Factors affecting perception of child weight
Cite this dataset
Woods, Tanna (2021). Factors affecting perception of child weight [Dataset]. Dryad. https://doi.org/10.5061/dryad.8pk0p2nnc
Abstract
Background
Parental misperception and underestimation of their child’s weight are documented in studies. Demographic factors like age and gender have been linked to misclassification. However, modifiable factors that could potentially frame future intervention and prevention strategies have not been explored. This study aimed to assess factors that could predict parental misclassification of their preschool child’s weight.
Methods
This was a cross-sectional study with 198 parents and their 2- to 5-year-old children who attended standalone preschools or childcare centers with preschools. Parents completed a questionnaire that asked about demographic features, personal and family health, and the assessment of their child’s weight using the three most frequently utilized measures. Logistic regression was conducted to assess the association between parental factors and child weight classification status. Instruments included the Parental Self-Efficacy for Promoting Healthy Physical Activity and Dietary Behaviors in Children Scale (PSEPAD), the Obesity Risk Scale (ORK-10), and the Adolescent Obesity Risk Scale (AORK). Analyses included frequencies, chi-square tests, Kappa coefficients, and logistic regressions.
Results
Parents were least accurate (35.9%) identifying child weight when selecting a picture (κ =-.028, p = .42). The pictorial and Likert method (κ = -.032, p = .37) showed parental agreement with child weight was not significantly better than chance. Statistically, a significant agreement was found in the weight-reporting method (κ = .21). Two of the three HBM-related measures were significantly related to accurate classification. Logistic regression showed child sex, PSEPAD scores, and ORK-10 scores were statistically significant predictors in the Likert method. The model had no statistical significance for the pictorial or weight-reporting method.
Conclusion
Results indicate parents support intervening if aware of child weight problems. However, parents do not accurately recognize healthy versus unhealthy weights and report that health providers are not informing them of weight deviations. Further, important relationships between the HBM variables were identified. Results show barriers (self-efficacy) mediate the impact of perceived severity (knowledge) regarding the parental ability to assess child weight accurately. These relationships and incorporation of the HBM principles of barriers and severity into prevention/intervention strategies need further exploration.
Methods
This was a cross-sectional study with 198 parents and their 2- to 5-year-old children who attended standalone preschools or childcare centers with preschools. Parents completed a questionnaire that asked about demographic features, personal and family health, and the assessment of their child’s weight using the three most frequently utilized measures. Logistic regression was conducted to assess the association between parental factors and child weight classification status. Instruments included the Parental Self-Efficacy for Promoting Healthy Physical Activity and Dietary Behaviors in Children Scale (PSEPAD), the Obesity Risk Scale (ORK-10), and the Adolescent Obesity Risk Scale (AORK). Analyses included frequencies, chi-square tests, Kappa coefficients, and logistic regressions.
Usage notes
Early Childhood and Family Health Questionnaire
Coding Guide
|
QUESTION |
FIELD |
DESCRIPTION |
TYPE |
COLUMNS |
EXPECTED RANGE |
CODES |
|
N/A |
ID |
Assigned ID Number |
Text |
NA |
#### |
A-Z and Number (i.e. A001) |
|
N/A |
CHCLASS |
Child Classification based on actual weight/height |
Categorical |
# |
1-4 |
1=Underweight 2=Health weight 3=Overweight 4=Obese
|
|
4 |
CHID |
Unique child identifier |
Text |
NA |
### |
NA |
|
|
LBCLASS |
