| Literature DB >> 20027261 |
Nawi Ng1, Mohammad Hakimi, Hoang Van Minh, Sanjay Juvekar, Abdur Razzaque, Ali Ashraf, Syed Masud Ahmed, Uraiwan Kanungsukkasem, Kusol Soonthornthada, Tran Huu Bich.
Abstract
BACKGROUND: Physical inactivity leads to higher morbidity and mortality from chronic non-communicable diseases (NCDs) such as stroke and heart disease. In high income countries, studies have measured the population level of physical activity, but comparable data are lacking from most low and middle-income countries.Entities:
Keywords: Asia; WHO STEPS; chronic non-communicable diseases; low and middle-income countries; physical inactivity; risk factors surveillance
Year: 2009 PMID: 20027261 PMCID: PMC2785136 DOI: 10.3402/gha.v2i0.1985
Source DB: PubMed Journal: Glob Health Action ISSN: 1654-9880 Impact factor: 2.640
Criteria used for establishing levels of physical activity
| Levels of physical activity | Criteria |
|---|---|
| High | A person reaching any of the following criteria is classified in this category: |
| – Vigorous-intensity activity on at least three days achieving a minimum of atleast 1,500 MET-minutes/week OR; and | |
| – seven or more days of any combination of walking, moderate or vigorous intensity activities achieving a minimum of at least 3,000 MET-minutes per week. | |
| Moderate | A person not meeting the criteria for the ‘high’ category, but meeting any of the following criteria is classified in this category: |
| – three or more days of vigorous-intensity activity of at least 20 minutes per day OR; | |
| – five or more days of moderate-intensity activity or walking of at least 30 minutes per day OR; and | |
| – five or more days of any combination of walking, moderate or vigorous intensity activities achieving a minimum of at least 600 MET-minutes per week. | |
| Low | A person not meeting any of the above mentioned criteria falls in this category. |
Source: WHO GPAQ STEPS Manual (14).
.Prevalence of physical inactivity (95% CI) in nine HDSS sites by gender.
Percentage of population not engaging in vigorous activity (95% CI) in nine rural Asian HDSS sites by gender and age-groups
| Bangladesh | India | Vietnam | Indonesia | Thailand | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| No vigorous activity | Matlab ( | Mirsarai ( | Abhoynagar ( | WATCH ( | Vadu ( | Chililab ( | Filabavi ( | Purworejo ( | Kanchanaburi ( | ||
| Men | |||||||||||
| 25–34 | 92.7 (89.5–96) | 78.9 (73.8–84) | 79 (73.7–84.2) | 45.2 (39–51.4) | 92 (88.7–95.3) | 31.5 (25.9–37) | 49.1 (39.9–58.3) | 30 (24.3–35.8) | 48.8 (42.7–54.9) | ||
| 35–44 | 90 (86.3–93.7) | 75 (69.7–80.3) | 82.3 (77.7–87) | 35.3 (29.4–41.3) | 85.7 (81.6–89.9) | 39.2 (33.4–45) | 55.6 (47.5–63.8) | 25.9 (20.4–31.4) | 51.3 (45.3–57.4) | ||
| 45–54 | 90.7 (87.2–94.2) | 76.9 (71.7–82) | 84.5 (80–89) | 40 (33.9–46.1) | 83.7 (79.1–88.2) | 45.7 (40.1–51.3) | 50 (41.7–58.3) | 19.3 (14.4–24.2) | 55.5 (49.5–61.5) | ||
| 55–64 | 93.4 (90.5–96.4) | 82.4 (77.8–87.1) | 92.9 (89.7–96.1) | 53.2 (47–59.4) | 82.4 (77.7–87.2) | 63.4 (57.4–69.4) | 65 (55.6–74.4) | 23.6 (18.3–28.9) | 64 (58.3–69.7) | ||
| Total | 91.5 (89.7–93.3) | 77.9 (75.2–80.6) | 83.3 (80.8–85.8) | 42.2 (38.9–45.4) | 86.8 (84.7–88.9) | 41.5 (38.5–44.5) | 53.1 (48.5–57.7) | 24.5 (21.8–27.2) | 53.5 (50.4–56.7) | ||
| Women | |||||||||||
| 25–34 | 97.3 (95.3–99.3) | 97.5 (95.6–99.5) | 95.8 (93.2–98.3) | 72.8 (67.3–78.3) | 89.6 (85.8–93.4) | 73.1 (67.8–78.3) | 58.9 (51.6–66.2) | 68.8 (62.9–74.6) | 72.6 (67.2–77.9) | ||
| 35–44 | 93 (89.9–96.1) | 95.4 (92.9–98) | 95.3 (92.7–97.9) | 68.8 (63.1–74.5) | 88 (84.1–92) | 59.9 (54.1–65.8) | 53.6 (46.3–60.8) | 50.2 (43.9–56.6) | 60.9 (55.2–66.7) | ||
| 45–54 | 96 (93.6–98.5) | 95.3 (92.7–97.9) | 97.6 (95.7–99.5) | 75.6 (70.3–80.9) | 82.1 (77.5–86.6) | 65.5 (60.2–70.8) | 53.1 (45.8–60.4) | 49.4 (43.2–55.6) | 62.2 (56.5–67.9) | ||
| 55–64 | 96.8 (94.6–99) | 96 (93.6–98.4) | 99.2 (98.1–100.3) | 83.2 (78.6–87.8) | 82 (77.2–86.7) | 78.1 (73–83.2) | 61.7 (52.8–70.6) | 57.8 (51.4–64.2) | 68 (62.5–73.6) | ||
| Total | 95.7 (94.3–97) | 96.2 (95–97.4) | 96.5 (95.3–97.8) | 73.4 (70.3–76.5) | 86.3 (84.2–88.4) | 67.6 (64.7–70.5) | 55.8 (51.8–59.7) | 55.4 (52.1–58.6) | 65.6 (62.7–68.5) | ||
.Average time spent in physical activity per day in minutes (median value with inter-quartile ranges) in nine HDSS sites.
Level of physical inactivity in different domains of activities in nine rural Asian HDSS sites by gender and age-groups
| Bangladesh | India | Vietnam | Indonesia | Thailand | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Percentage (%) reported (95% CI) | Matlab ( | Mirsarai ( | Abhoynagar ( | WATCH ( | Vadu ( | Chililab ( | Filabavi ( | Purworejo ( | Kanchanaburi ( | ||
| Men | |||||||||||
| Percentage (%) reported no vigorous or moderate activities at work | 66.5 (63.4–69.5) | 57.9 (54.7–61.0) | 46 (42.8–49.3) | 27 (24.1–30.1) | 85.6 (83.3–87.6) | 18.2 (16.0–20.6) | 62.1 (58.9–65.2) | 1.4 (0.9–2.3) | 9 (7.4–11.0) | ||
| Percentage (%) who did not walk or cycle from places to places | 24.6 (21.9–27.5) | 26.4 (23.6–29.3) | 14.6 (12.5–17.1) | 7.3 (5.7–9.2) | 29.9 (27.1–32.9) | 46.3 (43.3–49.4) | 11.2 (8.4–14.8) | 41.7 (38.6–44.9) | 53 (49.9–56.1) | ||
| Percentage (%) reported no vigorous or moderate activities during leisure | 98.9 (97.8–99.4) | 96 (94.4–97.2) | 96.8 (95.4–97.8) | 93.2 (91.3–94.8) | 94.5 (93.0–95.8) | 61.8 (58.8–64.7) | 86.5 (84.1–88.6) | 93.3 (91.6–94.7) | 73.6 (70.7–76.3) | ||
| Women | |||||||||||
| Percentage (%) reported no vigorous or moderate activities at work | 22.2 (19.7–24.8) | 55.2 (51.9–58.4) | 25.1 (22.3–28.1) | 17.3 (14.8–20.1) | 80.7 (78.2–83.1) | 14 (12.0–16.2) | 49.7 (46.5–52.9) | 1.4 (0.8–2.4) | 10.5 (8.7–12.5) | ||
| Percentage (%) who did not walk or cycle from places to places | 72.7 (69.7–75.5) | 78.5 (75.7–81.1) | 64 (60.8–67.1) | 80.2 (77.3–82.8) | 33.8 (30.9–36.9) | 21 (18.6–23.7) | 4.3 (2.9–6.3) | 50.4 (47.2–53.7) | 52.2 (49.1–55.2) | ||
| Percentage (%) reported no vigorous or moderate activities during leisure | 99.6 (98.9–99.9) | 99.3 (98.4–99.7) | 99.9 (99.0,100) | 93.9 (92.0–95.4) | 93.8 (92.2–95.1) | 76.9 (74.3–79.3) | 86.9 (84.6–89.0) | 97.5 (96.2–98.3) | 86.7 (84.5–88.7) | ||
Strength of association between demographic variables and low levels of activity (odds ratio and its 95% CI) in nine rural Asian HDSSs
| Bangladesh | India | Vietnam | Indonesia | Thailand | |||||
|---|---|---|---|---|---|---|---|---|---|
| Variables | Matlab | Mirsarai | Abhoynagar | WATCH | Vadu | Chililab | Filabavi | Purworejo | Kanchanaburi |
| Sex | |||||||||
| Men | 0.29 (0.23–0.35) | 0.15 (0.12–0.19) | 0.36 (0.29–0.45) | 0.38 (0.28–0.51) | 0.84 (0.69–1.02) | 1.43 (1.09–1.87) | 1.49 (1.23–1.8) | 0.35 (0.28–0.46) | 0.51 (0.41–0.65) |
| Women | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Age groups (years) | |||||||||
| 25–34 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| 35–44 | 0.89 (0.68–1.16) | 0.69 (0.52–0.92) | 0.68 (0.51–0.91) | 0.78 (0.54–1.13) | 0.85 (0.66–1.1) | 0.69 (0.48–1) | 0.82 (0.63–1.05) | 1.1 (0.79–1.52) | 0.83 (0.6–1.14) |
| 45–54 | 0.99 (0.76–1.29) | 0.93 (0.7–1.24) | 0.64 (0.48–0.87) | 1.05 (0.74–1.49) | 0.95 (0.73–1.24) | 0.86 (0.61–1.21) | 0.85 (0.66–1.1) | 0.85 (0.6–1.22) | 0.83 (0.59–1.16) |
| 55–64 | 1.52 (1.16–1.97) | 1.22 (0.92–1.62) | 1.07 (0.8–1.42) | 2.02 (1.45–2.82) | 1.01 (0.76–1.34) | 0.68 (0.47–1) | 1.66 (1.25–2.19) | 1.12 (0.78–1.62) | 1.01 (0.74–1.4) |
| Highest education levels | |||||||||
| No schooling and not graduated from primary school | 0.82 (0.58–1.16) | 0.57 (0.37–0.88) | 0.65 (0.4–1.04) | 0.24 (0.15–0.37) | 0.78 (0.6–1.02) | 0.8 (0.49–1.28) | 0.33 (0.22–0.5) | 0.31 (0.21–0.47) | 0.55 (0.37–0.81) |
| Graduated from primary school | 0.84 (0.58–1.22) | 0.61 (0.36–1.03) | 1 (0.57–1.74) | 0.58 (0.34–0.99) | 0.88 (0.63–1.22) | 0.4 (0.26–0.62) | 0.36 (0.25–0.51) | 0.42 (0.3–0.59) | 0.68 (0.48–0.97) |
| Graduated from secondary school | 0.93 (0.54–1.62) | 0.78 (0.49–1.23) | 0.82 (0.5–1.35) | 0.48 (0.27–0.87) | 0.93 (0.7–1.24) | 0.53 (0.39–0.71) | 0.41 (0.3–0.56) | 0.64 (0.45–0.93) | 0.57 (0.34–0.95) |
| Graduated from high school or university | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |