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Background: Despite high projected burden, hypertension incidence data are lacking in South Asian population. We measured hypertension prevalence and incidence in the Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) adult cohort. Methods: The CARRS Study recruited representative samples of Chennai, Delhi, and Karachi in 2010/11, and socio-demographic and risk factor data were obtained using a standard common protocol. Blood pressure (BP) was measured in the sitting position using electronic sphygmomanometer both at baseline and two year follow-up. Hypertension and control were defined by JNC 7 criteria. Results: In total, 16,287 participants were recruited (response rate=94.3%) and two year follow-up was completed in 12,504 (follow-up rate=79.2%). Hypertension was present in 30.1% men (95% CI: 28.7-31.5) and 26.8% women (25.7-27.9) at baseline. BP was controlled in 1 in 7 subjects with hypertension. At two years, among non-hypertensive adults, average systolic BP increased 2.6mm Hg (95% CI: 2.1-3.1), diastolic BP 0.7mm Hg (95% CI: 0.4-1.0), and 1 in 6 developed hypertension (82.6 per 1000 person years, 95% CI: 80.8-84.4). Risk for developing hypertension was associated with age, low socio-economic status, current alcohol use, overweight, pre-hypertension, and dysglycemia. Risk of incident hypertension was highest (RR=2.95, 95% CI: 2.53-3.45) in individuals with pre-hypertension compared to normal BP. Collectively, 4 modifiable risk factors (pre-hypertension, overweight, dysglycemia, and alcohol use) accounted for 78% of the population attributable risk of incident hypertension. Conclusion: High prevalence and poor control of hypertension, along with high incidence, in South Asian adult population call for urgent preventive measures.
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Accepted Manuscript
Title: Prevalence and incidence of hypertension: Results from
a representative cohort of over 16,000 adults in three cities of
South Asia
Authors: Dorairaj Prabhakaran, Panniyammakal Jeemon,
Shreeparna Ghosh, Roopa Shivashankar, Vamadevan S. Ajay,
Dimple Kondal, Ruby Gupta, Mohammed K. Ali, Deepa
Mohan, Viswanathan Mohan, Masood M. Kadir, Nikhil
Tandon, Kolli Srinath Reddy, K.M. Venkat Narayan
PII: S0019-4832(17)30228-6
DOI: http://dx.doi.org/doi:10.1016/j.ihj.2017.05.021
Reference: IHJ 1211
To appear in:
Received date: 26-3-2017
Accepted date: 27-5-2017
Please cite this article as: Dorairaj Prabhakaran, Panniyammakal Jeemon, Shreeparna
Ghosh, Roopa Shivashankar, Vamadevan S.Ajay, Dimple Kondal, Ruby Gupta,
Mohammed K.Ali, Deepa Mohan, Viswanathan Mohan, Masood M.Kadir, Nikhil
Tandon, Kolli Srinath Reddy, K.M.Venkat Narayan, Prevalence and incidence of
hypertension: Results from a representative cohort of over 16,000 adults in three cities
of South Asia (2010), http://dx.doi.org/10.1016/j.ihj.2017.05.021
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1
Prevalence and incidence of hypertension: Results from a representative cohort of over
16,000 adults in three cities of South Asia.
Short title: Incidence of hypertension in South Asia.
Authors: Dorairaj Prabhakaran1,2, Panniyammakal Jeemon1,2, Shreeparna Ghosh1,2, Roopa
Shivashankar1,2, Vamadevan S Ajay1,2, Dimple Kondal1,2, Ruby Gupta1,2, Mohammed K Ali2,3,
Deepa Mohan4, Viswanathan Mohan4, Masood M Kadir5, Nikhil Tandon2,6, Kolli Srinath
Reddy1,2, K M Venkat Narayan2,3.
Affiliations:
1Public Health Foundation of India, New Delhi, India
2Centre for Control of Chronic Conditions, New Delhi, India
3Rollins School of Public Health, Emory University, Atlanta, USA
4Madras Diabetes Research Foundation, Chennai, India
5Aga Khan University, Karachi, Pakistan
6All India Institute of Medical Sciences, New Delhi, India
The authors’ takes responsibility for all aspects of the reliability and freedom from bias of
the data presented and their discussed interpretation.
Corresponding author:
Prof. D Prabhakaran
Vice President, Public Health Foundation of India
Director, Centre for Control of Chronic Conditions
Sector 44, Plot 47, Gurgaon, NCR, Haryana, 122001
Email: dprabhakaran@ccdcindia.org
2
Abstract
Background: Despite high projected burden, hypertension incidence data are lacking in
South Asian population. We measured hypertension prevalence and incidence in the Center
for cArdio-metabolic Risk Reduction in South Asia (CARRS) adult cohort. Methods: The CARRS
Study recruited representative samples of Chennai, Delhi, and Karachi in 2010/11, and
socio-demographic and risk factor data were obtained using a standard common protocol.
Blood pressure (BP) was measured in the sitting position using electronic
sphygmomanometer both at baseline and two year follow-up. Hypertension and control
were defined by JNC 7 criteria. Results: In total, 16,287 participants were recruited
(response rate=94.3%) and two year follow-up was completed in 12,504 (follow-up
rate=79.2%). Hypertension was present in 30.1% men (95% CI: 28.7-31.5) and 26.8% women
(25.7-27.9) at baseline. BP was controlled in 1 in 7 subjects with hypertension. At two years,
among non-hypertensive adults, average systolic BP increased 2.6 mm Hg (95% CI: 2.1-3.1),
diastolic BP 0.7 mm Hg (95% CI: 0.4-1.0), and 1 in 6 developed hypertension (82.6 per 1000
person years, 95% CI: 80.8-84.4). Risk for developing hypertension was associated with age,
low socio-economic status, current alcohol use, overweight, pre-hypertension, and
dysglycemia. Risk of incident hypertension was highest (RR=2.95, 95% CI: 2.53-3.45) in
individuals with pre-hypertension compared to normal BP. Collectively, 4 modifiable risk
factors (pre-hypertension, overweight, dysglycemia, and alcohol use) accounted for 78% of
the population attributable risk of incident hypertension. Conclusion: High prevalence and
poor control of hypertension, along with high incidence, in South Asian adult population call
for urgent preventive measures.
3
Key words: Hypertension, prevalence, incidence, South Asia, India
Introduction
Hypertension is a common risk factor for cardiovascular disease (CVD) and a major global
public health problem [1]. Globally, hypertension affects approximately one in four adults
[2] and results in over ten million deaths annually [3]. Furthermore, low- and middle-income
countries (LMIC) contribute to nearly two-thirds of the mortality attributable to
hypertension [4]. Although the average systolic blood pressure (SBP) is decreasing
worldwide since 1980’s at the rate of 1 mmHg SBP per decade, it is increasing in LMICs,
especially in the South Asian population [5]. There are several studies that document the
prevalence of hypertension in South Asian countries [6-8], and numerous meta-analyses
have unequivocally demonstrated that treating and effectively lowering blood pressure (BP)
is associated with reductions in cardiovascular events and mortality [9, 10]. However, the
treatment and control among prevalent hypertension cases are relatively poor in resource
poor settings, though data are quite limited and little is known about hypertension
management in South Asia [6].
Studies conducted in the Indian sub-continent suggest that hypertension onset occurs
relatively early in life [11] and is often associated with clustering of multiple cardiovascular
diseases risk factors [12]. However, there is paucity of data on the incidence and factors
associated with progression to hypertension in this population. Reliable data on
hypertension incidence is important to estimate the future burden of hypertension and to
identify potential risk factors and subpopulations to target with preventive interventions.
