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Erschienen in: BMC Public Health 1/2015

Open Access 01.12.2015 | Research article

Association of physical activity with blood pressure and blood glucose among Malaysian adults: a population-based study

verfasst von: Chien Huey Teh, Ying Ying Chan, Kuang Hock Lim, Chee Cheong Kee, Kuang Kuay Lim, Pei Sien Yeo, Omar Azahadi, Yusoff Fadhli, Aris Tahir, Han Lim Lee, Wasi Ahmad Nazni

Erschienen in: BMC Public Health | Ausgabe 1/2015

Abstract

Background

The health-enhancing benefits of physical activity (PA) on hypertension and diabetes have been well documented for decades. This study aimed to determine the association of PA with systolic and diastolic blood pressure as well as blood glucose in the Malaysian adult population.

Methods

Data were extracted from the 2011 National Health and Morbidity Survey (NHMS), a nationally representative, cross-sectional study. A two-stage stratified sampling method was used to select a representative sample of 18,231 Malaysian adults aged 18 years and above. The PA levels of the respondents were categorised as low, moderate or high according to the International Physical Activity Questionnaire (IPAQ)-short form. Blood pressure and fasting blood glucose levels were measured using a digital blood pressure-measuring device and finger-prick test, respectively.

Results

Systolic blood pressure (SBP) level was positively associated with PA level (p = 0.02) whilst no significant association was noted between PA level and diastolic blood pressure (DBP). In contrast, respondents with low (adjusted coefficient = 0.17) or moderate (adjusted coefficient = 0.03) level of PA had significantly higher blood glucose level as compared to those who were highly active (p = 0.04).

Conclusions

A significant negative association was observed between PA level and blood glucose only. Future studies should employ an objective measurement in estimating PA level in order to elucidate the actual relationship between PA, hypertension and diabetes for the development of effective interventions to combat the increasing burden of premature-mortality and cardiovascular disease-related morbidity in Malaysia.
Hinweise

Competing interests

The authors declare that they no competing interests.

Authors’ contributions

TCH as the first author, collected data and supervised data collection at the field, analyzed and interpreted the data, and drafted the manuscript. CYY and LKH helped in literature review, prepared the Results and Discussion sections of the article and critically reviewed the manuscript. LKK collected data, supervised data collection at the field and revised the manuscript critically. KCC and YPS helped in data analysis and interpretation and helped to draft the manuscript. AO and FY designed the study and helped in data analysis. LHL and NWA reviewed and revised the manuscript for important intellectual content. TA gave substantial contribution to the conception and design of the study, and critically reviewed the manuscript. All authors had given the final approval to publish the submitted manuscript in its present form.
Abkürzungen
AAMI
American Association for the Advancement Medical Instrumentation
BHS
British Hypertension Society
BMI
body mass index
BOD
burden of disease
CI
confidence interval
CVD
cardiovascular disease
DALYs
disability-adjusted life years
DBP
diastolic blood pressure
DOS
Department of Statistics
EB
enumeration block
FVs
fruits and vegetables
IPAQ
international physical activity questionnaire
LQ
living quarter
MET
metabolic equivalent
MLR
multivariable linear regression
MREC
Medical Review and Ethics Committee
NHMS
National Health and Morbidity Survey
PA
physical activity
PSU
primary sampling unit
RCT
randomised controlled trial
SBP
systolic blood pressure
SD
standard deviation
SSU
secondary sampling unit
WHO
World Health Organisation
YLLs
years of life lost

