PDF(Pubmed)
Abstract：
UNASSIGNED: Many studies define obesity based on body mass index (BMI) and explore its relationship with adult asthma. However, BMI only considers height and weight, ignoring other factors such as body fat, which may have a greater impact on health. We investigated the relationship between body fat distribution and adult asthma using both a cross-sectional study and bidirectional Mendelian randomization (MR) analysis.
UNASSIGNED: Weighted logistic regression models were used to examine the relationship between body fat distribution measurements and adult asthma in the cross-sectional study from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Restricted cubic spline (RCS) curves were employed to explore the dose-response relationship between them. The inverse-variance weighted (IVW) method was used as the main method of MR analysis to explore the causal effect of exposure on outcome.
UNASSIGNED: After adjusting for all covariates, weighted logistic regression analysis indicated that fat mass in the left arm, left leg, right arm, right leg, trunk, and total body is associated with an increased risk of developing adult asthma (p < 0.05). RCS curves showed that all six fat mass indicators exhibit a J-shaped relationship with adult asthma. Forward MR analysis found a causal effect of six fat mass indicators on the increased risk of adult asthma (p < 0.05). However, reverse MR did not reveal any causal effect of adult asthma on these six fat mass indicators (p > 0.05).
UNASSIGNED: Our study supports a positive correlation and a unidirectional causality between body fat distribution measurements and the risk of adult asthma. Further studies are needed to validate our findings.
UNASSIGNED: Weighted logistic regression models were used to examine the relationship between body fat distribution measurements and adult asthma in the cross-sectional study from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Restricted cubic spline (RCS) curves were employed to explore the dose-response relationship between them. The inverse-variance weighted (IVW) method was used as the main method of MR analysis to explore the causal effect of exposure on outcome.
UNASSIGNED: After adjusting for all covariates, weighted logistic regression analysis indicated that fat mass in the left arm, left leg, right arm, right leg, trunk, and total body is associated with an increased risk of developing adult asthma (p < 0.05). RCS curves showed that all six fat mass indicators exhibit a J-shaped relationship with adult asthma. Forward MR analysis found a causal effect of six fat mass indicators on the increased risk of adult asthma (p < 0.05). However, reverse MR did not reveal any causal effect of adult asthma on these six fat mass indicators (p > 0.05).
UNASSIGNED: Our study supports a positive correlation and a unidirectional causality between body fat distribution measurements and the risk of adult asthma. Further studies are needed to validate our findings.
摘要：
■许多研究根据体重指数（BMI）定义肥胖，并探讨其与成人哮喘的关系。然而,BMI只考虑身高和体重,忽略其他因素，如身体脂肪，这可能会对健康产生更大的影响。我们使用横断面研究和双向孟德尔随机化（MR）分析研究了体脂分布与成人哮喘之间的关系。
■在2011-2018年国家健康和营养调查（NHANES）的横断面研究中，使用加权逻辑回归模型来检查体脂分布测量与成人哮喘之间的关系。采用限制性三次样条（RCS）曲线来探索它们之间的剂量反应关系。使用逆方差加权（IVW）方法作为MR分析的主要方法，以探讨暴露对结局的因果影响。
■对所有协变量进行调整后，加权logistic回归分析显示左臂脂肪量，左腿,右臂,右腿,树干,全身与成人哮喘发病风险增加相关(p<0.05)。RCS曲线显示6项脂肪量指标均与成人哮喘呈J型关系。前向MR分析发现六个脂肪量指标对成人哮喘风险增加的因果关系(p<0.05)。然而,反向MR未显示成人哮喘对这6项脂肪量指标的因果效应(p>0.05).
■我们的研究支持体脂分布测量与成人哮喘风险之间的正相关和单向因果关系。需要进一步的研究来验证我们的发现。
■在2011-2018年国家健康和营养调查（NHANES）的横断面研究中，使用加权逻辑回归模型来检查体脂分布测量与成人哮喘之间的关系。采用限制性三次样条（RCS）曲线来探索它们之间的剂量反应关系。使用逆方差加权（IVW）方法作为MR分析的主要方法，以探讨暴露对结局的因果影响。
■对所有协变量进行调整后，加权logistic回归分析显示左臂脂肪量，左腿,右臂,右腿,树干,全身与成人哮喘发病风险增加相关(p<0.05)。RCS曲线显示6项脂肪量指标均与成人哮喘呈J型关系。前向MR分析发现六个脂肪量指标对成人哮喘风险增加的因果关系(p<0.05)。然而,反向MR未显示成人哮喘对这6项脂肪量指标的因果效应(p>0.05).
■我们的研究支持体脂分布测量与成人哮喘风险之间的正相关和单向因果关系。需要进一步的研究来验证我们的发现。
