Association between Physical Activity Knowledge and Levels of Physical Activity in Chinese Adults with Type 2 Diabetes

<div><p>Background</p><p>Physical activity (PA) is an important treatment regimen for diabetes. The purposes of this study were to evaluate people’s knowledge of how exercise influences wellbeing (termed “PA knowledge” or “knowledge of PA” in this paper) and the resulting association with levels of PA in Chinese adults with Type 2 diabetes, and to identify the valuable demographic and lifestyle factors that possibly influence the association between PA knowledge and level of PA.</p><p>Methods</p><p>Two hundred and fifty-eight adults with Type 2 diabetes completed an interviewer-administered survey at a diabetes clinic in Hong Kong. Data on demographics, lifestyle factors and diabetes-related medical indicators were obtained. A 20-item questionnaire was developed to measure PA-related knowledge (one point scored for each correct answer; aggregate score up to 20 points). level of PA was measured by the International Physical Activity Questionnaire.</p><p>Results</p><p>The proportions of correct answers to each question ranged from 19.4 to 90.7%. Compared with poorly educated participants, those with university education level and above had PA knowledge scores 1.7 points higher (14.3 <i>vs.</i> 12.6, <i>P<</i>0.05). Younger, female, and obese participants were more likely to have lower level of PA (all <i>P<</i>0.05). After adjustment for age, gender, (BMI) and education level, the odds of having a moderate-to-high level of PA was 19% greater with 1 unit increase in PA knowledge score [95% confidence interval (CI): 1.09–1.29; <i>P<</i>0.001], this association was strongest in participants with tertiary education level or above [odds ratio (OR): 1.35; 95% CI: 1.03–1.77; <i>P<</i>0.05].</p><p>Conclusions</p><p>PA knowledge was positively associated with level of PA. Education level significantly influenced the association between PA knowledge and level of PA, leading to the suggestion of vulnerable groups to target for PA improvement in the face of diabetes.</p></div

Descriptive statistic of participants (<i>n</i> = 258).

<p>Descriptive statistic of participants (<i>n</i> = 258).</p

Proportions of different answers in each physical activity knowledge question.

<p>Proportions of different answers in each physical activity knowledge question.</p

Physical activity knowledge score according to different demographic and lifestyle factors.

<p>Physical activity knowledge score according to different demographic and lifestyle factors.</p

Physical activity level according to different demographic and lifestyle factors.

<p>Physical activity level according to different demographic and lifestyle factors.</p

Odds ratios (ORs) for level of PA per unit increase in PA knowledge score by logistic regression analysis.

<p>Odds ratios (ORs) for level of PA per unit increase in PA knowledge score by logistic regression analysis.</p

Validity indicators for categorical variables BMI, waist circumference, and blood pressure, including the classification percentage and weighted kappa coefficient of the self-reported and clinical body measures, 2011, Hong Kong (<i>N</i> = 144).

<p>Validity indicators for categorical variables BMI, waist circumference, and blood pressure, including the classification percentage and weighted kappa coefficient of the self-reported and clinical body measures, 2011, Hong Kong (<i>N</i> = 144).</p

Mean values of measured and self-reported variables, mean differences, and the correlations between paired variables, 2011, Hong Kong (<i>N</i> = 144).

<p>Mean values of measured and self-reported variables, mean differences, and the correlations between paired variables, 2011, Hong Kong (<i>N</i> = 144).</p

Characteristics of the validation study sample (<i>n</i> = 144) and the total sample (<i>n</i> = 1253), 2011, Hong Kong.

<p>Characteristics of the validation study sample (<i>n</i> = 144) and the total sample (<i>n</i> = 1253), 2011, Hong Kong.</p

Linear regression analyses predicting body mass index (BMI) from daily TV viewing time.

<p>a. Only TV viewing time entered the model as independent variable.</p><p>b. Model was adjusted for gender and age.</p><p>c. Model was adjusted for gender, age, employment status, marital status, education level.</p><p>d. Model was adjusted for gender, age, employment status, marital status, education level and vigorous physical activity.</p><p>e. Models were adjusted for age, employment status, marital status, education level and vigorous physical activity. The interaction terms were constructed for each moderator.</p><p>f. Models were adjusted for age, employment status, marital status, education level and vigorous physical activity.</p><p>g. Models were adjusted for gender, employment status, marital status, education level and vigorous physical activity.</p