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R E S E A R C H Open Access
Ethnic differences in prevalence and risk
factors for hypertension in the Suriname
Health Study: a cross sectional population
study
Ingrid S. K. Krishnadath
1*
, Vincent W. V. Jaddoe
3,4
, Lenny M. Nahar-van Venrooij
1
and Jerry R. Toelsie
2
Abstract
Background: Limited information is available about the prevalence, ethnic disparities, and risk factors of
hypertension within developing countries. We used data from a nationwide study on non-communicable disease
(NCD) risk factors to estimate, explore, and compare the prevalence of hypertension overall and in subgroups of risk
factors among different ethnic groups in Suriname.
Method: The Suriname Health Study used the World Health Organization Steps design to select respondents with
a stratified multistage cluster sample of households. The overall and ethnic specific prevalences of hypertension
were calculated in general and in subgroups of sex, age, marital status, educational level, income status,
employment, smoking status, residence, physical activity, body mass index (BMI), and waist circumference (WC).
Differences in the prevalence between ethnic subgroups were assessed using the Chi-square test. We used several
adjustment models to explore whether the observed ethnic differences were explained by biological, demographic,
lifestyle, or anthropometric risk factors.
Results: The prevalence of hypertension was 26.2 % (95 % confidence interval 25.1 %-27.4 %). Men had higher
mean values for systolic and diastolic blood pressure compared to women. Blood pressure increased with age.
The prevalence was highest for Creole, Hindustani, and Javanese and lowest for Amerindians, Mixed, and Maroons.
Differences between ethnic groups were measured in the prevalence of hypertension in subcategories of sex,
marital status, education, income, smoking, physical activity, and BMI. The major difference in association of ethnic
groups with hypertension was between Hindustani and Amerindians.
Conclusion: The prevalence of hypertension in Suriname was in the range of developing countries. The highest
prevalence was found in Creoles, Hindustani, and Javanese. Differences in the prevalence of hypertension were
observed between ethnic subgroups with biological, demographic, lifestyle, and anthropometric risk factors. These
findings emphasize the need for ethnic-specific research and prevention and intervention programs.
Keywords: Amerindian, Ethnicity, Hypertension, Risk factors, Suriname
* Correspondence: Ingrid.Krishnadath@uvs.edu
1
Department of Public Health, Faculty of Medical Sciences, Anton de Kom
University of Suriname, Paramaribo, Suriname
Full list of author information is available at the end of the article
© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Krishnadath et al. Population Health Metrics (2016) 14:33
DOI 10.1186/s12963-016-0102-4
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Hypertension is the fourth-largest contributor to prema-
ture death in industrialized countries and the seventh in
developing countries [1–3]. The increasing prevalence of
hypertension in developing countries could be the result
of factors like urbanization, population aging, unhealthy
dietary habits, and social stress [4]. In several industrial-
ized countries, ethnic differences in the prevalence of
hypertension and its risk factors have been described
extensively [5–17]. In contrast, in developing countries
less research has been conducted. Studies reported
higher prevalence of hypertension among adults from
African descent followed by those of Asian or Hispanic
descent, as compared to Caucasians [7–9, 18–20].
The Republic of Suriname, located on the northeast of
South America, is an upper-middle income country with
a multi-ethnic and multicultural population, with inhabi-
tants of mainly Indian, African, and Indonesian descent.
In this country, cardiovascular disease has been the main
cause of mortality for decades in each ethnic group [21].
However, information about the prevalence and risk
factors of hypertension among these different groups is
limited. So far, a study from 2001, limited to three
coastal districts, reported a hypertension prevalence of
33 % in adults between the ages of 18-55 years [22]. Of
all participants, 70 % were physically inactive, 30 %
smoked, 20 % were obese, and 15 % had high total choles-
terol levels. In adults, the highest prevalence of hyperten-
sion has been observed in Creoles [22]. In adolescents,
hypertension was measured more frequently in Hindustani
and Javanese [23].
Weuseddatafromanationwidestudyonnon-
communicable disease (NCD) risk factors [24], to estimate,
explore, and compare the prevalence of hypertension over-
all and in subgroups of biological, demographic, lifestyle,
and anthropometric risk factors among different ethnic
groups in Suriname.
Methods
Design
We used data from the Suriname Health Study, the first
nationwide study on NCD risk factors [24], which was
designed according to World Health Organization
(WHO) Steps guidelines [25]. The Ethics Committee of
the Ministry of Health in Suriname (Commissie mensge-
bonden wetenschappelijk onderzoek (ref: VG 004-2013))
approved this research. Suriname has approximately
550,000 inhabitants, categorized into 15.7 % Creole
(descendants of African plantation slaves), 27.4 %
Hindustani (people of Indian heritage), 13.7 % Javan-
ese (descendants from Indonesians), 21.7 % Maroon
(descendants of African refugees who escaped slavery
and formed independent settlements in the hinterland),
13.4 % mixed, 7.6 % others, including Amerindians
(original inhabitants), and 0.6 % unknown [26]. Because of
financial restraints and the extended survey area in
Suriname we used a stratified multistage cluster sample of
households to select respondents between March and
September 2013 for this study [24]. The strata were based
on the geographic location of the sampling units in the
various districts. The Primary Sampling Unit (PSU) of the
sampling frame consists of the 10 districts of Suriname.
The Secondary Sampling Units (SSU) consisted of 101
randomly selected enumeration areas (EAs) in nine
districts and four randomly selected village areas in a
remote tenth district, Sipaliwini. The SSU was divided into
343 clusters, which were selected randomly within the
enumeration areas. Except for the 16 clusters in district
Sipaliwini, each cluster contained 25 households. The
clusters in Sipaliwini contained 40 households, due to the
large cost of transportation to the isolated villages in the
tropical rainforest. In the selected households, the
respondent was identified using the Kish method based
on gender and age [27]. In total, 7493 individuals between
the age of 15 and 65 years were invited to participate in
the study. The response rate was 76.8 %, resulting in 5748
participants. The percentage of missing data was relatively
small (1.1 %) for most variables except for income
status (30.2 %) [24].