Is parental classification in pounds correct or incorrect? |
Categorical |
# |
1-2 |
0=Incorrect 1=Correct |
|
7 |
PICTURE |
Picture that represents child |
Categorical |
## |
1-7 |
1= Very underweight 2= Underweight 3= Slightly underweight 4=Healthy weight 5= Slightly overweight 6= Overweight 7= Obese |
|
|
PICLASS
|
Is parental picture selection correct or incorrect |
Categorical |
## |
1 |
0=Incorrect 1=Correct |
|
|
PTYPE
|
Classification of parent selection versus actual child weight |
Categorical |
# |
1-3 |
1= Correct 2 = Underestimation 3 = Overestimation |
|
|
PICCAT
|
Categorization of picture selection 1-4. Code picture 1-2 as underweight (1). 3-4 as healthy weight (2). 5-6 as overweight (3), and 7 as obese (4) |
Categorical |
# |
1-4 |
1 = Underweight 2 = Healthy weight 3 = Overweight 4 = Obese |
|
10 |
CBMI |
Child’s BMI |
Continuous |
## |
0-32 |
NA |
|
|
PERCENT |
Percentile of child weight |
Continuous |
## |
0-99 |
NA |
|
|
CBMIC
|
Child’s BMI by age category |
Categorical |
# |
1-4 |
1=Underweight 2=Health weight 3=Overweight 4=Obese
Varies by age. |
|
11 |
CLIKE
|
Description of child weight by Likert scale |
Categorical |
# |
1-5 |
1= Very Underweight 2= Underweight 3= Healthy weight 4= Overweight 5= Obese
|
|
|
LIKCLASS
|
Is description of child weight by Likert accurate? |
Categorical |
# |
1-2 |
0=Incorrect 1=Correct |
|
|
LIKTYPE
|
Classification of parent selection versus actual child weight. |
Categorical |
# |
1-3 |
1 = Correct 2 = Underestimation 3 = Overestimation |
|
|
LIKCAT
|
Categorization of Likert on scale. Code Likert to 1-2 as underweight (1), 3 as healthy weight (2), 4 as overweight (3), and 5 as obese (4) |
Categorical |
# |
1-4 |
1 = Underweight 2 = Healthy weight 3 = Overweight 4 = Obese |
|
12 |
CONCERN
|
Concern of child overweight in future |
Ordinal |
# |
1-5 |
1= Unconcerned 2= A little concerned 3= Concerned 4= Fairly concerned 5= Very concerned |
|
13 |
NCONCERN
|
Concern of child in nation being overweight |
Ordinal |
# |
1-5 |
1= Unconcerned 2= A little concerned 3= Concerned 4= Fairly concerned 5= Very concerned |
|
20 |
HCPW
|
Health care provider mentioned child overweight |
Binary |
# |
0-1 |
0 = No 1 = Yes |
|
21 |
CHCPOW |
If told overweight, how concerned would be?
|
Binary |
# |
1-5 |
1= Not at all concerned 2=Slightly concerned 3=Somewhat concerned 4= Moderately concerned 5= Extremely concerned
|
|
22 |
CHCPO
|
If told obese, how concerned would be?
|
Ordinal |
# |
1-5 |
1= Not at all concerned 2=Slightly concerned 3=Somewhat concerned 4= Moderately concerned 5= Extremely concerned
|
|
23 |
LTDS
|
Likelihood to do something about it |
Ordinal |
# |
1-5 |
1=Not likely 2=Slightly likely 3=Somewhat likely 4=Moderately likely 5=Extremely likely |
|
24 |
CONTROL
|
Control overweight weight of 2-5-year-old |
Ordinal |
# |
1-5 |
1=No control 2= Slight control 3=Some control 4=Moderate control 5=Extreme control |
|
|
PBMIC
|
Adult BMI Category |
Categorical |
# |
1-4 |
1= Below 18.5 (Underweight) 2= 18.5-24.9 (Normal or Healthy Weight) 3 = 25-29.9 (Overweight) 4 = 30.0 and Above (Obese) |
|
34 |
PLIKE
|
Describe own weight by Likert scale |
Categorical |
# |
1-4 |
1=Underweight 2=Healthy weight 3=Overweight 4=Obese |
|
|
PRIGHT
|
Is parental description of weight by Likert scale accurate? |
Categorical |
# |
1-2 |
0=Incorrect 1=Correct |
|
35 |
NDX
|
Number of adult diagnoses selected |
Numerical |
# |
0-5 |
NA |
|
|
OWEX
|
Exposure to overweight in family |
Binary |
# |
0-1 |
0=No 1=Yes
|
|
|
OEX |
Exposure to obesity in family |
Binary |
# |
0-1 |
0=No 1=Yes
|
|
Knowledge scale |
ORKT |
Total of ORK-10 score on knowledge scale |
Numerical |
## |
0-10 |
NA |
|
Knowledge scale 2 |
AORK |
Total score of 10 on AORK knowledge scale |
Ordinal |
## |
0-10 |
NA |
|
PSE |
PSET |
Total parental self-efficacy score |
Ordinal |
### |
0-160 |
NA |
Funding
2018 Sigma/Chamberlain College of Nursing Education Research Grant, Award: 14306
2018 Sigma/Chamberlain College of Nursing Education Research Grant, Award: 14306