4
In this report, we used data from a large, urban population cohort representative of three
large cities in South Asia with the objective to examine prevalence, treatment and control,
two year incidence, and factors associated with incident hypertension.
Methods
Population
The CARRS Study [13] recruited representative population cohorts of three metropolitan
urban cities in south Asia with large, growing, and heterogeneous populations, namely
Chennai, Delhi and Karachi. The cities were choosen based on convenience. The detailed
methods including sample selection and measurements have been published elsewhere
[13]. Briefly, households were selected in each of the three cities using a multi-stage cluster
random sampling technique (selection of districts followed by random selection of
municipal wards or census enumeration blocks and finally the selection of households
within these sampling units) to ensure representativeness of the population. Two
participants, one man and one woman, aged 20 years or older, were selected from each
household based on “Kish method” as used in the WHO’s STEPS surveys [14].
Measurements
Trained field workers collected socio-demographic and risk factor data from all eligible
participants using a structured questionnaire. Baseline assessment was done in year 2010-
11. They also measured height, weight, waist circumference, systolic and diastolic BP from
all participants using standardized equipment and measurement techniques. Blood pressure
was recorded in the sitting position using electronic sphygmomanometer; Omron HEM-7080
5
and HEM-7080IT-E; Omron Corporation, Tokyo, Japan (certified by the British Hypertensive
Society and the American association for Advancement of Medical Instrumentation [AAMI]
protocols). A minimum of 2 measurements were taken, and 5 minutes apart. A third reading
was also taken if the difference between first and second readings were ≥ 10 or ≥ 5 mm Hg
for systolic and diastolic BP, respectively. The mean of the last two was used for analyses.
Additionally, fasting blood samples were also collected for biochemistry analyses. Standard
assay methods for assessment of diabetes (plasma glucose, haemoglobin A1c) and
dyslipidemia (total cholesterol, VLDL-cholesterol, LDL- cholesterol, HDL-cholesterol and
triglycerides) were used across the three sites. All laboratories participated in an external
quality assurance program (RIQAS) from RANDOX for clinical chemistry, lipids and HbA1c.
Performance of all participating labs were within the acceptable levels of <2 in the Cycle
Average Standard Deviation Index (score close to zero indicates optimal performance) for all
the parameters in the RIQAS. A summary of all surveillance indicators, measures, methods
and instruments used in the study has been published in detail [13].
Annual follow-up
Trained field workers contacted all the study participants in the baseline survey annually
and collected information on risk factors using a structured questionnaire. Additionally,
anthropometry measurements and blood pressure readings were taken from all eligible
participants during the second year follow-up. We used the same make of equipment for BP
and anthropometric measurements, and standardization procedures for all study related
measurements in the annual surveys as in the baseline survey. Year-2 follow-up was
conducted in 2013-14.
Definitions
6
Hypertension prevalence, awareness, and treatment
Hypertension was defined as SBP of ≥140 mmHg and/or a diastolic blood pressure (DBP) of
≥90 mmHg and/or self-reported treatment for hypertension. Similarly, incident
hypertension was defined as follow-up SBP of ≥140 mmHg and/or DBP of ≥90 mmHg and/or
self-reported diagnosis of hypertension by a qualified physician among those who were not
hypertensive at baseline [15]. Pre-hypertension was defined as SBP of 120 and/or DBP of
≥80 among individuals without hypertension. Incidence was estimated in individuals without
hypertension at baseline.
To estimate awareness, treatment, and control of hypertension, we used the common
denominator of total number of individuals with hypertension. Participants who had been
told that they had hypertension by a healthcare professional and self-reported their status
were categorised as ‘aware’, and those who reported current use of prescribed anti-
hypertensive medication/s were categorised as ‘treated’. ‘Control of hypertension’ was
defined as having an average of <140 and <90 mmHg for SBP and DBP, respectively, in
hypertensive subjects at baseline. Parental history of hypertension was defined as self-
reported status of treatment of hypertension in parents when they were <60 years old.
Socioeconomic Status (SES)
Household asset index and education were used to describe the SES of each participant.
Principal components analysis was used to estimate cumulative household assets based on
weighted scores for ownership of different household assets. Asset scores were then
divided into tertiles of SES [16]. Education categories included in the analyses were ES1;
“graduation & above”, ES2; “up to secondary”, ES3; “up to primary”, and ES4; “illiterates or
individuals with no formal education”.
7
Others covariates:
Physical activity was assessed using International Physical Activity Questionnaire (IPAQ).
Waist circumference was used to define central obesity (men: ≥90 cm and women: ≥80 cm).
A body mass index (BMI) of ≥25 kg/m2 was defined as overweight. Diabetes was defined as
having either HbA1c value more than equal to 6.5% or fasting blood glucose more than
equal to 126 mg/dL or self-reported glycemia-lowering medications. Prediabetes was
defined as having HbA1c value between 5.7 to 6.5% and/or fasting glucose between 100 to
125 mg/dL. Dysglycemia was defined as either pre-diabetes or diabetes. Chronic kidney
disease (CKD) status was derived from serum creatinine based estimated glomerular
filtration rate (eGFR) measurements using the Chronic Kidney Disease Epidemiology
Collaboration (CKD-EPI) [17] study equation. An eGFR of less than 60 ml/min/1.73 m2 was
defined as CKD. We did not have data from Karachi on serum creatinine.
Research ethics oversight
The Institutional Review Boards (IRBs) of the Public Health Foundation of India, New Delhi,
All India Institute of Medical Sciences, New Delhi, Madras Diabetes Research Foundation,
Chennai, India, Aga Khan University, Karachi, Pakistan, and Emory University, Atlanta, USA
approved the CARRS study. All respondents gave written informed consent, themselves or
through a next of kin/family member in the case of illiterate respondents, prior to
enrolment and participation in the study.
Statistical analyses
The characteristics of the study population were summarized separately for men and
women. The data were presented as mean with their standard deviation (SD) for continuous
8
variables or as percentages for categorical variables. All estimates of mean BP, prevalence
and incidence of hypertension were age-standardized to the 2010 World Bank regional
population. Estimates were also adjusted based on survey weights to account for population
representation due to sampling at different levels in each cluster. Prevalence estimates
were calculated after accounting for the complex multi-stage survey design, stratification,
and sampling weights.
Incidence of hypertension was estimated using follow-up data collected up to the second
year among non-hypertensive individuals at baseline. Uneven response rate in the follow-up
surveys in different risk groups was adjusted by inclusion of weights generated for non-
response. Initially, logistic regression model coefficients were generated to estimate the
probability of non-response after adjusting for baseline variables such as location (city), age,
sex, education, tobacco use, BMI, pre-hypertension and diabetes. Further, we used an
inverse propensity score as a weight in estimating the incidence of hypertension. Incidence
rates were calculated per 1000 person years of follow-up and also as cumulative
percentages over two year follow-up period with their 95% confidence intervals.
Generalised linear model with Poisson family was employed to calculate the incidence
relative risk ratio (RR) of potential risk factors of hypertension. Multivariable models
included all baseline variables that were associated with incident hypertension in the
bivariate models at 2nd year follow-up (p<0.05). Parental history of blood pressure before
age 60 was also included in the multivariable model. Analyses were repeated after imputing
missing co-variates at baseline by using multiple imputation involving chained equations.