Main outcome
We measured blood pressure three times with the
Omron HEM-780 blood-pressure monitor.
Before measurements, respondents were seated (legs
uncrossed) to rest for at least 15 min. Measurements
were repeated at a time interval of three minutes. The
mean of the last two measurements was used to calcu-
late the blood pressure of the participant [28]. Hyperten-
sion was defined as a systolic blood pressure ≥140 mm
Hg, diastolic pressure ≥90 mm Hg, or current treatment
with antihypertensive medication [29].
Hypertensive respondents were considered aware of
their condition when previously diagnosed and using
antihypertensive medication. Additionally, they were
considered to have their hypertensive condition under
control when they used antihypertensive medication and
had measurements of <140 mm Hg for systolic blood
pressure and <90 mm Hg for diastolic blood pressure.
Risk factors
We used interviews and hands-on measurements to col-
lect information. Trained interviewers used an adapted
WHO steps questionnaire to collect demographic and
lifestyle information. Participants were categorized into a
specific ethnic group if at least three of four grandpar-
ents were of this ethnicity. Anybody else was considered
to be of mixed ethnicity. Next to ethnicity, we consid-
ered biological factors like sex and age; demographic
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 2 of 11
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factors like marital status, educational level, income
status, employment, and residence (stratified into urban,
rural coastal, and rural interior areas); lifestyle factors
like cigarette smoking and physical activity (in Metabolic
Equivalent of Task (MET) minutes); and anthropometric
factors like body mass index (BMI) and waist circumfer-
ence (WC) as risk factors for hypertension. The Global
Physical Activity Questionnaire (GPAQ) was used to
measure physical activity. All measurements were car-
ried out as described in Part 3 “Training and Practical
guides”of the WHO steps manual with the recom-
mended equipment [28]. Height was measured with the
Seca 213 stand-alone stadiometer, and WC was deter-
mined with the Seca 201 measuring tapes. The respon-
dents were weighed with the Tanita HS302 solar scale.
BMI was classified in the categories; <23, 23-25, 25-27.5,
27.5-30 and 30+, taking into account the WHO ethnic-
specific cutoff points for overweight and obesity.
According to WHO, a WC of ≥88 cm for women and
≥102 cm for men is associated with substantially in-
creased metabolic risk [30]. We applied the values above
this WC cut off point to classify the waist as large.
Household income was classified as the income status
quintile from the Ministry of Internal Affairs of Suriname
in Surinamese dollars, SRD (1USD = 3.35 SRD). Because
of the small amount of respondents in the fourth and fifth
quintile, these two were combined in the analysis. The
residential addresses were stratified to urban, rural coastal
areas, and the rural interior [31]. Physical activity was
classified according to WHO recommendations in
groups <600 MET and ≥600 MET.
Statistical analysis
First, we calculated the overall and ethnic-specific preva-
lence of hypertension and the main risk factors. Differ-
ences in the prevalence between ethnic subgroups were
assessed using the Chi-square test. The collected data
were subjected to a weighting procedure so inferences
could be made to the whole population. The weights
used for analysis were calculated to adjust for probability
of selection, non-response, and differences between the
sample population and target population. The adjust-
ment weight for sample correction was calculated per
sex, 10-year age group, and, where applicable, ethnicity
[24]. Second, we used several adjustment models to
explore whether the observed differences in association
were influenced by biological, demographic, lifestyle, or
anthropometric risk factors. We tested potential interac-
tions between Hindustani (the group with the highest
prevalence of hypertension from the two largest groups)
and other ethnic groups, adjusted for sex and age in
relation to modifiable cardiovascular risk factors. All
models were evaluated with the Hosmer and Lemeshow
goodness to fit test. We used the statistical software Epi
Info 3.2 and the Statistical Packages for Social Sciences
(SPSS 21.0) for analyses.
Results
Subject characteristics
Table 1 presents the subjects’characteristics of the study
population overall and per ethnic subgroup. Amerindians
and Maroons had the lowest percentages of male partici-
pants and smokers and the highest percentages of subjects
with low education, low income, and living in rural inter-
ior areas. Also, Amerindians had the highest BMI and
WC but the lowest mean systolic blood pressure. Com-
pared to the other ethnic groups, Creoles had the highest
percentages of male participants and high education
and income groups. Creoles had the lowest percent-
age of subjects living with a partner and the highest
percentages of subjects who were employed or met
the required level of physical activity. Also, they had
the highest mean systolic blood pressure. Creoles,
Hindustani, and Javanese exhibited low levels of living
in rural interior areas. Hindustani subjects had the highest
mean diastolic blood pressure. Javanese had the highest
median age and the highest percentages of living with a
partner and smoking. Maroons had the lowest median
and mean values for BMI and WC.
Table 2 shows that the mean systolic and diastolic
blood pressure is higher in men and increases with age,
whereas the mean BMI was higher in women and in-
creases with age.
Table 3 shows that a higher percentage of men smoke
and comply with the recommended levels of physical
activity. In both sexes, smoking increased and physical
activity decreased with age.
Hypertension prevalence
The estimated overall prevalence of hypertension was
26.2 % (95 % confidence interval [CI] 25.1 %-27.4 %).
Fig. 1 gives the prevalence of hypertension with and
without medication use in the six ethnic groups. Creole,
Hindustani, and Javanese had the highest prevalence of
hypertension, and Mixed and Maroons subjects had the
lowest prevalence. More than 50 % of participants with
hypertension were not diagnosed previously and about
25 % of those treated effectively and had normal values
of blood pressure. The highest proportion of undiag-
nosed hypertension was found in Maroons. Hindustani
and Amerindians had the largest proportion of subjects
with hypertension who were treated effectively, and
Maroons had the lowest.