Background

Hypertension and diabetes are major and common risk factors for cardiovascular disease. Cardiovascular diseases (CVDs) account for approximately one third of deaths worldwide, with high blood pressure being the leading cause of cardiovascular death in the South East Asia Region. Together with a number of lifestyle risk factors (alcohol use, tobacco use, high body mass index (BMI), high cholesterol, low fruit and vegetable intake and physical activity), high blood pressure and high blood glucose account for 61 % of cardiovascular deaths and more than 75 % of deaths from ischaemic and hypertensive heart disease globally [1].
In Malaysia, the prevalence of hypertension among adults aged 18 years and above has been persistent at 32.2 % in 2006 [2] and 32.7 % in 2011 [3], whereas the prevalence of diabetes has been increasing steadily from 11.6 % in 2006 [2] to 15.2 % in 2011 [3]. The high prevalence of hypertension and diabetes are anticipated to cause an epidemic of cardiovascular disease. The Malaysian Second Burden of Disease and Injury Study (BOD) in 2012 reported that ischaemic heart disease was the top killer and ranked first in the top 10 causes of premature mortality (Years of Life Lost, YLLs) and top 10 based on burden of disease (Disability Adjusted Life Years, DALYs) [4]. Therefore, the implementation of intensive targeted strategies based on scientific evidence to prevent and control these conditions is of paramount importance.
For decades, a plethora of epidemiological studies have demonstrably proven the metabolic and cardiovascular benefits of physical activity (PA), either alone or in conjunction with dietary changes in reducing the risk of hypertension and diabetes [57]. Findings from prospective studies [8, 9] and meta-analysis of randomised controlled trials (RCTs) [10, 11] indicated that regular moderate-intensity activity and resistance exercise lowered the blood pressure in both normotensive and hypertensive individuals. Similarly, studies [7, 12, 13] also demonstrated that moderate- and high-intensity PA conferred evident health benefits amongst both non-diabetic and diabetic populations by improving insulin sensitivity and glycaemic control. A RCT reported that the incidence of diabetes among high-risk individuals was reduced by 40–60 % through proper diet control and programmed PA over 3 to 4 years [13].
Nonetheless, despite established evidence of the beneficial relationship between PA, hypertension and diabetes, there is a lack of national data reporting on the association of PA with systolic and diastolic blood pressure as well as blood glucose level among the Malaysian population. Therefore, in the present study, we aimed to determine these associations by analysing data obtained from the National Health and Morbidity Survey (NHMS) 2011 among Malaysian adults aged 18 years and above, while adjusted for other potential confounders. Findings from this study could provide evidence-based information to assist policy-making decisions pertaining to primary prevention and treatment of hypertension and diabetes, as well as interventional strategies.

Methods

Study sample

Data were extracted from a cross-sectional multi-ethnic population-based study, the 2011 NHMS, which was conducted from April to July 2011, across 13 states (Penang, Perlis, Kedah, Perak, Selangor, Negeri Sembilan, Melaka, Johor, Kelantan, Terengganu, Pahang, Sabah, Sarawak) and 2 Federal Territories (Kuala Lumpur and Putrajaya) in Malaysia. Samples were selected using a two-stage stratified sampling method, by which the first stage stratification was performed by states and the second stage stratification was performed by urban/rural localities. The urban area is defined as a gazetted administrative area (a carefully mapped area with definite boundaries which had been notified in the government gazette for public information) with adjoining built-up areas of more than 10,000 people while a gazetted administrative area of less than 10,000 people is defined as a rural area. The Malaysian Department of Statistics (DOS) provided the Primary Sampling Units (PSUs) or Enumeration Blocks (EBs) for first stage sampling and Secondary Sampling Units (SSUs) or Living Quarters (LQs) for second stage sampling according to the 2010 census.
A total of 794 EBs (484 urban and 310 rural EBs) were systematically selected from all EBs in Malaysia via a probability-proportional-to-size sampling technique. Subsequently, 12 Living Quarters (LQs) or Secondary Sampling Units (SSUs) were randomly selected from each EB. Finally, all households and eligible household members within the selected LQs were included in the sample. Details of the sampling method and calculation of sample size have been described elsewhere [14]. For the present study, a total of 18,231 eligible respondents (aged 18-year-old and above) were recruited in the study and written consent for participation was obtained before they were interviewed. The study protocol was approved by the Medical Review and Ethics Committee (MREC), Ministry of Health Malaysia.

Data collection

The data collection was conducted from April 2011 to July 2011 by trained interviewers via face-to-face interviews using a standardised questionnaire; whilst clinical assessment, which included measurement of blood pressure and blood glucose level, was performed by trained staff nurses. To ensure a higher response rate, only selected respondents who were not at home after at least 3 attempted visits were excluded from the survey.

Physical activity

The International Physical Activity Questionnaire-short form (IPAQ-SF) estimates the overall PA level of an individual in MET-minutes/week by determining the duration (in minutes) and number of days (in one week) of engagement in three specific types of activity (walking, moderate-intensity and high-intensity activities) across a comprehensive set of domains (leisure time, work-related and transport-related physical activities, domestic and gardening activities) in the past seven days. MET or metabolic equivalent is a unit that is used to estimate the amount of oxygen used by the body during physical activity. A MET-minutes/week is computed by multiplying the MET score of an activity (3.3 for walking, 4.0 for moderate-intensity and 8.0 for vigorous-intensity) by the minutes and days (or sessions) of engagement. Respondents were classified into three levels of PA as low, moderate or high according to the cutoff of total MET-minutes/week in each category [15] as follow:
  • Category 1 Low
Individuals who do not meet the criteria for Category 2 (moderately active) and 3 (highly active) were considered to have a ‘low’ PA level or were physically inactive.
  • Category 2 Moderate
    a)
    3 or more days of vigorous-intensity activity of at least 20 min per day, or
     
    b)
    5 or more days of moderate-intensity activity and/or walking of at least 30 min per day, or
     
    c)
    5 or more days of any combination of walking, moderate- or vigorous-intensity activities achieving a minimum total PA of at least 600 MET-minutes/week
     
  • Category 3 High
    a)
    vigorous-intensity activity on at least 3 days achieving a minimum total PA of at least 1500 MET-minutes/week, or
     
    b)
    7 or more days of any combination of walking, moderate- or vigorous-intensity activities achieving a minimum total PA of at least 3000 MET-minutes/week.
     

Hypertension

Blood pressure level was measured twice in an interval of 10 min by a trained nurse using a calibrated digital blood pressure-measuring device, OMRON HEM-907. This device was evaluated for compliance to both the American Association for the Advancement Medical Instrumentation (AAMI) and British Hypertension Society (BHS) protocols for accuracy for a non-invasive blood pressure-monitoring device using single observer readings [16]. Both known hypertension and undiagnosed hypertension constituted the overall prevalence of hypertension. “Known hypertension” is defined as self-report of being told they have hypertension by a doctor or medical assistant; “undiagnosed hypertension” is defined as self-perceived as non-hypertensive and had a SBP of 140 mmHg or more and/or DBP of 90 mmHg or more [17].

Diabetes

Respondents were asked to fast for at least 6 h for the measurement of fasting blood glucose level using a validated CardioChek PA Analyser [18] via finger-prick test by trained nurses. Respondents with known diabetes or undiagnosed diabetes constituted the overall prevalence of diabetes. “Known diabetes” is defined as self-report of being told they have diabetes by a doctor or medical assistant; a respondent was classified as having ‘undiagnosed diabetes’ when the respondent was not known to have diabetes and had a fasting capillary blood glucose (FBG) of 6.1 mmol/L or more or non-fasting blood glucose of more than 11.1 mmol/L [19].

Anthropometric measurements and obesity

SECA bodymeter 206 (SECA, Germany) and TANITA318 digital weighing scale (TANITA, Japan) were used to measure the height and weight of respondents to the nearest 0.1 cm and 0.1 kg, respectively. Anthropometric measurements were taken twice and the average values were used for data analysis. Body mass index (BMI, weight/height2 in kg/m2) was used to classify respondents into underweight, normal, overweight and obese based on the cut-off points recommended by the World Health Organization (WHO) [20].

Smoking

Respondents were classified as non-smokers if they answered “No” to the question “Have you ever smoked shisha, cigarettes, cigars and pipes?”; whilst respondents who answered “Yes” to both questions “Have you ever smoked shisha, cigarettes, cigars and pipes?” and “Do you currently smoke?” were classified as smokers.

Data analysis

SPSS version 19.0 with add-on complex sample analysis was used to analyse the data after the adjustment for stratification using post-stratified weights. Descriptive statistics were used to illustrate the characteristics of the study population by PA level (low, moderate or high) and socio-demographic variables (gender, locality, age, ethnicity, educational level, household monthly income, employment and marital status). Multivariable linear regression (MLR) or ordinary least square was performed to elucidate the associations of PA levels with SBP, DBP and blood glucose while controlling for gender, locality, age, ethnicity, educational level, household monthly income, employment and marital status, body mass index status and smoking status. Missing data were excluded from analyses and it was ignorable since the NHMS 2011 had taken a 20 % non-response rate into consideration at the sample size calculation stage. All statistical tests were conducted at a 95 % confidence interval (CI).

Results

Of the 18,231 eligible respondents aged 18 years and above, 99.1, 99.3 and 97.5 % of them responded to the PA, hypertension and diabetes modules of the questionnaire, respectively. The mean age (SD) of the respondents was 42.0 (16.0) years. The characteristics of respondents are provided in Table 1. The population was almost equally composed of men (51.1 %) and women (48.9 %). A large portion of respondents were urban dwellers (73.1 %). Almost half of the Malaysian population was constituted by the Malays, followed by the Chinese (25.4 %), other ethnic groups (Serani, Iban, Kadazan, Dusun, Bidayuh, Melanau and Bumiputras from the State of Sabah and Sarawak, as well as the aborigines, 17.8 %) and Indians (7.0 %). Most of the respondents attained a tertiary level of education (college/university graduates). Men accrued a higher level of high-intensity PA whilst women were engaged more in low- and moderate-intensity activities. Almost 1 in every 3 adults was overweight or hypertensive and 2 in every 13 were diabetic.
Table 1
Characteristics of the study population, Malaysia, April-June 2011
Socio-demographics
Male
Female
All
 
n
N (%)
n
N (%)
n
N (%)
 
8536
51.1
9695
48.9
18231
100
Locality
      
 Urban
4874
73.0
5730
73.3
10604
73.1
 Rural
3662
27.0
3965
26.7
7627
26.9
Age
      
 18-24
1445
20.3
1448
20.1
2893
20.2
 25-34
1889
26.7
2097
25.7
3986
26.2
 35-44
1643
19.9
2000
20.2
3643
20.0
 45-54
1620
16.4
1862
16.0
3482
16.2
 55-64
1159
10.0
1301
10.2
2460
10.1
 65 and above
780
6.7
987
7.8
1767
7.3
Ethnicity
      
 Malay
4858
48.5
5532
51.0
10390
49.8
 Chinese
1666
25.9
1856
25.0
3522
25.4
 Indian
651
6.8
808
7.3
1459
7.0
 Others
1361
18.8
1499
16.8
2860
17.8
Educational Level
      
 Primary
2106
22.1
2263
20.8
4369
21.4
 Secondary
4091
48.6
4191
45.6
8282
47.1
 Tertiary
1825
23.7
2040
23.9
3865
23.8
 No formal education
514
5.6
1201
9.7
1715
7.6
Household Income/montha
      
 Less than RM2000
3102
32.3
4038
38.4
7140
35.3
 RM2000-RM2999
1526
17.5
1562
16.1
3088
16.8
 RM3000-RM3999
1172
14.0
1236
13.2
2408
13.6
 At least RM4000
2736
36.2
2859
32.4
5595
34.3
Employment Status
      
 Government/semi-government
1075
12.3
1073
10.4
2148
11.4
 Private
3389
51.0
2308
33.9
5697
42.7
 Self-employed
2376
27.4
1243
13.2
3619
20.5
 Homemaker/unpaid worker
100
1.3
3094
33.9
3194
17.1
 Retiree
789
8.1
949
8.6
1738
8.3
Marital Status
      
 Single
2356
32.9
1875
24.0
4231
28.6
 Married
5954
65.2
6554
65.6
12508
65.4
 Widow/Widower/Divorcee
216
1.9
1254
10.4
1470
6.0
BMI Status
      
 Underweight
638
8.4
639
8.2
1277
8.3
 Normal
3833
48.0
3797
46.4
7630
47.2
 Overweight
2538
30.9
2615
27.8
5153
29.4
 Obese
1021
12.7
1729
17.6
2750
15.1
Smoking Status
      
 Current smoker
3973
46.9
160
1.9
4133
25
 Non-current smoker
4510
53.1
9430
98.1
13940
75
Physical Activity Level
      
 Low
2581
30.1
3899
40.4
6480
35.2
 Moderate
2729
32.5
3898
41.2
6627
36.7
 High
3122
37.4
1841
18.4
4963
28.1
Hypertension
      
 Yes
3130
33.7
3570
31.6
6700
32.7
 No
5330
66.3
6068
68.4
11398
67.3
Diabetes
      
 Yes
1555
15.8
1647
14.5
3202
15.2
 No
6754
84.2
7826
85.5
14580
84.8
Abbreviations: RM Ringgit Malaysia
a1 RM ≈ 0.24 US Dollar
Generally, both simple and multivariable linear regression (MLR) analyses demonstrated that PA level was positively associated with systolic blood pressure (SBP) (P < 0.05). However, such association was not significant between PA level and diastolic blood pressure (SDP) in the adjusted MLR analyses (Table 2). In contrast, both simple and multivariable linear regression (MLR) analyses revealed that there was a significant dose response relationship between PA level and blood glucose level (P < 0.05). Respondents with low level of PA had significantly higher blood glucose level as compared to those who were moderately or highly active (reference group), and also, those who were moderately active had significantly higher blood glucose level than their highly active counterparts (Table 3).
Table 2
Coefficients from multiple linear logistic regression of systolic and diastolic blood pressure on physical activity level
Physical activity level
Systolic blood pressure
Diastolic blood pressure
Crude
Adjusted
Crude
Adjusted
Coefficient
Standard error
*p-value
Coefficient
Standard error
*p-value
Coefficient
Standard error
*p-value
Coefficient
Standard error
p-value
Low (high)
−2.30
0.54
<0.001
−1.35
0.49
0.02
−1.20
0.33
0.001
−0.49
0.33
0.31
Moderate (high)
−1.72
0.51
−0.57
0.48
−0.41
0.32
−0.24
0.32
n
17,568
14,923
17,567
14,922
aCoefficient values were adjusted for gender, locality, age, ethnicity, educational level, household monthly income, employment and marital status, body mass index status and smoking status
*Significant p values at 95 % confidence interval
Table 3
Coefficients from multiple linear logistic regression of blood glucose on physical activity level
Physical activity level
Crude
Adjusted
Coefficient
Standard error
*p-value
Coefficienta
Standard error
*p-value
Low (High)
0.26
0.07
0.002
0.17
0.07
0.04
Moderate (High)
0.12
0.06
0.03
0.06
n
16,181
13,973
aCoefficient values were adjusted for gender, locality, age, ethnicity, educational level, household monthly income, employment and marital status, body mass index status and smoking status
*Significant p values at 95 % confidence interval

Discussion

This is the first national, multi-ethnic study to cross-sectionally examine the effects of PA against SBP, DBP and blood glucose among Malaysians aged 18 years and above, while controlling for other potential confounders. The present findings demonstrated a positive association between physical activity and systolic blood pressure. However, observations from several well-controlled cohort studies [8, 9] and randomised control trials (RCTs) [10, 11] had proven unequivocally an independent, negative association between PA and blood pressure.
One of the plausible explanations for the above findings could be due to differential misclassification, in which either the hypertensive respondents were differentially misclassified as having high PA or those with low PA were differentially misclassified as non-hypertensive. However, the latter (misclassification of hypertensive status) was unlikely as blood pressure of respondents were measured twice at a 10-min interval using calibrated devices, OMRON HEM-907 by trained nurses. Therefore differential misclassification of hypertensive respondents as highly active, or normal respondents as lowly active could occurred as a result of information bias as the use of IPAQ in the estimation of PA level was rather subjective and subjected to recall bias and tendency of respondents to report a socially desirable response, which may lead to an over-estimation of PA. Lee and his colleagues who performed a systematic review on the validation of IPAQ-SF with objective measurements stated that IPAQ-SF typically overestimated physical activity by an average of 84 % [21]. Therefore, the possible presence of differential misclassification of PA due to poor PA ascertainment in attenuating the real effect of PA against blood pressure should not be overlooked. In addition, more than three-quarters of respondents with known hypertension claimed that they were on oral anti-hypertensive drugs within the past 2 weeks of the interview date (data not shown), and this may again attenuate the beneficial effect of PA against SBP. Furthermore, the cross-sectional nature of the present study had also limited the inference of a direct causal relationship between PA and blood pressure. Therefore, only a properly conducted prospective cohort on healthy individuals [22] or a RCT which employs objective measurement for PA, such as accelerometer, pedometer or doubly labelled water [21], could conclusively determine the causal as well as dose–response relationship between PA level and blood pressure.
In contrast, a significant negative association was observed between PA and blood glucose among Malaysian adults. The present findings were consistent with those reported from other cross-sectional studies [6, 7, 12] and were corroborated by prospective observational studies [8, 23]. Furthermore, an interventional study by Knowler et al. [24] had demonstrated a 58 % (96 % CI: 48–66) reduction of diabetes incidence among the intervention group, which targeted at least a 7 % weight loss and at least 150 min of PA per week, compared to placebo. Additionally, findings from a large cohort study among more than 70,000 healthy women aged 40–65 years in the United States had substantiated the beneficial effects of moderate- and vigorous-intensity PA against diabetes, whereby brisk walking and more vigorous exercise were found to be associated with a 25 % reduction in diabetes incidence [25].
Despite the cross-sectional nature of the study and the use of a subjective instrument (IPAQ) in the estimation of PA level, the large sample size and its representativeness as well as the high response rate were the major strengths of the present study. In addition, underestimations of the prevalence of hypertension and diabetes among the population were unlikely as measurements of blood pressure and fasting blood glucose levels were taken properly by trained nurses using calibrated devices rather than self-reported.

Conclusions

Generally, a significant dose–response relationship was observed between physical activity and blood glucose, but not between physical activity and blood pressure. Nonetheless, in order to elucidate the true association between physical activity and hypertension or diabetes, the use of an objective instrument for the estimation of the physical activity level is highly recommended for future study.

Acknowledgements

The authors would like to thank the Director General of Health, Malaysia for his permission to publish this study. We would like to also convey our sincerest tribute to the field supervisors, nurses and data collectors for their dedicated efforts in conducting this survey. This research was supported by the Research and Development Fund, Ministry of Health Malaysia (NMRR-10-757-6837).
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.

Competing interests

The authors declare that they no competing interests.

Authors’ contributions

TCH as the first author, collected data and supervised data collection at the field, analyzed and interpreted the data, and drafted the manuscript. CYY and LKH helped in literature review, prepared the Results and Discussion sections of the article and critically reviewed the manuscript. LKK collected data, supervised data collection at the field and revised the manuscript critically. KCC and YPS helped in data analysis and interpretation and helped to draft the manuscript. AO and FY designed the study and helped in data analysis. LHL and NWA reviewed and revised the manuscript for important intellectual content. TA gave substantial contribution to the conception and design of the study, and critically reviewed the manuscript. All authors had given the final approval to publish the submitted manuscript in its present form.
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Metadaten
Titel
Association of physical activity with blood pressure and blood glucose among Malaysian adults: a population-based study
verfasst von
Chien Huey Teh
Ying Ying Chan
Kuang Hock Lim
Chee Cheong Kee
Kuang Kuay Lim
Pei Sien Yeo
Omar Azahadi
Yusoff Fadhli
Aris Tahir
Han Lim Lee
Wasi Ahmad Nazni
Publikationsdatum
01.12.2015
Verlag
BioMed Central
Erschienen in
BMC Public Health / Ausgabe 1/2015
Elektronische ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-015-2528-1

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