# Research of Interindividual Differences in Physiological Response under Hot-Dry and Warm-Wet Climates

^{*}

## Abstract

**:**

_{2max}/mass) were adopt to establish a revised body characteristic index (RBCI). RBCI was proved having significant correlation with physiological parameters, which means RBCI as the combined factors of somatotype and habitus parameters can be applied to evaluate the effect of individual characteristics on physiological systems.

## 1. Introduction

_{2max}/mass to evaluate the relative effect of individual characteristics on heat strain. In order to improve the BCI, this paper increases the number of subjects from 20 to 60 and replaced oral temperature with rectal temperature that is closer to human’s core temperature to establish a revised body characteristic index (RBCI). Moreover, there are also some improvements in experiment and analysis processes, such as classifying the subjects into four groups, analyzing the differences of physiological parameters among groups and presenting the change trends of physiological parameters in climate chamber. The entire research process of this paper is more reasonable, comprehensive, and reliable than the previous article [34].

## 2. Materials and Methods

#### 2.1. Chamber

#### 2.2. Subjects

#### 2.3. Experimental Condition

#### 2.4. Experimental Parameters and Instruments

_{2max}) and skinfold thickness. Table 3 shows these parameters and their corresponding instruments.

_{b}is the naked body mass in kg; H

_{b}is body height in m.

_{b}is body density in kg/m

^{3}; c is a regression coefficient, taking 1.1631 for males aged from 20 to 29 years old, 1.1599 for females aged 20 to 29 years old; m is a regression coefficient, taking 0.0632 for males aged from 20 to 29 years old, 0.0717 for females aged 20 to 29 years old; T

_{s}is skinfold thickness in mm.

_{2max}was measured with a incremental load treadmill in comfortable climate. The initial speed of the treadmill was set to 5 km/h and increased by 1 km/h every 5 min. The tested subjects wore a respiratory mask that was used to continually collect expiratory gas in the process of exercise. Expiratory gas was sent to a Powerlab gas analyzer. With the increase of walking speed, heart rate and oxygen consumption increased gradually. When the treadmill load increased to a certain extent, the subjects might appear the following conditions: (a) oxygen consumption reached the highest level for several seconds and then declined; (b) the breath quotient exceeded 1.1; (c) heart rate reached 180 beats/min; and (d) inhaled oxygen was under 150 mL/min. When the tested subjects meet three of the four conditions, the oxygen consumption is defined as VO

_{2max}.

#### 2.5. Experimental Process

#### 2.5.1. Subject Classification Stage

_{2max}/mass. Data analyses were performed in the statistical package and social sciences software (SPSS) which provides tools that allow users to quickly view data, formulate hypotheses for additional testing, and carry out procedures to clarify relationships between variables, create clusters, identify trends, and make predictions [42,43]. Subjects were classified by the method of principal component cluster analysis [44,45]. The reliability and validity of data should be analyzed before applying the method. Table 4 shows the KMO and Bartlett test [46]. The statistics of Bartlett’s Sphericity Test is 19.559. Its probability sig. is 0.000 (p < 0.05) and the value of KMO is 0.694 (KMO > 0.5), which indicates that the data are suitable for factor analysis. Then, the main component analysis was conducted. As shown in Table 5, the cumulative contribution rate of the first two main components is 84.304%, which indicates that most information about the BSA/mass, %fat, and VO

_{2max}/mass can be expressed by the first two common factors and the common factor analysis results are satisfactory.

_{2max}/mass. The contribution rate of the two factors are opposite, which indicates that the differences between somatotype and habitus parameters are significant. If the value is positive, the subject will be strong and thin. The second component is BSA/mass and its value is positive. If the value of the second component is positive, the subject will be thin, tall and weak. Through the calculation of the two components, subjects were divided into four groups: (A) thin and strong (16 subjects); (B) thin and weak (12 subjects); (C) fat and strong (14 subjects); (D) fat and weak (18 subjects). The basic body parameters of each group are shown in Table 7.

