Skip to main content
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2019 Jan 28.
Published in final edited form as: Public Health. 2016 Apr 7;137:131–138. doi: 10.1016/j.puhe.2016.02.028

Physical activity levels in Bangladeshi adults: results from STEPS survey 2010

M Moniruzzaman a,*, M Mostafa Zaman a, MS Islalm b, HAMN Ahasan c, H Kabir d, R Yasmin c
PMCID: PMC6349143  EMSID: EMS81257  PMID: 27063947

Abstract

Objectives

Physical inactivity is an established risk factor for non-communicable diseases (NCD) and identified as the major public health concern worldwide. However, nationally representative and internationally comparable data on physical activity (PA) are lacking in Bangladesh. The objective of this paper was to determine nationally representative prevalence of PA levels among Bangladeshi adults.

Study design

Cross-sectional survey.

Methods

Data, on PA for this paper, were analysed from the NCD risk factors survey 2010 in Bangladesh. A standardized approach known as STEPS (STEPSwise approach to Surveillance for NCD risk factors) was followed for this survey. A total of 9275 adults (aged ≥ 25 years) were interviewed. Data on PA were processed and analysed according to Global Physical Activity Questionnaire (GPAQ) version 2 analysis framework.

Results

Of total 9275 respondents 4312 were men and 4963 women with a mean age of 42.4 (±13.5) years. Median MET-minutes of total PA in a typical week was double in rural areas (3360) than urban (1680) areas. The overall country wide prevalence of low PA was 34.5% (95% confidence interval, 33.5–35.5), urban 37.7% (36.3–39.1) and rural 31.6% (30.3–32.9). Women in general were more inactive (women, 53.6% [52.2–55.0], men 15.4% [14.9–17.1]). The main contributions to total PA were from work (urban 47.0%, rural 61.0%), and active commuting (38.0%, 30.0%) domains. Leisure-time PA represented only a small proportion (15.0%, 9.0%).

Conclusions

Insufficient physical activity is highly prevalent among the Bangladeshi adult population. Promoting overall PA at leisure-time and commuting considering country context can be feasible options with special attention to the women.

Keywords: Physical inactivity, Metabolic equivalent tasks (MET), Global physical activity questionnaire (GPAQ), Physical activity, Bangladeshi adults

Introduction

Physical activity (PA) is now a topic of global discussion in the contemporary healthcare market, specifically in the context of non-communicable diseases (NCDs) prevention and health promotion because of its very vital role in both primary and secondary prevention.13 A large number of epidemiological studies show the evidence that regular PA is associated with decreased risk of coronary heart disease,37 hypertension,4,8,9 stroke,10 type 2 diabetes mellitus,4,11,12 certain cancer,4,13,14 chronic obstructive pulmonary diseases15 and obesity.4,1618 PA helps to enhance the quality of life for people of all ages and abilities.19 Physical inactivity, on the other hand, is indicated as the major public health concerns all over the world.2025 It has been identified as the independent and fourth leading risk factor for global mortality which accounts 6.0% (3.2 million) of deaths in 2008.26 However, recent evidence shows that physical inactivity causes 9.0% (5.3 million) of annual deaths worldwide and 6–10.0% of deaths caused by non-communicable diseases are attributed to physical inactivity.27 Physical inactivity levels are rising in both developed and developing countries with major implications for increases in the prevalence of non-communicable diseases and the general health of the population worldwide.2834 Recent estimates indicate that the worldwide prevalence of physical inactivity in adults is 31.0%.29,35,36 Data from 76 countries, most of which were from developing countries, showed that the prevalence of physical inactivity among individuals aged 15 years or older ranged from 2.6% to 62.3%.31 The existing data suggests that physical inactivity is already a global public health problem and increasing rapidly in developing countries. However, many developing countries have a lack of data on PA levels in their population.37 Bangladesh is one of the developing countries where nationally representative and internationally comparable data on PA levels are still inadequate. Therefore, the objectives of this paper were to provide nationally representative prevalence of PA levels in Bangladesh, and explore difference in PA levels between adults living in urban vs rural settings in Bangladesh.

Methods

Data, on PA for this paper, were analysed from the NCD risk factors survey 2010 in Bangladesh. This national survey was conducted by standardized approach devised by WHO known as STEPS (STEPwise approach to Surveillance) for NCD risk factors.38 Details of the methods have been described elsewhere.39 Briefly, this survey was conducted among a Bangladeshi adult population aged 25 years or older. A total of 9275 (response rate 93.3%) individuals were interviewed. Samples were drawn from 398 randomly selected primary sampling units from rural and urban areas of Bangladesh. People of eligible age who stayed in the household the night before the day of survey were listed. One individual per household was recruited by using Kish method.40 The STEPS questionnaire for the survey was translated into Bengali and entered to a personal data assistant for electronic collection. Data were transferred to the National Data Center through secured system of file transfer protocol server on daily basis.

