Faculty of Medicine, University of Coimbra, Rua Larga, 3004-504, Coimbra, Portugal.
Liga Portuguesa Contra o Cancro, Núcleo Regional do Centro, Rua Dr. António José de Almeida, 329 - piso 2 - Sala 56, 3000-045, Coimbra, Portugal.
BMC Womens Health. 2023 Sep 7;23(1):476. doi: 10.1186/s12905-023-02608-5.
This work aims to study the spatio-temporal evolution of a woman's age at menarche in the central region of Portugal. One of the concerns of the study is early or late menarches; thus, we consider percentile regression to build the respective curves as opposed to the more traditional mean regression approach.
We analysed the data from [Formula: see text] women born in the period 1920-1973 who attended a free breast cancer screening program between 1990 and 2019. Distributional regression models inside the package GAMLSS in R were considered. These methods allowed us not only to model the location (mean) of the specific probability distribution of the age at menarche, but also allowed for the scale (variance) parameter of this distribution to depend on covariates. Additionally, a spatial random-effect was considered in order to capture the correlation at the regional level. The obtained clustered spatial effects were analysed to assess geographical differences among the percentiles of the age at menarche by year of birth.
A decreasing trend in the age at menarche (about 1.5 years in 5 decades) and regional differences for all the considered percentiles were found. Women living in the north-central areas of the central region of Portugal tend to have menarche at older ages.
We obtained percentile estimates for the age at menarche by year of birth and region of residence and demonstrated that these two explanatory variables have an impact on the explanation about the decreasing trend in age at a woman's first menstruation.
本研究旨在探讨葡萄牙中部地区女性初潮年龄的时空演变。研究关注的一个问题是初潮过早或过晚；因此，我们考虑使用百分位回归来构建相应的曲线，而不是使用更传统的均值回归方法。
我们分析了 1920 年至 1973 年期间出生的[Formula: see text]名女性的数据，这些女性参加了 1990 年至 2019 年期间的免费乳腺癌筛查计划。我们考虑了 R 软件中 GAMLSS 包内的分布回归模型。这些方法不仅允许我们对特定初潮年龄概率分布的位置（均值）进行建模，还允许该分布的规模（方差）参数依赖于协变量。此外，还考虑了空间随机效应，以捕捉区域水平的相关性。分析获得的聚类空间效应，以评估不同出生年份的初潮百分位数之间的地理差异。
我们发现初潮年龄呈下降趋势（50 年内约 1.5 岁），所有考虑的百分位数都存在区域差异。居住在葡萄牙中部地区中北部地区的女性初潮年龄往往较晚。
我们获得了按出生年份和居住地区划分的初潮年龄百分位数估计值，并证明这两个解释变量对女性初潮年龄下降趋势的解释有影响。
