低生育率可能是全球卵巢癌的一个重要决定因素：来自 182 个国家的横断面数据的生态学分析。
Low fertility may be a significant determinant of ovarian cancer worldwide: an ecological analysis of cross- sectional data from 182 countries.
机构信息
Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia.
Institute of Evolutionary Medicine, University of Zürich, 8057, Zurich, Switzerland.
出版信息
J Ovarian Res. 2018 Aug 16;11(1):68. doi: 10.1186/s13048-018-0441-9.
BACKGROUND
Ageing, socioeconomic level, obesity, fertility, relaxed natural selection and urbanization have been postulated as the risk factors of ovarian cancer (OC56). We sought to identify which factor plays the most significant role in predicting OC56 incidence rate worldwide.
METHODS
Bivariate correlation analysis was performed to assess the relationships between country-specific estimates of ageing (measured by life expectancy), GDP PPP (Purchasing power parity), obesity prevalence, fertility (indexed by the crude birth rate), opportunity for natural selection (I) and urbanization. Partial correlation was used to compare contribution of different variables. Fisher A-to-Z was used to compare the correlation coefficients. Multiple linear regression (Enter and Stepwise) was conducted to identify significant determinants of OC56 incidence. ANOVA with post hoc Bonferroni analysis was performed to compare differences between the means of OC56 incidence rate and residuals of OC56 standardised on fertility and GDP respectively between the six WHO regions.
RESULTS
Bivariate analyses revealed that OC56 was significantly and strongly correlated to ageing, GDP, obesity, low fertility, I and urbanization. However, partial correlation analysis identified that fertility and ageing were the only variables that had a significant correlation to OC56 incidence when the other five variables were kept statistically constant. Fisher A-to-Z revealed that OC56 had a significantly stronger correlation to low fertility than to ageing. Stepwise linear regression analysis only identified fertility as the significant predictor of OC56. ANOVA showed that, between the six WHO regions, multiple mean differences of OC56 incidence were significant, but all disappeared when the contributing effect of fertility on OC56 incidence rate was removed.
CONCLUSIONS
Low fertility may be the most significant determining predictor of OC56 incidence worldwide.
背景
衰老、社会经济水平、肥胖、生育力、自然选择放松和城市化被认为是卵巢癌（OC56）的危险因素。我们试图确定哪个因素对全球范围内预测 OC56 发病率的作用最大。
方法
采用双变量相关分析评估了国家特定的衰老（用预期寿命衡量）、国内生产总值购买力平价（PPP）、肥胖流行率、生育力（用粗出生率衡量）、自然选择机会（I）和城市化之间的关系。采用偏相关比较不同变量的贡献。Fisher A-to-Z 用于比较相关系数。采用多元线性回归（Enter 和 Stepwise）确定 OC56 发病率的显著决定因素。采用方差分析（ANOVA）和事后 Bonferroni 分析比较六个世界卫生组织（WHO）区域之间 OC56 发病率的平均值和 OC56 标准化生育率和 GDP 残差之间的差异。
结果
双变量分析表明，OC56 与衰老、国内生产总值、肥胖、低生育力、I 和城市化显著相关且呈强相关。然而，偏相关分析确定，当其他五个变量保持统计学不变时，生育力和衰老才是与 OC56 发病率具有显著相关性的唯一变量。Fisher A-to-Z 显示，OC56 与低生育力的相关性明显强于与衰老的相关性。逐步线性回归分析仅确定了生育力是 OC56 的显著预测因子。ANOVA 显示，在六个 WHO 区域之间，OC56 发病率的多个平均值差异显著，但当生育力对 OC56 发病率的影响去除后，所有差异均消失。
结论
低生育力可能是全球范围内预测 OC56 发病率的最重要决定因素。
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