Measurement of PA

Data on PA were collected through a face-to-face interview by using the Global PA Questionnaire Version 2 (GPAQ: 2). It was developed by the World Health Organization for PA surveillance and is used for measuring PA levels. The GPAQ-2 contains 16 questions on frequency (days) and duration (minutes/hours) of moderate and vigourous intensity PA in three settings (or domains: work, transportation, and recreation) and on sedentary behaviour; questions are asked in terms of behaviour in a typical or usual week.41 The GPAQ-2 analysis protocol was followed for all data collection and processing and analysis.41

Conversion of PA data to estimated energy expenditure

METs (Metabolic Equivalent Tasks) are commonly used to express the intensity of PA. A MET is the ratio of specific PA metabolic rates to the resting metabolic rate, with one MET defined as the energy cost of sitting quietly (equivalent to a caloric consumption of 1 kcal/kg/hour).41

For this study, energy expenditure was estimated based on the duration, intensity and frequency of PA performed in a typical or usual week. The unit for measuring PA energy expenditure, Metabolic Equivalent (MET), was applied to PA variables derived from the GPAQ-2.

MET values and formulas for computation of MET minutes are based on the intensity of specific PA. It is estimated that, compared to sitting quietly, a person's caloric consumption is four times higher when being moderately active, and eight times higher when being vigorously active.

Therefore, when calculating a person's overall energy expenditure using GPAQ-2, moderate-intensity activities during work, commuting and recreation are assigned a value of 4 METs; vigorous-intensity activities are assigned a value of 8 METs. The total PA score is computed as the sum of all MET/minutes/week from moderate-to vigorous-intensity PA performed in work, commuting and recreation.41

So for the calculation of a person's overall energy expenditure using GPAQ-2 data, the above mentioned MET values were used.41

Procedures of classifying PA levels

For the calculation of a categorical indicator, the total time spent in PA during a typical week, the number of days as well as the intensity of the PA was taken into account. A person's normal level of PA was classified as low, moderate, and high as defined by the GPAQ analysis framework.41 The criteria of these levels are shown below-

High: A person reaching any of the following criteria:

  • (a)

    Vigorous-intensity activity on at least three days and accumulating at least 1500 MET-minutes/week OR

  • (b)

    Seven or more days of any combination of walking, moderate- or vigorous-intensity activities accumulating at least 3000 MET-minutes/week.

Moderate: A person not meeting the criteria for the ‘High’ category, but meeting any of the following criteria is classified in this category:

  • (a)

    Three or more days of vigorous-intensity activity of at least 20 min per day OR

  • (b)

    Five or more days of moderate-intensity activity and/or walking of at least 30 min per day OR

  • (c)

    Five or more days of any combination of walking, moderate- or vigorous-intensity activities accumulating at least 600 MET minutes/week.

Low: A person not meeting any of the above mentioned criteria falls in this category. No activity is reported or some activity is reported but not enough to meet high and moderate categories.

Data analysis

The prevalence of PA levels and other categorical variables are reported as proportions with 95% confidence interval (CI). Continuous variables, such as time spent in PA, are summarized with means, medians and inter-quartile ranges. Data were analysed using SPSS version 16.0.

Ethical considerations

Before the interview, written (or thumb impression) was obtained as appropriate. International ethical guidelines for biomedical research involving human subjects were followed throughout the study.42

Results

Sociodemographic characteristics

Of the 9275 respondents (urban − 4629, rural − 4646), 4312 (46.5%) were men. The mean age of respondents was 42.4 (±13.5) years. They had median three years of schooling. One-quarter of men were farmers, another quarter were labourers (agriculture, industrial or otherwise), and one-tenth was salary men in non-public sectors. In women, 83.0% were home makers. Almost 90.0% of the participants were Muslim. Detailed descriptions have been mentioned elsewhere.39

Time (in minutes) spent by the respondents in work, transport and recreation-related PA in a typical week

Based on quartile distribution, at least 50.0% of the respondents spent less than 150 min PA in each work, transport and recreation domain in a typical week expect work domain in rural areas. Counting all domains, on an average a person's total PA time was found more in rural areas (1242 min) than the amount found in urban areas (931 min). In general younger and productive age groups were found to spend relatively more time for work related PA and the trend is persistent across other domains (Table 1).

Table 1. Time (in minutes) spent by the respondents of urban and rural areas in work, transport and recreation-related physical activity in a typical week.

Domains Urban areas Rural areas


Age groups (yrs) 25–34 35–44 45–54 55–64 ≥65 All ages 25–34 35–44 45–54 55–64 ≥65 All ages