Ethnic differences in the prevalence of hypertension in
risk factor categories
Table 4 shows that the prevalence of hypertension was
higher in men among Hindustani; for Maroons and
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 3 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Javanese the prevalence was higher in women. The
prevalence of hypertension increased with age in all
ethnic groups. For demographic risk factors, among all
ethnic groups except Amerindians, the prevalence of
hypertension in participants living with a partner was
higher compared to single participants. Residential area
was only associated with the prevalence of hypertension
in Maroons. The prevalence of hypertension differed
according to educational level among Maroons and
Hindustani. When analyzing the influence of income,
theprevalenceofhypertensionincreasedforhigher
incomes in Creoles, whereas it decreased for lower in-
comes among Hindustanis. This table shows that among
Hindustani the smokers, and those with physical activity
less than 600 MET per week had a higher prevalence of
hypertension. This corresponds with Creole subjects
who smoked and Maroon subjects who performed
less than 600 MET of physical activity per week. For
anthropometric risk factors, we observed that the preva-
lence of hypertension increased with BMI for all ethnici-
ties except for Amerindians. For all ethnic groups, the
prevalence of hypertension was higher in those with a lar-
ger WC.
Ethnic differences between the odds ratios of
hypertension
Table 5 shows that in the model adjusted for age and sex
only, Amerindians had a lower odds ratio (OR) for
hypertension compared to Hindustani (OR: 0.7 [95 % CI
0.6-1.0]). Adding demographic factors in model 2 further
reduced the odds of hypertension in Amerindians (OR:
0.5 [95 % CI 0.4-0.8]) and also showed a weaker as-
sociation in Javanese (OR: 0.8 [95 % CI 0.1-1.0]). In
model 3, the difference between the OR for Hindustani
Table 1 Subject characteristics, overall and by ethnic subgroup (N= 5641)
Characteristics Overall Amerindian Creole Hindustani Javanese Maroon Mixed
N= 5641 N= 427 N= 677 N= 1315 N= 923 N= 1377 N= 817
Men % (95 % CI) 49.7(48.4-51) 37.6(31.7-44) 54.4(50.6-58.2) 52.8(50.4-55.2) 51.2(47.7-54.6) 43.2(40.3-46.2) 46.3(43.1-49.6)
Age in years, median (95 % range) 35.0(15.0-62.0) 35.0(16.0-62.0) 36.0(16-62) 37.0(16.0-62.0) 40.0(15.0-62.2) 30.0(15.0-61.0) 32.0(15.0-62.0))
Education % (95 % CI)
Low 53(51.7-54.3) 78.6(73-83.5) 37.5(33.8-41.4) 54.3(51.8-56.7) 53.3(49.8-56.8) 77.3(74.7-79.8) 34.8(31.7-38.0)
Middle 27.9(26.7-29.1) 17.8(13.2-23.1) 34.8(31.1-38.6) 27.9(25.7-30.1) 32(28.8-35.4) 14.1(12.1-16.4) 35.4(32.3-38.6)
High 19.1(18.1-20.2) 3.6(1.7-6.8) 27.7(24.4-31.4) 17.9(16.1-19.8) 14.7(12.4-17.4) 8.5(7-10.4) 29.8(26.9-32.9)
Income % (95 % CI)
< SRD 800/month 33.6(32-35.2) 54.7(46-63) 23.0(19.0-27.6) 30.9(28.0-34.0) 23.9(20.3-27.9) 58.3(54.4-62) 23.4(19.9-27.3)
SRD 800-1499/month 33.9(32.3-35.5) 26.4(19.3-34.4) 39.9(35.0-45.0) 37.6(34.6-40.8) 37.8(33.6-42.2) 27.6(24.3-31.2) 28.3(24.6-32.4)
SRD 1500-2199/month 15(13.8-16.3) 7.2(3.5-12.7) 16.2(12.8-20.4) 17.2(14.9-19.7) 19.4(16.1-23.2) 7.5(5.6-9.8) 16.8(13.7-20.3)
SRD 2200/month 17.5(16.2-18.8) 11.7(6.7-17.9) 20.9(17.0-25.3) 14.3(12.2-16.7) 18.9(15.6-22.6) 6.7(5.0-8.9) 31.5(27.6-35.7)
Area % (95 % CI)
Urban coastal 75.5(74.3-76.6) 31.2(25.4-37.2) 85.8(82.9-88.3) 83.9(82-85.6) 70.7(67.4-56.8) 52.3(49.2-55.3) 85.4(83-38)
Rural coastal 16.1(15.1-17) 32(26.1-38) 14.1(11.7-17) 16.1(14.4-18) 29.3(26.2-35.4) 6.9(5.5-8.7) 14.3(12.2-38.6)
Rural interior 8.5(7.8-9.2) 36.9(30.9-43.2) 0(0-0.7) 0(0-0.3) 0(0-17.4) 40.8(37.9-43.8) 0.3(0.1-32.9)
Living with partner % (95 % CI) 51.7(50.4-53) 66(59.7-71.7) 32.3(28.8-36) 60.4(58-62.7) 70.7(67.4-73.8) 40.1(37.2-43.1) 44(40.8-47.2)
Working or studying % (95 % CI) 69(67.8-70.2) 44.3(38.2-50.8) 78.7(75.4-81.6) 67.8(65.5-70) 71.9(68.7-74.9) 58.7(55.7-61.6) 77.2(74.3-79.8)
Smoking % (95 % CI) 14.7(13.8-15.6) 5.3(2.8-8.7) 19.1(16.2-22.3) 16.2(14.5-18.1) 20.2(17.5-23.1) 6.5(5.1-8.2) 14(11.9-16.4)
Recommended physical activity %
(95 % CI)
64.3(62.9-65.6) 66.3(59.1-73.1) 69.6(65.7-73.3) 65.4(63-67.8) 60(56.3-63.5) 59.2(55.9-62.5) 65.6(62.2-68.8)
Body mass index, kg/m
2
, median
(95 % range)
25.7(25.6-25.9) 26.7(18.4-40.7) 25.5(17.6-41.0) 26.3(17.1-39.1) 26.1(17.8-40.1) 24.9(17.5-41.3) 25.8(17.2-39.8)
Waist circumference, cm,
mean (SD)
87.3(15.6) 90.0(14.4) 88.2(16.3) 89.4(15.7) 86.0(14.9) 84.6(15.0) 86.4(16.0)
Systolic blood pressure, mmHg,
mean (SD)
119.0(19.3) 117.3(18.6) 122.4(19.7) 119.1(19.3) 119.3(19.5) 118.4(18.9) 117.5(19.5)
Diastolic blood pressure, mmHg,
mean (SD)
78.6(12.7) 76.3(11.4) 79.4(13.2) 79.6(12.3) 79.4(13.0) 77.3(13.2) 77.4(12.2)
The values are estimated means (standard deviation, SD), medians (range) or proportions (confidence interval, CI) and are based on weighted data. The sample
weights included population adjustment weights for sex and age. For analysis on the overall population, additional adjustment weights for ethnicity were
included. The sample of the overall population included the presented ethnic subgroups (n= 5536) plus other unspecified ethnicities (n= 105)
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 4 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
and Amerindians was no longer significant, although the
value for the OR remained 0.7. Thus, no material
changes in associations with hypertension were observed
between ethnicities after additional adjustment for life-
style and anthropometric factors (models 3 and 4).
