Norris Jean C, van der Laan Mark J, Lane Sylvia, Anderson James N, Block Gladys
Public Health Institute, Oakland, CA 94607-4046, USA.
Health Serv Res. 2003 Dec;38(6 Pt 2):1791-818. doi: 10.1111/j.1475-6773.2003.00203.x.
To examine nonlinearity of determinants of morbidity in the United States
A secondary analysis of data on individuals with dietary data from the Cancer Epidemiology Supplement and National Health Interview Survey (NHIS) 1987, a cross-sectional, stratified random sample of the U.S. population (n = 22,080).
A statistical exploration using additive multiple regression models.
A Morbidity Index (0-30 points), derived from 1987 National Health Interview Survey data, combines number of conditions, hospitalizations, sick days, doctor visits, and degree of disability. Behavioral (health habits) variables were added to multivariate models containing demographic terms, with Morbidity Index and Self-assessed Health outcomes (n = 17,612). Tables and graphs compare models of morbidity with self-assessed health models, with and without behavioral terms. Graphs illustrate curvilinear relationships.
Morbidity and health are associated nonlinearly with age, race, education, and income, as well as alcohol, diet change, vitamin supplement use, body mass index (BMI), marital status/living arrangement, and smoking. Diet change and supplement use, education, income, race/ethnicity, and age relate differently to self-assessed health status than to morbidity. Morbidity is strongly associated with income up to about dollars 15,000 above poverty. Additional income predicts no further reduction in morbidity. Better health is strongly related to both higher income and education. After controlling for income, black race does not predict morbidity, but remains associated with lower self-assessed health.
Good health habits, as captured in these models, are associated with a 10-20-year delay in onset and progression of morbidity.
研究美国发病率决定因素的非线性特征
对来自癌症流行病学补充调查和1987年美国国家健康访谈调查（NHIS）中具有饮食数据的个体数据进行二次分析，这是美国人口的横断面分层随机样本（n = 22,080）。
使用加法多元回归模型进行统计探索。
从1987年美国国家健康访谈调查数据得出的发病率指数（0 - 30分），综合了疾病数量、住院次数、病假天数、看医生次数和残疾程度。行为（健康习惯）变量被添加到包含人口统计学变量的多变量模型中，同时纳入发病率指数和自我评估健康结果（n = 17,612）。表格和图表比较了有和没有行为变量的发病率模型与自我评估健康模型。图表展示了曲线关系。
发病率和健康状况与年龄、种族、教育程度、收入以及饮酒、饮食变化、维生素补充剂使用、体重指数（BMI）、婚姻状况/生活安排和吸烟呈非线性相关。饮食变化和补充剂使用、教育程度、收入、种族/族裔以及年龄与自我评估健康状况的关系和与发病率的关系不同。发病率与高于贫困线约15,000美元的收入密切相关。额外收入并不能预测发病率的进一步降低。更好的健康状况与更高的收入和教育程度都密切相关。在控制收入后，黑人种族并不能预测发病率，但仍与较低的自我评估健康状况相关。
这些模型所体现的良好健康习惯与发病率的发病和进展延迟10 - 年相关。