(n = 1694) (n = 1291)  (n = 887) (n = 479) (n = 278) (n = 4629) (n = 1470) (n = 1240)  (n = 960) (n = 536) (n = 407) (n = 4646)
Working      Mean  712  695 753  549  280  672  962 1003 1128 828  541  952
     Median  0  0 30  0  0  0  300 420 480 165  0  300
     (25th, 75th)  (0, 1050)  (0, 960) (0, 1080)  (0, 600)  (0, 60)  (0, 900)  (0, 1680) (0, 1725) (0, 2100) (0, 1440)  (0, 600)  (0, 1680)
Transport (commuting)      Mean  190  221 229  232  216  209  221 240 301 301  261  255
     Median  70  80 80  50  15  70  40 60 120 140  90  70
     (25th, 75th)  (0, 300)  (0, 360) (0, 420)  (0, 420)  (0, 360)  (0, 360)  (0, 420) (0, 420) (0, 622) (0, 622)  (0, 420)  (0, 420)
Recreation (leisure)      Mean  43  51 62  55  125  49  34 37 33 41  33  35
     Median  0  0 0  0  0  0  0 0 0 0  0  0
     (25th, 75th)  (0, 0)  (0, 0) (0, 45)  (0, 0)  (0, 0)  (0, 0)  (0, 0) (0, 0) (0, 0) (0, 0)  (0, 0)  (0, 0)
All domains      Mean  945  958 1044  836  522  931  1216 1279 1462 11,691  835  1242
     Median  360  420 450  385  180  390  600 755 885 695  350  720
     (25th, 75th)  (45, 1440)  (80, 1350) (120, 1470)  (16, 980)  (0, 720)  (60, 1290)  (89, 1920) (140, 2160) (180, 2520) (90, 1897)  (0, 1080)  (105, 2070)

Sex specific time (in minutes) spent by the respondents of urban and rural areas in doing PA in a typical week

In general, on average men were found to spend three-fold more time doing PA than women in both urban and rural areas. Based on quartile distribution, at least 25.0% of women were found doing no PA in both urban and rural areas. Overall both sexes in rural areas spent more time in PA than their counter part in urban areas (Table 2).

Table 2. Sex specific time (in minutes) spent by the respondents of urban and rural areas in doing physical activity in a typical week.

Sex Urban areas Rural areas


Age groups (yrs) 25–34 35–44 45–54 55–64 ≥65 All age 25–34 35–44 45–54 55–64 ≥65 All age












(n = 1694)
(m = 635,
w = 1059)
(n = 1291)
(m = 582,
w = 709)
(n = 887)
(m = 480,
w = 407)
(n = 479)
(m = 286,
w = 193)
(n = 278)
(m = 192,
w = 86)
(n = 4629)
(m = 2175,
w = 2454)
(n = 1470)
(m = 537,
w = 933)
(n = 1240)
(m = 494,
w = 746)
(n = 960)
(m = 491,
w = 469)
(n = 536)
(m = 299,
w = 237)
(n = 407)
(m = 316,
w = 124)
(n = 4646)
(m = 2137,
w = 2509)
Women Mean 509 518 462 374 214 483 613 777 692 480 387 653
Median 140 180 180 75 0 150 210 360 225 120 0 210
(25th, 75th) (0, 530) (0, 545) (0, 500) (0, 420) (0, 180) (0, 490) (0, 840) (45, 1080) (0, 930) (0, 600) (0, 217) (0, 870)
Men Mean 1673 1493 1538 1147 660 1436 2264 2037 2197 1715 1010 1934
Median 1100 870 840 600 360 840 2100 1842 1920 1340 630 1675
(25th, 75th) (420, 2880) (307, 2355) (363, 2572) (240,1800) (0, 840) (310, 360) (867, 3407) (757, 3247) (840, 3360) (600, 2700) (142, 1502) (720, 3105)
Both Mean 945 958 1044 836 522 931 1216 1279 1462 11,691 835 1242
Median 360 420 450 385 180 390 600 755 885 695 350 720
(25th, 75th) (45, 1440) (80, 1350) (120, 1470) (16, 980) (0, 720) (60, 1290) (89, 1920) (140, 2160) (180, 2520) (90, 1897) (0, 1080) (105, 2070)

Distribution of total PA MET-minutes in a typical week by area of residence

Based on quintile distribution, the median MET-minutes of total PA per week was double in rural areas than urban areas, and inter-quartile rage found wider in rural areas than urban areas (Fig. 1).

Fig. 1. Distribution of total physical activity MET-minutes in a typical week by area of residence.

Fig. 1

Composition of total PA in urban and rural areas

Work and transportation domains were the major contributors to the composition of total PA in both urban and rural areas. About two-thirds of the total activity in rural areas was contributed by work-related activity (61.0%) followed by commuting (30.0%) and recreational activity (9.0%), whereas in urban areas the composition was work-related activity (47.0%), commuting (38.0%) and recreational activity (15.0%) as shown in Fig. 2.

Fig. 2. Composition of total physical activity (%) in urban and rural areas.

Fig. 2

Prevalence of PA levels (low, moderate and high) in urban and rural areas

According to the GPAQ-2 classification, the prevalence of low PA level was found more in urban areas (37.7%) than rural areas (31.6%). The prevalence of moderate level of PA was found more in rural (52.4%) than urban areas (39.2%). However, the prevalence of high PA level was higher in urban areas (23.1%) compared to the prevalence found in rural areas (16.0%).

The country wide prevalence of PA levels was low 34.5% (95% CI, 33.5–35.5), moderate 46.0% (45.0–47.0) and high 19.5% (18.7–20.3) (Table 3).

Table 3. Prevalence of physical activity levels in urban and rural area,% (95% CI).