Discussion
In this study, the prevalence of hypertension overall and
in risk factor subgroups was assessed in the six major
ethnic groups of Suriname. The estimated prevalence of
hypertension was above 25 %. The highest prevalence
was found in Creoles, Hindustani, and Javanese. Half of
all hypertensive participants were not diagnosed previ-
ously and a quarter were treated effectively. We ob-
served differences in the prevalence of hypertension
between ethnic subgroups with biological, demographic,
lifestyle, and anthropometric risk factors and variation in
the association of ethnic groups with hypertension. The
major difference in association of ethnic groups with
hypertension was between Hindustani and Amerindians.
Prevalence
The estimated prevalence of hypertension in our study is
in line with previous reports from countries of the
Caribbean, Latin America, and developing countries,
which describe a prevalence of hypertension between
16 % and 35 % [4, 32–37]. Most studies in western
countries indicate higher prevalences of hypertension in
African descendants, followed by Asian descendants,
Hispanics, and Caucasians [8, 12, 38–40]. In addition,
studies in Amerindians report low prevalences of hyper-
tension [41–43]. The results of our study concur with
the literature for all ethnicities except for Maroons.
Previous studies suggest that differences in prevalence of
hypertension among adults of African descent are
caused by demographic, lifestyle, and anthropometric
factors [44–46]. This is supported by our results, as
the ethnic groups with the highest prevalence of
hypertension (Creoles) and the lowest prevalence
(Maroons), are both from African descent and have
similar biological characteristics.
Awareness and treatment
In this study, awareness in hypertensive participants falls
within the range of other developing countries, but the
proportion of adequately treated subjects is higher. In
other developing countries, it has been estimated that
between 23 % and 71 % of all hypertensive people were
aware of their condition and 4 % to 16 % were
adequately treated [4, 47]. Success rates may be high
in Suriname compared to other developing countries
[4, 48], because of the country’sextensiveprimary
Table 2 Mean systolic and diastolic blood pressure and mean BMI by age and sex
Age group Systolic blood pressure Diastolic blood pressure BMI
Mean ± SD (SE) Mean ± SD (SE) Mean ± SD (SE)
Male Female Male Female Male Female
(n= 2102) (n= 3524) (n= 2102) (n= 3522) (n= 2052) (n= 3302)
15-24 years 115.1 ± 12.6 (0.5) 102.6 ± 11.1 (0.4) 71.5 ± 9.8 (0.4) 69.5 ± 8.4 (0.3) 23.0 ± 4.8 (0.2) 24.2 ± 5.2 (0.2)
25-34 years 120.3 ± 13.0 (0.5) 108.5 ± 14.4 (0.5) 78.3 ± 10.6 (0.4) 75.2 ± 11.8 (0.4) 25.7 ± 5.2 (0.2) 27.9 ± 5.9 (0.2)
35-44 years 123.5 ± 15.6 (0.6) 117.4 ± 18.4 (0.8) 82.3 ± 11.5 (0.5) 81.2 ± 12.9 (0.5) 26.5 ± 5.2 (0.2) 29.1 ± 6.1 (0.3)
45-54 years 128.5 ± 19.0 (0.8) 126.3 ± 20.6 (0.9) 84.3 ± 12.5 (0.5) 83.6 ± 12.2 (0.5) 26.1 ± 5.1 (0.2) 29.2 ± 5.8 (0.3)
55-64 years 137.9 ± 23.6 (1.4) 134.6 ± 22.0 (1.2) 86.6 ± 13.4 (0.8) 84.3 ± 12.3 (0.7) 26.2 ± 5.2 (0.3) 29.7 ± 6.3 (0.3)
Total pop. 123.1 ± 17.5 (0.3) 115.2 ± 20.1 (0.4) 79.4 ± 12.5 (0.2) 77.5 ± 12.8 (0.2) 25.3 ± 5.2 (0.1) 27.7 ± 6.2 (0.1)
The values are estimated means ± the standard deviation (SD) with the standard error (SE) and are based on weighted data. Total pop. = total population
Table 3 Prevalence of smoking and weekly required physical activity by age and sex
Age group Smoking Recommended physical activity
%(CI 95 %) % (CI 95 %)
Male Female Male Female
(n= 2093) (n= 3533) (n= 1784) (n= 3070)
15-24 years 8.8(6.9-11.2) 0.6(0.2-1.5) 82.2(78.9-85.2) 61.9(58.0-65.7)
25-34 years 23.1(20.0-26.6) 3.8(2.6-5.6) 75.5(71.6-79.0) 55.8(51.7-59.9)
35-44 years 28.9(25.3-328) 5.6(3.9-7.9) 68.7(64.4-72.8) 57.0(52.6-61.4)
45-54 years 35.9(31.8-40.2) 7.5(5.5-10.2) 66.0(61.4-70.3) 55.8(51.2-60.3)
55-64 years 33.6(28.1-39.4) 5.8(3.7-9.1) 50.6(43.3-57.1) 49.5(43.7-55.5)
Total pop. 24.4(22.8-26.0) 4.3(3.6-5.1) 71.3(69.4-73.2) 56.9(54.9-58.9)
The values are estimated proportions (95 % confidence interval [CI]) and are based on weighted data. Total pop = total population
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 5 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
health care system [49]. However, awareness and the ratio
of effectively treated patients is higher in developed coun-
tries. In the United States, just over 80 % of hypertensive
subjects were aware of their condition and slightly more
than 50 % were treated effectively [50]. Besides dissimilar
resources between developed and developing countries,
there are also differences in ethnic composition. Thus, in
addition to the differences in compliance with treatment
and availability of medication, different responses to anti-
hypertensive treatment by ethnic groups should also be
considered to explain discrepancies in the efficacy of
treatment [20]. This argument is supported by Amerin-
dians having the highest levels of effective treatment
and Maroon subjects having the lowest. Therefore,
ethnic-specific treatment for hypertension may be indi-
cated and should be explored further. The findings of
thisstudyindicatethatmoreeffortmustbetakento
improve awareness by people with hypertension and ef-
ficacy of treatment.
