Department of Biological Sciences, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK.
Nutrients. 2024 Aug 5;16(15):2567. doi: 10.3390/nu16152567.
Over the past decades, China has been undergoing rapid economic growth, which may have significantly influenced the dietary patterns and health status of the Chinese population. Our study aimed to assess the associations of potential macronutrient trajectory patterns with chronic diseases and all-cause mortality using the latent class trajectory model (LCTM) and the longitudinal data of the China Health and Nutrition Survey obtained between 1991 and 2015. A 24-hour diet recall was used to assess the dietary intake. The Poisson regression model was employed to investigate the correlations between trajectory patterns and chronic diseases and all-cause mortality. A total of 8115 participants were included in the final analysis. We explored four and three trajectory patterns for male and female populations, respectively. We found that a decreasing very high-carbohydrate trajectory together with a U-shape protein trajectory was associated with a higher risk of diabetes in the male population (odds ratio (OR): 2.23; 95% confidence interval (CI): 1.31-3.77). A similar pattern for moderate protein intake was also associated with the risk of diabetes in the female population (OR: 1.82; 95% CI: 1.18-2.79). In addition, we show that a decreasing low-carbohydrate trajectory and an increasing high-fat trajectory were associated with a lower risk of all-cause mortality (OR: 0.76; 95% CI: 0.60-0.96) and a higher risk of obesity (OR: 1.24; 95% CI: 1.05-1.47) in males. Our results shed light on some salient nutritional problems in China, particularly the dual challenges of undernutrition and overnutrition.
在过去的几十年里，中国经济飞速增长，这可能极大地影响了中国人口的饮食模式和健康状况。我们的研究旨在使用潜在类别轨迹模型（LCTM）和 1991 年至 2015 年期间获得的中国健康与营养调查的纵向数据，评估潜在的宏量营养素轨迹模式与慢性病和全因死亡率之间的关联。使用 24 小时饮食回忆来评估饮食摄入。采用泊松回归模型研究轨迹模式与慢性病和全因死亡率之间的相关性。共有 8115 名参与者纳入最终分析。我们分别为男性和女性人群探索了四个和三个轨迹模式。我们发现，男性人群中，碳水化合物摄入量持续减少且蛋白质呈 U 型轨迹与糖尿病风险增加相关（比值比（OR）：2.23；95%置信区间（CI）：1.31-3.77）。女性人群中，中等蛋白质摄入量的类似模式也与糖尿病风险相关（OR：1.82；95%CI：1.18-2.79）。此外，我们还表明，男性人群中，碳水化合物摄入量持续减少且脂肪摄入量持续增加与全因死亡率降低（OR：0.76；95%CI：0.60-0.96）和肥胖风险增加（OR：1.24；95%CI：1.05-1.47）相关。我们的研究结果揭示了中国存在的一些突出营养问题，特别是营养不良和营养过剩的双重挑战。