Sex    Age (yrs) Urban Rural Overall



n Low Moderate High n Low Moderate High n Low Moderate High
Men 25–34   635 12.6 (10.0–15.2) 66.1 (62.4–69.8) 21.3 (18.1–24.5)   537   7.8 (5.5–10.1) 82.5 (79.3–85.7)   9.7 (7.2–12.2) 1172 10.4 (8.7–12.1) 73.6 (71.1–76.1) 16.0 (13.9–18.1)
35–44   582 16.3 (13.3–19.3) 62.7 (58.8–66.6) 21.0 (17.7–24.3)   494 11.3 (8.5–14.1) 76.3 (72.6–80.0) 12.3 (9.4–15.2) 1076 14.0 (11.9–16.1) 69.0 (66.2–71.8) 17.0 (14.8–19.2)
45–54   480 13.5 (10.4–16.5) 63.1 (58.8–67.4) 23.3 (19.5–27.1)   491   7.1 (4.8–9.4) 82.7 (79.4–86.0) 10.2 (7.5–12.9)   971 10.3 (8.4–12.2) 73.0 (70.2–75.8) 16.7 (14.4–19.0)
55–64   286 21.0 (16.3–25.7) 50.3 (44.5–56.1) 28.7 (23.5–33.9)   299 12.7 (8.9–16.5) 71.9 (66.8–77.0) 15.4 (11.3–19.5)   585 16.8 (13.8–19.8) 61.4 (57.5–65.3) 21.9 (18.5–25.3)
≥65   192 37.5 (30.6–44.3) 34.9 (28.2–41.6) 27.6 (21.3–33.9)   316 30.1 (25.0–35.2) 47.2 (41.7–52.7) 22.8 (18.2–27.4)   508 32.9 (28.8–37.0) 42.5 (38.2–46.8) 24.6 (20.9–28.3)
≥25 (Crude) 2175 17.1 (15.5–18.7) 59.7 (57.6–61.8) 23.2 (21.4–25.0) 2137 12.4 (11.0–13.8) 74.4 (72.5–76.3) 13.1 (11.7–14.5) 4312 14.8 (13.7–15.9) 67.0 (65.6–68.4) 18.2 (17.0–19.4)
≥25 (age standardized)a 2175 18.5 (16.9–20.1) 57.9 (55.8–60.0) 23.6 (21.8–25.4) 2137 12.4 (11.0–13.8) 74.4 (72.5–76.3) 13.1 (11.7–14.5) 4312 15.4 (14.9–17.1) 66.1 (64.6–67.4) 18.5 (17.3–19.7)
Women 25–34 1059 53.5 (50.5–56.5) 24.6 (22.0–27.2) 21.9 (19.4–24.4)   933 46.8 (43.6–50.0) 34.3 (31.3–37.3) 18.9 (16.4–21.4) 1992 50.4 (48.2–52.6) 29.1 (27.1–31.1) 20.5 (18.7–22.3)
35–44   709 50.2 (46.5–53.9) 25.2 (22.0–28.4) 24.5 (21.3–27.7)   746 39.0 (35.5–42.5) 41.3 (37.8–44.8) 19.7 (16.8–22.6) 1455 44.5 (41.9–47.1) 33.5 (31.1–35.9) 22.1 (20.0–24.2)
45–54   407 51.8 (46.9–45.7) 28.8 (24.4–33.2) 23.3 (19.2–27.4)   469 47.3 (42.8–51.8) 35.6 (31.3–39.9) 17.1 (13.7–20.5)   876 49.4 (46.1–52.7) 30.6 (27.5–33.7) 20.0 (17.4–22.6)
55–64   193 63.7 (56.9–70.5) 17.6 (12.2–23.0) 18.7 (13.2–24.2)   237 56.1 (49.8–62.4) 27.0 (21.3–32.7) 16.9 (12.1–21.7)   430 59.5 (54.9–64.1) 22.8 (18.8–26.8) 17.7 (14.1–21.3)
≥65     86 77.9 (69.1–86.7)   5.8 (0.9–10.7) 16.3 (8.5–24.1)   124 72.6 (64.7–80.5) 16.9 (10.3–23.5) 10.5 (5.1–15.9)   210 74.8 (68.9–80.7) 12.4 (7.9–16.9) 12.9 (8.4–17.4)
≥25 (Crude) 2454 54.0 (52.0–56.0) 23.6 (21.9–25.3) 22.5 (20.8–24.2) 2509 46.8 (44.8–48.8) 35.1 (33.2–37.0) 18.2 (16.7–19.7) 4963 50.3 (48.9–51.7) 29.4 (28.1–30.7) 20.3 (19.2–21.4)
≥25 (age standardized)a 2454 57.4 (55.4–59.4) 21.9 (20.3–23.5) 21.5 (19.9–23.1) 2509 50.1 (48.1–52.1) 32.7 (30.9–34.5) 17.2 (15.7–18.7) 4963 53.6 (52.2–55.0) 27.1 (25.9–28.3) 19.3 (18.2–20.4)
Both 25–34 1694 38.2 (35.9–40.5) 40.1 (37.8–42.4) 21.7 (19.7–23.7) 1470 32.6 (30.2–25.0) 51.9 (49.3–54.5) 15.5 (13.6–17.4) 3164 35.6 (33.9–37.3) 45.6 (43.9–47.3) 18.8 (17.4–20.2)
35–44 1291 34.9 (32.3–37.5) 42.1 (39.4–44.8) 22.9 (20.6–25.2) 1240 28.0 (25.5–30.5) 55.2 (52.4–58.0) 16.8 (14.7–18.9) 2531 31.5 (29.7–33.3) 48.6 (46.7–50.5) 19.9 (18.3–21.5)
45–54   887 31.1 (28.1–34.1) 45.5 (42.2–48.8) 23.3 (20.5–26.1)   960 26.8 (24.0–29.6) 59.7 (56.6–62.8) 13.5 (11.3–15.7) 1847 28.9 (26.8–31.0) 52.9 (50.6–55.2) 18.2 (16.4–20.0)
55–64   479 38.2 (33.8–42.6) 37.2 (32.9–41.5) 24.6 (20.7–28.5)   536 31.9 (28.8–35.8) 52.1 (47.9–56.3) 16.0 (12.9–19.1) 1015 34.9 (32.0–37.8) 45.0 (41.9–48.1) 20.1 (17.6–22.6)
≥65   278 50.0 (44.1–55.9) 25.9 (20.8–31.0) 24.1 (19.1–29.1)   440 42.0 (37.4–46.6) 38.6 (34.1–43.1) 19.3 (15.6–23.0)   718 45.1 (41.5–48.7) 33.7 (30.2–37.2) 21.2 (18.2–24.2)
≥25 (Crude) 4629 36.6 (35.2–38.0) 40.6 (39.2–42.0) 22.8 (21.6–24.0) 4646 31.0 (29.7–32.3) 53.2 (51.8–54.6) 15.9 (14.8–17.0) 9275 33.8 (32.8–34.8) 46.9 (45.9–47.9) 19.3 (18.5–20.1)
≥25 (age standardized)a 4629 37.7 (36.3–39.1) 39.2 (37.8–40.6) 23.1 (21.9–24.3) 4646 31.6 (30.3–32.9) 52.4 (51.0–53.8) 16.0 (14.9–17.1) 9275 34.5 (33.5–35.5) 46.0 (45.0–47.0) 19.5 (18.7–20.3)
a

