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Results of May Measurement Month (MMM) 2017: A Global blood pressure screening campaign.
Authors:
1. T Beaney, MRCP, Imperial College London, St Dunstan’s Road, London, W6 8RP2. A E Schutte, PhD, North-West University, Potchefstroom 2520, South Africa3. M Tomaszewski, MD, Division of Cardiovascular Sciences, University of Manchester, UK4. C Ariti, MSc, Cardiff University, Centre for Medical Education, Heath Park, Cardiff, CF14 4XN5. R Castillo, FPCP, Manila Doctors’ Hospital, 667 United Nations Ave. Manilla 1000, Philippines6. A Damasceno, PhD, Eduardo Mondlane University, Av. Salvador Allende, Maputo7. R Kruger, PhD, North-West University, Potchefstroom 2520, South Africa8. P Nilsson, MD, Lund University, Skane University Hospital, Malmo, Sweden9. D Prabhakaran, DM, Public Health Foundation of India, Plot 47, Sector 44, Haryana, India10. A Ramirez, MD, Hospital Universitario Fundación Favaloro, Buenos Aires, Argentina11. M Schlaich, MD, The University of Western Australia, 50 Murray St, Perth WA 600012. H Wang, PhD, Nanjing Medical University, Guangzhou Road 300, Nanjing 21002913. N R Poulter, FMed Sci, Imperial College London, 68 Wood Lane, London, W12 7TA
on behalf of the MMM Investigators
Corresponding Author:Professor Neil R Poulter, Imperial College London, 68 Wood Lane, London, W12 7TATel: 0207 594 3446 Email: [email protected]
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Total word count: 3502
Summary word count: 298
(Total word count cannot be over 3,500 words)
Summary:
Background:
Raised blood pressure is the biggest contributor to the global burden of disease and mortality. Data
suggest that fewer than half of those with hypertension are aware of it. May Measurement Month
(MMM) was initiated as a pragmatic interim solution to the shortfall in systematic screening
programmes.
Methods:
A cross-sectional survey of volunteers aged >18 years who ideally had not had their blood pressures
measured in the last year was set up. Three blood pressures were measured, and a questionnaire
including demographic, lifestyle and environmental factors administered. The primary objective was
to raise awareness of blood pressure, measured by number of countries involved, number screened
and number identified with untreated or inadequately treated hypertension (systolic >140 mmHg
and/or diastolic >90 mmHg or on antihypertensive medication). Secondary objectives were to
evaluate associations between blood pressure and screenee characteristics and environmental factors.
Multiple imputation was used to impute the mean of the second and third measurements if not
recorded. Measures of association were analysed by multivariable linear regression.
Findings:
Over 100 countries took part and data on 1202940 from 80 countries were analysed. Approximately
one third (34·6%) of screenees were hypertensive, of whom 141272 were untreated and 102603 were
treated but not controlled (to <140 systolic and <90 mmHg diastolic). Significant differences in fully-
2
adjusted blood pressures and hypertension prevalence were apparent across regions and national
income strata.
Adjusted blood pressure levels were higher among those with diabetes, prevalent cardiovascular
disease, smokers and alcohol drinkers. Blood pressures were higher when measured on the right arm
and at the weekend.
Interpretation:
Inexpensive global screening of blood pressure is achievable using volunteers, and convenience
sampling. Pending the set-up of systematic surveillance systems worldwide, MMM will be repeated
annually to raise awareness of blood pressure.
Funding:
ISH, CDC, Servier Pharmaceutical Co. Ltd
3
Research in context
Evidence before this study:
Raised blood pressure remains the biggest cause of global mortality and disease burden despite the
existence of effective treatments. The identification of hypertension remains a major challenge, with
effective blood pressure surveillance systems needed.
Added value of this study:
May Measurement Month (MMM) 2017 is the largest ever synchronised standardised multinational
screening campaign of any cardiovascular risk factor. Data on the blood pressures of 1·2 million
individuals from 80 countries are presented, with two-thirds having three measurements taken. MMM
was the largest ever blood pressure survey carried out in over 33 countries. Of screenees not on anti-
hypertensive treatment, over 140000 individuals were identified with high blood pressure. Of those on
4
treatment over 100000 screenees had uncontrolled blood pressure. This study has huge power to
detect associations of blood pressure variation including significant variations by day of the week.
