Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
Department of Food Science and Biotechnology, Dongguk University, Goyang, South Korea.
BMJ. 2018 Jul 3;362:k2575. doi: 10.1136/bmj.k2575.
To investigate the association of predicted lean body mass, fat mass, and body mass index (BMI) with all cause and cause specific mortality in men.
Prospective cohort study.
Health professionals in the United States PARTICIPANTS: 38 006 men (aged 40-75 years) from the Health Professionals Follow-up Study, followed up for death (1987-2012).
All cause and cause specific mortality.
Using validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey, lean body mass and fat mass were estimated for all participants. During a mean of 21.4 years of follow-up, 12 356 deaths were identified. A J shaped association was consistently observed between BMI and all cause mortality. Multivariable adjusted Cox models including predicted fat mass and lean body mass showed a strong positive monotonic association between predicted fat mass and all cause mortality. Compared with those in the lowest fifth of predicted fat mass, men in the highest fifth had a hazard ratio of 1.35 (95% confidence interval 1.26 to 1.46) for mortality from all causes. In contrast, a U shaped association was found between predicted lean body mass and all cause mortality. Compared with those in the lowest fifth of predicted lean body mass, men in the second to fourth fifths had 8-10% lower risk of mortality from all causes. In the restricted cubic spline models, the risk of all cause mortality was relatively flat until 21 kg of predicted fat mass and increased rapidly afterwards, with a hazard ratio of 1.22 (1.18 to 1.26) per standard deviation. For predicted lean body mass, a large reduction of the risk was seen within the lower range until 56 kg, with a hazard ratio of 0.87 (0.82 to 0.92) per standard deviation, which increased thereafter (P for non-linearity <0.001). For cause specific mortality, men in the highest fifth of predicted fat mass had hazard ratios of 1.67 (1.47 to 1.89) for cardiovascular disease, 1.24 (1.09 to 1.43) for cancer, and 1.26 (0.97 to 1.64) for respiratory disease. On the other hand, a U shaped association was found between predicted lean body mass and mortality from cardiovascular disease and cancer. However, a strong inverse association existed between predicted lean body mass and mortality from respiratory disease (P for trend <0.001).
The shape of the association between BMI and mortality was determined by the relation between two body components (lean body mass and fat mass) and mortality. This finding suggests that the "obesity paradox" controversy may be largely explained by low lean body mass, rather than low fat mass, in the lower range of BMI.
探讨预测瘦体重、体脂肪量和体重指数(BMI)与男性全因死亡率和死因特异性死亡率的相关性。
前瞻性队列研究。
美国健康专业人员。
来自健康专业人员随访研究的 38006 名男性(年龄 40-75 岁),随访至死亡(1987-2012 年)。
全因死亡率和死因特异性死亡率。
使用先前从国家健康和营养检查调查中开发的经过验证的人体测量学预测方程,对所有参与者进行了瘦体重和体脂肪量的估计。在平均 21.4 年的随访期间,共确定了 12356 例死亡。BMI 与全因死亡率之间存在一致的 J 形关联。包括预测体脂肪量和瘦体重的多变量调整 Cox 模型显示,预测体脂肪量与全因死亡率之间存在强烈的正单调关联。与预测体脂肪量最低五分位数的男性相比,预测体脂肪量最高五分位数的男性全因死亡率的风险比为 1.35(95%置信区间 1.26-1.46)。相比之下,预测瘦体重与全因死亡率之间呈 U 形关联。与预测瘦体重最低五分位数的男性相比,第二至第四五分位数的男性全因死亡率的风险降低了 8-10%。在限制立方样条模型中,全因死亡率的风险在预测体脂肪量达到 21 公斤之前相对平稳,之后迅速增加,每标准差的风险比为 1.22(1.18-1.26)。对于预测瘦体重,在较低范围内,风险大幅降低,每标准差的风险比为 0.87(0.82-0.92),此后风险增加(P<0.001 表示非线性)。对于死因特异性死亡率,预测体脂肪量最高五分位数的男性患心血管疾病的风险比为 1.67(1.47-1.89),癌症为 1.24(1.09-1.43),呼吸系统疾病为 1.26(0.97-1.64)。另一方面,预测瘦体重与心血管疾病和癌症死亡率之间呈 U 形关联。然而,预测瘦体重与呼吸系统疾病死亡率之间存在很强的反比关系(P<0.001 表示趋势)。
BMI 与死亡率之间的关联形状由两个身体成分(瘦体重和体脂肪量)与死亡率之间的关系决定。这一发现表明,“肥胖悖论”争议可能主要归因于 BMI 较低范围内的低瘦体重,而不是低体脂肪量。