Risk factors
As in previous studies, the results in our study for sex-
specific prevalence are ambiguous [51, 52]. We observed
a higher prevalence of hypertension for men among
Hindustani subjects and for women in Maroons and
Javanese. The findings of our study in regards to age
are also in line with the literature, as hypertension
increases with age regardless of race and ethnicity
[53]. However, the age- and sex-adjusted risk for
hypertension was equal for all ethnicities, with ex-
ception of the Amerindians for whom the risk was
lower. Biological mechanisms that explain higher
blood pressure levels in people of African descent
are described in the literature, but to our knowledge,
mechanisms explaining lower blood pressure levels
in Amerindians are not known and need to be stud-
ied in more depth. Neither age nor sex are modifi-
able risk factors. However, they may be relevant for
identification of groups at risk.
Demographic factors like education, income, employ-
ment, and area of residence have been associated with
hypertension [54–60]. In this study, the prevalence of
hypertension increased with income in Creoles, living in
the rural interior in Maroons, and living with a partner
in Hindustani, Javanese, and Maroons. Prevalence de-
creased with education in Hindustani and Maroons, with
employment in Hindustani, Javanese, and Maroons, and
with level of income in the Hindustani. After adjusting
for all risk factors, we measured a weaker association of
Javanese and Amerindians with hypertension compared
to Hindustani, which might indicate that some of these
factors influence the level of hypertension for these two
ethnic groups. Previous studies report higher prevalences of
hypertension in urban areas compared to rural areas [61–
63]. Published results on physical activity from the Steps
Survey 2013 in Suriname, report the percentage of required
physical activity in the rural coastal area compared to the
urban area [64]. A lower percentage of required physical
Fig. 1 The prevalence of people with hypertension per ethnic group, presented in groups not treated or treated with uncontrolled and
controlled hypertension
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 6 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 4 Prevalence of hypertension in risk factor categories among six ethnic groups (N= 5641)
Characteristics Amerindian Creole Hindustani Javanese Maroon Mixed
N= 427 N=677 N= 1315 N= 923 N=1377 N=817
Prev(CI 95 %) Prev(CI 95 %) Prev(CI 95 %) Prev(CI 95 %) Prev(CI 95 %) Prev(CI 95 %)
Sex
Male 27.5 % (18.8 % - 37.6 %) 28.7 % (24.2 % - 33.6 %) 33.5 % (30.4 % - 36.7 %) 25.7 % (21.7 % - 30.2 %) 17.3 % (14.0 % - 21.1 %) 23.0 % (19.2 % - 27.2 %)
Female 19.5 % (13.8 % - 26.8 %) 33.9 % (28.7 % - 39.5 %) 27.4 % (24.4 % - 30.7 %) 32.5 % (28.0 % - 37.3 %) 23.4 % (20.2 % - 27.0 %) 21.2 % (17.7 % - 25.0 %)
p= 0.161 p= 0.143 p< 0.006 p< 0.030 p< 0.014 p< 0.509
Age group (years)
15-24.9 9.0 % (3.8 % - 18.2 %) 9.0 % (5.2 % - 14.7 %)a 4.7 % (2.8 % - 7.6 %)a 5.2 % (2.2 % - 9.9 %)a 5.2 % (3.2 % - 8.3 %) 5.2 % (3.1 % - 8.5 %)a
25-34.9 13.0 % (4.7 % - 25.0 %) 13.4 % (8.5 % - 20.1 %)a,b 20.6 % (16.8 % - 25.0 %)a 13.9 % (8.6 % - 20.1 %)b 12.2 % (9.0 % - 16.3 %) 14.9 % (10.5 % - 20.4 %)b
35-44.9 25.5 % (14.8 % - 39.2 %) 32.9 % (24.9 % - 41.7 %)b,c 24.4 % (20.1 % - 29.2 %)b 31.6 % (25.3 % - 38.1 %)c 30.1 % (24.0 % - 37.1 %) 28.0 % (21.6 % - 34.9 %)c
45-54.9 38.8 % (24.9 % - 54.3 %) 47.6 % (39.3 % - 56.3 %)c 48.1 % (43.1 % - 53.2 %)c 44.3 % (37.1 % - 51.6 %)d 43.6 % (35.1 % - 52.8 %) 36.5 % (29.0 % - 44.9 %)c
55-64.9 43.6 % (25.4 % - 64.6 %) 67.3 % (57.0 % - 76.2 %)c 73.3 % (66.6 % - 79.3 %)d 52.6 % (42.9 % - 62.5 %)d 60.1 % (48.7 % - 70.7 %) 60.3 % (49.3 % - 70.6 %)d
p< 0.001 p< 0.001 p< 0.001 p< 0.001 p< 0.001 p< 0.001
Living with a partner