Implications of all the available evidence:
Volunteer screening can be carried out cost-effectively on convenience samples and can identify large
numbers of individuals who may benefit from treatment or enhanced treatment. Pending the
establishment of systematic blood pressure screening systems, MMM is a cost-effective substitute and
raises awareness of hypertension across the world. MMM will be repeated annually for the purposes
of screening and boosting awareness of raised blood pressure.
Introduction:
Raised blood pressure continues to be the biggest contributor to the global burden of disease and to
global mortality, leading to 10·5 million deaths each year.1 This situation is expected to worsen over
the coming decades as the global population increases and ages.
Despite the existence of several major drug classes which are effective at lowering blood pressure and
at reducing the associated risk of adverse cardiovascular events,2 only a small minority of patients
with hypertension have their blood pressures controlled to hitherto generally accepted targets (<140
5
mmHg systolic blood pressure and <90 mmHg diastolic blood pressure)3. This is mainly due to the
fact that most people with hypertension are not treated which is largely due to the low rates of
awareness and screening for raised blood pressure.3
Recent reports from the World Heart Federation4 and the Lancet Commission on Hypertension5 highlighted the importance of improving awareness of raised blood pressure as a critical action
needed to address the associated health burden.
Blood pressure measurement is a cheap, simple and non-invasive technique which allows
hypertension to be detected and, assuming effective therapy is supplied, leads to highly cost-effective
protection against death and disability2,5 which usually arises from myocardial infarction,
cerebrovascular disease and renal failure.
Despite this, routine blood pressure screening is not systematically applied in many countries of the
world. Unfortunately, introduction of systematic blood pressure surveillance systems requires
significant funding, governmental support and is unlikely to happen in the near future. Meanwhile,
with over ten million people dying annually due to raised blood pressure,1 urgent action is required.
Hence, as a pragmatic and urgent approach to addressing the problem of insufficient awareness of
hypertension, we expanded World Hypertension Day to become May Measurement Month (MMM)6 –
a month of standardised global blood pressure measurement and data collection.
Methods:
MMM is a cross-sectional survey set up between October 2016 and April 2017 in at least 100
countries worldwide. In each country one or more national leaders were identified. They were
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responsible for obtaining ethical clearance for the survey and for recruiting volunteer staff to set up
screening sites. Sites were set up in a wide range of locations including pharmacies, supermarkets,
places of worship, shopping malls, sports grounds, schools and existing clinics in primary and
secondary care facilities. Target screenees were volunteer adults aged >18 years who ideally had not
had their blood pressures measured in the previous year. The campaign was promoted internationally
by the ISH and the World Hypertension League newsletter and locally by celebrity and government
endorsements, on television, radio and through the media and social media.
Volunteer staff were trained to measure blood pressure via video recordings housed on the bespoke
MMM website.7 Standard methods were recommended including three seated recordings with one-
minute intervals between readings when the pulse rate was recorded. Omron Healthcare donated
20000 blood pressure machines which were distributed to sites as required.
A limited amount of additional data were collected on each screenee via a questionnaire (see
supplementary appendix) and these data were entered, where internet access was available, onto a
study-specific mobile application produced in 6 languages. Alternatively, data were entered on paper
forms and later transferred to spreadsheets.
Hypertension was defined based on the mean of the second and third reading, as a systolic blood
pressure ≥ 140mmHg, and/or a diastolic blood pressure ≥ 90mmHg, or those known to be on anti-
hypertensive treatment. Among those on treatment, controlled blood pressure was defined as a blood
pressure of <140/90 mmHg. Screenees found to have blood pressures in the hypertensive range were
provided, as a minimum, with printed evidence-based dietary and lifestyle advice designed to lower
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blood pressure (see top ten tips in supplementary appendix). Advice for further follow-up tailored to
locally available facilities was also provided.
