Yingting Cao

Dr. Yingting Cao

Implementation Science Lab, Baker Heart and Diabetes Institute, 75 Commercial Rd, Melbourne VIC 3004, Australia
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Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 November 2020 in Diabetes, Obesity and Metabolism
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Journal Article
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Sathish ThirunavukkarasuSathish Thirunavukkarasu
Sathish Thirunavukkarasu
NKNitin Kapoor
Nitin Kapoor
Yingting CaoYingting Cao
Yingting Cao
RTRobyn J. Tapp
Robyn J. Tapp
PZPaul Zimmet
Paul Zimmet
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1 January 2011 in International Journal of Behavioral Nutrition and Physical Activity
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VSViktoria Svensson
Viktoria Svensson
LLLinda Lundborg
Linda Lundborg
Yingting CaoYingting Cao
Yingting Cao
PNPaulina Nowicka
Paulina Nowicka
CMClaude Marcus
Claude Marcus
TSTanja Sobko
Tanja Sobko
The Children's Eating Behaviour Questionnaire (CEBQ) is a multi-dimensional, parent-reported questionnaire measuring children's eating behaviours related to obesity risk, i.e. 'enjoyment of food', 'food responsiveness', 'slowness in eating' and 'satiety responsiveness'. It has not previously been validated in a Swedish population, neither on children under the age of 2 years. In the present study we examined the factor structure and the reliability of the Swedish version of the CEBQ, for use in an obesity intervention programme targeting preschool children 1-6 years. Further, the associations between eating behaviours and children's age, gender and relative weight (BMI SDS) and parental weight were investigated. Parents to 174 children aged 1-6 years (50% girls, mean age 3.8 years), recruited from five kindergartens in Stockholm, completed the Swedish version of the CEBQ. Data on children's weight and height, parental weight, height and educational level was collected. Children's relative weight was calculated for a subpopulation (mean BMI SDS -0.4, n = 47). Factorial validation (Principal Component Analysis) on all CEBQ items was performed. Differences in eating behaviours by age, gender and parental weight were examined. Correlations between eating behaviours and the child's BMI SDS were analysed controlling for age, gender, parental weight and education in linear regression analyses. The factor analysis revealed a seven factor solution with good psychometric properties, similar to the original structure. The behaviour scales 'overeating'/'food responsiveness', 'enjoyment of food' and 'emotional undereating' decreased with age and 'food fussiness' increased with age. Eating behaviours did not differ between girls and boys. The children's relative weight was not related to any of the eating behaviours when controlling for age, gender, parental weight and education, and only associated with parental weight status. Our results support the use of the CEBQ as a psychometric instrument for assessing children's eating behaviours in Swedish children aged 1-6 years. Measuring obesity related eating behaviours in longitudinal and interventional studies would offer opportunities for studying causal effects of eating behaviours in the development of obesity in children.

24 January 2012 in International Journal of Behavioral Nutrition and Physical Activity
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Yingting CaoYingting Cao
Yingting Cao
VSViktoria Svensson
Viktoria Svensson
CMClaude Marcus
Claude Marcus
JZJing Zhang
Jing Zhang
JZJianduan Zhang
Jianduan Zhang
TSTanja Sobko
Tanja Sobko
Background: Eating behaviours have been suggested relating to obesity development. The Children's Eating Behaviour Questionnaire (CEBQ) is a parent-report measure constructed to assess multiple dimensions of eating behavior for children. This study aimed to test the validity of the Chinese version of Children's Eating Behaviour Questionnaire (CEBQ) in Chinese children aged 12-18 months. We examined factor structure and the reliability of the Chinese version of the CEBQ, the associations between children's eating behaviours and children's weight (BMI SDS) were assessed. Methods: 219 questionnaires were filled out by the caregivers, approached in community health care centers in two cities in China. BMI of each child was calculated and converted to BMI SDS. Factor validation (Principal Component Analysis, exploratory factor analysis) on all CEBQ items was performed and gender difference in eating behaviours was examined. Correlations between eating behaviours and the child's BMI SDS were analyzed by linear regression analysis controlling for gender, parental combined weight, and education. Results: The factor analysis revealed a seven-factor solution, with factor 'food responsiveness' (FR) split into two. 'Satiety responsiveness' (SR) and 'Enjoyment of food' (EF) factors were not detected. Interestingly, boys scored higher than girls in the FR scales, whereas girls had a higher score in 'food fussiness' (FF) scale. Conclusions: We conclude that although a valuable psychometric instrument, CEBQ might be affected by age and cultural differences. Therefore, adjusting it in order to fit the Chinese population was suggested. We did not find an association between eating behaviours and children's BMI SDS, when it was controlled for gender and parental weight.

5 May 2023 in BMC Health Services Research
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LNLi Nie
Li Nie
BOBrian Oldenburg
Brian Oldenburg
Yingting CaoYingting Cao
Yingting Cao
WRwenjie ren
wenjie ren
Background: Mobile health (mHealth) services can not give full play to their value if only it is used in the short term, and their continuous usage can achieve better effects in health management. This study aims to explore the factors that affect continuous usage intentions of mHealth services and their mechanism of action. Methods: First, considering the uniqueness of health services and social environmental factors, this study constructed an extended Expectation Confirmation Model of Information System Continuance (ECM-ISC) to investigate factors that may influence the intention of continuous usage of mHealth services based on three dimensions, namely individual characteristics, technology and environment. Second, the survey method was used to validate the research model. The questionnaire items were derived from validated instruments and discussed by experts and data were collected both online and offline. The structural equation model was used for data analysis. Results: There were 334 avidity questionnaires through cross-sectional data and these participants had used mHealth services ever. The reliability and validity of the test model were good, in which Cronbach’s Alpha values of 9 variables exceeded 0.9, composite reliability 0.8, the average variance extracted value 0.5, and the factor loading 0.8. The modified model had a good fitting effect and strong explanatory power. It accounted for 89% of the variance in expectation confirmation, 74% of the variance in perceived usefulness, 92% of the variance in customer satisfaction, and 84% of the variance in continuous usage intention. Compared with the initial model hypotheses, perceived system quality was deleted according to the heterotrait-monotrait ratio, so paths related to it were deleted; perceived usefulness wasn’t positively associated with customer satisfaction, and its path was also deleted. Other paths were consistent with the initial hypothesis. The two new added paths were that subjective norm was positively associated with perceived service quality (β = 0.704, P < 0.001), and perceived information quality (β = 0.606, P < 0.001). Electronic health literacy (E-health literacy) was positively associated with perceived usefulness (β = 0.379, P < 0.001), perceived service quality (β = 0.200, P < 0.001), and perceived information quality (β = 0.320, P < 0.001). Continuous usage intention was influenced by perceived usefulness (β = 0.191, P < 0.001), customer satisfaction (β = 0.453, P < 0.001), and subjective norm (β = 0.372, P < 0.001). Conclusions: The study constructed a new theoretical model including E-health literacy, subjective norm and technology qualities to clarify continuous usage intention of mHealth services, and empirically validated the model. Attention should be paid to E-health literacy, subjective norm, perceived information quality, and perceived service quality to improve continuous usage intention of users and self–management by mHealth Apps managers and governments. This research provides solid evidence for the validity of the expanded model of ECM-ISC in the mHealth field, which can be a theoretical and practical basis for mHealth operators’ product research and development.

21 September 2018 in Nutrients
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Yingting CaoYingting Cao
Yingting Cao
SZShiqi Zhen
Shiqi Zhen
ATAnne Taylor
Anne Taylor
SASarah Appleton
Sarah Appleton
EAEvan Atlantis
Evan Atlantis
Zumin ShiZumin Shi
Zumin Shi
(1) Background: In clinical trials, dietary magnesium use can improve insomnia symptoms. However, little is known about the association between dietary magnesium consumption and sleep disorder symptoms including daytime falling asleep, sleepiness and snoring at the population level. (2) Methods: We used data from 1487 adults aged 20 and above attending the Jiangsu Nutrition Study. At baseline in 2002, dietary magnesium was assessed by 3-day weighed food records. At follow-up in 2007, sleep disorder symptoms, including daytime falling asleep, sleepiness and snoring at night, were gathered using a sleep questionnaire. (3) Results: The mean intake of magnesium was 332.5 mg/day. In total, 5.3%, 13.2% and 35.7% of the subjects reported daytime falling asleep, daytime sleepiness, and snoring during sleep, respectively. Compared with the lowest quartile of magnesium intake, the highest quartile was associated with decreased likelihood of falling asleep (odds ratio (OR) 0.12 (0.02, 0.57)) in women but not in men after adjusting for demographic, anthropometric, lifestyle factors, hypertension, and overall dietary patterns. No associations were found between dietary magnesium intake and daytime sleepiness nor night snoring in either gender. (4) Conclusions: Dietary magnesium intake may have long-term benefits in reducing the likelihood of daytime falling asleep in women.

1 August 2020 in The American Journal of Surgery
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Journal Article
Closed access
LSLei Sheng
Lei Sheng
JSJinyuan Shi
Jinyuan Shi
BHBo Han
Bo Han
BLBin Lv
Bin Lv
LLLuchuan Li
Luchuan Li
QZQingdong Zeng
Qingdong Zeng