No 21.8 % (13.9 % - 32.3 %) 27.1 % (23.1 % - 31.5 %) 22.5 % (19.4 % - 25.9 %) 23.0 % (17.8 % - 28.8 %) 17.1 % (14.3 % - 20.3 %) 17.7 % (14.5 % - 21.3 %)
Yes 22.9 % (16.7 % - 30.0 %) 39.1 % (32.6 % - 46.0 %) 36.2 % (33.2 % - 39.2 %) 31.4 % (27.7 % - 35.4 %) 26.3 % (22.2 % - 30.8 %) 27.4 % (23.2 % - 32.1 %)
p< 0.161 p< 0.143 p< 0.006 p< 0.05 p< 0.05 p< 0.509
Geographic area
Urban area 22.7 % (14.2 % - 33.7 %) 30.5 % (26.8 % - 34.4 %) 29.8 % (27.5 % - 32.3 %) 28.1 % (24.6 % - 32.0 %) 16.3 % (13.4 % - 19.7 %)a 21.6 % (18.8 % - 24.6 %)
Rural coastal area 24.6 % (15.8 % - 35.6 %) 34.6 % (24.9 % - 44.7 %) 34.8 % (29.1 % - 40.7 %) 31.1 % (25.3 % - 37.3 %) 20.6 % (12.6 % - 32.0 %)a,b 24.8 % (18.0 % - 33.2 %)
Rural interior 20.5 % (12.8 % - 30.1 %) N/A N/A N/A 26.5 % (22.5 % - 30.9 %)b N/A
p<0.797 p= 0.446 p= 0.113 p= 0.390 p< 0.001 p= 0.373
Schooling
Primary 23.7 % (17.9 % - 30.2 %) 30.1 % (24.3 % - 36.2 %) 35.7 % (32.6 % - 39.0 %) 31.2 % (26.9 % - 35.9 %) 23.2 % (20.4 % - 26.2 %) 21.9 % (17.6 % - 27.0 %)
Secondary 21.8 % (11.3 % - 37.4 %) 34.3 % (28.0 % - 40.8 %) 27.4 % (23.4 % - 31.8 %) 28.1 % (22.8 % - 34.1 %) 11.6 % (6.7 % - 17.5 %) 21.0 % (16.8 % - 26.0 %)
Higher 2.6 % (2.1 % - 34.6 %) 30.1 % (23.5 % - 37.3 %) 18.5 % (14.2 % - 23.4 %) 25.6 % (18.0 % - 34.4 %) 11.6 % (6.2 % - 20.5 %) 20.2 % (15.5 % - 25.4 %)
p= 0.253 p= 0.549 p< 0.001 p= 0.440 p< 0.001 p= 0.864
Working or studying
Yes 21.8 % (15.5 % - 29.8 %) 35.8 % (27.9 % - 44.1 %) 39.7 % (35.6 % - 43.9 %) 38.1 % (31.8 % - 44.7 %) 24.6 % (20.8 % - 29.0 %) 26.5 % (20.9 % - 33.1 %)
No 23.3 % (15.8 % - 32.2 %) 29.8 % (26.0 % - 33.9 %) 26.4 % (23.8 % - 29.0 %) 25.5 % (22.0 % - 29.2 %) 18.0 % (15.2 % - 21.3 %) 20.6 % (17.8 % - 23.8 %)
P= 0.816 p= 0.178 p< 0.001 p< 0.001 p< 0.008 p< 0.057
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 7 of 11
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Table 4 Prevalence of hypertension in risk factor categories among six ethnic groups (N= 5641) (Continued)
Income quintile in SRD
Q1 < 800/month 21.5 % (13.3 % - 32.8 %) 18.6 % (11.5 % - 28.7 %)a 33.9 % (28.6 % - 39.6 %) 26.9 % (19.4 % - 35.9 %) 24.7 % (20.6 % - 29.4 %) 22.1 % (14.9 % - 20.2 %)
Q2 800-1499/month 32.7 % (18.0 % - 49.9 %) 27.4 % (20.4 % - 35.1 %)a,b 33.0 % (28.3 % - 38.2 %) 27.8 % (21.8 % - 34.9 %) 22.0 % (16.4 % - 28.9 %) 30.9 % (23.5 % - 38.8 %)
Q 3 1500-2199/month 21.9 % (2.5 % - 55.8 %) 40.3 % (27.9 % - 53.3 %)b,c 29.1 % (22.3 % - 36.7 %) 29.1 % (20.5 % - 39.2 %) 26.8 % (14.8 % - 40.7 %) 20.4 % (12.5 % - 30.2 %)
Q4 and Q5 > 2200/month 18.9(4.0 %-45.0 %) 42.2 % (31.2 % - 53.7 %)c 19.7 % (13.4 % - 27.3 %) 29.7 % (21.1 % - 40.2 %) 16.7 % (6.6 % - 30.0 %) 25.8 % (19.4 % - 33.2 %)
p= 0.732 p< 0.003 p< 0.03 p= 0.965 p= 0.558 p= 0.467
Daily smoking
No 23.1 % (17.9 % - 28.9 %) 29.0 % (25.3 % - 33.1 %) 28.8 % (26.5 % - 31.3 %) 29.5 % (26.0 % - 33.1 %) 20.8 % (18.4 % - 23.5 %) 20.0 % (17.4 % - 23.0 %)
Yes 12.1 % (1.8 % - 43.6 %) 39.1 % (30.7 % - 48.1 %) 40.0 % (34.1 % - 45.9 %) 27.3 % (20.5 % - 34.6 %) 20.6 % (11.4 % - 31.4 %) 34.0 % (26.0 % - 42.7 %)
p= 0.443 p< 0.023 p< 0.001 p= 0.547 p= 0.865 p< 0.001
Physical activity
< 600 MET 29.0 % (17.9 % - 41.4 %) 34.8 % (27.9 % - 42.4 %) 40.4 % (36.1 % - 44.7 %) 28.8 % (23.7 % - 34.2 %) 23.9 % (19.7 % - 28.7 %) 23.4 % (18.6 % - 28.7 %)
≥600 MET 18.8 % (12.2 % - 26.6 %) 29.5 % (25.1 % - 34.2 %) 26.1 % (23.4 % - 28.9 %) 28.4 % (24.3 % - 32.8 %) 18.2 % (15.1 % - 21.8 %) 21.3 % (18.0 % - 25.0 %)
p= 0.75 p= 0.354 p< 0.001 p= 0.775 p< 0.05 p= 0.417
Body mass index
< 23 18.4 % (9.1 % - 33.0 %) 12.4 % (8.2 % - 17.6 %)a 14.3 % (11.3 % - 18.0 %) 8.7 % (5.5 % - 13.4 %) 11.3 % (8.4 % - 15.0 %)a 9.8 % (6.5 % - 13.7 %)a
23-24.9 20.4 % (10.5 % - 35.1 %) 17.9 % (10.6 % - 26.6 %)a 29.4 % (23.1 % - 35.9 %) 22.9 % (15.3 % - 31.7 %) 9.5 % (5.2 % - 15.2 %)a 12.5 % (7.4 % - 19.0 %)a