The methods of multiple imputation have been explained elsewhere [18]. Proportion of
data missing ranged from 1% for socio-demographic data to 23% for body weight. Multiple
imputation was done using multiple imputation chained equations (MICE) approach for all
9
missing observations in the exposure variables of interest at baseline. Ten imputed datasets
were generated. Imputed values of missing continuous variables were modelled using linear
regression and predictive mean matching, and imputed values of ordinal variables were
modelled using ordinal logistic regression. Model convergence was checked, and diagnostics
were performed on the imputed dataset. Population attributable fraction (PAF) of major
modifiable risk factors were also estimated directly from the RR coefficients (Box 1, online
supplement).
Results
Enrolment and Response rate
We approached a total of 17,274 individuals in 10,002 households in the three study sites
and 16,287 participants were recruited (the overall response rate was 94.3% at the
participant level; 6,906 Chennai [90.9%], 5,364 Delhi [98.9%], and 4,017 Karachi [94.3%]).
There were 2393 households with single subjects (827 males and 1566 females). Fasting
blood samples were collected at baseline from 13,720 of the participants (response
rate=84.2%). The response rate in the first, second and either of the initial two annual
follow-up surveys were 78.6%, 79.2% and 93.2%, respectively. Individuals with elevated
levels of CVD risk factors (for example; elevated BP in the prehypertension range)
responded more than individuals with all optimal level risk factors. In the second annual
follow-up survey the odds of participation among tobacco users [OR: 1.19; 1.04-1.36], and
individuals with pre-hypertension [OR: 1.18; 1.02-1.36] were high as compared to non-users
and normotensives, respectively.
General characteristics of the study population
10
The mean age (SD) of the population was 42 years (13.3) and 40 years (12.9) in men and
women, respectively. Women were 52% of the study population. Nearly 55% of men and
41% women reported more than secondary education, and one of five individuals was
either illiterate or had no formal education (Table 1). Men were relatively older in Karachi
(mean age 43.2, SD=16.2 years) as compared to Chennai (41.0, 13.1) and Delhi (42.2, 11.8).
Less than primary school education among participants was more frequent in Karachi than
Chennai or Delhi (Table 1).
Mean blood pressure levels
The mean SBP was highest in Delhi (men; 129±17 mmHg and women; 121±18) and lowest in
Karachi (men; 123±20 mmHg and women 117±23). In older age groups, mean SBP was
higher in both men (mean SBP in <=24 and >=65 years age group: 117.4 and 140.1 mmHg)
and women (105.1 and 139.3 mmHg) (Table S1). DBP was also elevated in higher age groups
until the age of 64 years and then started showing a decline especially in Delhi.
Prevalence, awareness, treatment and control of hypertension
Consistent with the mean blood pressure levels, the age adjusted prevalence of
hypertension in men was highest in Delhi (37%) and lowest in Karachi (24%). Twenty eight
percent of women in Delhi and Karachi were hypertensive, and in Chennai, 29% men and
25% women were so (Figure S1). The prevalence was higher with age in both men and
women (Table S2). Hypertension prevalence was particularly high in men <24 years in Delhi
in comparison to adults of same age category in other cities (Table S2). Prehypertension was
prevalent in nearly one third (30.3%) of the study population (men: 36%, and women:
11
25.2%) and the overall prevalence was highest in Delhi (33.3%) and lowest in Karachi
(26.5%) (Figure S1).
Among those with hypertension at baseline, awareness levels were highest in Karachi (men;
27% and women; 57%). They were 24 and 38% respectively, in Chennai and 22 and 36%
respectively, in Delhi. Overall, treatment and control levels of hypertension, respectively,
were very low in Delhi (men; 18 and 7%, women; 33 and 16%) and Chennai (men; 22 and
10%, women; 37 and 20%). More than half of women (55%) in Karachi were treated for
hypertension, while BP control status was observed in 27% (Figure 1 and Table S3).
Although hypertension control rates were higher in individuals with established disease
conditions such as diabetes (22.9%), chronic kidney disease (22.4%), heart disease (38.2%),
and stroke (32.2%), they were still far less than optimal level (Table S4). Based on self-
reported data at the time of the survey, more than two third (68.3%) of individuals with
known hypertension were taking drugs regularly.
Hypertension awareness, treatment, and control showed a positive linear relationship with
educational status (the rates were lowest in illiterate or participants with no formal
education and highest in participants with more than graduate level education) only in men
(Figure S2). However, hypertension prevalence was not associated with educational status.
Incidence of hypertension
The mean SBP and DBP each increased in both men and women without hypertension at
baseline during the two year follow-up period (Figure S3). The highest secular increase in
SBP was in women in the older age groups (>55 years) (Table S5). On average SBP increased
by 2.6 mm Hg (95% CI: 2.1-3.1) and DBP by 0.7 mm Hg (95% CI: 0.4-1.0) over a mean follow
up of 2 years. One of six participants without hypertension (16.2%) at baseline developed
12
hypertension during the 2 year follow-up period. The overall age and non-response rate
adjusted incidence rate was 82.6 per 1000 person-years (95% CI: 80.8-84.4), whereas the
incidence rate adjusted only for non-response rate was 74.6 per 1000 person-years (95% CI:
70.5-79.1) (Table S6 and Table 2). Age adjusted incidence was highest in Delhi (94, 72 and 69
per 1000 person years of follow-up in Delhi, Chennai and Karachi, respectively). Nearly 9 of
10 incident cases (87.9%) were detected at the time of second year survey. Overall, there
were no differences in the incidence of hypertension in men and women (Fig 2). The
incidence of hypertension, however, was lower in women than in men in the younger age
group (<55 years), but was higher in women than men in the older age group (>55 years).
Incidence of hypertension was more than two times higher in participants with pre-
hypertension in all age groups at baseline than those with normal blood pressure (Figure
S4).
Predictors of incident hypertension
Hypertension incidence was similar in men and women (adjusted RR=1.08, 95% CI: 0.92-
1.26) in the multi-variable regression model. Hypertension incidence rate was positively and
linearly associated with age, and inversely and linearly associated with educational status
(Table 2). Overweight (BMI≥25.0 kg/m2) was associated with 28% higher incidence of
hypertension than those with BMI 18-23 kg/m2 (RR=1.28; 95% CI: 1.04-1.59). Current
alcohol use was associated with a 34% higher risk of hypertension relative to non-drinkers
(RR=1.34, 95% CI: 1.10-1.62). Presence of dysglycemia at baseline was associated with
higher incidence of hypertension (RR for diabetes=1.27, 95% CI: 1.05-1.53 and RR for pre-
diabetes=1.12; 95% CI: 0.96-1.32) in comparison to participants with normal glycemic levels.
Incident hypertension was three times higher (RR=2.95, 95% CI: 2.53-3.45) in individuals
13
with pre-hypertension at baseline in comparison to individuals with normal BP. Regression
results were comparable in the complete case analyses and in the analyses with imputed
missing covariates at baseline (Table 2). Collectively, 4 modifiable risk factors (pre-
hypertension, overweight, dysglycemia, and alcohol use) accounted for 78%% of the
population attributable risk of incident hypertension (Table S7).
Discussion
Based on population-based data from adults over 20 years of age from three large cities in
South Asia, we estimated that on an average, one of three men and one of four women
have hypertension. Hypertension awareness, treatment, and control are alarmingly low.
Among non-hypertensive subjects, one of six adults developed hypertension over a two year
period, probably the highest incidence reported in the world. Propensity to develop
hypertension was higher among older, low socio-economic status participants, current
alcohol users, and individuals characterized as overweight, pre-hypertensive and
dysglycemic. The rate of progression from pre-hypertension to hypertension is three times
higher than that of individuals with normal BP.
Our study findings on prevalence, awareness, and treatment of hypertension are consistent
with previously reported data from the Indian sub-continent [6, 19, 20]. The incidence of
hypertension among one of six adults over a two year period is a great cause of concern. It
was significantly higher than the incidence data reported from developed countries [21, 22].