Cleaning of data was carried out either locally or centrally depending on local capacity. Data cleaning
rules and cut-off ranges were devised and provided to all sites (see rules in supplementary appendix)
For full details of the statistical analysis, see the supplementary appendix. Submitted data were
collated centrally and analysed using Stata version 14.2. Data on 190955 individuals collected by the
Public Health Foundation of India (PHFI) could not be provided at an individual level. Instead these
data were analysed locally, with results submitted and incorporated either using weighted averages or
meta-analysis. Global data were sub-divided into seven regions based on the United Nations
geographic regions with some modifications.8 Information on country income was sourced from the
World Bank classification of economies (as of June 2017).9
Ideally three blood pressures were recorded and crude analyses were performed using the mean of the
second and third blood pressure measurements, where available. For comparisons of mean blood
pressure and of the proportion with hypertension using different combinations of the three readings,
only those individuals with all three readings were analysed.
Multiple imputation was used to impute the mean of the second and third blood pressure readings
when the second and/or third reading were not recorded. Age (as a restricted cubic spline with 5
knots) and gender were included in the imputation model, along with an interaction term. Mean blood
pressures were standardised for age and sex according to the WHO world age-standard population
along with an assumed female:male ratio of 1:1.10,11 Linear regression models were run separately
8
for systolic and diastolic blood pressures. In all models, the association of blood pressure with age and
sex was modelled along with an interaction term.
Role of the funding source:
The majority of the study funding was raised at the national level and was used to cover study
expenses (screener travel expenses, printing etc). The majority of the central funding was supplied by
ISH to cover ethics submissions, salaries of the secretariat and travel expenses. Small donations from
CDC and Servier were used to supplement central costs. None of the funding sources influenced the
conduct, analysis and publication of results.
Results:
Over 100 countries took part in MMM but only data from the 80 countries which produced data on at
least 10 screenees were included in analyses. Data from 1202940 screenees were cleaned, collated
centrally and analysed. Of 45 countries surveyed after the study was completed 33 (73%) national
leaders reported that MMM was the largest blood pressure survey ever carried out in their country.
Only approximately 8% of the data were collected onto the bespoke mobile application. Because data
collection was incomplete for some of the variables included on the study questionnaire, numbers
used in different analyses varied.
Table 1 stratifies numbers of screenees included in the database across seven regions and by countries
in each region with mean ages and distribution between men and women provided at the regional
level. Only countries with >1000 screenees are named in Table 1 (a complete list of countries can be
found in Table A1 of the supplementary appendix). The percentages of screenees arising from high,
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upper middle, lower middle, and low income countries were 9·6%, 20·0%, 68·8% and 1·6%
respectively.
More women than men were screened in all regions except in the South Asian and Northern Africa
and Middle East regions. Mean ages ranged from 37·4 years in North Africa and the Middle East to
55·0 years in East Asia. The proportion of screenees on anti-hypertensive medications was 24·2% and
at a regional level varied between 3·3% in Northern Africa and the Middle East and 56·8% in East
Asia (Table 1).
Among screenees overall, 8·6% reported having type 2 diabetes with 3·1% and 1·8% reporting a past
history of a myocardial infarction or stroke, respectively. 11·5% of respondents were current smokers
and 7·5% consumed alcohol once or more per week, while over 7000 women (1·1% of female
respondents) were pregnant. The mean BMI of respondents was 24·6 kg/m² (SD: 4·5) (Table A2 of
the supplementary Appendix).
Among the 818411 respondents with three blood pressures recorded, blood pressures fell on average
by 3·1/1·5 mmHg between the first and third readings (Table 2). Likewise, the prevalence of
hypertension fell on subsequent readings, with a difference of 3.9% in the prevalence of hypertension
between the first and third reading. The mean of the second and third reading generated the lowest
prevalence.
The sensitivity of the first measurement in predicting hypertension (based on the mean of the second
and third) was 0·904 with a specificity of 0·903. The sensitivity of the second reading was higher than
the third (0·949 vs 0·922) but with a lower specificity (0·956 vs 0·970). These results are shown in
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Table A3 of the supplementary appendix. The area under the curve (AUC) was highest for the second
reading (0.952).
Multiple imputation was used to impute the mean of the second and third reading based on any single
reading reported. The value of R2 was 0·83 and 0·74 for systolic and diastolic blood pressure,
respectively, based on a regression against the first reading alone, implying a major proportion of the
variation in the mean of the second and third readings was explained by a single blood pressure
measurement. Five imputations were deemed to be sufficient, with no significant change in
coefficients using further imputations. Each imputed data-set was checked to determine the spread of
values and no major differences were seen. A sensitivity analysis was performed to impute the
difference in blood pressure between a single reading and the mean, rather than the mean value itself,
which found no difference between the methods. A total of 295129 readings were imputed.
