor: The funders and sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; in the preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication.
PURE Project Office Staff, National Coordinators, Investigators, and Key Staff: Dr Chow reports having worked as senior research fellow and project officer for the PURE study 2007-2009, wrote the analysis plans and had the primary responsibility for writing this paper. Dr S. Yusuf is the principal investigator of the PURE study and conceived, initiated, and supervised its conduct and data analyses. Dr Teo is the coprincipal investigator of the PURE study. Dr McKee contributed to the interpretation of the data and to drafts of the manuscript. All other authors coordinated the PURE study in their respective countries and provided comments on drafts of the manuscript. Project office staff (Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada): Coordination and Data Management: S. Rangarajan (Project Manager); K.K. Teo, C.K. Chow; S. Islam (Statistician), M. Zhang (Statistician), C. Kabali (Statistician), M. Dehghan (Nutritionist), J. Xiong, A. Mente, J. DeJesus, P. Mackie, M. Madhavan, D. Corsi, L. Farago, J. Michael, I. Kay, S Zafar, D. Williams, R. Solano, N. Solano, M. Farago, J. Rimac, S. Trottier, W. ElSheikh, M. Mustaha, J. Kaszyca, R. Hrnic, S. Yusuf (Principal Investigator). Core Laboratories: M. McQueen, K. Hall, J. Keys (Hamilton), X. Wang (Beijing, China), J. Keneth (Bangalore, India). Argentina: R. Diaz*, A. Orlandini, C. Bahit, B. Linetsky, S. Toscanelli, G. Casaccia, J.M. Maini Cuneo. Bangladesh: O. Rahman*, R. Yusuf, A.K. Azad, K.A. Rabbani, H.M. Cherry, A. Mannan, I. Hassan, A.T. Talukdar, R.B. Tooheen, M.U. Khan. Brazil: A. Avezum*, G.B. Oliveira, C.S. Marcilio, A.C. Mattos. Canada: K. Teo*, S. Yusuf*, J. Dejesus, S. Zafar, D. Williams, J. Rimac, G. Dagenais, P. Poirier, G. Turbide, D. Auger, A. LeBlanc De Bluts, M.C. Proulx, M. Cayer, N. Bonneville, S. Lear, A. Chockalingam, D. Gasevic, S. Gyawali, S. Hage-Moussa, G. Mah, M. MacLeod, I. Vukmirovich, A. Wielgosz, G. Fodor, A. Pipe, S. Papadakis I. Moroz, S. Muthuri. Chile: F. Lanas*, P. Seron, S. Martinez. China: Liu Lisheng*, Li Wei*, Chen Chunming, Wang Xingyu, Zhao Wenhua, Bo Jian, Chang Xiaohong, Chen Tao, Chen Hui, Cheng Xiaoru, Deng Qing, He Xinye, Hu Bo, Jia Xuan, Li Jian, Li Juan, Liu Xu, Ren Bing, Sun Yi, Wang Wei, Wang Yang, Yang Jun, Zhai Yi, Zhang Hongye, Zhao Xiuwen, Zhu Manlu, Lu Fanghong, Wu Jianfang, Li Yindong, Hou Yan, Zhang Liangqing, Guo Baoxia, Liao Xiaoyang, Zhang Shiying, Bian Rongwen, Tian Xiuzhen, Li Dong, Chen Di, Wu Jianguo, Xiao Yize, Liu Tianlu, Zhang Peng, Dong Changlin, Li Ning, Ma Xiaolan,Yang Yuqing, Lei Rensheng, Fu Minfan, He Jing, Liu Yu, Xing Xiaojie, Zhou Qiang. Colombia: P. Lopez-Jaramillo*, R. Garcia, J.F. Arguello, R. Dueñas, S. Silva, L.P. Pradilla, F. Ramirez, D.I. Molina, C. Cure-Cure, M. Perez, E. Hernandez, E. Arcos, S. Fernandez, C. Narvaez, J. Paez, A. Sotomayor, H. Garcia, G. Sanchez, T. David, D. Gómez-Arbeláez, A. Rico. India: M. Vaz*, A.V. Bharathi, S. Swaminathan, P. Mony, K. Shankar A.V. Kurpad, K.G. Jayachitra, N. Kumar, HAL Hospital, V. Mohan, M. Deepa, K. Parthiban, M. Anitha, S. Hemavathy, T. Rahulashankiruthiyayan, D. Anitha, K. Sridevi, R. Gupta, R.B. Panwar, I. Mohan, P. Rastogi, S. Rastogi, R. Bhargava, R. Kumar, J.S. Thakur, B. Patro, R. Mahajan, P. Chaudary, V. Raman Kutty, K. Vijayakumar, K. Ajayan, G. Rajasree, A.R. Renjini, A. Deepu, B. Sandhya, S. Asha, H.S. Soumya. Iran: R. Kelishadi*, A. Bahonar, N. Mohammadifard, H. Heidari. Malaysia: K. Yusoff*, H.M. Nawawi, T.S. Ismail, A.S. Ramli, R. Razali, NAMN Khan, N.M. Nasir, R. Ahmad, T. Winn, F.A. Majid, I. Noorhassim, M.J. Hasni, M.T. Azmi, M.I. Zaleha, K.Y. Hazdi, A.R. Rizam, W. Sazman, A. Azman. Pakistan: R. Iqbal*, M. Shahid, R. Khawaja, K. Kazmi. Poland: W. Zatonski*, R. Andrzejak, A. Szuba, K. Zatonska, R. Ilow, M. Ferus, B. Regulska-Ilow, D. Różańska, M. Wolynie. SouthAfrica: A. Kruger*, H.H. Voster, A.E. Schutte, E. Wentzel-Viljoen, F.C. Eloff, H. de Ridder, H. Moss, J. Potgieter, A.A. Roux, M. Watson, G. de Wet, A. Olckers, J.C. Jerling, M. Pieters, T. Hoekstra, T. Puoane, E. Igumbor, L. Tsolekile, D. Sanders, P. Naidoo, N. Steyn, N. Peer, B. Mayosi, B. Rayner, V. Lambert, N. Levitt, T. Kolbe-Alexander, L. Ntyintyane, G. Hughes, R. Swart, J. Fourie, M. Muzigaba, S. Xapa, N. Gobile, K. Ndayi, B. Jwili, K. Ndibaza, B. Egbujie, T. de Lima, M. Petersen, S. Govender. Sweden: A. Rosengren*, K. Bengtsson Boström, U. Lindblad, P. Langkilde, A. Gustavsson, M. Andreasson, M. Snällman, L. Wirdemann, K. Pettersson, E. Moberg. Turkey: A. Oguz*, AAK Akalin, KBT Calik, N. Imeryuz, A. Temizhan, E. Alphan, E. Gunes, H. Sur, K Karsidag, S. Gulec, Y. Altuntas. United Arab Emirates: A.M. Yusufali*, W. Almahmeed, H. Swidan, E.A. Darwish, A.R.A. Hashemi, N. Al-Khaja, J.M. Muscat-Baron, S.H. Ahmed, T.M. Mamdouh, W.M. Darwish, M.H.S. Abdelmotagali, S.A. Omer Awed, G.A. Movahedi, F. Hussain, H. Al Shaibani, RIM Gharabou, D.F. Youssef, AZS Nawati, ZAR Abu Salah, RFE Abdalla, S.M. Al Shuwaihi, M.A. Al Omairi, O.D. Cadigal, R.S. Alejandrino. Zimbabwe: J. Chifamba*, L. Gwaunza, G. Terera, C. Mahachi, P. Mrambiwa, T. Machiweni, R. Mapanga.