In absolute terms, this translates to more than doubling of the prevalence of hypertension
(assuming that the same rate continues for a decade) in a span of ten years with a
corresponding 243% and 271% increase among men and women, respectively. Our findings
imply that the previous estimates by Kearney and colleagues on the prevalence of
14
hypertension by 2025 (25% increase) is probably an under-estimate [2]. The anticipated
increase in hypertension prevalence, in concurrence with a projected increase in prevalence
of diabetes in this population [23], will lead to dramatic rises in the incidence of
cardiovascular diseases.
We report that the risk for progression to hypertension in this population is associated with
several socio-demographic (age, and educational status) and biological factors (overweight,
blood pressure levels, and dysglycemia). Unlike the previous studies where they had used
prevalent hypertension [24, 25], the outcome variable in our analyses was incident
hypertension, confirming temporality of association. Some findings of public health
significance are that the incidence of hypertension in individuals with pre-hypertension is
more than three times than in those with normal BP, and furthermore, it is considerably
higher in older age groups. Even at younger age groups, hypertension incidence risk is
significantly higher in individuals with pre-hypertension than in those with normal BP. Risk
stratification and targeted preventive strategies among non-hypertensive persons who are
at greatest risk for progression to hypertension may help prevent the rapid rise in
prevalence of hypertension.
Although the overall incidence of hypertension was similar in men and women, the pattern
was distinctly different in older and younger age groups. The advantage women had in the
younger age group is completely offset by higher incidence of hypertension in the older age
group in comparison to men. This may be due to changes in the level of endogenous sex
hormones in the post-menopausal age group as they are associated with greater
longitudinal rise in BP [26]. The predilection of hypertension was 28% higher in participants
above the BMI of 25 kg/m2, in comparison to individuals with BMI of 18-22.99 kg/m2, after
15
adjustment of the effect of waist circumference and other potential confounding variables.
However, it was similar in individuals with BMI of 23-24.99 kg/m2 and in individuals with
BMI of 18-22.99 kg/m2. This implies that the overweight cut-off of BMI>23 kg/m2 as
suggested by some of the authors [27] are probably not relevant for hypertension risk
stratification in South Asian settings.
The susceptibility to develop hypertension is higher in lower educated groups. These
findings affirm our previous observations [28, 29] and is in contrast to the opinion expressed
by a selected group of authors that non-communicable diseases and their risk factors are
not a problem in poor communities [30]. The social gradient in hypertension has profound
implications for the countries and the health care system in south Asia. As described in our
study, a large majority of the incident hypertension remain undiagnosed in the absence of
regular surveillance. They are more likely to result in complications of hypertension. Even if
they are identified earlier, the probability of receiving treatment will be relatively low
especially among individuals in the low socio-economic strata. Further it is well-established
that majority of patients with hypertension will require 2 or more drugs to achieve BP
control [31]. In this context, the high incidence rate of hypertension will also have huge
financial implications for drug requirements. With families and individuals spending a
significant proportion of their income for health care in South Asian countries especially in
the lower socio-economic strata, the impact of the rising prevalence of hypertension on
household economy is substantial.
Strengths and limitations
Prevalence and incidence estimates based on representative population-based sample from
three large cities in South Asia, standardized measurement techniques, uniform study
16
protocol and estimates after accounting for the complex study design are the major
strengths of the study. The response rate in the baseline and follow-up surveys are very
high. The incidence estimates are also adjusted for relatively lower non-response rate in the
follow-up surveys. Finally, generalizability of our findings is limited to adult men and women
living in metropolitan cities in the Indian sub-continent.
Sources of funding
This project has been funded in part by with Federal funds from the United States the
National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH),
Department of Health and Human Services, under contract no. HHSN268200900026C; and
the UnitedHealth Group, Minneapolis, MN, USA. Several members of the research team at
PHFI, Emory University, All India Institute of Medical Sciences, Aga Khan University and
Madras Diabetes Research Foundation were/are supported by D43 NCDs in India Training
Program through Award Number D43HD05249 from the Eunice Kennedy Shriver National
Institute of Child Health & Human Development (NICHD) and Fogarty International Center;
and the Wellcome Trust (Grant No: 096735/B/11/Z). Panniyammakal Jeemon is currently
supported by a Wellcome Trust-DBT India Alliance Clinical and Public Health Intermediate
Fellowship.
Disclosures: None
Acknowledgement of grant support: This project has been funded in part by with Federal
funds from the United States the National Heart, Lung, and Blood Institute (NHLBI), National
Institutes of Health (NIH), Department of Health and Human Services, under contract no.
HHSN268200900026C; and the UnitedHealth Group, Minneapolis, MN, USA.
Potetial conflicts of interests: None to declare
17
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19
Figure legends
Figure 1: Prevalence, awareness, treatment and control of hypertension in adults over 20-
years of age in three South Asian cities. The denominator for awareness, treatment and
control are all individuals with hypertension at baseline.
Figure 2: Incidence of hypertension stratified by age groups in men and women. Incidence
rate is given per 1000 person years of follow-up.
20
Table 1. General characteristics of the study population
Variables
Chennai
Delhi
Karachi
Total
Women
(N=3718)
Women
(N=2684)
Women
(N=2125)
Women
(N=8527)
Mean age
(SD)
39.25 (11.9)
41.23 (11.1)
40.01 (12.9)
40.12 (12.9)
Education, %
ES1
9.3
24.4
9.8
14.8
ES2
27.3
24.4
26.2
26
ES3
44.1
24
21.6
31.9
ES4
19.2
27.2
42.5
27.3
Socio economic status, %
High
18.8
45.3
32.9
31.3
Medium
35.2
23.5
48.1
34.0
Low
46.1
31.2
19.1
34.7
21
ES1=educational status (above graduates), ES2=secondary school education, ES3=primary school and above, ES4=lower than primary or no
formal education or illiterates. High is third tertile, medium is second tertile, low is first tertile in the principal component analysis score.
22
Table 2: Incidence of and risk factors for hypertension
Variables
N
Un-adjusted
incidence rate per
1000 p-y (95% CI)
Adjusted
incidence rate
per 1000 p-y
(95% CI)
Unadjusted RR, CI
Adjusted RR,CI
(n=6250)
Adjusted RR,CI
(without
Karachi)
(n=4680)
Adjusted RR, CI
(Missing co-
variates
imputed at
baseline)
Overall
8146
80.5 [76.3,85.0]
74.6[70.5,79.1]
City
Chennai
3528
76.0[69.6,83.1]
71.5[65.4,78.2]
1
1
1
1
Delhi
2408
95.7[87.6,104.6]
93.6[85.8,102.2]
1.54ǂ[1.36,1.74]
1.27** [1.09,1.47]
1.21*[1.04,1.41]
1.28***[1.12,1.4
7]
Karachi
2210
70.4[63.3,78.3]
69.0[62.0,76.9]
1.16* [1.01,1.33]
1.20 [1.00,1.44]
NA
1.23* [1.05, 1.45]
Age groups, years
20-24
718
28.6[21.1,38.7]
26.8[19.2,38.6]
1
1
1
1
25-34
2346
50.1[44.1,56.9]
45.1[39.3,52.0]
1.63**[1.12,2.36]
1.38 [0.89,2.13]
1.33 [0.76,2.35]
1.37 [0.94, 2.00]
35-44
2588
74.8[67.7,82.6]
65.2[58.6,72.8]
2.38ǂ[1.66,3.41]
1.62*[1.05,2.48]
1.65 [0.95,2.88]
1.64** [1.13,
2.37]
45-54
1530
113.9[102.5,126.5]
110.1[98.9,122.8]
3.99ǂ[2.78,5.71]
2.35ǂ [1.52,3.63]
2.32ǂ [1.33,4.06]
2.42ǂ [1.66,3.52]
55-64
670
160.9[140.8,183.8]
162.1
[143.2,184.3]
5.97ǂ[4.15,8.61]
3.44ǂ [2.21,5.35]
3.45ǂ [1.95,6.09]
3.46ǂ [2.36,5.07]
65-65
294
147.2[119.5,181.5]
152.9[125.9,187.
7]
5.71ǂ[3.84,8.48]
3.15ǂ [1.96,5.06]
3.38ǂ [1.86,6.16]
3.08ǂ [2.04,4.65]
Sex
Female
4627
70.9[65.7,76.5]
65.4[60.3,71.1]
1
1
1
1
Male
3519
93.1[86.3,100.5]
92.3[85.3,99.9]
1.43ǂ[1.28,1.60]
1.08 [0.92,1.26]
1.17 [0.98,1.40]
1.05 [0.92, 1.21]
23
Education
ES1
1385
75.7[66.3,86.5]
67.0[58.3,77.3]
1
1
1
1
ES2
2442
77.8[70.4,86.0]
71.6[64.5,79.8]
1.02 [0.85,1.22]
1.15 [0.95,1.39]
1.15 [0.93,1.44]
1.13 [0.95, 1.34]
ES3
2672
80.8[73.4,88.8]
75.1[68.0,83.2]
1.04[0.87,1.24]
1.19 [0.98,1.45]
1.23 [0.99,1.54]
1.14 [0.95, 1.36]
ES4
1647
88.3[78.8,99.0]
85.8[76.3,97.0]
1.24*[1.03,1.49]
1.29*[1.05,1.60]
1.25*[0.97,1.61]
1.23* [1.02, 1.49]
BMI, kg/m2
<18.00
454
40.5[29.5,55.7]
34.0[24.3,49.0]
0.65*[0.45,0.94]
0.73 [0.50,1.07]
0.82[0.53,1.25]
0.82 [0.60, 1.12]
18.00-22.99
2010
59.1[52.1,67.1]
54.3[47.6,62.2]
1
1
1
1
23.00-24.99
1031
79.7[68.3,93.0]
72.5[62.1,85.2]
1.31**[1.07,1.61]
1.14 [0.92,1.42]
1.05 [0.82,1.34]
1.10 [0.91, 1.34]
≥25.00
3272
98.6[91.2,106.6]
87.7[81.1,95.0]
1.57ǂ[1.34,1.83]
1.28*[1.04,1.59]
1.18 [0.91,1.52]
1.25* [1.03, 1.52]
Waist circumference , cm
Non obese
3917
60.0[54.8,65.7]
55.2[50.1,61.1]
1
1
1
1
Obese
4229
99.4[92.9,106.3]
89.5[83.4,96.1]
1.63ǂ[1.44,1.84]
1.04 [0.86,1.26]
1.05 [0.84,1.32]
1.06 [0.90, 1.27]
Tobacco use
Never users
6326
75.8[71.2,80.8]
70.4[65.8,75.3]
1
1
1
1
Ever users
1820
96.6[87.1,107.1]
96.5[86.9,107.5]
1.41ǂ[1.24,1.59]
1.08 [0.92,1.27]
1.04 [0.86,1.26]
1.09 [0.95, 1.26]
Current alcohol use
No
7231
75.8[71.4,80.4]
70.8[66.5,75.5]
1
1
1
1
Yes
915
119.3[104.3,136.4]
113.2[98.8,130.3]
1.55ǂ[1.33,1.80]
1.34**
[1.10,1.62]
1.25**[1.02,1.54]
1.37ǂ [1.15,1.63]
Physical Activity
Low
811
92.9[79.6,108.5]
85.0[72.8,100.0]
1
1
1
1
Medium
2181
84.7[76.7,93.6]
77.6[69.8,86.5]
0.88[0.73,1.07]
0.94 [0.76,1.16]
1.01 [0.77,1.33]
0.96 [0.80, 1.15]
High
5154
76.5[71.3,82.1]
72.3[67.1,78.0]
0.76**[0.63,0.90]
1.03 [0.85,1.26]
1.00 [0.77,1.30]
1.03 [0.86, 1.23]
24
Glycemic status
Normal
2892
123.9[111.0,138.4]
49.7[44.3,55.8]
1
1
1
1
Diabetes
1282
83.5[76.4,91.1]
119.2[106.9,133.
2]
2.39ǂ[2.04,2.80]
1.27*[1.05,1.53]
1.32* [1.06,1.64]
1.22* [1.03, 1.44]
Pre-diabetes
2977
54.4[48.7,60.8
77.3[70.7,84.8]
1.56ǂ[1.34,1.80]
1.12 [0.96,1.32]
1.14 [0.94,1.39]
1.09 [0.95, 1.26]
Parental history of hypertension
No
6896
82.1[77.5,87.0]
74.9[70.4,79.8]
1
1
1
1
Yes
1250
71.9[62.2,83.2]
73.2[62.9,85.6]
0.97 [0.83,1.15]
1.11 [0.93,1.32]
1.20 [0.99,1.47]
1.10 [0.93, 1.29]
eGFR , ml/min/1.73 m2
>=60
7137
77.8[73.3,82.5]
73.3[69.0,78.0]
1
NA
1
NA
<60
121
142.4[103.2,196.5]
128.7[95.5,177.4]
1.94ǂ[1.42,2.66]
1.10 [0.69,1.74]
Baseline blood pressure levels , mmHg
Normal BP
4420
38.0[34.1,42.3]
35.7[31.8,40.3]
1
1
1
1
Pre-
hypertension
3726
131.1[123.1,139.6]
129.4
[121.5,137.9]
3.62ǂ [3.17,4.14]
2.95ǂ
[2.53,3.45]
3.3ǂ[2.74,4.04]
2.90ǂ [2.52,3.34]
Years of
follow-up
1.22**[1.08,
1.38]
1.23** [1.06,
1.41]
1.22* [1.04,
1.41]
1.18* [1.04, 1.35]
*p<0.05, **P<0.01, ǂp<0.001, RR=relative risk ratio, Adjusted for uneven response rate in different risk groups, model includes serum
creatinine based eGFR measurements from Delhi and Chennai (data are not available in Karachi). p-y=person years, ci=confidence interval,
eGFR=estimated glomerular filtration rate, BMI=body mass index, ES1=educational status (above graduates), ES2=secondary school education,
ES3=primary school and above, ES4=lower than primary or no formal education or illiterates.
... In addition, the prevalence of prehypertension was also assessed among the study population. Though pre-hypertension has not been recognized as a separate category of BP, it has been demonstrated to be an important risk factor for developing hypertension in the future in many studies 10 . ...
... Men exhibited higher prevalence of hypertension than women in our study which was 10 ; young adults in our study may be at increased risk for developing hypertension in the near future. Similar results were noted in a few other studies 20,29 indicating that lifestyle diseases such as hypertension are no longer limited to elderly population. ...
... Mean systolic and diastolic blood pressure (mmHg) by age, gender and blood pressure categories SD, standard deviation; BP, blood pressure; HTN, hypertension in accordance with most epidemiological studies of hypertension3,5,7,10,14,20,24,25,28 . Age was found to be the most important risk factor for hypertension with the mean systolic and diastolic BPs showing linear increase with advancing age in both sexes. ...