25-27.5 17.3 % (7.0 % - 31.6 %) 41.1 % (30.4 % - 52.1 %)b 31.8 % (26.6 % - 37.4 %) 35.3 % (27.5 % - 43.8 %)a 23.3 % (16.8 % - 30.9 %)b 21.3 % (15.1 % - 29.1 %)b
27.5-30 14.0 % (5.6 % - 29.4 %) 49.7 % (38.3 % - 61.0 %)b 39.1 % (33.0 % - 45.4 %)a 36.6 % (28.1 % - 45.3 %)a,b 24.4 % (17.0 % - 32.7 %)b 29.0 % (21.1 % - 37.9 %)b
≥30 33.8 % (22.8 % - 45.6 %) 44.8 % (37.6 % - 52.3 %)b 44.2 % (39.4 % - 49.2 %)a 46.1 % (38.9 % - 53.3 %)b 39.4 % (33.2 % - 45.7 %) 40.1 % (33.7 % - 46.7 %)
p= 0.111 p< 0.001 p< 0.001 p< 0.001 p< 0.001 p< 0.001
Waist circumference
Normal 18.3 % (12.6 % - 25.8 %) 24.6 % (20.6 % - 29.0 %) 21.7 % (19.2 % - 24.3 %) 21.6 % (18.3 % - 25.2 %) 12.6 % (10.3 % - 15.3 %) 15.4 % (12.7 % - 18.5 %)
High 30.8 % (21.5 % - 40.9 %) 46.3 % (39.7 % - 53.3 %) 46.4 % (42.3 % - 50.5 %) 49.2 % (42.5 % - 56.1 %) 39.1 % (33.6 % - 44.7 %) 40.2 % (34.1 % - 46.4 %)
p< 0.001 p< 0.001 p< 0.001 p< 0.001 p< 0.001 p= 0.033
The values are estimated proportions (with confidence interval in parentheses) and are based on data weighted for sample correction including population adjustment weights for sex and age. Pearson chi-square tests
were calculated for the differences between prevalence in the subset of categories of the risk factors per ethnic group. Each subscript letter (a, b c…) denotes a subset of categories with column proportions that do
not differ significantly from each other at the .05 level. N/A indicates not applicable
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 8 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
activity could be associated with the higher prevalence of
hypertension measured in the rural coastal area in our
study. Possibly, our observations in this study of Maroons
having higher levels of employment, higher levels of edu-
cation, and lower prevalences of hypertension, are related
to the fact that they are more likely to live in urban areas.
In such a case, it is plausible that these factors have an im-
pact on the prevalence of hypertension in the urban set-
ting. However, no previous studies have compared
hypertension in urban and rural settings in Suriname, and
the higher prevalence observed in Maroons living in rural
coastal and rural interior areas requires further research.
The results clearly demonstrate that the prevalence of
hypertension in demographic risk factor subgroups differed
between ethnic groups. We also observed a change in the
different associations of ethnic groups with hypertension
after adjusting for demographic factors. These results imply
that achievement of uniform intervention programs will be
limited and tailor-made programs should be developed.
For lifestyle factors, the prevalence of hypertension
was higher in Hindustani and Creole smokers, and in
Maroon and Hindustani subjects performing less than
600 MET of physical activity per week. Previous studies
show that lifestyle factors like low physical activity
and cigarette smoking are associated with hyperten-
sion [65–68]. These risk factors are modifiable and
are valuable points of interest for intervention programs.
Many studies show that high BMI or WC are risk
factors of hypertension [69–71]. In this study, the preva-
lence of hypertension increased with BMI and WC
categories for all ethnicities. The BMI subgroups for
Amerindians, however, were too small to show significant
differences at a 0.05 level, thus the increase with BMI
categories for this group could not be tested for statis-
tical significance. Adjustment for these anthropometric
factors in addition to sex and age did not affect the
association with hypertension, and the OR remained
lower in Amerindians. The results suggest that public
health interventions focusing on both BMI and WC
control should not be aimed at specific ethnic groups;
however, in order to confirm this suggestion, this asso-
ciation should be explored in additional studies.