#### 2.5.2. Testing Stage

#### 2.6. Statistical Analysis

## 3. Results

#### 3.1. Analysis of Physiological Parameter Differences

- (a)
- Rectal temperature

- (b)
- Heart Rate

#### 3.2. Correlation Analysis

_{re}and ΔHR that were calculated by the Equations (4) and (5). To eliminate the influence of work intensities on physiological parameter, ΔT

_{re}

_{(M+H)}and HR

_{(M+H)}were calculated by Equations (6) and (7) for correlation analysis.

_{re}

_{60}is the rectal temperature at 60 min; T

_{re}

_{0}is the rectal temperature at 0 min.

_{60}is the heart rate at 60 min; HR

_{0}is the heart rate at 0 min.

_{reM}is the change value of rectal temperature at moderate work intensity; ΔT

_{reH}is the change value of rectal temperature at heavy work intensity.

_{M}is the change value of heart rate at moderate work intensity; ΔHR

_{H}is the change value of rectal temperature at heavy work intensity.

_{re(M+H}

_{)}and BSA/mass, and negative correlation between ΔT

_{re(M+H)}and %fat are presented; ΔHR

_{(M+H)}presents negative correlation with BSA, while it presents significant positive correlations with BSA/mass and %fat. For hot-dry climate, significant positive correlation between ΔT

_{re(M+H)}and BSA/mass is presented; ΔHR

_{(M+H)}does not present significant correlation with somatotype parameters except %fat. For warm-wet climate, ΔT

_{re(M+H)}presents significant positive correlation with BSA/mass; ΔHR

_{(M+H)}presents significant positive correlations with BSA/mass and %fat. It can be seen that ΔT

_{re(M+H)}and ΔHR

_{(M+H)}have significant correlations with BSA, BSA/mass, and %fat, and the effect of BSA/mass and %fat are more significant.

_{2max}and VO

_{2max}/mass are used to represent the habitus conditions of subjects. Table 9 shows Pearson correlation coefficients between habitus parameters and physiological parameters. Significant negative correlation between ΔT

_{re(M+H)}and VO

_{2max}/mass are presented in all conditions. ΔHR

_{(M+H)}shows significant positive correlation with VO

_{2max}/mass in comfortable and hot-dry climates. ΔT

_{re(M+H)}and ΔHR

_{(M+H)}do not have significant correlation with VO

_{2max}in all conditions. In conclusion, ΔT

_{re(M+H)}and ΔHR

_{(M+H)}have significant correlation with VO

_{2max}/mass, while no significant correlation is seen with VO

_{2max}.

_{2max}, and VO

_{2max}/mass, which helps to understand the inner relationship among individual parameters. BSA presents significant correlation with BSA/mass and VO

_{2max}. BSA/mass has significant correlation with BSA and VO

_{2max}. %fat does not show significant correlation with other parameters except VO

_{2max}/mass. VO

_{2max}presents significant correlation with other parameters except %fat.

_{2max}/mass have significant correlations with ΔT

_{re(M+H)}and ΔHR

_{(M+H)}based on the correlation analyses above. However, BSA only has significant correlation with ΔHR

_{(M+H)}in comfortable climate. Moreover, it has significant correlation with BSA/mass and VO

_{2max}, which means its effect can be represented by other individual parameters. Thus, BSA/mass, %fat, and VO

_{2max}/mass are seen as three independent variables that influence physiological parameters.

#### 3.3. The Establishment of RBCI Equation

_{2max}/mass, BSA/mass, and %fat are chosen as the variable factors for RBCI after correlations analysis above. ΔT

_{re(M+H)}and ΔHR

_{(M+H)}are considered as dependent variables. Climate, VO

_{2max}/mass, BSA/mass, and %fat are considered as independent variables. Table 11 shows the results of multiple regression analysis in SPSS. The fitting degrees of all independent variables to ΔT

_{re(M+H)}and ΔHR

_{(M+H)}are above 80%, which means the fitting effect is ideal.