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Background & objectives: The prevalence of hypertension is increasing among all ethnic groups across the globe with only a handful of studies from India addressing the prevalence of hypertension among tribal population. In view of paucity of data, this study was aimed at estimating the prevalence of hypertension and associated risk factors among tribal population of Kashmir, India. Methods: This cross-sectional survey included 6808 tribals aged >20 yr (5695 Gujjars and 1113 Bakarwals) from five randomly selected districts of Kashmir. Modified WHO-STEPS surveillance questionnaire was used to collect relevant data. Hypertension was defined by Joint National Committee on Prevention, Detection, Evaluation and Treatment of Hypertension (JNC 8) criteria. Results: The mean age of our study participants was 43.12 ± 15.69 years. Overall prevalence of hypertension [95% confidence interval (CI)] was 41.4% (39.9-42.9%) [men=46.7% (44.1-49.1%); women=37.9% (35.9-39.9%)]. The prevalence of prehypertension (95% CI) in our study was 35 per cent (33.7-36.6%). Higher age [adjusted odds ratio (OR) (95% CI): >70 yr-2.2 (1.9-2.4)], passive smoking [OR-1.3 (1.1-1.5)], family history of hypertension [OR-1.6 (1.4-1.7)] and obesity [OR-1.3 (1.1-1.6)] were significantly associated with hypertension. A weak positive correlation was observed between BP (systolic/diastolic) with haemoglobin, red blood cell count and haematocrit (P<0.05). Interpretation & conclusions: Gujjar and Bakarwal tribes of Jammu and Kashmir showed high prevalence of hypertension. Hence, urgent policies and reforms are needed to tackle this silent epidemic and further studies focusing on community-based interventions are required.
... Essential hypertension (HT) is a major public health problem worldwide and indeed, associated with increased blood pressure and its related complications. In particular, HT patients have at greater risk for manifestation of stroke and cardiovascular disease (CVD), including myocardial infarction [1]. Although precise etiology of this disease is poorly understood, probability of HT patients to develop future CVD risk appears to be more due to involvement of some common risk factors such as aging, high body mass index, dyslipidemia and sedentary lifestyle [2]. ...
... Essential hypertension is a major and escalating public-health and clinical challenge worldwide in the wake of urbanization, surplus energy intake, increasing body weight, and sedentary life habits. HT confers a 2-fold the risk of developing cardio vascular disease [1,5]. It has been documented that hypertension also act as a driver of cardio-metabolic risks [9]. ...
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... Task shifting and task sharing allow tasks to be shifted from highly trained healthcare workers (HCWs) to HCWs with less training and qualifications, respectively, and jobs to be shared with an equally competent cadre of HCWs. During the COVID-19 pandemic, this enables for more efficient use of limited human resources working in overcrowded health systems (6) . ...
... The present study revealed that the incidence of hypertension was high among the studied populations. This finding agrees with results from previous studies conducted in the Gulf region and other developing countries [18,19]. An increase in BP with age is considered a universal aspect of human aging and the present study supported the fact that advancing age is an important risk factor for hypertension. ...
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Background Hypertension is a major global health concern affecting approximately 1.13 billion people worldwide, with most of them residing in developing countries. The aim of this study was to determine the incidence of different stages of hypertension and its associated modifiable and non-modifiable risk factors among patients in military-setting hospitals in Tabuk, Saudi Arabia. Methods This retrospective cohort study was conducted at two hospitals in Tabuk, Saudi Arabia. The data were collected from hospital electronic records from 1 January 2019 to 31 December 2019. The blood pressure levels of patients from the last three separate medical visits were recorded. Descriptive statistics and multinomial logistic regression were used for the data analysis. Results The study included 884 hypertensive patients. The incidences of stage of elevated BP, stage 1, stage 2, and hypertension crisis were 60.0, 29.5, 7.0, and 3.5 cases per 1000 persons. Multivariate analysis indicated that progression from the stage of elevated blood pressure to hypertension crisis was significantly associated with advanced age (odds ratio [OR] = 3.62, 95% confidence interval [CI] = 1.99–8.42), male sex (OR = 2.84, 95% CI: 0.57–5.92), and a positive family history of hypertension (OR = 1.95, 95% CI: 1.23–3.09). Other key determinants of the development of stage of elevated blood pressure to hypertension crisis were current smoking status (OR = 1.74, 95% CI: 1.23–4.76), and physical inactivity (OR = 6.48, 95% CI: 2.46–9.14). Conclusion The incidence stage of elevated blood pressure was high among the patients investigated at armed forces hospitals in Tabuk, Saudi Arabia. The logistic regression model proposed in the present study can be used to predict the development of different stages of hypertension. Age, sex, marital status, family history, smoking status, and physical activity play an important role in the development of hypertension. Better strategies to improve awareness, screening, treatment, and management of hypertension are required in Saudi Arabia.
Thesis
L’hypertension artérielle (HTA) est l’un des principaux facteurs de risque de maladies cardiovasculaires. Elle touche près d’un adulte sur trois dans le monde et occupe la première place en termes d’années de vie en bonne santé perdues chez les femmes, et la deuxième chez les hommes derrière le tabagisme. La prévalence de l’HTA, comme l’incidence, varient entre différentes zones géographiques mais également selon le statut socioéconomique. Ces inégalités territoriales et socioéconomiques sont cependant encore mal comprises. Or, peu de travaux se sont penchés sur ces inégalités en France et les études d’incidence de l’HTA restent rares. Dans ce contexte, l’objectif principal de cette thèse est d’estimer et d’expliquer les inégalités territoriales et sociales dans l’HTA. Les données de deux cohortes ont été exploitées : la cohorte française CONSTANCES qui regroupe des individus âgés de 18 à 69 ans et recrutés depuis 2012 (n=63 000) et la cohorte américaine HRS qui inclut des adultes de plus de 50 ans suivi depuis le début des années 90 (n=17 000). Ce travail met en évidence l’existence d’une part, de fortes disparités territoriales et d’autre part, d’inégalités sociales marquées de prévalence de l’HTA en France. Des inégalités sociales importantes sont également observées dans l’incidence de l’HTA aux Etats-Unis. Cependant, les déterminants comportementaux et anthropométrique pris en compte n’expliquent que partiellement les inégalités observées. Par ailleurs, l’ampleur des inégalités et la forme des associations entre statut socioéconomique, facteurs comportementaux et anthropométrique, et HTA diffèrent entre les hommes et les femmes. Ces travaux apportent de nouveaux éléments pour une meilleure identification des populations les plus vulnérables et des leviers d’action efficaces pour la prévention de l’HTA et la réduction des inégalités dans l’HTA.
Chapter
Asia is the largest and most populous continent, with roughly 60% of the total population in the world. It is divided into five regions, namely Middle East, East Asia, South Asia, Southeast Asia, and Central Asia. Asian countries of interest in this chapter would include Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei, Cambodia, China, Georgia, India, Indonesia, Iran, Iraq, Israel, Japan, Jordan, Kazakhstan, Kuwait, Kyrgyzstan, Laos, Lebanon, Malaysia, Maldives, Mongolia, Myanmar, Nepal, North/South Korea, Oman, Pakistan, Philippines, Qatar, Russia, Saudi Arabia, Singapore, Sri Lanka, Syria, Tajikistan, Thailand, Timor-Leste, Turkey, Turkmenistan, United Arab Emirates, Uzbekistan, Vietnam, and Yemen. Much of the literature reviewed would involve the countries in Southeast Asia (SEA) (e.g., Malaysia, Indonesia, Thailand, Singapore, Philippines, Vietnam, Laos, Cambodia, Myanmar, Brunei, East Timor), Japan, and countries in the middle East. This chapter discusses the prevalence, incidence, and risk factors of hypertension across the Asian countries. It is important to highlight that the various literature reviewed here would have different definitions of hypertension and blood pressure control, as well as different methods in determining blood pressure measurements. Period of evaluation also varies from study to study. Caution must be exercised when interpreting the presented numbers, specifically for the prevalence and incidence data.
