[Current situation of food consumption and its correlation with climate among rural residents in China, 2000-2012].

OBJECTIVE

To study the differences in food consumption among rural residents in various regions of China, and to analyze the climatic factors that affect the food consumption of rural residents.

METHODS

Based on the consumption data of 13 kinds of food of rural residents including wheat, rice, other grain, fresh vegetables, pork, beef and mutton, poultry, eggs and related products, milk and related products, aquatic products, edible oil, sugar and liquor collected from the China Statistical Yearbook and China's Economic and social data research platform during 2000 to 2012, cluster analysis was conducted to partition the dietary structure and compare the differences in food consumption in each geographical area. Selecting the average temperature, annual temperature difference, daily temperature difference, average air pressure, average daily precipitation, average wind speed, average relative humidity, average sunshine duration, 8 climatic factors as independent variables from the "Dataset of daily surface observations values in individual years( 1981-2010) in China "and "Dataset of annual values of climate data from Chinese surface stations for global exchange " released by China Meteorological Data Service Center to establish a multivariate linear regression model to study the correlation between food consumption and climate.

RESULTS

The geographical partition of dietary structure of rural residents in China was as follows: Beijing-Tianjin region, northeast region, upstream and downstream parts of the Yellow River region, southeast coastal area, the part middle and lower reaches of the Yangtze River region, Lingnan area, southwest region, Inner Mongolia, Tibet, Qing-Xin( Qinghai and Xinjiang)region. In the comparison of annual per capita food consumption in various regions: the consumption of eggs and related products( 12. 96 kg) and edible oil( 10. 18 kg) in BeijingTianjin region, vegetable( 128. 20 kg) in northeastern region, aquatic products( 15. 81 kg) and liquor( 19. 04 kg) in the southeastern coastal areas, rice( 189. 36 kg) and poultry( 10. 17 kg) in Lingnan area, pork( 26. 46 kg) in southwest China, other food( 126. 31 kg), milk and related products( 32. 38 kg), beef and mutton( 12. 87 kg) and sugar( 2. 65 kg) in Tibet, and wheat( 184. 63 kg) in Qingxin region was the highest in China. While the consumption of sugar( 0. 79 kg) in northeastern region, other food( 10. 64 kg) in the southeastern coastal areas, wheat( 0. 60 kg) and milk and related products( 0. 33 kg) in Lingnan area, beef and mutton( 0. 43 kg) in southwest China, edible oil( 4. 21 kg) in Inner Mongolia, vegetables( 19. 21 kg), eggs and related products( 0. 60 kg), aquatic products( 0. 01 kg), pork( 2. 23 kg) and poultry( 0. 03 kg) in Tibet, and rice( 13. 00 kg)and liquor( 2. 25 kg) in Qing-Xin regions was the lowest in China. The result of multiple linear regression analysis of climate and food consumption showed that consumption of wheat in staple foods was negatively correlated with average daily precipitation( P < 0. 01, Adj. R2= 0. 632); and there was a positive correlation between rice consumption and average daily precipitation, and a negative correlation with average temperature and daily temperature difference( P < 0. 01, Adj. R2= 0. 839). There was a positive correlation between vegetable consumption and annual temperature difference, and negative correlation with average sunshine duration( P < 0. 01, Adj. R2= 0. 450). The pork consumption was negatively correlated with the average sunshine duration( P < 0. 01, Adj. R2= 0. 386).

CONCLUSION

The dietary structure of rural residents in China can bedivided into 10 kinds of geographical partitions. Average daily precipitation is negatively and positively correlated with consumption of wheat and rice, respectively. Average sunshine duration has negative impact on vegetable and pork consumption. Average temperature and daily temperature difference are negatively correlated with rice consumption. And annual temperature difference has positive impact on vegetable consumption.