Based on the mean of blood pressure readings 2 and 3 (including imputed results) approximately one
third of all screenees (368215 [34·6%]) were found to be hypertensive. Of these, 141272 (16·9%)
were not taking anti-hypertensive medication (Table 3). Among those on treatment for hypertension
102603 (46·3%) were not controlled.
Based on a linear regression model, the global association between age and sex with systolic blood
pressures among those not on anti-hypertensive treatment showed a linear increase, with female blood
pressures overtaking men at 80 years of age. For diastolic blood pressure, the relationship shows an
inverted ‘u’ shape with highest levels occurring between 50-55 years, and with women once again
having lower blood pressures until the age of 80 years (Fig 1).
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The differential distribution in age and sex among those screened in the seven regions demonstrates
the need for standardisation in order to make comparisons between regions. Table 4 shows the age-
and sex- standardised mean blood pressures by region, along with the standardised proportion with
hypertension in those untreated, and the proportion with uncontrolled hypertension in those on
treatment. There is a strong correlation between mean blood pressure and hypertension proportions
(0·84 for systolic and 0·93 for diastolic blood pressure). Both systolic and diastolic pressures and
proportion with hypertension were higher in Sub-Saharan Africa than other regions. Systolic was
lowest in South-East Asia and Australasia, whereas diastolic was lowest in East Asia and the
Americas. The crude measurements, along with the age and sex-standardised blood pressures before
imputation are shown in the supplementary appendix Table A4.
Following adjustment for age and sex (allowing for an interaction), significantly higher levels of
systolic blood pressure were apparent among those on anti-hypertensive treatment. Adjusting for age,
sex and antihypertensive treatment, systolic blood pressure was significantly higher in those with
diabetes and those with a previous history of myocardial infarction or stroke (Fig 2). Diastolic blood
pressures showed the same significant differences except among those with a previous myocardial
infarction. Current smoking, alcohol intake and increasing levels of body mass index (BMI) (Fig 3)
were also associated with significant increases in both systolic and diastolic blood pressures. By
contrast, pregnancy and blood pressures measured on the left arm were significantly reduced (Fig 2).
Further adjustment of smoking for BMI did not affect the results. Coefficients for the regression
analyses are shown in the supplementary appendix (Tables A5-8).
Systolic and diastolic blood pressures varied significantly by day of the week (Fig 4) with the highest
levels recorded on Saturday and Sunday and the lowest levels on Tuesday after adjusting for age, sex
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and anti-hypertensive medication. Adjusting in addition for alcohol levels did not significantly alter
results (results not shown).
Relatively modest differences in systolic and diastolic blood pressures were apparent across the four
strata of national incomes. After multivariable adjustment for other participant characteristics (age,
sex, treatment, BMI, ethnicity, diabetes, previous myocardial infarction or stroke, alcohol intake,
smoking habit and day of the week) and using blood pressure levels in lower-middle income countries
as the referent group, both systolic and diastolic levels were significantly lower in upper middle
countries with significantly lower diastolic pressures in high income countries and higher diastolic
pressures in low income countries (Fig 5).
Discussion:
MMM 2017 is the largest synchronised standardised multinational screening campaign of any
cardiovascular risk factor ever carried out. In at least 33 countries this was the largest blood pressure
survey ever conducted. That 1·2 million adults could be screened in 80 countries during a one-month
period, with only seven months’ preparation, highlights the fact that mass screening is possible and
can greatly enhance blood pressure awareness in large numbers of people.
Because MMM relied heavily on volunteer staff and donations of blood pressure machines plus
locally-raised support and funds, the cost of the campaign was modest, with ISH spending only
approximately USD 0·22 per patient screened. The identification of about 250000 adults whose raised
blood pressure was identified (141272 untreated plus 102603 treated but still raised) for this modest
level of central funding makes the exercise appear cost-effective at approximately USD 1 per
identified case. Pending the establishment of blood pressure surveillance systems around the world
13
this inexpensive screening model may help to offset the enormous health burden attributed to raised
blood pressure.