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Background In the Sub-Saharan African region, data on Arterial Hypertension (AHT) from longitudinal studies are scattered.This work analyzes the prevalence and incidence of AHT and its associated factors in an open cohort of Congolese adults in South Kivu. Methods Between 2012 and 2019, 2,633 subjects aged ≥ 15 years were monitored for at least 3 years. Baseline and follow-up included blood pressure (BP) measurements. AHT was defined as BP of at least 140/90 mmHg or intake of antihypertensive medication in patients with known AHT. Cox regression was used to analyze the association between risk factors and risk of AHT. Results The prevalence of AHT increased from 24.8% to 29.0% and the proportion of controlled hypertensive participants rose from 46.9% to 56.6% (p=0.03). During the 7,525 person-years observation period, the incidence of AHT among 1,981 participants without AHT at baseline was 19.4/1000 person-years. The annual incidence of AHT (2.4% per year) was higher in urban (5.0% per year) than in rural areas (2.0% per year). The strongest determinants for incident AHT (p<0.05) were male gender [adjusted HR (aHR)=1.67 (1.08-2.59)], age between 40-59 years [aHR=2.26 (1.48-3.45)], age ≥ 60 years [aHR=3.53 (2.11-5.93)], urban residence [aHR=3.37 (2.07-5.50)], pre-hypertension [aHR=1.77 (1.16-2.70)], abdominal obesity [aHR=1.99 (1.29-3.07)] and smoking [aHR=2.01 (1.12-3.60)]. Conclusion The present study shows that the prevalence and incidence of AHT are increasing in the Congolese general population. Consequently, improved strategies for the prevention and management of non-communicable diseases are very important in Sub-Saharan Africa.
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Background India faces a high burden of diabetes and hypertension. Currently, there is a dearth of economic evidence about screening programmes, affected age groups, and frequency of screening for these diseases in Indian settings. We assessed the cost effectiveness of population-based screening for diabetes and hypertension compared with current practice in India for different scenarios, according to type of screening test, population age group, and pattern of health-care use. Methods We used a hybrid decision model (decision tree and Markov model) to estimate the lifetime costs and consequences from a societal perspective. A meta-analysis was done to assess the effectiveness of population-based screening. Primary data were collected from two Indian states (Haryana and Tamil Nadu) to assess the cost of screening. The data from the National Health System Cost Database and the Costing of Health Services in India study were used to determine the health system cost of diagnostic tests and cost of treating diabetes or hypertension and their complications. A total of 962 patients were recruited to assess out-of-pocket expenditure and quality of life. Parameter uncertainty was evaluated using univariate and multivariable probabilistic sensitivity analyses. Finally, we estimated the incremental cost per quality-adjusted life-year (QALY) gained with alternative scenarios of scaling up primary health care through a health and wellness centre programme for the treatment of diabetes and hypertension. Findings The incremental cost per QALY gained across various strategies for population-based screening for diabetes and hypertension ranged from US$0·02 million to $0·03 million. At the current pattern of health services use, none of the screening strategies of annual screening, screening every 3 years, and screening every 5 years was cost-effective at a threshold of 1-time per capita gross domestic product in India. In the scenario in which health and wellness centres provided primary care to 20% of patients who were newly diagnosed with uncomplicated diabetes or hypertension, screening the group aged between 30 and 65 years every 5 years or 3 years for either diabetes, hypertension, or a comorbid state (both diabetes and hypertension) became cost-effective. If the share of treatment for patients with newly diagnosed uncomplicated diabetes or hypertension at health and wellness centres increases to 70%, from the existing 4% at subcentres and primary health centres, annual population-based screening becomes a cost saving strategy. Interpretation Population-based screening for diabetes and hypertension in India could potentially reduce time to diagnosis and treatment and be cost-effective if it is linked to comprehensive primary health care through health and wellness centres for provision of treatment to patients who screen positive. Funding None.
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Background: The benefits of blood pressure lowering treatment for prevention of cardiovascular disease are well established. However, the extent to which these effects differ by baseline blood pressure, presence of comorbidities, or drug class is less clear. We therefore performed a systematic review and meta-analysis to clarify these differences. Method: For this systematic review and meta-analysis, we searched MEDLINE for large-scale blood pressure lowering trials, published between Jan 1, 1966, and July 7, 2015, and we searched the medical literature to identify trials up to Nov 9, 2015. All randomised controlled trials of blood pressure lowering treatment were eligible for inclusion if they included a minimum of 1000 patient-years of follow-up in each study arm. No trials were excluded because of presence of baseline comorbidities, and trials of antihypertensive drugs for indications other than hypertension were eligible. We extracted summary-level data about study characteristics and the outcomes of major cardiovascular disease events, coronary heart disease, stroke, heart failure, renal failure, and all-cause mortality. We used inverse variance weighted fixed-effects meta-analyses to pool the estimates. Results: We identified 123 studies with 613 815 participants for the tabular meta-analysis. Meta-regression analyses showed relative risk reductions proportional to the magnitude of the blood pressure reductions achieved. Every 10 mm Hg reduction in systolic blood pressure significantly reduced the risk of major cardiovascular disease events (relative risk [RR] 0·80, 95% CI 0·77-0·83), coronary heart disease (0·83, 0·78-0·88), stroke (0·73, 0·68-0·77), and heart failure (0·72, 0·67-0·78), which, in the populations studied, led to a significant 13% reduction in all-cause mortality (0·87, 0·84-0·91). However, the effect on renal failure was not significant (0·95, 0·84-1·07). Similar proportional risk reductions (per 10 mm Hg lower systolic blood pressure) were noted in trials with higher mean baseline systolic blood pressure and trials with lower mean baseline systolic blood pressure (all ptrend>0·05). There was no clear evidence that proportional risk reductions in major cardiovascular disease differed by baseline disease history, except for diabetes and chronic kidney disease, for which smaller, but significant, risk reductions were detected. β blockers were inferior to other drugs for the prevention of major cardiovascular disease events, stroke, and renal failure. Calcium channel blockers were superior to other drugs for the prevention of stroke. For the prevention of heart failure, calcium channel blockers were inferior and diuretics were superior to other drug classes. Risk of bias was judged to be low for 113 trials and unclear for 10 trials. Heterogeneity for outcomes was low to moderate; the I(2) statistic for heterogeneity for major cardiovascular disease events was 41%, for coronary heart disease 25%, for stroke 26%, for heart failure 37%, for renal failure 28%, and for all-cause mortality 35%. Interpretation: Blood pressure lowering significantly reduces vascular risk across various baseline blood pressure levels and comorbidities. Our results provide strong support for lowering blood pressure to systolic blood pressures less than 130 mm Hg and providing blood pressure lowering treatment to individuals with a history of cardiovascular disease, coronary heart disease, stroke, diabetes, heart failure, and chronic kidney disease. Funding: National Institute for Health Research and Oxford Martin School.
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Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.
