To investigate the association between a vegetable-rich food pattern and obesity among Chinese adults.
A food pattern rich in vegetables is associated with lower risk of obesity and non-communicable chronic disease in Western countries. A similar food pattern is found in the Chinese population but the cooking method is different. A cross-sectional household survey of 2849 men and women aged 20 years and over was undertaken in 2002 in Jiangsu Province (response rate, 89.0%). Food intake was assessed by food frequency questionnaire. Factor analysis was used to identify food patterns. Nutrient intake was measured by food weighing plus consecutive individual 3-day food records. Height, weight and waist circumference were measured.
The prevalence of general obesity (BMI ⩾28 kg m−2) was 8.0% in men and 12.7% in women, central obesity was 19.5% (⩾90 cm) and 38.2% (⩾80 cm), respectively. A four-factor solution explained 28.5% of the total variance in food frequency intake. The vegetable-rich food pattern (whole grains, fruits and vegetables) was positively associated with vegetable oil and energy intake. Prevalence of obesity/central obesity increased across the quartiles of vegetable-rich food pattern. After adjusting for sociodemographic factors and four distinct food patterns, the vegetable-rich pattern was independently associated with obesity. Compared with the lowest quartile of vegetable-rich pattern, the highest quartile had higher risk of general obesity (men, prevalence ratio (PR): 1.82, 95% confidence interval (CI): 1.05–3.14; women, PR: 2.25, 95% CI: 1.45–3.49).
The vegetable-rich food pattern was associated with higher risk of obesity/central obesity in Chinese adults in both genders. This association can be linked to the high intake of energy due to generous use of oil for stir-frying the vegetables.
China is facing an obesity epidemic. Between 1992 and 2002, the prevalence of overweight and obesity increased in all gender and age groups and in all geographic areas of the country. Using the World Health Organization (WHO) body mass index (BMI) cutoff points, the combined prevalence of overweight and obesity increased from 14.6 to 21.8%1 during this period. Changes in diet and physical activity are associated with this epidemic.2
Generally, the Chinese diet is characterized by a high intake of vegetables and other plant foods, and thus the intake of carbohydrates and fiber is high. Even with the ongoing nutrition transition, the average intake of vegetables is still higher than those in the western countries. At a national level, the mean intake of vegetables was 276 g per day in 2002, which is 40 g per day less than 20 years ago.3 Understanding the immediate causes of the rapid increase in the prevalence of obesity is of importance.
The beneficial association between intake of vegetables and fruits and obesity has been well documented in different populations.4 In Western populations, high intake of fruits and vegetables is associated with lower intake of energy and a healthy lifestyle and thus a lower risk of obesity.4 No research has examined the association between obesity and a diet rich in vegetables in China.
In recent years, food pattern analysis has attracted the attention of researchers because it focuses on the whole diet, making it possible to look at the interaction between foods and nutrients in relation to health.5 In Western countries, the food patterns like ‘healthy’, ‘prudent’, ‘western’, and so on derived by factor analysis are associated with many health outcomes including obesity, diabetes, cardiovascular disease, inflammation and cancer.5, 6, 7, 8, 9, 10, 11, 12, 13, 14 The same method has been used in studies done in China and other Asian countries. A similar ‘prudent/healthy’ pattern is found and is negatively associated with anemia and mortality.15, 16, 17, 18, 19 The objective of the present article is to look at the association between a vegetable-rich food pattern derived from factor analysis and the risk of obesity in Chinese adults.
Subjects and methods
In 2002, China launched a national study in nutrition and health under the approval of the Chinese Ministry of Health. A multistage cluster sampling method was used to select the participants.15 The data presented in this article are based on a subsample from Jiangsu province, one of the economically booming areas in China with a population of 73.6 million. The rural sample was selected from six counties (Jiangyin, Taicang, Suining, Jurong, Sihong and Haimen). From each of the six counties, three towns were randomly selected. The urban sample was selected from two prefecture capital cities (Nanjing and Xuzhou). From each prefecture city, three streets were randomly selected. The six counties and two prefectures cities represented a geographically and economically diverse population with gross domestic product ranging from 3221 yuan/capita per year (US$403) to 35169 yuan/capita per year ($4396) (mean, $1993).20 In each town/street, two villages/neighborhoods were further randomly selected. In each village/neighborhood, 30 households were randomly selected. All members of the households were invited to take part in the study. Written consents were obtained from all the participants. In the study presented here, we analyzed only data for adults aged 20 years and over. The total sample included 1308 men and 1541 women, of them 711 participants were from the urban area. The response rate was 89.0%.
Measurement and interview
Participants were interviewed in their homes by trained health workers using a precoded questionnaire. Interviews took approximately 2 h to complete and included questions on diet, sociodemographic information, medical history, health habits such as cigarette smoking and physical activity, and other lifestyle factors.
Height, weight and waist circumference
Anthropometric measurements were carried out at the study site by health workers. Height was measured without shoes and weight was measured with light clothing. Waist circumference was measured at midway between the inferior margin of the last rib and the iliac crest in a horizontal plane. BMI was calculated as weight in kilograms divided by the square of the height in meters. General obesity was defined as BMI ⩾28 kg m−2 according to the Chinese standard.21 Central obesity was defined as waist circumference ⩾90 cm in men and ⩾80 cm in women according to the International Diabetes Federation criteria.22
Diet during the past year was investigated by a series of detailed questions about usual frequency and quantity of intake of 33 food groups and beverages. The list of foods was further collapsed into 25 food groups in the analysis because of low intake of some items. Portion size for each food was established by reference to food models. Subjects were asked to recall the frequency of consumption of individual food items (number of times per day, week, month and year) and the estimated portion size, using local weight units (liang (50 g)) or natural units (cups). Intakes of foods were converted into liang or cups (for beer and beverage) per day and were used in the further analysis. These food intake variables were standardized (mean, 0; s.d., 1) before performing factor analysis.
The food frequency questionnaire has been validated23, 24 and reported to be a useful method for the collection of individual food consumption information in face-to-face interviews, but not in self-administered surveys due to the current educational level of the majority of the Chinese population.
Dietary patterns were identified by factor analysis, using standard principal component analysis method. Factors were rotated with an orthogonal (varimax) rotation to improve interpretability and minimize the correlation between the factors. The number of factors retained from each food classification method was determined by eigenvalue (>1), scree plot, factor interpretability and the variance explained (>5%) by each factor. Labeling of the factors was primarily descriptive and based on our interpretation of the pattern structures.
Participants were assigned pattern-specific factor scores. Scores for each pattern were calculated as the sum of the products of the factor loading coefficients and standardized daily intake of each food associated with that pattern. Only foods with factor loadings of >0.20 and <−0.20 were included in calculation of pattern scores, because these items represent the foods most strongly related to the identified factor.
Nutrient and vegetable oil intakes were measured both by food weighing and by consecutive individual 3-day food records. We did not consider under- and over-report of energy intake as an issue of concern because any unreliable data were checked by the health workers during the survey. Food consumption data were analyzed using the Chinese Food Composition Table.25 Energy intake was compared with Chinese reference nutrient intakes (RNIs).
Income was assessed by the question ‘What was your family's income per person in 2001?’ The response categories for the question were <800, 800–1999, 2000–4999, 5000–9999, 10 000–19 999 and >20 000 yuan. Responses were further categorized into the following groups: ‘low’, <1999 yuan; ‘medium’, 2000–4999 yuan; ‘high’, >5000 yuan. Education was recoded into three categories based on six education categories in the questionnaire: low: illiteracy, primary school; medium: junior middle school and high: high middle school or higher. Active commuting (walking or cycling to and from work) and leisure time physical activity were both categorized into three groups: none, 1–30 min per day and more than 30 min per day.
Factor scores were divided into quartiles, implying increased intake from quartiles 1–4 (Q1–4). χ2-test was used to compare difference between categorical variables. Because the prevalence of obesity was higher than 10%, Poisson regression with robust variance26 was used to determine the association between food pattern and obesity adjusted for age, income, education, occupation, active commuting, smoking, drinking and energy intake. Linear trends in prevalence ratio (PR) were tested for by modeling quartiles of intake as a continuous variable. Factor analysis was performed using SPSS 11 0 (SPSS Inc., Chicago, IL, USA). All the other analyses were performed by using STATA 9 (Stata Corporation, College Station, TX, USA).
The data set contained 1308 men and 1541 women. About 80% of the participants had an education level of primary or junior school. The prevalence of general obesity was 8.0% in men and 12.7% in women; central obesity was 19.5% in men and 38.2% in women (Table 1). The mean age was 47.0 years (s.d., 14.5). Mean BMI were 23.4 (s.d., 3.2) kg m−2 for men and 23.6 (s.d., 3.7) kg m−2 for women. The prevalence of general obesity increased with increasing age (5.5, 8.8 and 13.0% in age groups 20–30, 31–45, 46 and above) (data not shown).
Four food patterns were obtained by factor analysis. Factor loadings (equivalent to simple correlations between the food items and the dietary patterns) for the four food patterns are presented in Table 2. Factor 1 (‘macho’) was characterized by various kinds of animal foods and alcohol, that is, foods commonly eaten by men. The ‘traditional’ pattern (factor 2) loaded heavily on rice and fresh vegetable and inversely on wheat flour. Factor 3 (‘sweet tooth’) contained cake, milk, yoghurt and drinks. Factor 4 (‘vegetable rich’ pattern) included whole grains, fruits, root vegetables, fresh and pickled vegetables, milk, eggs and fish. The four factors explained 28.5% of the variance in intake (9.8, 8.0, 5.5 and 5.2% for factors 1–4, respectively).
There were significant differences in intake of fruits, vegetables, whole grains, animal foods, milk, fish and eggs across quartiles of the vegetable-rich food pattern in both genders (Table 3). Education was positively associated while income was negatively associated with this pattern. A clear increasing trend of intake of energy, protein and carbohydrate was seen across quartiles of intake of the vegetable-rich food pattern from low to high in men and women. Men in the highest quartile of this pattern consumed 120 kcal per day more than those in the lowest quartile; the corresponding figure in women was 200 kcal per day. Among women aged 31–45, the energy intake difference between Q4 and 1 of the vegetable-rich food pattern was 310 kcal per day (data not shown).
The mean daily intake of vegetable oil was 42 g (45 g in men, 39 g in women). The most common cooking fat used was unhydrogenated vegetable oil (99.4%). Significant differences in the mean intake of vegetable oil were seen among those having a vegetable-rich food pattern in women: from Q1 to 4, the mean intakes were 33, 39, 40 and 42 g per day in women (P<0.001); and 43, 46, 46 and 46 g per day in men (P=0.405). In multivariate linear model adjusting for age and gender, the vegetable-rich food pattern score (continuous) was positively associated with vegetable oil intake: regression coefficient was 1.40 (95% confidence interval (CI): 0.41–2.40) (data not shown). No difference was found in the consumption of animal cooking fat across vegetable-rich food pattern quartiles (all groups below 0.4 g per day) (data not shown). Not only was there any significant difference in the intake of this fat across quartiles of this food pattern; the fat energy percentage was also similar.
In women, 21.9% of those in the highest quartile of the vegetable-rich food pattern had total energy intake more than 120% of the RNI, compared with 12.8% of the women in the lowest quartile (P<0.001). A similar trend was also seen in men although it was not significant. Mean fat energy percentage was about 31% in most of the quartile groups, and half the sample had a fat energy percentage above 30%. The vegetable-rich food pattern was positively associated with active commuting and leisure time physical activity in both genders (Table 3).
Intake of vegetables was significantly associated with intake of vegetable oil. The regression coefficient for vegetable oil (g per day) by fresh vegetable (liang per day) was 0.55 (95% CI: 0.09–1.02) in men, 0.68 (95% CI: 0.28–1.07) in women and 0.66 (95% CI: 0.35–0.97) in men and women combined (data not shown).
A clear increasing trend in the prevalence of general obesity was found across quartiles of the vegetable-rich food pattern from low to high in women (Q1–4: 8.0, 12.1, 11.9, and 18.0%, P<0.001). The same, although not significant, trend was found in men (Table 4). Intake of vegetable-rich pattern was significantly associated with prevalence of central obesity in both genders. The prevalence of central obesity comparing fourth and first quartile intake of this pattern in men was 23.8 vs 15.6%.
In multivariate analysis, after adjusting for age, smoking, drinking, income, education, occupation, active commuting, leisure time physical activity, energy intake and other food patterns, people in the second to fourth quartiles were more likely to be obese compared with the lowest quartile (Table 5). The PR of general obesity, comparing Q4 and 1 vegetable-rich pattern groups was 2.25 (95% CI: 1.45–3.49) in women, 1.82 (95% CI: 1.05–3.14) in men and 2.06 (95% CI: 1.46–2.89) in men and women combined (adjusted also for sex). The PR of central obesity, comparing Q4 and 1 of vegetable-rich pattern groups, was 1.48 (95% CI: 1.06–2.05) in men, 1.29 (95% CI: 1.07–1.56) in women and 1.31 (95% CI: 1.11–1.54) in men and women combined.
The ‘traditional’ food pattern, ‘macho’ food pattern and ‘‘sweet tooth’ pattern were not associated with the risk of general obesity. The sex- and multivariate-adjusted prevalence ratios of general obesity across quartiles were 1, 1.33 (0.95–1.86), 1.04 (0.70–1.53) and 1.27 (0.88–1.83) (P for trend=0.482) for ‘traditional’ pattern; 1, 0.79 (0.57–1.08), 0.94 (0.69–1.28) and 1.12 (0.81–1.53) (P for trend=0.413) for ‘macho’ pattern; and 1, 0.77 (0.56–1.05), 0.59 (0.41–0.84) and 0.84 (0.60–1.17) (P for trend=0.202) for ‘sweet tooth’ pattern, respectively (data not shown). An inverse association between ‘sweet tooth’ pattern and the risk of central obesity was observed. The multivariable-adjusted PRs of central obesity across quartiles of ‘sweet tooth’ pattern were 1, 0.90 (0.65–1.26), 0.92 (0.65–1.31) and 0.76 (0.53–1.09) (P for trend=0.164) in men; 1, 0.82 (0.68–0.98), 0.78 (0.64–0.95) and 0.84 (0.69–1.04) (P for trend=0.140) in women; and 1, 0.85 (0.72–1.00), 0.81 (0.68–0.97) and 0.81 (0.67–0.97) (P for trend=0.028) in men and women combined. Neither association between the ‘macho’ pattern nor ‘traditional’ pattern and the risk of central obesity was observed (data not shown).
Stratified analyses showed no interaction in the risk of general obesity/central obesity between the vegetable-rich food pattern and smoking, gender and high energy intake (data not shown). There was an interaction between age and this pattern; in the youngest group, a negative association between intake of vegetable-rich foods and general obesity/central obesity was observed, while in the other age groups the association was positive (Table 6).
High intake of energy (>120% of RNI) was associated with high risk of obesity. In women, the prevalence of obesity in the group with high energy intake was 20.9% compared with 11.0% in the non-high energy intake group. In men, the corresponding figures were 9.5 vs 7.7%, respectively, but this difference was not statistically significant (data not shown). In multivariate analysis combining both genders (model 3 in Table 5), after adjusting for age, gender, smoking, drinking, education, income, occupation, active commuting and leisure time physical activities, the PR of obesity for energy intake above 120% RNI was 1.40 (95% CI: 1.10–1.79), the corresponding PR of central obesity was 1.23 (95% CI: 1.08–1.40).
In this cross-sectional study, we found a positive association between a vegetable-rich food pattern and general obesity and central obesity. A positive association between this food pattern and high intake of energy was also found. Intake of vegetables was highly associated with increased intake of vegetable oil. This is opposite to the findings in Western countries.
Using factor analysis, we identified four food patterns in the sample. The food patterns were found to be associated with anemia in a previous article based on the same sample.15 The vegetable-rich food pattern was characterized by high intake of fruits, vegetables, whole grains, animal foods, milk and eggs. The food items included in this pattern are recommended by the Chinese Nutrition Association. The highest intake of the vegetable-rich pattern corresponded to an intake of vegetables of around 300 g per day, which was about 100 g per day more than the lowest intake group. This intake level meets the WHO recommendation on intake of fruits and vegetables. According to present knowledge and methods in identifying food patterns in Western countries, this pattern would be defined as healthy. Both education and physical activity was positively associated with intake of the vegetable-rich pattern in the sample.
Food weighing plus consecutive individual 3-day food records were used in the present study to assess nutrient intake. Therefore, the method provides a more accurate estimate of individual intake than 24 h food records only. A positive association between intake of vegetable-rich food pattern and intake of energy was found. In general, individuals in the highest quartile of this pattern consumed about 100–200 kcal per day more than the lowest group. In some groups this difference reached 300 kcal per day. Disparity in vegetable oil intake explained part of this difference. Although the mean energy percentage from fat was about 31% which is close to the WHO recommendation of 30%,4 more than half of the sample exceeded this figure in all vegetable-rich food pattern groups. The fact that we found no differences in energy percentage from fat across quartiles of this pattern may suggest that the total energy intake rather than the role of fat in explaining the association is the most important factor.
The average intake of vegetable oil in China was 33 g per day in 2002, while this figure was only 22 g per day in 1992 and 18 g per day in 1982.3 Compared with the national mean, our data showed a higher intake of vegetable oil (42 vs 33 g per day). This increase could be due to the better economic situation in the region, which is ranked as one of the best in China. Eating animal cooking fat was rare in the sample. The high intake of edible fats attracts the concern of health workers and researchers.3, 27 Due to the limitation of the study, we do not have information on saturated fat intake. However, the proportion of saturated fat is probably below 10% of the total energy intake as observed in another study from China.27
Increased intake of the vegetable-rich pattern was found to be positively associated with risk of obesity in the study. The prevalence of obesity among women with highest intake of this pattern was more than double than that of the lowest intake group. The PR of general obesity for comparing Q4 and 1 of vegetable-rich pattern was 2.25 (95% CI: 1.45–3.49) in women and 1.82 (95% CI: 1.05–3.14) in men. High intake of vegetable-rich food was associated with high energy intake, probably due to the high proportion of energy coming from fat which contributes to a high energy density, which is known to affect obesity prevalence.28, 29 In our study, a large proportion of the participants had energy intake more than 120% of RNI. After adjusting for confounding factors, energy intake of more than 120% RNI had a PR of general obesity of 1.40 (95% CI: 1.10–1.79). If the nutrition transition in China continues, it may imply that the proportion of total energy coming from fat will continue to increase, leading to even more obesity in the future.
The strong association between vegetable-rich food pattern and central obesity needs special attention because abdominal adiposity is associated with risk of metabolic syndrome30 and mortality risk in Chinese population.31, 32
The benefits of intake of vegetables are well documented and WHO recommends 400–500 g fruits and vegetables a day.4 Most of the findings on the association between intake of fruits and vegetables and obesity are from Western countries. Literature in the health benefits of intake of vegetables in China is limited. In Shanghai Women's Health study, a food pattern characterized by high vegetable intake shows no reduction in mortality, while a fruit-rich diet was related to lower mortality.16 Our results are partly consistent with these findings. Vegetable cooking methods in China differ from those of the Western countries. In China, the majority of oil is used for cooking vegetables; the usual method is to stir-fry them. In the present study, a positive association between intake of vegetables and vegetable oil was observed. Eating raw vegetable is not common, thus the intake of vegetables is associated with high intake of energy. Stir-fry not only destroys nutrient values of vegetables,33 but also gives rise to a wide variety of mutagenic substances that are carcinogenic.34, 35 In a large population study in Spain, intake of fried foods was found to be associated with both general obesity and central obesity.36 Stir-fry cooking method in the Chinese population may thus partly explain the positive association between a seemingly vegetable-rich food pattern and obesity, which was independent of energy intake in multivariate analysis in our study.
Interaction between age and the vegetable-rich food pattern in regard to risk of general obesity/central obesity was observed in the present study. High intake of the vegetable-rich food pattern was negatively associated with risk of obesity among younger participants. This may be explained by the fact that there is more health awareness among young people, especially young girls. High intake of this food may at the same time mean a healthier lifestyle and weight perceptions that prevent excessive intake. Even among adolescent girls, efforts to be slim are common in China.37, 38 Furthermore, the prevalence of obesity among youngest age group was low (5.5%).
A negative association between the ‘sweet tooth’ pattern and central obesity was found in men and women combined. This association can be explained by the negative association between this pattern and energy intake. However, this association was not significant when men and women were analyzed separately. Further research is needed to interpret this association.
The limitation of the study is that it is cross-sectional. Thus, we cannot conclude about the etiological link between the vegetable-rich food pattern and obesity. However, this limitation does not affect the significance of the study. Even if this association between a vegetable-rich food pattern and obesity is caused by the possibility that the obese people may change their diet toward eating more vegetables, such food pattern may not be so healthy because of the high energy and oil intake. Since daily intake of nutrients is variable, using cross-sectional nutritional surveys, especially 24 h food records, may attenuate the associations between dietary factors and BMI. The strength of the study is that we combined both food frequency questionnaire and food weighing plus consecutive individual 3-day food records. The food frequency questionnaire has been validated and have a good validity.24 The intake of vegetable oil was assessed by weighed method and gave reliable information.
Despite these limitations, our results suggest that eating the recommended amount of vegetables does not decrease the risk of obesity. Thus, when making recommendation on intake of vegetables, the importance of limiting the use of cooking oil as well as the cooking method should be emphasized in the Chinese context. Our findings may also be relevant to other countries in Asia like India, Pakistan and Bangladesh with the same cooking tradition. The prevalence of obesity is high and increasing in these countries.
In conclusion, we found a positive association between intake of vegetable-rich food pattern and obesity. This association can be linked to the high intake of energy due to liberal use of vegetable oil for cooking vegetables. Such vegetable-rich pattern considered to be healthy by the Western concept is not so healthy in China since it may lead to a risk of overconsumption in terms of energy relative to energy needs. When making recommendation on vegetable intake in the Chinese context, vegetable oil consumption and cooking method should also be taken into consideration.
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We thank the participating Regional Centers for Disease Control and Prevention in Jiangsu province, including the Nanjing, Xuzhou, Jiangyin, Taicang, Suining, Jurong, Sihong and Haimen Centres, for their support of the data collection. This work was supported by Jiangsu Provincial Health Bureau. Zumin Shi was supported by a fellowship from Newcastle Institute of Public Health—Hunter Medical Research Institute through the New South Wales Health Department Capacity Building and Infrastructure Grant.
Disclosure/conflict of interest
The authors have no relevant financial interest in this article.
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Cite this article
Shi, Z., Hu, X., Yuan, B. et al. Vegetable-rich food pattern is related to obesity in China. Int J Obes 32, 975–984 (2008). https://doi.org/10.1038/ijo.2008.21
- food pattern
- factor analysis
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British Journal of Nutrition (2018)