_{2max}/mass, BSA/mass, and %fat in Table 11 can be converted into standardized regression coefficients in Table 12. Weight coefficients of VO

_{2max}/mass, BSA/mass, and %fat can be calculated based on standardized regression coefficients. Assuming that the total contribution of VO

_{2max}/mass, BSA/mass, and %fat is 10, the weight coefficients of VO

_{2max}/mass, BSA/mass, and %fat in RBCI are given in Table 12.

_{2max}/mass, BSA/mass, and %fat are 4.4, 3.0, and 2.6 m, respectively, in the ΔT

_{re(M+H)}model and 1.4, 2.9, and 5.7, respectively, in the ΔHR

_{(M+H)}model. Thus, the RBCI equations [47] are shown as follows:

_{re(M+H)}model

_{(M+H)}model

## 4. Discussion

#### 4.1. Physiological Parameters

- (a)
- Rectal temperature

- (b)
- Heart rate

#### 4.2. RBCI

_{2max}/mass were extracted to compose RBCI equation through analyzing the correlations between individual characteristic and physiological parameters in comfortable, hot-dry, and warm-wet climates. To verify whether RBCI has significant influence on ΔT

_{re(M+H)}and ΔHR

_{(M+H)}, it is also necessary to make correlation analysis. As shown in Table 14, ΔT

_{re(M+H)}and ΔHR

_{(M+H)}have significant correlation with RBCI and the correlation coefficients in hot-dry and warm-wet climates are larger than the values in comfortable climate. Figure 6 and Figure 7 show the unary linear regression modules of RBCI and physiological response in comfortable, hot-dry and warm-wet climates. It can be seen that the fitting degrees of RBCI (T

_{re}) to ΔT

_{re(M+H)}and RBCI (HR)to ΔHR

_{(M+H)}are above 50% except the condition of RBCI (T

_{re}) to ΔT

_{re(M+H)}in comfortable climate. Therefore, the RBCI can be applied to evaluate the effect of somatotype and habitus parameters on rectal temperature and heart rate.

## 5. Conclusions

_{2max}/mass were extracted to compose the RBCI equation. The correlation coefficient between the BCI and physiological parameter variations in hot-dry and warm-wet climates are larger than the values in comfortable climate, which indicates that the evaluation ability of RBCI increases with the increase of environmental intensity. Therefore, the RBCI can be used to predict the effect of somatotype and habitus parameters on physiological parameter variations during heat exposure experiment.

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## Abbreviations

RBCI | A revised body characteristic index |

CFM | Comfortable climate and moderate work intensity |

CFH | Comfortable climate and heavy work intensity |

HDM | Hot-dry climate and moderate work intensity |

HDH | Hot-dry climate and heavy work intensity |

WWM | Warm-wet climate and moderate work intensity |

WWH | Warm-wet climate and heavy work intensity |

BSA | Body surface area |

BSA/mass | Body surface area per unit of body mass |

VO_{2max} | Maximum oxygen consumption |

VO_{2max}/mass | Maximum oxygen consumption per unit of body mass |

%fat | Percentage of body fat |

SPSS | Statistical package and social sciences software |

ΔT_{re} | The change value of rectal temperature |

ΔHR | The change value of heart rate |

ΔT_{re(M+H)} | The sum of ΔT_{re} in moderate and heavy intensity work |

ΔHR_{(M+H)} | The sum of ΔHR in moderate and heavy intensity work |

RBCI (T_{re)} | The RBCI in ΔT_{re(M+H)} model |

RBCI (HR) | The RBCI in ΔHR_{(M+H)} model |

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**Figure 2.**The rectal temperature of groups A, B, C, and D. (

**a**) CFM condition; (

_{1}**a**) CFH condition; (

_{2}**b**) HDM condition; (

_{1}**b**) HDH condition (

_{2}**c**) WWM condition (

_{1}**c**) WWH condition.

