Vegetable and Fruit Consumption among Chinese Adults and Associated Factors: A Nationally Representative Study of 170,847 Adults.

OBJECTIVE: This study examined vegetable and fruit (VF) consumption rate and its associated factors among Chinese adults. METHODS: Nationally representative data from the 2013 China Chronic Disease Surveillance survey were used. Dietary intake data, including VF consumption during the last 12 months, were collected. All analyses were weighted to obtain nationally representative estimates. Associations between VF consumption and other factors (e.g., meal frequency and physical activity) were examined through logistic regression analysis. RESULTS: The average fruit consumption was 102.3 g/day (95% CI: 97.0-107.6) and the average vegetable consumption was 350.6 g/day (95% CI: 339.3-361.8). Over half (53.2%, 95% CI: 50.9-55.4) of Chinese adults met the VF consumption of 400 g/day recommended by the World Health Organization (WHO). Rural residents had a higher prevalence of low VF consumption rate than urban residents [49.20% (95% CI: 46.2%-52.2%) vs. 44.0% (95% CI: 41.7%-46.3%) P < 0.01]. Old age (OR = 1.01, 95% CI: 1.00-1.01), low educational level, low income, minority ethnicity (OR = 1.41, 95% CI: 1.15-1.74), underweight (OR = 1.17, 95% CI: 1.03-1.33), single marital status (OR = 1.20, 95% CI: 1.08-1.33), low health literacy, irregular breakfast (OR = 1.20, 95% CI: 1.04-1.38) or lunch (OR = 1.58, 95% CI: 1.26-1.99) habits, and no leisure-time physical activity were associated with low VF consumption. CONCLUSION: Only half of Chinese adults met the VF consumption recommended by the WHO. Low socio-economic status, irregular diet, and poor health literacy were likely associated with low VF consumption. National efforts and programs are needed to promote VF consumption.

Self-rated health and health-related quality of life among Chinese residents, China, 2010.

BACKGROUND: Self-rated health (SRH) and health-related quality of life (HRQOL) are two outcome measures used to assess health status. However, little is known about population-based SRH and HRQOL in China. METHODS: Data from the 2010 China Chronic Disease and Risk Factor Surveillance, a nationally representative sample of 98,658 adults (≥18-year-old) residing in China, were analyzed. SRH was assessed by asking "Would you say that, in general, your health is very good, good, general, poor, or very poor?" HRQOL was assessed by asking "For about how many days during the past 30 days was your health not good due to physical illnesses, injuries, or mental unhealthy?". RESULTS: Overall, 6.3 % of participants rated their health as poor or very poor. The prevalence of poor/very poor health increased with advancing age ranging from 2.0 % in the 18-24 year-olds to 14.9 % in those ≥75 years-old, while it decreased with education levels from 13.0 % in illiterates/those with some primary school education to 2.2 % in college graduates or above. Additionally, women were more likely than men to rate their health as poor or very poor (7.2 % vs. 5.4 %). The reported rate of poor/very poor health was higher in western region residents compared to those in the east (7.4 % vs. 5.3 %). The mean numbers of self-reported physically unhealthy days, injury-caused unhealthy days, or mentally unhealthy days during the past 30 days were 1.48, 0.20, and 0.54, respectively. Older adults had more physically unhealthy days than the younger ones ranging from 2.92 days in those ≥ 75 year-old to 0.95 days in 18-24 year-olds. Women had more physically unhealthy days and mentally unhealthy days than men (1.72 vs. 1.23; 0.62 vs. 0.46, respectively). The highest mean number of physically unhealthy days (2.32) was reported by illiterates or those with some primary school education. The highest mean number of mentally unhealthy days (0.86) reported by college graduates or above. CONCLUSIONS: Substantial variations existed in SRH and HRQOL among age groups, gender groups, education groups, and across regions in China. Considering these disparities will be important when developing health policies and allocating resources.

[Disease burden on diabetes in China, 2010].

OBJECTIVE: To estimate the disease burden of diabetes in China, 2010. METHODS: We calculated the disability adjusted life years (DALYs) of diabetes, using data from both the Mortality Surveillance in National Disease Surveillance Points System and the China Chronic Disease Surveillance (2010). We also examined the differences of DALYs by gender, age, urban/rural areas and geographical locations. RESULTS: The overall disease burden of diabetes was 19.12 DALYs per 1000 population. Men (18.30 DALYs per 1000) had a higher DALY rate than in women (19.97 DALYs per 1000). We observed an upside-down "U" relationship between DALY rate and age. Residents aged 15 - 79 years bore most part of disease burden and the burden peaked among population at age from 45 to 60 years (30.39 DALYs per 1000). There was a higher DALY rate seen in the population from the urban areas (17.83 DALYs per 1000) than those from the rural areas (17.03 DALYs per 1000). In order, the burden showed a decrease from the eastern region (22.28 DALYs per 1000), middle region (19.62 DALYs per 1000) to the western region (13.54 DALYs per 1000), in the country. CONCLUSION: China is currently carrying considerable burden caused by diabetes among the population of labor force while inequity of burden was seen among different geographical regions within China.

[Self-rated health status among Chinese residents, China, 2010].

OBJECTIVE: To investigate the self-rated health status among Chinese residents in 2010. METHODS: Data was from the Non-communicable Disease & Risk Factor Surveillance in China, 2010. A total of 98 638 adults aged ≥ 18 years were included in the study. Self-rated health was assessed by four questions: (1) Would you assess your health status as very good or good, general (not good/not poor), poor or very poor? (2) How many days was your health not good for physical illness during the past 30 days? (3) How many days was your health not good for injury during the past 30 days? (4) How many days was your health not good for mental illness, which include stress and problem with emotions depression during the past 30 days? After being weighed according to complex sampling scheme and post-stratification, the sample was used to estimate the prevalence of self-rated health. The Rao-scott χ(2) test with different samples was adopted for comparison among groups. RESULTS: In total, 57.5% (95%CI:55.5%-59.5%) of the participants rated their health as being either very good or good, 36.2% (95%CI:34.5%-37.8%) as general, and only 6.3% (95%CI:5.7%-6.9%) as poor or very poor; In different age groups and gender, the differences were statistically significant (χ(2) values were 1179.88, 85.36, both P values were < 0.05) . The reported rate of poor or very poor health increased significantly with advancing age ranging from 2.0% (95%CI:1.5%-2.4%)in 18-24 year-old group to 14.9% (95%CI:12.6%-17.2%) in ≥ 75 year-old group; Females were more likely than males to rate their health as poor or very poor , respectively (7.2%; 95%CI 6.5%-7.9% and 5.4%; 95%CI:4.9%-5.9%). During the past 30 days 18.5% (95%CI:17.1%-19.8%) of the participants was not in good health for physical illness. The reported rate of physical illness increased significantly with advancing age (χ(2) = 211.99, P < 0.01), and it was the lowest in 25-34 year-old group (15.4%; 95%CI:13.7%-17.0%), and the highest in ≥ 75 year-old group (28.3%; 95%CI:24.9%-31.6%) . It was statistically higher among females (21.1%; 95%CI:19.5%-22.6%) compared to males (15.9%; 95%CI:14.6%-17.3%) (χ(2) = 231.81, P < 0.01); the reported rates of physical illness were 17.4% (95%CI:15.3%-19.5%) among residents in the east region, 17.2% (95%CI:14.7%-19.6%) in the middle region, and 21.5% (95%CI:18.7%-24.4%) in the western region(χ(2) = 6.75, P < 0.01). During the past 30 days 2.7% (95%CI:2.3%-3.2%) of the participants was not in good health for injure. The reported rate of injure decreased significantly with advancing age (χ(2) = 25.54, P < 0.01), and it was the highest in 18-24 year-old group (3.8%; 95%CI:2.6%-5.0%), and the lowest in 35-44 year-old group (2.3%; 95%CI:1.8%-2.7%) . It was statistically higher among males (3.0%; 95%CI:2.4%-3.5%) compared to females (2.5%; 95%CI:2.1%-2.9%) (χ(2) = 8.89 P < 0.01) ; the reported rates of injure were 2.3% (95%CI:1.9%-2.7%) among residents in the east region , 2.1% (1.7%-2.4%) in the middle region, and 4.1% (95%CI:2.6%-5.6%) in the west region (χ(2) = 16.26, P < 0.01). During the past 30 days 10.0% (95%CI:8.8%-11.3%) of the participants was not in good health for mental illness. The reported rate of mental illness decreased significantly with advancing age (χ(2) = 92.14 P < 0.01), and it was the highest in 18-24 year-old group (12.9%; 95%CI: 10.6%-15.2%), and the lowest in ≥ 75 year-old group (5.7%; 95%CI: 4.4%-7.0%) .It was statistically higher among females (10.8%; 95%CI:9.5%-12.1%) than males (9.2%; 95%CI:7.9%-10.5%) (χ(2) = 21.59, P < 0.01). CONCLUSION: The self-rated health status among Chinese residents was good in 2010. Substantial variation exists in self-rated health status across age groups, between genders, and across regions. Considering these disparities will be important for developing health policy and allocating resources.

[Leisure-time physical activity and sedentary behaviors among Chinese adults in 2010].

OBJECTIVE: To understand the prevalence of participation in leisure-time physical activity, and sedentary behaviors among Chinese adults. METHODS: Data from Chinese Chronic Disease Surveillance (2010) was used. Among adults aged 18 years old and over, the information on frequency and duration of occupational activity, house chores, commuting and leisure time activity was collected by an interview with Global Physical Activity Questionnaire (GPAQ). The time spent on watching TV, reading, using computers or playing games after work was also surveyed. This present study only analyzed the percentage of participating in leisure time moderate or vigorous intensity physical activity at least 10 minutes three days per week and the time spent on TV, reading, using computer and playing games during after hours among Chinese adults of 98 649 subjects. RESULTS: 11.9% (95%CI: 10.5% - 13.3%) of all adults took part in leisure time moderate or vigorous intensity physical activity at least 10 minutes for three days per week, with-group the percentage highest among age-group 18 - 24 (15.6%, 95%CI: 10.5% - 13.3%) and lowest among age 25 - 34 (9.9%, 95%CI: 8.0% - 11.7%) and 75 years old and over (9.9%, 95%CI: 8.2% - 11.6%) (P < 0.01). The age related change showed a double-peak curve. The percentage was higher in male (13.1%, 95%CI: 11.6% - 14.6%) than in female (10.6%, 95%CI: 9.3% - 12.0%) (P < 0.01). Among the populations engaged in diverse occupations, the lowest percentage was detected among those in farming, forestry, husbandry and fishing (4.2%, 95%CI: 3.4% - 4.9%). Higher percentage was found among the residents lived in urban areas (19.9%, 95%CI: 17.4% - 22.5%) than in rural areas (8.2%, 95%CI: 6.7% - 9.8%) (P < 0.01), and higher in the east area (14.8%, 95%CI: 11.9% - 17.6%) compared to that in central (9.7%, 95%CI: 8.1% - 11.3%) or in west areas (10.3%, 95%CI: 8.4% - 12.3%) in China (P < 0.01). Furthermore, (2.7 ± 2.0) hours per day was spent in sedentary behaviors, such as watching TV, reading, using computers or playing games during after hours. Those aged 18 - 24 years-old spent most time (3.8 ± 2.6) hours per day in sedentary behaviors and the time reduced with age (P < 0.01). More time on Sedentary behaviors were taken by male (2.9 ± 2.1 hours per day) than by female ((2.6 ± 1.9) hours per day) (P < 0.01), with more hours spent in urban ((3.3 ± 2.2) hours per day) than that in rural ((2.5 ± 1.9) hours per day) (P < 0.01). No difference was detected among the residents lived in east ((2.9 ± 2.1) hours per day), central ((2.7 ± 2.0) hours per day) and west area ((2.6 ± 2.0) hours per day) (P > 0.05). CONCLUSION: The percentage of taking part in moderate and vigorous activity during leisure time was generally low. Average time spent in after hours sedentary behaviors was long.