Standardized to the age distribution of the new WHO world standard population (2000–2025).

Discussion

This is the first ever nationally representative and internationally comparable data on PA in Bangladesh which stands limited in many developing countries. Policy makers are currently interested in addressing PA as one of the priority intervention strategies to achieve nine voluntary global targets for prevention and control of NCDs by 2025.43 Although this survey was done in 2010, the national benchmark for Bangladesh is yet to be set out for achieving targets on PA indicator.

This paper also caries high importance for many developing countries especially those who are passing through epidemiological transition having impact on lifestyles. PA data using GPAQ are yet to be made available in many of these countries. This report will help them conceptualizing PA measurements that would be internationally comparable. This study has set an example that GPAQ is a feasible option in low resource settings.

In this study, our estimate for prevalence of physical inactivity among Bangladeshi adults is 34.5%, which is similar to global estimate (31.0%).29,35,36 This estimate is also comparable and found similar to many other low- and middle-income countries that participated in large scale multinational prevalence studies.30,31,33,37

Because the population in Bangladesh is large, one-third of whom are physically inactive accounts a huge number. Therefore it has merited not only increased health risk but also social burden as well as developmental issues. This increased prevalence can be explained by the shifting towards urbanization and industrialization in lower income countries from agricultural labour. It implies a reduction in energy expenditure with changes in lifestyle to sedentary pattern44 and thus changes occur in PA patterns. Moreover, currently the developing countries like Bangladesh have been experiencing rapid changes in the social and economic landscapes with profound effects of urbanization, workforce structure and lifestyle patterns.4547

Changes in the socio-economic environment have also resulted in the overall shifting of the population from active work-related PA and commuting to sedentary lifestyle.4749 On the other hand, participation in recreational activity is not yet common in many developing countries which substantially have further increased the prevalence of overall physical inactivity.32,50

In this study, in general men are more active in doing physical activities compared to women in both urban and rural areas (Tables 2 and 3). This finding is the case in most countries (80.0%) of WHO Regions.29,31 PA at work and transport domains are the main contributors to total PA among study populations (Fig. 2). Leisure-time activity contributed only 9.0% in rural and 15.0% in urban areas. These findings are also in line with many low- and middle-income countries where work and transport-related activities are the prime contributors to overall PA.3033,51 Nonetheless, in some developed countries leisure-time PA is a major component of total PA instead.30,52 This may be due to favourable infrastructure and accessibility to sports or recreational facilities and a history of long term promotion of exercise.

Many people in Bangladesh spend a significant amount of time and energy doing hard PA for their livelihood. This leads to a very thin body mass.53 In our sample, one-quarter of people were thin (body mass index <18.5 kg/m2). Leisure time PA is not popular in Asian culture in many countries especially in rural settings.33 Therefore it is a challenge to design pragmatic strategies for them to promote leisure time PA in Bangladesh. However, promoting PA at leisure time and commuting can be a feasible intervention for urban dwellers especially for women and richer segments of the society. In this study, women reported more than three-fold physical inactivity compared to men. Therefore an innovative strategy for uplifting PA of women without conflicting with social and religious norms is required. Non-health sectors have a major role in promoting PA in such cases. Collaboration with local governments (city corporations, and municipalities), ministry of education, mass transportation, roads and highways etc. is necessary to promote PA. Removal of environmental barriers (such as lack of play grounds, parks, walkable footpaths, safe roads for bicycles, etcetera) to PA will play a critical role.