_{2}**Figure 3.**The error bars of rectal temperatures in different conditions. (

**a**) Comfortable climate; (

**b**) Hot-dry climate; (

**c**) Warm-wet climate.

**Figure 4.**The heart rate of groups A, B, C, and D. (

**a**) CFM condition; (

_{1}**a**) CFH condition; (

_{2}**b**) HDM condition; (

_{1}**b**) HDH condition (

_{2}**c**) WWM condition (

_{1}**c**) WWH condition.

_{2}**Figure 5.**The error bar of heart rate in different conditions. (

**a**) Comfortable climate; (

**b**) Hot-dry climate; (

**c**) Warm-wet climate.

Parameter | Range |
---|---|

Temperature | −20 °C–85 °C |

Relative humidity | 20%–98% |

Temperature fluctuation | ≤±0.3 °C |

Relative humidity fluctuation | ≤±3.0% |

Parameter | Comfortable Climate | Hot-Dry Climate | Warm-Wet Climate |
---|---|---|---|

Temperature (°C) | 26 | 40 | 32 |

Relative humidity (%) | 50% | 30% | 80% |

WBGT (°C) | 21.32 ± 0.20 | 30.30 ± 0.20 | 30.06 ± 0.20 |

Air velocity (m/s) | 0.5 ± 0.1 | 0.5 ± 0.1 | 0.5 ± 0.1 |

Parameter | Instrument | Model | Range | Accuracy |
---|---|---|---|---|

Height | Tape | Seca206 | 0–220 cm | ±1 mm |

Body mass | Electronic scales | TCS150 | 0–150 kg | ±10 g |

skinfold thickness | Caliper | Fc-02 | 0–70 mm | ±0.02 mm |

VO_{2max} | Physiological recorder | Powerlab16 | - | - |

Heart rate | ||||

Rectal temperature | Thermotron | MC-347 | 32–42 °C | ±0.1 °C |

Kaiser-Meyer-Olkin Measure | 0.694 |

Bartlett’s Test of Sphericity. Approx. Chi-Square | 19.559 |

df | 3 |

Sig. | 0.000 |

Component | Initial Eigenvalue | Extraction Sum of Squared Loading | ||||
---|---|---|---|---|---|---|

Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | |

1 | 1.566 | 52.195 | 52.195 | 1.566 | 52.195 | 52.195 |

2 | 0.963 | 32.109 | 84.304 | 0.963 | 32.109 | 84.304 |

3 | 0.471 | 15.696 | 100.000 |

Title | Component | |
---|---|---|

1 | 2 | |

BSA/mass | 0.365 | 0.924 |

%fat | −0.867 | 0.082 |

VO_{2max}/mass | 0.825 | −0.322 |

Group | Number | Parameter | Maximum | Minimum | Average |
---|---|---|---|---|---|