Clinic-based blood pressures are frequently measured in trials by recording three blood pressures and
taking the mean of the second and third readings. This practice is supported by our findings in that
globally, blood pressures decreased significantly with each subsequent reading, with a marked
difference in the proportion with hypertension dependent on which reading is used and the mean of
the second and third readings was most suitable for identifying hypertension if values from only one
set of readings are to be used.
Given the convenience sampling, arising from divergent screening sites and including a wide
spectrum of types of screenees, it is inappropriate to try to compare the variable prevalence rates of
hypertension observed around the world. However, associations with levels of blood pressure in such
large cross-sectional datasets are valid – and of interest. We confirmed lower blood pressure levels
among pregnant women, the ‘usual’ pattern of rising systolic blood pressure whilst diastolic blood
pressures rise and fall with age and that alcohol consumption is associated with higher blood
pressures. The data shown in Figure 2 highlight that those with established hypertension or diabetes or
cardiovascular disease all have less well-controlled blood pressure and emphasises the need for more
assertive treatment in such high-risk patients.
That blood pressure levels were higher when readings were taken from the right arm may be
associated with right handedness being more common than left handedness and hence on average
right upper arms are larger. However, other explanations for higher levels on the right have been
hypothesised, including the anatomy of the aortic arch and its branches.12 The finding of higher blood
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pressures among smokers is at odds with several previous studies,13 which may reflect reporting bias
among screenees or the inability to distinguish duration and degree of exposure.
The finding of high blood pressures on Saturday and Sunday with lowest blood pressures on Tuesdays
presumably relates to increased exposure to one or more environmental factor which exerts a pressor
effect. For example, in some cultures, intakes of alcohol are higher over the “weekend” although
adjustment for the crude strata of alcohol intakes we recorded did not affect this finding. However,
alcohol consumption is also likely to be under-reported, and may show regional and cultural
differences in the accuracy of the reported intake. Further interrogation of these data in regions where
alcohol is rarely consumed may shed light on these findings.
The global prevalence of hypertension (including those on treatment) was high at 34·6% but had we
applied the definition espoused in the most recent American Guidelines which redefined stage 1
hypertension as systolic >130mmHg and/or >80 mmHg diastolic14 the proportion almost doubles to
57·3%.
Limitations of these data include that by design, they were not intended to be based on representative
samples of the countries where screening took place. Furthermore, although almost 40% of readings
were taken using OMRON machines and common training materials,7 standardisation of blood
pressure measurement methods around the world was undoubtedly suboptimal. However, by virtue of
having over 800000 screenees with all three recordings we were able to ‘adjust’ submitted data based
on one reading, to the mean of the second and third reading using multiple imputation. The need to
adjust the readings is evident in the decline in mean blood pressure and hypertension across the 3
readings. As in any blood pressure screening taking place on a single occasion, a proportion of false
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positive diagnoses is likely to have arisen. However, healthy diet and lifestyle advice was provided
and appropriate follow up advice was given to all such people. Even if only 50% of hypertension
cases were correctly identified, approximately 125000 adults with truly elevated blood pressure were
identified in MMM 2017 and at worst harmless advice was provided to those who had high normal
rather than truly hypertensive pressures.
The mobile application produced for the campaign caused logistic problems and hence most of the
data were entered onto spreadsheets often having been collected by hand and transferred. This slowed
down data collection and was a frustration both for screenees and for the volunteer staff. Furthermore,
data cleaning was a much more protracted procedure which has delayed generation of this report.
The analyses of mean blood pressures and hypertension rates by which readings are used to define
these outcomes (Table 2) highlight the importance of standardising such data when making
comparisons across populations and when making the diagnosis at an individual level. As expected
there was a strong correlation between higher mean blood pressures and higher rates of hypertension
across regions after adjusting for age and sex. Hence small, albeit highly significant differences in
mean blood pressure levels found for example in Figure 2 also reflect differences in hypertension
rates. There were significant differences across regions in the proportions with hypertension in
untreated populations, and in the control of those on treatment. The significant association of income
level on blood pressure persisted even after adjusting for multiple potential confounders and may
explain some of the regional differences. Region- and country-specific analyses led by national
leaders will help elucidate these questions.
16
With valuable lessons learnt, the MMM campaign will be repeated in 2018 with a much improved
data collection system (15) and it is anticipated that at least a similar sized population will be screened
during May 2018 with more complete data. Increased focus on the impact of other variables such as
‘room’ temperature and altitude (at the site of blood pressure measurement) will be investigated more
thoroughly in 2018.
Meanwhile, pending the establishment of systematic blood pressure surveillance systems around the
world, we believe that MMM as a large, inexpensive blood pressure screening campaign based on
convenience sampling represents a useful and reasonably cost-effective tool in helping to raise
awareness among the general population and potentially among health policy makers and thereby to
help to address the burden of disease caused by raised blood pressure. We therefore propose that
MMM should continue on an annual basis as long as significant numbers of people with raised blood
pressure can be identified and until suitable surveillance systems are in place.
17
References:
1. Gakidou E, Afshin A, Abajobir AA, et al. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet; 390(10100): 1345-422.
2. Turnbull F, Woodward M, Neal B, Barzi F, Ninomiya T, Chalmers J, Perkovic V, Li N, MacMahon S and the Blood Pressure Lowering Treatment Trialists’ Collaboration. Do men and women respond differently to blood pressure-lowering treatment? Results of prospectively designed overviews of randomized trials. European Heart Journal 2008; 29,2669-2680
3. Chow CK, Teo KK, Rangarajan S, et al, and the PURE (Prospective Urban Rural Epidemiology) Study investigators. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA 2013; 310: 959-68.
4. Adler AJ, Prabhakaran D, Bovet P, et al. Reducing cardiovascular mortality through prevention and management of raised blood pressure: a World Heart Federation roadmap. Glob Heart 2015; 10: 111-22.
5. Olsen MH, Angell SY, Asma S, et al. A call to action and a lifecourse strategy to address the global burden of raised blood pressure on current and future generations: The Lancet Commission on hypertension Lancet 2016; 388: 2287-712.
6. NR. Poulter, DT. Lackland. May Measurement Month: a global blood pressure screening campaign. Lancet 2017 Vol 389: 1678-1680
7. MMM 2017 website: http://www.whleague.org/index.php/2014-07-09-22-47-11/may-measurement-month-2017
8. United Nations Statistics Division. Standard country or area codes for statistical use (M49). 1999. https://unstats.un.org/unsd/methodology/m49/ (accessed 20/02/2018 2018).
9. The World Bank. World Bank Country and Lending Groups. 2017. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed 20/02/2018 2018).
10. Surveillance Epidemiology and End Results (SEER) Program. SEER*Stat Database: Standard Populations - Single Ages to 84 and then 85+. 2013. http://www.seer.cancer.gov/ (accessed 20/02/2018 2018).
11. Surveillance Epidemiology and End Results (SEER) Program. Standard Populations - Single Ages. 2013. https://seer.cancer.gov/stdpopulations/stdpop.singleages.html (accessed 20/02/2018 2018).
18
12. Vasava P, Jalali P, Dabagh M, Kolari PJ. Finite Element Modelling of Pulsatile Blood Flow in Idealized Model of Human Aortic Arch: Study of Hypotension and Hypertension. Comput Math Methods Med 2012; 2012: 14.
13. Primatesta P, Falaschetti E, Gupta S, Marmot MG, Poulter NR. Association between smoking and blood pressure. Evidence from the Health Survey for England. Hypertension 2001;37:187-193.
14. Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults. A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines 2017.
15. MMM 2018 Website: www.maymeasure.com
Figure 1: Change in blood pressure with age and gender
19
Figure 2: Difference in mean blood pressure according to individual characteristic from linear regression
model (adjusted)
20
Figure 3: Difference in mean blood pressure according to body mass index from linear regression
(adjusted)
21
Figure 4: Difference in mean blood pressure according to day of the week from linear regression
(adjusted)
22
Figure 5: Differences in mean blood pressure according to country income from linear regression
(adjusted)
23
Table 1: Total participant numbers by region and country with regional age, sex and anti-hypertensive
treatment distributions
Region and country
To
Percentage
Me
Fe
Ma
On treatment
South-east Asia & Australasia
35
29·9%
42
21
13
78973 (22·5%)
Philippines
27
22·6%
Indonesia
69
5·8%
Viet Nam
10
0·9%
Malaysia
41
0·3%
Australia
38
0·3%
South Asia
26
21·9%
39
11
14
27691 (15·5%)
India
24
20·0%
B 11
0
24
angladesh
·9%
Nepal
59
0·5%
Pakistan
53
0·4%
East Asia
18
15·0%
55
95
82
44843 (56·8%)
China
12
10·4%
Taiwan
52
4·4%
Hong Kong
23
0·2%
Sub-Saharan Africa
13
10·8%
39
68
58
12109 (9·6%)
Ivory Coast
24
2·0%
Nigeria
19
1·7%
Angola
17
1·5%
Cameroon
16
1·3%
K
en14
1·
25
ya 2%
Zambia
96
0·8%
Mozambique
44
0·4%
Malawi
40
0·3%
Congo
38
0·3%
South Africa
32
0·3%
C
abo Verde
26
0·2%
M
auritius
23
0·2%
Burundi
18
0·2%
Botswana
16
0·1%
Others
36
0·3%
26
Table 1 (continued)
Region and country
To
Percentage
Me
Fe
Ma
On treatment
Europe
10
9·0%
52
64
43
42354 (43·5%)
Ukraine
45
3·8%
Italy
10
0·8%
Armenia
91
0·8%
Georgia
61
0·5%
Poland
58
0·5%
Russia
56
0·5%
UK
50
0·4%
Hungary
39
0·3%
Spain
38
0·3%
Austria
27
0·2%
Ireland
26
0·2%
Lith
20
0·
27
uania
2%
Switzerland
11
0·1%
Albania
10
0·1%
Others
41
0·3%
Americas
10
8·9%
48
64
42
32307 (30·6%)
Argentina
32
2·7%
Colombia
22
1·9%
Venezuela
21
1·8%
Brazil
73
0·6%
Ecuador
69
0·6%
Chile
47
0·4%
Uruguay
24
0·2%
USA
19
0·2%
Paraguay
11
0·1%
Mexico
11
0·1%
28
Others
56
0·5%
Northern Africa and Middle East
53
4·4%
37
19
32
1742 (3·3%)
Sudan
44
3·7%
UAE
61
0·5%
Others
26
0·2%
Total
12
44
64
54
240019 (24·2%)
29
Table 2: Differences in mean blood pressures and numbers with hypertension depending on measurement
used (out of a total of 818411)
Reading 1 Reading 2 Reading 3 Mean of 1&2 Mean of 2&3Mean systolic blood pressure
(mmHg) 126·6 124·7 123·5 125·7 124·3
Mean diastolic blood pressure (mmHg) 79·4 78·5 77·9 79·1 78·3
Total with hypertension 331309 310034 299546 305927 290932
Percentage with hypertension 40·5% 37·9% 36·6% 37·4% 35·5%
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Table 3: Total number with hypertension and by treatment for each region
Region Total with hypertension Percentage Total with hypertension - excluding those on treatment Percentage Total with uncontrolled BP in those
on treatment Percentage
South-East Asia & Australasia 121347 34·0% 42374 15·3% 34090 44·9%
South Asia 36458 26·8% 21843 18·0% 6285 43·0%
East Asia 61518 34·3% 16675 12·4% 15971 35·8%
Sub-Saharan Africa 36024 28·3% 23915 20·8% 6618 56·1%
Europe 59758 55·0% 17404 26·2% 26743 63·6%
Americas 43071 41·3% 10764 15·0% 12142 39·5%
Northern Africa and Middle East 10039 19·0% 8297 16·2% 755 43·8%
Global 368215 34·6% 141272 16·9% 102603 46·3%
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Table 4: Mean blood pressures and percentages with hypertension (in those untreated and on treatment)
after standardising for age and sex distributions
Region Mean blood pressure * Percentage with hypertension - age and sex standardised *
Percentage with uncontrolled BP in those on treatment - age and sex
standardised
South-East Asia & Australasia 118·6 / 77·2 17·0% 39·6%
South Asia 122·4 / 77·8 19·8% 45·0%
East Asia 119·4 / 75·0 9·3% 31·7%
Sub-Saharan Africa 124·7 / 78·4 25·0% 51·2%
Europe 124·0 / 77·5 21·0% 48·7%
Americas 119·8 / 75·0 14·1% 33·5%
Northern Africa and Middle East 120·6 / 76·3 16·1% 38·1%
Total 120·6 / 76·8 16·5% 38·8%
*Excluding those on anti-hypertensive treatment
32
