Multi-Trajectories of Macronutrient Intake and Their Associations with Obesity among Chinese Adults from 1991 to 2018: A Prospective Study.
Xiaofan ZhangZhi-Hong WangWenwen DuChang SuYifei OuyangFeifei HuangXiaofang JiaLi LiJing BaiBing ZhangZhihong WangShufa DuHuijun WangPublished in: Nutrients (2021)
Studies on macronutrient intake and obesity have been inconclusive. This study examined the associations between multi-trajectories of macronutrients and the risk of obesity in China. We used data from 7914 adults who participated in the China Health and Nutrition Survey at least three times from 1991 to 2018. We collected detailed dietary data by conducting three 24 h dietary recalls and weighing foods and condiments in household inventories. We identified multi-trajectories using group-based multi-trajectory models and examined their associations with the risk of obesity with multiple Cox regression models. We found four multi-trajectories in rural areas: balanced macronutrient intake (BM), moderate protein, increasing low fat, and decreasing high carbohydrate (MP&ILF&DHC); decreasing moderate protein, decreasing high fat, and increasing moderate carbohydrate (DMP&DHF&IMC); increasing moderate protein, increasing high fat, and decreasing low carbohydrate (IMP&IHF&DLC)-35.1%, 21.3%, 20.1%, and 23.5% of our rural participant population, respectively. Compared with the BM trajectory, the hazard ratios of obesity in the DMP&DHF&IMC and the IMP&IHF&DLC groups were 0.50 (95% confidence interval (CI): 0.27-0.95) and 0.48 (95% CI: 0.28-0.83), respectively, in rural participants. Relatively low carbohydrate and high fat intakes with complementary dynamic trends are associated with a lower risk of obesity in rural Chinese adults.
Keyphrases
- insulin resistance
- weight gain
- metabolic syndrome
- weight loss
- high fat diet induced
- type diabetes
- south africa
- depressive symptoms
- high intensity
- adipose tissue
- body mass index
- healthcare
- public health
- mental health
- physical activity
- skeletal muscle
- small molecule
- machine learning
- binding protein
- big data
- deep learning
- social media
- climate change
- data analysis
- fatty acid