A | 16 | Mass (kg) | 68.07 | 41.44 | 56.15 |

BSA (m^{2}) | 1.781 | 1.366 | 1.634 | ||

BSA/mass (m^{2}/kg) | 0.033 | 0.026 | 0.029 | ||

%fat (%) | 20.6 | 10.2 | 13.5 | ||

VO_{2max} (L/min) | 5.20 | 2.94 | 4.33 | ||

VO_{2max}/mass (mL/(min·kg)) | 84.28 | 69.12 | 76.73 | ||

B | 12 | Mass (kg) | 68.80 | 44.01 | 54.44 |

BSA (m^{2}) | 1.850 | 1.367 | 1.588 | ||

BSA/mass (m^{2}/kg) | 0.031 | 0.027 | 0.0294 | ||

%fat (%) | 27.7 | 10.8 | 18.4 | ||

VO_{2max} (L/min) | 4.61 | 2.73 | 3.36 | ||

VO_{2max}/mass (mL/(min·kg)) | 67.49 | 55.53 | 61.72 | ||

C | 14 | Mass (kg) | 78.30 | 49.40 | 64.32 |

BSA (m^{2}) | 1.954 | 1.455 | 1.711 | ||

BSA/mass (m^{2}/kg) | 0.029 | 0.024 | 0.027 | ||

%fat (%) | 29.6 | 12.6 | 21.0 | ||

VO_{2max} (L/min) | 6.13 | 3.33 | 4.58 | ||

VO_{2max}/mass (mL/(min·kg)) | 85.54 | 56.84 | 70.90 | ||

D | 18 | Mass (kg) | 92.24 | 50.40 | 63.62 |

BSA (m^{2}) | 2.065 | 1.501 | 1.718 | ||

BSA/mass (m^{2}/kg) | 0.030 | 0.022 | 0.027 | ||

%fat (%) | 37.5 | 18.7 | 25.6 | ||

VO_{2max} (L/min) | 5.13 | 2.93 | 3.72 | ||

VO_{2max}/mass (mL/(min·kg)) | 65.86 | 50.44 | 58.35 |

Climate Condition | Physiological Response | BSA | BSA/Mass | %Fat |
---|---|---|---|---|

Comfortable | ΔT_{re(M+H)} | 0.137 | 0.478 * | −0.470 * |

ΔHR_{(M+H)} | −0.413 ** | 0.464 * | 0.628 ** | |

Hot-dry | ΔT_{re(M+H)} | −0.091 | 0.635 ** | −0.279 |

ΔHR_{(M+H)} | −0.039 | 0.308 | 0.501 ** | |

Warm-wet | ΔT_{re(M+H)} | −0.237 | 0.626 ** | −0.114 |

ΔHR_{(M+H)} | −0.260 | 0.432 * | 0.723 ** |

Climate Condition | Physiological Response | VO_{2max} | VO_{2max}/Mass |
---|---|---|---|

Comfortable | ΔT_{re(M+H)} | 0.136 | −0.556 ** |

ΔHR_{(M+H)} | −0.152 | 0.349 * | |

Hot-dry | ΔT_{re(M+H)} | −0.221 | −0.602 ** |

ΔHR_{(M+H)} | −0.051 | 0.402 * | |

Warm-wet | ΔT_{re(M+H)} | −0.238 | −0.495 * |

ΔHR_{(M+H)} | −0.253 | 0.191 |

Individual Parameters | BSA/Mass | %Fat | VO_{2max} | VO_{2max}/Mass |
---|---|---|---|---|

BSA | −0.863 ** | −0.004 | 0.760 ** | 0.051 |

BSA/mass | - | −0.181 | −0.678 ** | 0.060 |

%fat | - | - | −0.252 | −0.523 ** |

VO_{2max} | - | - | - | 0.657 ** |

Title | Constant | Climate | VO_{2max}/Mass | BSA/Mass | %Fat | R^{2}_{adj.} |
---|---|---|---|---|---|---|

ΔT_{re(M+H)} | 0.614 | 0.521 | −0.010 | 19.760 | −0.395 | 0.807 |

ΔHR_{(M+H)} | −112.589 | 16.596 | 0.305 | 3159.040 | 184.560 | 0.841 |

Individual Parameter | Standardized Regression Coefficient | Weight Coefficient |
---|---|---|

ΔT_{re(M+H)} | ||

VO_{2max}/mass | −0.225 | 4.4 |

BSA/mass | 0.149 | 3.0 |

%fat | −0.132 | 2.6 |

ΔHR_{(M+H)} | ||

VO_{2max}/mass | 0.112 | 1.4 |

BSA/mass | 0.228 | 2.9 |

%fat | 0.443 | 5.7 |

Experiment Condition | Category | Mean Difference | Sig. | Mean Difference | Sig. | |
---|---|---|---|---|---|---|