We acknowledge that a recall bias might have influenced the findings of this study. This includes categorization of vigorous and moderate activities, and the duration of such activities they had. Therefore chances of under- or over-reporting of PA level cannot be over ruled with certainty.

To conclude, low level of PA is highly prevalent among Bangladeshi adult population. One in three adults is insufficiently physically active. The results of this paper, at national level, will focus the necessity of PA intervention at population level for the primary prevention of NCDs and will give the baseline information about the PA levels of adult population in Bangladesh. It will help the policy-makers at national level to develop the national guideline for PA. Promoting overall PA level at leisure-time and commuting can be feasible options with special attention to the women.

Acknowledgements

This manuscript is based on the ‘STEPS Survey 2010 for NCD risk factors in Bangladesh’ done by Bangladesh Society of Medicine with technical support of WHO Country Office for Bangladesh.

Funding

Funded by the WHO Country Office for Bangladesh under the project number: SEBAN 1003650 and award number: 55475.

Footnotes

Ethical approval

Obtained from Bangladesh Medical Research Council.

Competing interest

The authors alone are responsible for views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.

Authors' contributions

M: Carried out data processing, treatment and analyses on physical activity and write up the manuscript.

MMZ: Designed the main survey, conceptualized the manuscript and critically review it. He is the guarantor of the study.

MSI: Involved in designing, guided data management and interpretation of data.

HAMNA: Implemented the survey, trained the field team and involved in drafting the manuscript.

HK: Implemented the survey, oversaw the quality control measure and involved in the final draft of manuscript.

RY: Implemented the survey and involved in drafting the manuscript.

