Abstract:To explore the sIgG antibody levels in 90 food and the correlation between common food sIgE in serum in patients with allergic respiratory diseases.Methods 178 patients with allergic respiratory diseases were detected 90 food sIgG and common food sIgE in the first affiliated hospital of Guangzhou Medical University from 2011.06-2014.10. Analyses were performed by using SPSS 19.0. Results The three leading positive food were milk and dairy products(42.63%), crustaceans (24.72%), meats and eggs (22.58%), the lowest were fruits (5.7%) and cereals (5.93%). The highest positive rate in food was eggs (70.79%), followed by white soft cheese (69.10%) and cow's milk (66.85%). The positive rate of sIgG antibodies in different age groups was varied in different categories and kinds of food. In 0-3 years old group, the highest positive rate of food item was milk and dairy products, and the positive rate gradually reduced as the age growing. On the contrary, the positive rate of crustacean showed rising trend after the age of 4. In the following categories of food , the positive rate of sIgG in male was higher than female:fruits, milk and dairy products in age group 0-3 years; cereals, fruits, meats and eggs in age group 4-6 years; crustacean in age group 7-16 years; legumes, vegetables, milk and dairy products, fishes, crustacean in age group ≥17 years. In the following categories of food, the positive rate of sIgG in female was higher than male:the other food in age group 4-6 years; milk and dairy products in age group 7-16 years. The above differences had statistical significance. A lot of food sIgG antibody levels were highly associated, mainly in milk and dairy products, fruits and vegetables. There were correlation between egg sIgG and albumen sIgE, milk and egg sIgG and sIgE(rs=0.518,0.438,0.392,P<0.05).Conclusion There was certain distribution characteristics of food sIgG antibodies positive rate in different age and gender, food sIgG detection could be a supplement to food sIgE. Clinical diagnosis should be combined with gender, dietary habits and other factors to make guidance more reasonable for patients' diet adjustment.