1 | 2 | Rectal Temperature | Heart Rate | |||

CFM | A | B | 0.11 * | 0.046 | 1.86 | 0.226 |

C | −0.21 * | 0.001 | 4.42 * | 0.007 | ||

D | −0.20 * | 0 | 3.43 * | 0.031 | ||

B | C | −0.32 * | 0 | 2.57 | 0.098 | |

D | −0.31 * | 0 | 1.57 | 0.303 | ||

C | D | 0.09 | 0.877 | −1 | 0.51 | |

CFH | A | B | 0.07 | 0.485 | −15.10 * | 0.048 |

C | −0.16 | 0.113 | −10 | 0.131 | ||

D | −0.1 | 0.321 | −11.43 | 0.128 | ||

B | C | −0.23 * | 0.027 | 5.14 | 0.435 | |

D | −0.17 | 0.098 | 3.71 | 0.614 | ||

C | D | 0.06 | 0.534 | −1.43 | 0.846 | |

HDM | A | B | 0.01 | 0.934 | −0.89 | 0.877 |

C | −0.21 | 0.163 | 4 | 0.491 | ||

D | −0.13 | 0.383 | 2.63 | 0.65 | ||

B | C | −0.22 | 0.165 | 4.89 | 0.4 | |

D | −0.14 | 0.369 | 3.52 | 0.544 | ||

C | D | 0.08 | 0.599 | −1.38 | 0.812 | |

HDH | A | B | −0.09 | 0.666 | −4.25 | 0.665 |

C | −0.15 | 0.494 | −3.13 | 0.75 | ||

D | −0.2 | 0.386 | −1.75 | 0.869 | ||

B | C | −0.05 | 0.8 | 1.13 | 0.909 | |

D | −0.11 | 0.637 | 2.5 | 0.813 | ||

C | D | −0.05 | 0.812 | 1.38 | 0.897 | |

WWM | A | B | 0.11 | 0.166 | −1.69 | 0.609 |

C | −0.07 | 0.413 | 8.11 * | 0.02 | ||

D | 0.06 | 0.476 | 4.87 | 0.162 | ||

B | C | 0.18 * | 0.034 | 9.80 * | 0.005 | |

D | −0.05 | 0.523 | 6.57 | 0.062 | ||

C | D | 0.13 | 0.141 | −3.23 | 0.36 | |

WWH | A | B | 0.06 | 0.652 | −1.92 | 0.79 |

C | −0.08 | 0.516 | −2 | 0.775 | ||

D | 0.01 | 0.963 | −4.58 | 0.539 | ||

B | C | −0.14 | 0.301 | −0.08 | 0.991 | |

D | −0.05 | 0.707 | −2.65 | 0.728 | ||

C | D | 0.08 | 0.519 | −2.58 | 0.729 |

Climate Condition | Physiological Response | RBCI |
---|---|---|

Comfortable | ΔT_{re(M+H)} | 0.678 ** |

ΔHR_{(M+H)} | 0.719 ** | |

Hot-dry | ΔT_{re(M+H)} | 0.771 ** |

ΔHR_{(M+H)} | 0.767 ** | |

Warm-wet | ΔT_{re(M+H)} | 0.714 ** |

ΔHR_{(M+H)} | 0.781 ** |

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Lu, S.; Sun, L.; Peng, H.; Ji, L.
Research of Interindividual Differences in Physiological Response under Hot-Dry and Warm-Wet Climates. *Sustainability* **2016**, *8*, 850.
https://doi.org/10.3390/su8090850

**AMA Style**

Lu S, Sun L, Peng H, Ji L.
Research of Interindividual Differences in Physiological Response under Hot-Dry and Warm-Wet Climates. *Sustainability*. 2016; 8(9):850.
https://doi.org/10.3390/su8090850

**Chicago/Turabian Style**

Lu, Shilei, Linwei Sun, Huaiyu Peng, and Liran Ji.
2016. "Research of Interindividual Differences in Physiological Response under Hot-Dry and Warm-Wet Climates" *Sustainability* 8, no. 9: 850.
https://doi.org/10.3390/su8090850