References

  • 1.Paffenbarger RS, Hyde RT, Wing AL, Hsieh C-C. Physical activity, all cause mortality, and longevity of college alumni. N Engl J Med. 1986;314:605–13. doi: 10.1056/NEJM198603063141003. [DOI] [PubMed] [Google Scholar]
  • 2.Morris JN, Clayton DG, Everitt MG, Semmence AM, Burgess EH. Exercise in leisure time: coronary attack and death rate. Br Heart J. 1990;63:325–34. doi: 10.1136/hrt.63.6.325. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Powell KE, Thompson PD, Caspersen CJ, Frod ES. Physical activity and incidence of coronary heart disease. Annu Rev Public Health. 1987;8:253–87. doi: 10.1146/annurev.pu.08.050187.001345. [DOI] [PubMed] [Google Scholar]
  • 4.Waxman A. WHO's global strategy on diet, physical activity and health: response to a worldwide epidemic of non-communicable diseases. Scand J Nutr. 2004;48(2):58–60. [Google Scholar]
  • 5.Moholdt T, Wisløff U, Nilsen TIL, Slørdahl SA. Physical activity and mortality in men and women with coronary heart disease: a prospective population-based cohort study in Norway (the HUNT study) Eur J Cardiovasc Prev Rehabil. 2008;15(6):639–45. doi: 10.1097/HJR.0b013e3283101671. [DOI] [PubMed] [Google Scholar]
  • 6.Lee I-M, Sesso HD, Paffenbarger RS., Jr Physical activity and coronary heart disease risk in men: does the duration of exercise episodes predict risk? Circulation. 2000;102(9):981–6. doi: 10.1161/01.cir.102.9.981. [DOI] [PubMed] [Google Scholar]
  • 7.Sundquist K, Qvist J, Johansson SS, Sundquist J. The long-term effect of physical activity on incidence of coronary heart disease: a 12-year follow-up study. Prev Med. 2005;41:219–25. doi: 10.1016/j.ypmed.2004.09.043. [DOI] [PubMed] [Google Scholar]
  • 8.Pereira MA, Folsom AR, McGovern PG, Carpenter M, Arnett DK, Liao D, et al. Physical activity and incident hypertension in black and white adults: the Atherosclerosis Risk in Communities Study. Prev Med. 1999;28:304–12. doi: 10.1006/pmed.1998.0431. [DOI] [PubMed] [Google Scholar]
  • 9.Barengo NC, Hu G, Kastarinen M, Lakka TA, Pekkarinen H, Nissinen A, et al. Low physical activity as a predictor for antihypertensive drug treatment in 25-64-year-old populations in eastern and south-western Finland. J Hypertens. 2005;23:293–9. doi: 10.1097/00004872-200502000-00011. [DOI] [PubMed] [Google Scholar]
  • 10.Wendel-Vos GC, Schuit AJ, Feskens EJ, Boshuizen HC, Verschuren WM, Saris WH, et al. Physical activity and stroke. A meta-analysis of observational data. Int J Epidemiol. 2004;33:787–98. doi: 10.1093/ije/dyh168. [DOI] [PubMed] [Google Scholar]
  • 11.Sigal RJ, Kenny GP, Wasserman DH, Castaneda-Sceppa C. Physical activity/exercise and type 2 diabetes. Diabetes Care. 2004;27(10):2518–39. doi: 10.2337/diacare.27.10.2518. [DOI] [PubMed] [Google Scholar]
  • 12.Meisinger C, Lowel H, Thorand B, Doring A. Leisure time physical activity and the risk of type 2 diabetes in men and women from the general population. The MONICA/KORA Augsburg Cohort Study. Diabetologia. 2005;48:27–34. doi: 10.1007/s00125-004-1604-3. [DOI] [PubMed] [Google Scholar]
  • 13.McTiernan A, Ulrich C, Slate S, Potter J. Physical activity and cancer etiology: associations and mechanisms. Cancer Causes Control. 1998;9(5):487–509. doi: 10.1023/a:1008853601471. [DOI] [PubMed] [Google Scholar]
  • 14.Slattery ML, Edwards S, Curtin K, Ma K, Edwards R, Holubkov R, et al. Physical activity and colorectal cancer. Am J Epidemiol. 2003;158(3):214–24. doi: 10.1093/aje/kwg134. [DOI] [PubMed] [Google Scholar]
  • 15.Watz H, Waschki B, Meyer T, Magnussen H. Physical activity in patients with COPD. Eur Respir J. 2009;33(2):262–72. doi: 10.1183/09031936.00024608. [DOI] [PubMed] [Google Scholar]
  • 16.Jakicic JM, Otto AD, Polzien K, Kelli D. Physical activity and obesity. In: Kushner RF, Bessesen DH, editors. Treatment of the obese patient. Humana Press; 2007. pp. 311–20. [Google Scholar]
  • 17.Hill JO, Wyatt HR. Role of physical activity in preventing and treating obesity. J Appl Physiol. 2005;99:765–70. doi: 10.1152/japplphysiol.00137.2005. [DOI] [PubMed] [Google Scholar]
  • 18.Sisson SB, Katzmarzyk PT. International prevalence of physical activity in youth and adults. Obes Rev. 2008;9(6):606–14. doi: 10.1111/j.1467-789X.2008.00506.x. [DOI] [PubMed] [Google Scholar]
  • 19.US Department of Health and Human Services (US DHHS) Physical activity and health: a report of the surgeon general. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention National Canter for Chronic Disease Control and Prevention and Health Promotion; 1996. [Google Scholar]
  • 20.Kujala UM, Kaprio J, Sarna S, Koskenvuo M. Relationship of leisure-time physical activity and mortality: the Finnish twin cohort. J Am Med Assoc. 1998;279:440–4. doi: 10.1001/jama.279.6.440. [DOI] [PubMed] [Google Scholar]
  • 21.Ferucci L, Izmirlian G, Leveille S, et al. Smoking, physical activity and active life expectancy. Am J Epidemiol. 1999;149:645–53. doi: 10.1093/oxfordjournals.aje.a009865. [DOI] [PubMed] [Google Scholar]
  • 22.The European Health Report. WHO regional publications. Copenhagen: European Series No. 97 WHO Regional Office for Europe; 2002. [Google Scholar]
  • 23.Russell JS, Craig CL. Physical Activity and Lifestyles in Canada 1981–1995. Canadian Fitness and Lifestyle Research Institute; [Google Scholar]
  • 24.Berlin JA, Colditz GA. A meta-analysis of physical activity in the prevention of coronary heart disease. Am J Epidemiol. 1990;132:639–46. doi: 10.1093/oxfordjournals.aje.a115704. [DOI] [PubMed] [Google Scholar]
  • 25.Global Strategy on Diet. Physical activity and health WHO report. Available at: http://www.who.int/dietphysicalactivity/publications/facts/pa/en.
  • 26.Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization; 2009. [Google Scholar]