The major difference in association of ethnic groups with
hypertension was between Hindustani and Amerindians.
Differences in associations of ethnic groups with hyperten-
sion were not materially affected by adjustment for lifestyle
factors or anthropometric factors. The differences in associ-
ations of the ethnic groups with hypertension were mostly
influenced by demographic risk factors, and these should
be addressed accordingly.
Strength and limitations
Strengths of this cross-sectional study include the design,
with a stratified multistage cluster and a large sample size,
which was adequate to represent the ethnic and geo-
graphic diversity of the Surinamese population by sex in
five different age groups [24]. The design included
measures like the Kish method and standardized data
collection tools to minimize selection and interviewer bias
[24, 27]. In addition, in the analysis, sample weights were
applied to correct for selection bias. Further, the percent-
ages of missing data in general were relatively small
(1.1 %), except for income status (30.2 %). However, the
model that included income as a confounder fit and was
not compromised (goodness to fit test). Still, some limita-
tions should be considered regarding this study. First,
despite the overall large sample size of the study some risk
factors were present in only a few participants when
analyzed per ethnic subgroup. In these cases, the sample
size was too small to measure statistical differences
between the observed hypertension rates at a significance
level of 0.05. Second, although the wide range of variables
evaluated in this study allowed us to control for con-
founders, residual confounding might still have occurred,
as with any observational study. For example, information
on nutrition was not considered in this paper.
Conclusion
The results of the present study showed that the prevalence
of hypertension in Suriname was in the range of developing
countries. By ethnic group, the highest prevalence was
found in Creoles and the lowest in Maroons. Next to
Creoles, Hindustani and Javanese also had high prevalences
of hypertension, and Amerindians exhibited a low preva-
lence, after Maroons. In the analysis, Amerindians had the
lowest OR for hypertension, in comparison to Hindustani.
The differences observed in the prevalence of hypertension
for risk factor subgroups between and within ethnic groups
allow us to generate valuable ethnic-specific hypotheses,
which are important for research on the development of
tailor-made public health interventions.
Table 5 Adjusted risk of hypertension between ethnic groups
Model 1 Model 2 Model 3 Model 4
OR (CI) OR (CI) OR (CI) OR (CI)
Hindustani 1 1 1 1
Creole 1.0(0.8-1.2) 1.0(0.7-1.3) 1.0(0.8-1.2) 1.0(0.8-1.3)
Javanese 0.9(0.7-1.1) 0.8(0.1-1.0)* 0.9(0.7-1.1) 1.0(0.8-1.2)
Mixed 0.8(0.7-1.0) 0.9(0.7-1.2) 0.8(0.6-1.0) 0.9(0.7-1.1)
Maroon 0.9(0.7-1.0) 0.9(0.6-1.2) 0.8(0.7-1.0) 0.8(0.7-1.0)
Amerindian 0.7(0.6-1)* 0.5(0.4-0.8)* 0.7(0.5-1.0) 0.7(0.5-0.9)*
*P< 0.05
Model 1 is the basic multivariate model adjusted for sex and age
Model 2 is adjusted for variables in model 1 plus demographic factors like
living area, marital status, education, income, and working status
Model 3 is adjusted for variables in model 1 plus lifestyle factors like smoking
and physical activity
Model 4 is adjusted for variables in model 1 plus anthropometric measures
like body mass index and waist circumference
Krishnadath et al. Population Health Metrics (2016) 14:33 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Abbreviations
BMI: Body mass index; GPAQ: Global Physical Activity Questionnaire;
MET: Metabolic Equivalent of Task; NCD: Non-communicable disease;
PAHO: Pan American Health Organization; WC: Waist circumference;
WHO: World Health Organization
Acknowledgments
This study was conducted by the Faculty of Medical Sciences of the Anton
de Kom University of Suriname in close collaboration with the Ministry of
Health and the Pan American Health Organization (PAHO). We acknowledge
the participation of all the respondents and the support of all the personnel
in this study. We especially thank Christel Smits from the department of
Public Health, Faculty of Medical Sciences, Anton de Kom University of
Suriname for her participation in the coordination team and her assistance
with data collection and control. We also thank Albert Hofman, from the
department of Epidemiology, Erasmus MC, University Medical Center,
Rotterdam, the Netherlands, for supervision on the realization of this study.
Funding
The research was funded by the Ministry of Health, Republic of
Suriname MOH/NCD/1214/GOS. The funding of the Ministry covered
the operational costs.
Availability of data and supporting materials
All authors have access to the data. Reviewers only have access to the data
for testing and are required to sign a confidentiality agreement.
Authors’contributions
ISKK participated in the design of the study, data collection, statistical
analysis, interpretation of data, and drafting the manuscript. VWVJ
collaborated in the design of the study, statistical analysis, interpretation of
data, and drafting the manuscript. LMN collaborated with the interpretation
of data and drafting the manuscript. JRT collaborated in the design of the
study, data collection, interpretation of data, and drafting the manuscript. All
authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Ethics approval and consent to participate
The Ethics Committee of the Ministry of Health in Suriname (Commissie
mensgebonden wetenschappelijk onderzoek (ref: VG 004-2013)) approved
this research.
Each study participant was first informed about the details of the study and
then asked to sign for consent. Apart from the aims and the survey
procedures, the respondent received details on how the information
gathered would be used. The respondent was also informed that he or she
could refuse to participate in any part of the study.
Author details
1
Department of Public Health, Faculty of Medical Sciences, Anton de Kom
University of Suriname, Paramaribo, Suriname.
2
Department of Physiology,
Faculty of Medical Sciences, Anton de Kom University of Suriname,
Paramaribo, Suriname.
3
Department of Epidemiology, Erasmus MC, University
Medical Center, Rotterdam, The Netherlands.
4
Department of Pediatrics,
Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
Received: 27 August 2015 Accepted: 9 September 2016
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