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Research on body morphology development and related factors of 2-5 year old children in some northern regions - 20

APPENDIX 4

NUTRITION PYRAMID FOR VIETNAMESE CHILDREN IN THE PERIOD 2016 - 2020

APPENDIX 5

LINEAR REGRESSION ANALYSIS BETWEEN ANTHROPOLOGETIC DIMENSIONS


Appendix 5.1. Linear regression analysis with chest circumference as the dependent variable, age and weight as independent variables.

- Model summary


Model

R

R 2

Adjusted R 2

Std. Error of the

Estimate

1

0.677

0.458

0.458

2,3167

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Adjusted R 2 correlation coefficient = 0.458, thus age and weight affected 45.8% of the change in chest circumference of children in the study.

- ANOVA analysis


Model


Sum of

Squares

df

Mean Square

F

Sig.


Regression

9475,801

2

4737,901

882,787

0.000

Residual

11200,882

2087

5,367



Total

20676,684

2089




F value = 882.787, with p < 0.05, the linear model built fits the population.

- Regression coefficient with bust circumference as dependent variable



Regression coefficient


t


p

95%CI

β

Std. Error

Lower

Bound

Upper

Bound

Constant

40,930

0.252

162,630

0.000

40,437

41,424

Year old

-0.167

0.063

-2,623

0.009

-0.291

-0.042

Weight

0.726

0.022

33,533

0.000

0.683

0.768

- Normalized residual frequency histogram Histogram


Standardized residual plot with chest circumference as the dependent variable

The standardized residual plot with chest circumference as the dependent variable shows the curve


has a bell-shaped shape that fits the graph of a normal distribution, with X = 0, SD = 1 so the assumption of a normal distribution of the residuals is not violated.

- Scatter Plot chart checks the assumption of linear relationship


Scatter Plot with chest circumference as dependent variable

Scatter Plot with chest circumference as dependent variable shows that standardized residuals are concentrated around the zero-intercept line, thus the linearity hypothesis is not violated.

The assumptions of linear regression analysis are satisfied. Therefore, age and weight are linearly related to chest circumference according to the linear regression equation:

Chest circumference = 40.93 - 0.167*Age + 0.726*Weight

Appendix 5.2. Linear regression analysis with VCTTD as dependent variable, age and weight as independent variables.

- Model summary


Model

R

R 2

Adjusted R 2

Std. Error of the

Estimate

1

0.598

0.358

0.357

1.0212

Adjusted R 2 correlation coefficient = 0.357, thus age and weight affected 35.7% of the change in VCTTD of children in the study.

- ANOVA analysis


Model


Sum of

Squares

df

Mean

Square

F

p


Regression

1213,626

2

606,813

581,893

0.000

Residual

2176,377

2087

1,043



Total

3390,003

2089




F value = 581.893, with p < 0.05, the linear model built fits the population.

- Regression coefficient with VCTTD as dependent variable



Regression coefficient


t


p

95%CI

β

Std. Error

Lower

Bound

Upper

Bound

Constant

11,468

0.111

103,369

0.000

11,250

11,685

Year old

-0.108

0.028

-3,861

0.000

-0.163

-0.053

Weight

0.269

0.010

28,236

0.000

0.251

0.288

- Normalized residual frequency histogram Histogram


Standardized residual plot with VCTTD as dependent variable

The standardized residual plot with VCTTD as the dependent variable shows that the curve has


The bell-shaped shape fits the graph of the normal distribution, with X = 0, SD = 1 so the assumption of the residuals having the form of a normal distribution is not violated.

- Scatter Plot chart checks the assumption of linear relationship


Scatter Plot with VCTTD as dependent variable

The Scatter Plot with VCTTD as the dependent variable shows that the standardized residuals are concentrated around the zero-intercept line, so the linearity hypothesis is not violated.

The assumptions of linear regression analysis are all satisfied. Therefore, age and weight are linearly related to VCTTD according to the linear regression equation:

VCTTD = 11.468 - 0.108*Age + 0.269*Weight

APPENDIX 6

TABLE OF QUANTIFYING QUALITATIVE VARIABLES INTO ORDINARY VARIABLES


Qualitative variables

Variable

on one's own


C1


Parents' occupation

Farmer

1

State employees

2

Business and other industries

3


C2


Parents' education level?

Unlettered

1

Elementary

2

Junior High School

3

High school or higher

4


C3


Total number of children in the family?

1-2 children

1

3 children

2

Over 3 children

3

C4

Total number of people in household?

3-5 people

1

5 people or more

2


C6


How long after birth can a baby be weaned?

Under 6 months

1

6-11 months

2

12 months and up

3


C14

Does the family regularly monitor the child's weight and height?

Do not follow

1

Rarely, occasionally

2

Frequent

3

C30

Do children often eat processed foods?

Are not

1

Have

2

C31

Do children often eat sweets?

Are not

1

Have

2

C34

Do children watch TV?

Are not

1

Have

2



C38


What water source does your family use for drinking?

River water, stream water, rain water, well water

open

1

Well

2

Tap water

3


C39


Type of toilet the family is using

Do not have

1

Pit latrine

2

2 compartment toilet, septic tank

3


C40


When do you think children should wash their hands?

No wash, no need to wash

1

Before eating or after going to the toilet

2

Before eating and after going to the toilet

3

C42

How often should children be dewormed?

1 year or more

1

Under 1 year

2


C44


Number of times brushing teeth per day

Don't brush your teeth

1

1 time

2

2 times or more

3


C46


Time to brush teeth?

Under 2 minutes

1

2-3 minutes

2

Over 3 minutes

3

C52

According to the family, is tooth decay harmful to children?

No or don't know

1

Have

2

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