  • 27.Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380(9838):219–29. doi: 10.1016/S0140-6736(12)61031-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.WHO. Global recommendations on physical activity for health. Switzerland: World Health Organization; 2010. [PubMed] [Google Scholar]
  • 29.Physical inactivity: a Global Public Health Problem. World Health Organization (WHO); [cited 2011 19 June]. Available at: http://www.who.int/dietphysicalactivity/factsheet_inactivity/en/index.html. [Google Scholar]
  • 30.Bauman A, Bull F, Chey T, Craig C, Ainsworth B, Sallis J, et al. The international prevalence study on physical activity: results from 20 countries. Int J Behav Nutr Phys Activity. 2009;6(1):21. doi: 10.1186/1479-5868-6-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Dumith SC, Hallal PC, Reis RS, Kohl Iii HW. Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Prev Med. 2011;53(1–2):24–8. doi: 10.1016/j.ypmed.2011.02.017. [DOI] [PubMed] [Google Scholar]
  • 32.Trinh O, Nguyen N, Dibley M, Phongsavan P, Bauman A. The prevalence and correlates of physical inactivity among adults in Ho Chi Minh City. BMC Public Health. 2008;8(1):204. doi: 10.1186/1471-2458-8-204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Ng N, Hakimi M, Van Minh H, Juvekar S, Razzaque A, Ashraf A, et al. Prevalence of physical inactivity in nine rural INDEPTH Health and demographic surveillance systems in five Asian countries. Glob Health Action Suppl. 2009;1 doi: 10.3402/gha.v2i0.1985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.World Health Organization (WHO) Global strategy on diet, physical activity and health. Geneva: WHO; 2004. [Google Scholar]
  • 35.Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012;380(9838):247–57. doi: 10.1016/S0140-6736(12)60646-1. [DOI] [PubMed] [Google Scholar]
  • 36.World Health Organization. Global Health Observatory Database: prevalence of insufficient physical activity. http://www.who.int/gho/ncd/risk_factors/physical_activity_text/en/index.html.
  • 37.Guthold R, Ono T, Strong KL, Chatteriji S, Morabia A. Worldwide variability in physical inactivity: a 51-country survey. Am J Prev Med. 2008;34(6):486–94. doi: 10.1016/j.amepre.2008.02.013. [DOI] [PubMed] [Google Scholar]
  • 38.Bonita R, de courten M, Dwyer T, Jamrozik K, Winkelmann R. Surveillance of risk factors for non-communicable diseases: the WHO STEP wise approach. Summary. Geneva: World Health Organization; 2001. [Google Scholar]
  • 39.Zaman MM, Rahman M, Rahman M, Bhuiyan MR, Karim M, Chowdhury MJ. Prevalence of risk factors for non-communicable diseases in Bangladesh: Results from STEPS survey 2010. Indian J Public Health. 2016;60:17–25. doi: 10.4103/0019-557X.177290. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Kish Leslie. A procedure for objective respondent selection with the household. J Am Stat Assoc. 1949;44(247):380–7. [Google Scholar]
  • 41.GPAQ: Global Physical Activity Questionnaire (version 2.0) Department of Chronic Diseases and Health Promotion, WHO; [cited 2010 13 August]. Available at: http://www.who.int/chp/steps/resources/GPAQ_Analysis_Guide.pdf. [Google Scholar]
  • 42.International ethical guidelines for biomedical research involving human subjects. The Council for International Organizations of Medical Sciences (CIOMS) in collaboration with the World Health Organization (WHO); [cited 2010 15 July]. Available at: http://www.codex.uu.se/texts/international.html. [Google Scholar]
  • 43.World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013–2020. Geneva: WHO; 2013. Available at: http://apps.who.int/iris/bitstream/10665/94384/1/9789241506236_eng.pdf?ua=1; 2013 http://www.amazon.com/Physical-Activity-Levels-Bangladesh-Prevalence/dp/3659186961. [Google Scholar]
  • 44.Popkin B. Nutrition in transition: the changing global nutrition challenge Asia. Pac J Clin Nutr. 2001;10:S13–8. [PubMed] [Google Scholar]
  • 45.United Nations Development Program (UNDP) Human development report 2007/2008. Fighting climate change: human solidarity in a divided world. New York: 2007. [Google Scholar]
  • 46.Zhai F, Wang H, Du S. Lifespan nutrition and changing socio-economic conditions in China. Asia Pac J Clin Nutr. 2007;16(Suppl. 1):374–82. [PubMed] [Google Scholar]
  • 47.Monda KL, Gordon-Larsen P, Stevens J. China's transition: the effect of rapid urbanisation on adult occupational physical activity. Soc Sci Med. 2007;64:858–70. doi: 10.1016/j.socscimed.2006.10.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Forrest KYZ, Bunker CH, Kriska AM. Physical activity and cardiovascular risk factors in a developing population. Med Sci Sports Exerc. 2000;33:1598–604. doi: 10.1097/00005768-200109000-00025. [DOI] [PubMed] [Google Scholar]
  • 49.Ma G, Luan D, Li Y. Physical activity level and its association with metabolic syndrome among an employed population in China. Obes Rev. 2008;9(Suppl. 1):113–8. doi: 10.1111/j.1467-789X.2007.00451.x. [DOI] [PubMed] [Google Scholar]
  • 50.Ku PW, Fox KR, McKenna J. Prevalence of leisure-time physical activity in Taiwanese adults: results of four national surveys, 2000e2004. Prev Med. 2006;43:45–7. doi: 10.1016/j.ypmed.2006.04.011. [DOI] [PubMed] [Google Scholar]
  • 51.Armstrong T, Bull F. Development of the World Health Organization global physical activity questionnaire (GPAQ) J Public Health. 2006;14(2):66–70. [Google Scholar]
  • 52.Parks SE, Housemann RA, Brownson RC. Different correlates of physical activity in urban and rural adults of various socioeconomic backgrounds in the United States. J Epidemiol Community Health. 2003;57:29–35. doi: 10.1136/jech.57.1.29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Zaman MM, Bhuiyan RM, Karim MN, MoniruzZaman Rahman MM, Akanda AW, Fernando T. Clustering of noncommunicable diseases risk factors in Bangladeshi adults: an analysis of STEPS survey 2013. BMC Public Health. 2015;15:659. doi: 10.1186/s12889-015-1938-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES