ABSTRACT

Body mass index (BMI) is commonly used as a proxy for adiposity in epidemiological and public health studies. However, BMI may suffer from issues of misreporting and, because it fluctuates over the life course, its association with morbidities such as diabetes is difficult to measure. We examined the associations between actual BMI, genetic propensity for high BMI, and diabetes to better understand whether a BMI polygenic score (PGS) explained more variation in diabetes than self-reported BMI. We used a sample of non-Hispanic white adults from the longitudinal Health and Retirement Study (1992–2016). Structural equation models were used to determine how much variation in BMI could be explained by a BMI PGS. Then, we used logistic regression models (n = 12,086) to study prevalent diabetes at baseline and Cox regression models (n = 11,129) to examine incident diabetes with up to 24 years of follow-up. We observed that while both actual BMI and the BMI PGS were significantly associated with diabetes, actual BMI had a stronger association than its genetic counterpart and resulted in better model performance. Moreover, actual BMI explained more variation in baseline and incident diabetes than its genetic counterpart which may suggest that actual BMI captures more than just adiposity as intended.

摘要

体重指数 (BMI) 通常用作流行病学和公共卫生研究中肥胖的代表。然而，BMI 可能存在误报问题，并且由于它在整个生命过程中波动，它与糖尿病等疾病的关联很难衡量。我们检查了实际 BMI、高 BMI 的遗传倾向和糖尿病之间的关联，以更好地了解 BMI 多基因评分 (PGS) 是否比自我报告的 BMI 解释了更多的糖尿病变异。我们使用了纵向健康和退休研究（1992-2016）中的非西班牙裔白人成年人样本。结构方程模型用于确定 BMI PGS 可以解释多少变化。然后，我们使用逻辑回归模型 (n = 12,086) 研究基线时的普遍糖尿病，并使用 Cox 回归模型 (n = 11, 129) 对糖尿病事件进行长达 24 年的随访检查。我们观察到，虽然实际 BMI 和 BMI PGS 都与糖尿病显着相关，但实际 BMI 比其遗传对应物具有更强的相关性，并导致更好的模型性能。此外，与遗传对应物相比，实际 BMI 解释了基线和糖尿病发病率的更多变化，这可能表明实际 BMI 捕获的不仅仅是预期的肥胖。