| Literature DB >> 29360730 |
Jingmei Dong1, Su Zhang2, Li Xia3, Yi Yu4, Shuangshuang Hu5, Jingyu Sun6, Ping Zhou7, Peijie Chen8.
Abstract
It is an extremely urgent problem that physical fitness promotion must face not only the increasing air pollution but also the decline of physical activity level of children and adolescents worldwide at present, which is the major reason that forms an inactive lifestyle and does harm to adolescents' health. Thus, it is necessary to focus on the exposure factor in environmental health risk assessment (EHRA) which conducts supervision of environmental pollution and survey of adolescents' activity patterns according to the harmful characteristics of air pollutant and relationship between dose and response. Some countries, such as USA, Canada and Australia, regard both respiratory rate and physical activity pattern as main exposure factors for adolescents in both air pollution health risk assessment and exercise risk assessment to forecast a safe exposing condition of pollutant for adolescents while they are doing exercise outdoors. In addition, it suggests that the testing indexes and testing methods of these two exposure factors, such as investigating the time of daily physical activity, strength, and characteristic of frequency, help to set up the quantitative relationship between environmental pollution index and the time, strength, frequency of daily activities, and formulate children's and adolescents' activity instructions under different levels of environmental pollutions. As smog becomes increasingly serious at present, it is meaningful to take physical activity as a critical composition of exposure factor and establish physical activity guideline, so as to reduce the risk of air pollution, and promote physical health of children and adolescents effectively.Entities:
Keywords: air pollution; children and adolescents; environmental health risk assessment; exposure factor; physical activity
Mesh:
Substances:
Year: 2018 PMID: 29360730 PMCID: PMC5857044 DOI: 10.3390/ijerph15020176
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Summaries of the surveys of physical activity pattern.
| Name | Organizer | Date | Location | Sample | Age | Duration (Month) | Method |
|---|---|---|---|---|---|---|---|
| CAPS | CARB | 1987–1988 | California | 1762 | >12 | 12 | 24-h retrospective diaries |
| 1989–1990 | California | 1200 | <12 | 12 | 24-h retrospective diaries | ||
| NHAPS | EPA | 1992–1994 | 48 states of the U.S. | 9386 | The total population | 24 | 24-h retrospective diaries |
| EPA | 2004–2008 | 48 states of the U.S. | 23,028 | The total population | 24 | GPS | |
| EPRI | 1994–1995 | The U.S. | 1200 | The total population | 12 | 24-h retrospective diaries | |
| CHAPS | EPA | 1994–1995 | Canada | 2381 | Thetotal population | 9 | 24-h retrospective diaries |
CARB: California Air Resources Board; EPA: United States Environmental Protection Agency; EPRI: Electric Power Research Institute (Duan et al., 2008) [36].
Inhalation rate of children and adolescents in Shanghai in different physical activities.
| Age (Year) | Gender | Rest (R) X ± S | Sedentary Behavior (SB) X ± S | Light Physical Activity (LPA) X ± S | Moderate Physical Activity (MPA) X ± S | Vigorous Physical Activity (VPA) X ± S |
|---|---|---|---|---|---|---|
| 6 | Male | 0.22 ± 0.03 | 0.27 ± 0.01 | 0.33 ± 0.01 | 0.89 ± 0.05 | 1.33 ± 0.12 |
| Female | 0.24 ± 0.03 | 0.29 ± 0.03 | 0.36 ± 0.01 | 0.95 ± 0.08 | 1.43 ± 0.15 | |
| 7 | Male | 0.23 ± 0.04 | 0.28 ± 0.03 | 0.35 ± 0.05 | 0.94 ± 0.07 | 1.4 ± 0.13 |
| Female | 0.25 ± 0.02 | 0.30 ± 0.01 | 0.37 ± 0.03 | 1.00 ± 0.08 | 1.49 ± 0.17 | |
| 8 | Male | 0.25 ± 0.02 | 0.30 ± 0.03 | 0.38 ± 0.03 | 1.01 ± 0.05 | 1.51 ± 0.12 |
| Female | 0.26 ± 0.01 | 0.310 | 0.39 ± 0.01 | 1.03 ± 0.11 | 1.55 ± 0.17 | |
| 9 | Male | 0.267 ± 0.01 | 0.321 | 0.40 ± 0.04 | 1.07 ± 0.11 | 1.60 ± 0.12 |
| Female | 0.270 ± 0.05 | 0.324 | 0.41 ± 0.02 | 1.08 ± 0.12 | 1.62 ± 0.21 | |
| 10 | Male | 0.283 ± 0.03 | 0.340 | 0.42 ± 0.03 | 1.13 ± 0.07 | 1.70 ± 0.14 |
| Female | 0.284 ± 0.04 | 0.341 | 0.42 ± 0.03 | 1.14 ± 0.19 | 1.71 ± 0.16 | |
| 11 | Male | 0.31 ± 0.02 | 0.371 | 0.46 ± 0.04 | 1.24 ± 0.08 | 1.85 ± 0.13 |
| Female | 0.30 ± 0.03 | 0.361 | 0.45 ± 0.02 | 1.21 ± 0.12 | 1.80 ± 0.17 | |
| 12 | Male | 0.34 ± 0.05 | 0.404 | 0.51 ± 0.05 | 1.35 ± 0.15 | 2.02 ± 0.15 |
| Female | 0.31 ± 0.11 | 0.374 | 0.47 ± 0.02 | 1.25 ± 0.13 | 1.87 ± 0.18 | |
| 13 | Male | 0.36 ± 0.04 | 0.429 | 0.54 ± 0.03 | 1.43 ± 0.17 | 2.14 ± 0.20 |
| Female | 0.32 ± 0.02 | 0.384 | 0.48 ± 0.04 | 1.28 ± 0.16 | 1.92 ± 0.15 | |
| 14 | Male | 0.37 ± 0.05 | 0.445 | 0.57 ± 0.04 | 1.48 ± 0.17 | 2.22 ± 0.12 |
| Female | 0.31 ± 0.04 | 0.390 | 0.49 ± 0.07 | 1.30 ± 0.15 | 1.95 ± 0.19 | |
| 15 | Male | 0.38 ± 0.02 | 0.460 | 0.58 ± 0.05 | 1.54 ± 0.12 | 2.30 ± 0.16 |
| Female | 0.33 ± 0.05 | 0.392 | 0.49 ± 0.04 | 1.31 ± 0.15 | 1.96 ± 0.18 | |
| 16 | Male | 0.38 ± 0.07 | 0.461 | 0.58 ± 0.08 | 1.54 ± 0.19 | 2.31 ± 0.22 |
| Female | 0.33 ± 0.01 | 0.392 | 0.49 ± 0.06 | 1.31 ± 0.12 | 1.96 ± 0.20 | |
| 17 | Male | 0.39 ± 0.03 | 0.466 | 0.58 ± 0.05 | 1.55 ± 0.19 | 2.33 ± 0.18 |
| Female | 0.33 ± 0.08 | 0.394 | 0.49 ± 0.08 | 1.31 ± 0.14 | 1.97 ± 0.16 | |
| 18 | Male | 0.41 ± 0.02 | 0.486 | 0.61 ± 0.07 | 1.62 ± 0.18 | 2.43 ± 0.22 |
| Female | 0.31 ± 0.01 | 0.368 | 0.46 ± 0.05 | 1.23 ± 0.13 | 1.84 ± 0.14 | |
| 19 | Male | 0.40 ± 0.03 | 0.480 | 0.60 ± 0.07 | 1.60 ± 0.11 | 2.40 ± 0.25 |
| Female | 0.30 ± 0.06 | 0.362 | 0.45 ± 0.06 | 1.21 ± 0.12 | 1.81 ± 0.23 | |
| 20 | Male | 0.39 ± 0.05 | 0.467 | 0.58 ± 0.07 | 1.56 ± 0.17 | 2.34 ± 0.27 |
| Female | 0.30 ± 0.01 | 0.363 | 0.45 ± 0.05 | 1.21 ± 0.12 | 1.81 ± 0.16 |
Figure 1Change characteristics of inhalation rate of children and adolescents of different ages and genders in Shanghai in different physical activities.
Figure 2Comparison of the inhalation rate of children and adolescents in Shanghai in different physical activities (male).
Figure 3Comparison of the inhalation rate of children and adolescents in Shanghai in different physical activities (female).
Long-term inhalation rates of Chinese children and adolescents.
| Age (Year) | Male | Female | ||
|---|---|---|---|---|
| Sample | Inhalation Rate (m3/d) | Sample | Inhalation Rate (m3/d) | |
| 1–2 | 35 | 4.7 ± 0.15 | 34 | 5.4 ± 0.16 |
| 3–5 | 168 | 5.9 ± 0.26 | 124 | 6.4 ± 0.42 |
| 6–8 | 161 | 9.1 ± 0.42 | 155 | 8.1 ± 0.67 |
| 9–11 | 193 | 10.6 ± 0.88 | 171 | 9.5 ± 0.91 |
| 12–14 | 206 | 12.2 ± 0.69 | 239 | 10.6 ± 1.02 |
| 15–18 | 239 | 13.5 ± 1.23 | 162 | 10.8 ± 0.88 |
Short-term inhalation rates (m3/h) at different activity levels of Chinese children and adolescents.
| Age (Year) | Gender | Rest | Sedentary | Light Intensity | Moderate Intensity | High Intensity | Extremely High Intensity |
|---|---|---|---|---|---|---|---|
| <6 | Male | 0.14 ± 0.02 | 0.17 ± 0.04 | 0.29 ± 0.04 | 0.57 ± 0.03 | 0.86 ± 0.07 | 1.43 ± 0.1 |
| Female | 0.14 ± 0.05 | 0.17 ± 0.08 | 0.28 ± 0.05 | 0.56 ± 0.06 | 0.84 ± 0.05 | 1.40 ± 0.12 | |
| 6–18 | Male | 0.29 ± 0.05 | 0.35 ± 0.29 | 0.59 ± 0.07 | 1.18 ± 0.1 | 1.77 ± 0.13 | 2.94 ± 0.23 |
| Female | 0.28 ± 0.04 | 0.34 ± 0.04 | 0.57 ± 0.03 | 1.14 ± 0.09 | 1.70 ± 0.12 | 2.84 ± 0.36 |
Figure 4Short-term inhalation rates at different activity levels of Chinese children and adolescents.
Figure 5Comparison of long-term inhalation rates of children between the U.S. and China.