碳水化合物品質指數與台灣成人體圍之相關性研究

Abstract

目的：已有研究指出碳水化合物與肥胖及代謝疾病風險增加有關，亞洲人口碳水化合物攝入量約佔總熱量50%以上，此種現象更顯現出碳水化合物在亞洲族群中的重要性，然而過去對於碳水化合物與疾病的探討卻很少強調其飲食來源，近年來，新指標―碳水化合物品質指數(carbohydrate quality index, CQI)的出現提供了一個良好的品質評估方式，但目前仍沒有文獻，探討其與不同體圍(上胸圍、中臂圍等)之相關性，因此本研究的目的是評估CQI與體位、體圍之間的關聯。方法：收集336份20-60歲台灣成年人飲食資料，經由本研究室資料庫運算出各營養素總攝取量後，計算CQI分數，再將其分類為五分位、四分位，分析每分類在營養素、食物類別之分布性，並與非飲食資料(6種體圍、腰圍衍生指標及BMI)進行相關性分析及風險評估。結果：CQI的五分位得分範圍Q1為4-9、Q2為10-11、Q3為12-13、Q4為14-15、Q5為16-19分。另外，由FIFFQ測出平均升糖指數為50.0 ± 4.0、膳食纖維為15.9 ± 12.4 g、全榖物碳水化合物/總穀物碳水化合物比值為0.17 ± 0.20、固體碳水化合物/總碳水化合物比值為0.89 ± 0.09、CQI分數為12.0 ± 3.1分。至於體位(圍)分布狀況，則平均體重為65.3 ± 13.4 kg、BMI為23.8 ± 3.7 kg/m2、上胸圍90.4 ± 9.3 cm、中臂圍29.2 ± 8.0 cm、腰圍83.2 ± 10.9 cm、臀圍96.1 ± 8.2 cm、大腿圍54.4 ± 5.4 cm、小腿圍-站姿36.1 ± 3.7 cm、小腿圍-坐姿36.4 ± 3.6 cm、腰臀比0.86 ± 0.09、腰高比0.50 ± 0.08。淨相關結果顯示，在調整干擾因子後，CQI與體重 (r = −0.12, p = 0.04)、BMI (r = −0.15, p = 0.01)、上胸圍 (r = −0.11, p = 0.04)、腰圍 (r = −0.13, p = 0.02)、腰臀比 (r = −0.12, p = 0.03)及腰高比 (r = −0.12, p = 0.03)有顯著負相關。進一步分析提供膳食纖維及碳水化合物的食物來源後，發現全穀類纖維及未精製飯類及穀片類碳水化合物與體位(圍)存在負相關；精製飯類製品、麵類及鍋貼、油煎餅類則與體位(圍)呈現正相關。而在調整干擾因子後的風險分析中發現，隨著CQI的增加，BMI過重 (model 1- p trend< 0.001; model 2- p trend = 0.001)、腰高比過大的風險 (model 1- p trend = 0.001; model 2- p trend = 0.004)有下降的趨勢。結論：更高的碳水化合物品質(CQI)，可能有助於降低過重、肥胖之風險，並且在食物來源上應選擇纖維含量高(主要來自全穀類)，如未精製的飯類(五穀飯)或麥片類，避免攝取鍋貼、油煎餅類等複合性的食品。Objectives: Previous studies have indicated that carbohydrate intake is associated with increased risk of obesity and metabolic diseases. Asian populations have a higher proportion of carbohydrate intake, making the role of carbohydrates even more significant in this group. However, past research on carbohydrates and diseases often overlooked the importance of their dietary sources. In recent years, the emergence of a new index, the Carbohydrate Quality Index (CQI), has provided a good way to assess the quality of carbohydrates. However, there is currently no literature exploring its correlation with different body circumferences (e.g., upper body fat, mid-arm circumference). Therefore, the aim of this study is to assess the association between CQI and body composition, including various body circumferences. Method: We collected dietary data from 336 Taiwanese adults aged 20-60 years. After calculating the nutrient intakes using our research food composition databases, we computed the CQI score. Participants were then classified into quintiles and quartiles based on their CQI scores. We analyzed the distribution of nutrients and food groups within each category and conducted correlation analysis and risk assessment with non-dietary data (including six body circumferences, waist circumference-derived indices, and BMI). Result: The five quartiles of CQI scores were as follows: Q1 ranged from 4 to 9, Q2 ranged from 10 to 11, Q3 ranged from 12 to 13, Q4 ranged from 14 to 15, and Q5 ranged from 16 to 19. Additionally, based on FIFFQ measurements, the mean glycemic index was 50.0 ± 4.0, dietary fiber intake was 15.9 ± 12.4 g, whole grain carbohydrate/total grain carbohydrate ratio was 0.17 ± 0.20, and solid carbohydrate/total carbohydrate ratio was 0.89 ± 0.09. The average CQI score was 12.0 ± 3.1. Regarding body composition distribution, the average weight was 65.3 ± 13.4 kg, BMI was 23.8 ± 3.7 kg/m2, upper chest circumference was 90.4 ± 9.3 cm, mid upper arm circumference was 29.2 ± 8.0 cm, waist circumference was 83.2 ± 10.9 cm, hip circumference was 96.1 ± 8.2 cm, thigh circumference was 54.4 ± 5.4 cm, calf circumference in a standing position was 36.1 ± 3.7 cm, calf circumference in a sitting position was 36.4 ± 3.6 cm, waist-to-hip ratio was 0.86 ± 0.09, and waist-to-height ratio was 0.50 ± 0.08. The adjusted correlations showed significant negative associations between CQI and body weight (r = −0.12, p = 0.04), BMI (r = −0.15, p = 0.01), upper chest circumference (r = −0.11, p = 0.04), waist circumference (r = −0.13, p = 0.02), waist-to-hip ratio (r = −0.12, p = 0.03), and waist-to-height ratio (r = −0.12, p = 0.03). Further analysis of dietary fiber and carbohydrate sources revealed negative correlations between whole grain fiber, unrefined rice, and cereal carbohydrate intake with body composition (circumference), while refined rice products, noodles, and pan-fried pancakes showed positive correlations with body composition (circumference). The risk analysis, after adjusting for confounding factors, indicated a decreasing trend in the risk of overweight BMI (model 1 - p trend< 0.001; model 2 - p trend = 0.001) and increased waist-to-height ratio (model 1 - p trend = 0.001; model 2 - p trend = 0.004) with increasing CQI scores. Conclusion: The study results suggest that a higher Carbohydrate Quality Index (CQI) may help reduce the risk of overweight and obesity. Choosing high-fiber foods (mainly from whole grains) such as unrefined rice (mixed grains rice) or cereal is recommended, while complex foods like pan-fried pancakes should be avoided.