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South Asian males constitute the largest proportion of the United Arab Emirates (UAE) population. Minimal data is available on the prevalence of hypertension among South Asian immigrants in the UAE. We determined the prevalence, associated factors, awareness, treatment, and control of hypertension among male South Asian immigrants from India, Pakistan and Bangladesh residing in the UAE. We recruited a representative sample (n = 1375; 76.4% participation rate) of South Asian adult (≥18 years) immigrant males, including Indian (n = 433), Pakistani (n = 383) and Bangladeshi (n = 559) nationalities in Al Ain, UAE (January-June 2012). Blood pressure, height, body mass, waist and hip circumference data were obtained using standard protocols. Information related to socio-demographics, lifestyle factors, history of diagnosis and treatment of hypertension was collected through a pilot-tested adapted version of the STEPS instrument, developed by the World Health Organization for the measurement of non-communicable disease risk factors at the country level . Mean age of participants was 34.0 years (95% confidence interval (CI): 33.4, 34.5 years) and the overall prevalence of hypertension was 30.5% (95% CI 28.0, 32.8). In this study, 62% of study participants had never had their blood pressure measured. Over three quarters (76%) of the sample classified as hypertensive were not aware of their condition. Less than half (48.5%) of the sample that were aware of their hypertension reported using antihypertensive medication and only 8.3% had their hypertension under control (<140/90 mmHg). Hypertensive participants were more likely to be overweight (adjusted odds ratio (AOR) = 1.43; 95% CI 1.01, 2.01); obese (AOR = 2.49; 95% CI: 1.51, 4.10); have central obesity (AOR = 2.01; 95% CI 1.37, 2.92); have a family history of hypertension (AOR = 1.51; 95% CI 1.05, 2.17); and were less likely to walk 30 minutes daily (AOR = 1.79; 95% CI 1.24, 2.60). The prevalence of hypertension in a representative sample of young male South Asian immigrants living in the UAE was relatively high. However, the awareness, treatment, and control of hypertension within this population were very low. Strategies are urgently needed to improve the awareness and control of hypertension in this large population of migrant workers in the UAE.
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Although South Asians experience cardiovascular disease (CVD) and risk factors at an early age, the distribution of CVD risks across the socioeconomic spectrum remains unclear. We analysed the 2011 Centre for Cardiometabolic Risk Reduction in South Asia survey data including 16,288 non-pregnant adults (≥20 years) that are representative of Chennai and Delhi, India, and Karachi, Pakistan. Socioeconomic status (SES) was defined by highest education (primary schooling, high/secondary schooling, college graduate or greater); wealth tertiles (low, middle, high household assets) and occupation (not working outside home, semi/unskilled, skilled, white-collar work). We estimated age and sex-standardized prevalence of behavioural (daily fruit/vegetables; tobacco use), weight (body mass index; waist-to-height ratio) and metabolic risk factors (diabetes, hypertension, hypercholesterolaemia; hypo-HDL; and hypertriglyceridaemia) by each SES category. Across cities, 61.2% and 16.1% completed secondary and college educations, respectively; 52.8% reported not working, 22.9% were unskilled; 21.3% were skilled and 3.1% were white-collar workers. For behavioural risk factors, low fruit/vegetable intake, smoked and smokeless tobacco use were more prevalent in lowest education, wealthy and occupation (for men only) groups compared to higher SES counterparts, while weight-related risks (body mass index 25.0-29.9 and ≥30 kg/m(2); waist-to-height ratio ≥0.5) were more common in higher educated and wealthy groups, and technical/professional men. For metabolic risks, a higher prevalence of diabetes, hypertension and dyslipidaemias was observed in more educated and affluent groups, with unclear patterns across occupation groups. SES-CVD patterns are heterogeneous, suggesting customized interventions for different SES groups may be warranted. Different behavioural, weight, and metabolic risk factor prevalence patterns across SES indicators may signal on-going epidemiological transition in South Asia. © The European Society of Cardiology 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
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Aim: To estimate the prevalence of, and assess factors associated with, diabetes and prediabetes in three South Asian cities. Methods: Using a multi-stage cluster random sample representative of each city, 16,288 subjects aged ≥20 years (Chennai: 6906, Delhi: 5365 and Karachi: 4017) were recruited to the Centre for cArdio-metabolic Risk Reduction in South-Asia (CARRS) Study. Fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) were measured in 13720 subjects. Prediabetes was defined as FPG 100-125mg/dl (5.6-6.9mmol/l) and/or HbA1c 5.7-6.4% (39-46mmol/mol) and diabetes as self-report and/or drug treatment for diabetes and/or FPG≥126mg/dl (≥7.0mmol/l) and/or HbA1c≥6.5% (48mmol/mol). We assessed factors associated with diabetes and prediabetes using polytomous logistic regression models. Results: Overall 47.3-73.1% of the population had either diabetes or prediabetes: Chennai 60.7% [95%CI: 59.0-62.4%] (diabetes - 22.8% [21.5-24.1%], prediabetes - 37.9% [36.1-39.7%]); Delhi 72.7% [70.6-74.9%] (diabetes - 25.2% [23.6-26.8%], prediabetes - 47.6% [45.6-49.5%]); and Karachi 47.4% [45.7-49.1%]; (diabetes - 16.3% [15.2-17.3%], prediabetes - 31.1% [29.5-32.8%], respectively). Proportions of self-reported diabetes were 55.1%, 39.0%, and 48.0% in Chennai, Delhi, and Karachi, respectively. City, age, family history of diabetes, generalized obesity, abdominal obesity, body fat, high cholesterol, high triglyceride, and low HDL cholesterol levels were each independently associated with prediabetes, while the same factors plus waist-to-height ratio and hypertension were associated with diabetes. Conclusion: Six in ten adults in large South Asian cities have either diabetes or prediabetes. These data call for urgent action to prevent diabetes in South Asia.
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Definitions for overweight and obesity are universally applied using body mass index (BMI), based on morbidity and mortality data derived from white populations. However, several studies have shown higher body fat, excess metabolic perturbations, and cardiovascular risk factors at lower value of BMI in Asian versus white populations. Definitive guidelines have been published to classify a BMI of ≥23 kg/m(2) and ≥25 kg/m(2) as overweight and obese, respectively, by the Indian Consensus Group (for Asian Indians residing in India) and a BMI of ≥23 kg/m(2) for screening for diabetes by the National Institute of Health and Care Excellence of the United Kingdom (for migrant south Asians) and, in an encouraging initiative recently (2015), by the American Diabetes Association (for all Asian ethnic groups in the United States). Overall, multiple studies, and now several guidelines, emphasize early intervention with diet and physical activity in Asian ethnic groups for prevention and management of obesity-related noncommunicable diseases. By application of these guidelines, an additional 10-15% of the population in India would be labeled as overweight/obese, and more South Asians/Asians will be diagnosed with diabetes in the United Kingdom and the United States. Additional health resources need to be allocated to deal with increasing numbers of Asians with obesity-related noncommunicable diseases, and research is needed to evolve cost-effective interventions. Finally, consensus based on data is needed so that the World Health Organization and other international agencies could take definitive steps for revision of classification of BMI for Asian populations globally.
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Raised blood pressure is the biggest single contributor to the global burden of disease and to global mortality. The numbers of people affected and the prevalence of high blood pressure worldwide are expected to increase over the next decade. Preventive strategies are therefore urgently needed, especially in less developed countries, and management of hypertension must be optimised. Genetic advances in some rare causes of hypertension have been made lately, but the aggregate effect on blood pressure of all the genetic loci identified to date is small. Hence, intervention on key environmental determinants and effective implementation of trial-based therapies are needed. Three-drug combinations can control hypertension in about 90% of patients but only if resources allow identification of patients and drug delivery is affordable. Furthermore, assessment of optimal drug therapy for each ethnic group is needed. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Background Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher levels.