Jiang Tao, Gilthorpe Mark S, Shiely Frances, Harrington Janas M, Perry Ivan J, Kelleher Cecily C, Tu Yu-Kang
Division of Epidemiology & Biostatistics, School of Medicine, University of Leeds, Room 8,49, Level 8, Worsley Building, Leeds LS2 9JT, UK.
BMC Public Health. 2013 Sep 25;13:889. doi: 10.1186/1471-2458-13-889.
Obesity is a growing problem worldwide and can often result in a variety of negative health outcomes. In this study we aim to apply partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI).
Using PLS we will obtain gender specific linear effects of age, period and cohort on obesity. We also explore and model nonlinear relationships of BMI with age, period and cohort. We analysed the results from 7,796 men and 10,220 women collected through the SLAN (Surveys of Lifestyle, attitudes and Nutrition) in Ireland in the years 1998, 2002 and 2007.
PLS analysis revealed a positive period effect over the years. Additionally, men born later tended to have lower BMI (-0.026 kg · m(-2) yr(-1), 95% CI: -0.030 to -0.024) and older men had in general higher BMI (0.029 kg · m(-2) yr(-1), 95% CI: 0.026 to 0.033). Similarly for women, those born later had lower BMI (-0.025 kg · m(-2) yr(-1), 95% CI: -0.029 to -0.022) and older women in general had higher BMI (0.029 kg · m(-2) yr(-1), 95% CI: 0.025 to 0.033). Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort.
We notice a generally positive age and period effect but a slightly negative cohort effect. Knowing this, we have a better understanding of the different risk groups which allows for effective public intervention measures to be designed and targeted for these specific population subgroups.
肥胖是一个在全球范围内日益严重的问题，常常会导致各种负面的健康结果。在本研究中，我们旨在应用偏最小二乘法（PLS）来估计年龄、时期和队列对通过体重指数（BMI）衡量的肥胖趋势的单独影响。
使用PLS，我们将获得年龄、时期和队列对肥胖的性别特异性线性影响。我们还将探索并建立BMI与年龄、时期和队列之间的非线性关系。我们分析了1998年、2002年和2007年通过爱尔兰的SLAN（生活方式、态度和营养调查）收集的7796名男性和10220名女性的结果。
PLS分析显示这些年存在正向的时期效应。此外，出生较晚的男性往往BMI较低（-0.026 kg·m⁻²·年⁻¹，95%置信区间：-0.030至-0.024），而年龄较大的男性总体上BMI较高（0.029 kg·m⁻²·年⁻¹，95%置信区间：0.026至0.033）。同样对于女性，出生较晚的女性BMI较低（-0.025 kg·m⁻²·年⁻¹，95%置信区间：-0.029至-0.022），年龄较大的女性总体上BMI较高（0.029 kg·m⁻²·年⁻¹，95%置信区间：0.025至0.033）。非线性分析表明，BMI与年龄存在显著的曲线关系，与出生队列的关系则较弱。
我们注意到年龄和时期总体上有正向效应，但队列效应略有负面。了解这些情况后，我们能更好地理解不同的风险群体，从而能够设计有效的公共干预措施并针对这些特定人群亚组。
