Early identification of older individuals at risk of mobility decline with machine learning.

Background: The early identification of individuals at risk of mobility decline can improve targeted strategies of prevention.

Aims: To evaluate the predictive performance of machine learning (ML) algorithms in identifying older individuals at risk of future mobility decline.

Methods: We used data from the SABE Study (Health, Well-being and Aging Study), a representative sample of people aged 60 years and more, living in the Municipality of São Paulo, Brazil.

Cause-specific mortality prediction in older residents of São Paulo, Brazil: a machine learning approach.

Background: Populational ageing has been increasing in a remarkable rate in developing countries. In this scenario, preventive strategies could help to decrease the burden of higher demands for healthcare services. Machine learning algorithms have been increasingly applied for identifying priority candidates for preventive actions, presenting a better predictive performance than traditional parsimonious models.

Blurred lines: racial misclassification in death certificates in Brazil.

Objectives: To analyze the agreement between self-reported race and race reported on death certificates for older (≥ 60 years) residents of São Paulo, Brazil (from 2000 to 2016) and to estimate weights to correct mortality data by race.

Methods: We used data from the Health, Well-Being and Aging Study (SABE) and from Brazil's Mortality Information System. Misclassification was identified by comparing individual self-reported race with the corresponding race on the death certificate (n = 1012).

Reproductive factors and age at natural menopause: A systematic review and meta-analysis.

Objectives: To systematically review the evidence on the association between age at natural menopause (NM) and reproductive factors such as age at menarche, parity and ever use of oral contraceptives.

Study Design: A literature search was carried out in PubMed, Scielo, Scopus and LILACS databases, without restriction of publication year until July 6, 2017. We excluded clinical trials, case-control studies, case reports and studies using statistical methods other than Cox proportional hazard models to assess the factors associated with age at NM.

Multilevel Analysis of the Patterns of Physical-Mental Multimorbidity in General Population of São Paulo Metropolitan Area, Brazil.

Chronic diseases are often comorbid and present a weighty burden for communities in the 21 century. The present investigation depicted patterns of multimorbidity in the general population and examined its association with the individual- and area-level factors in an urban sample of non-elderly adults of Brazil. Data were from the cross-sectional São Paulo Megacity Mental Health Survey, a stratified multistage area probability sampling investigation.

Age at natural menopause and mortality: A survival analysis of elderly residents of São Paulo, Brazil.

Objective: To conduct a survival analysis according to age at natural menopause (NM) in a representative sample of elderly women from the municipality of São Paulo, Brazil.

Study Design: We analyzed data from the Health, Well-Being and Aging study (SABE), a cohort that started in 2000. Mortality data up to September 2016 were obtained by linkage from the Program for Mortality Information of São Paulo (PRO-AIM).

Overachieving Municipalities in Public Health: A Machine-learning Approach.

Background: Identifying successful public health ideas and practices is a difficult challenge towing to the presence of complex baseline characteristics that can affect health outcomes. We propose the use of machine learning algorithms to predict life expectancy at birth, and then compare health-related characteristics of the under- and overachievers (i.e.

Individual and contextual characteristics of indoor and outdoor falls in older residents of São Paulo, Brazil.

Purpose Of The Study: To analyze a representative sample of older individuals of São Paulo, Brazil, according to outdoor fallers, indoor fallers and non-fallers, and to identify biological and socioeconomic (individual and contextual) factors associated with the occurrence and place of falls.

Materials And Methods: A cross-sectional study was conducted using data (n = 1345) from the 2010 wave of the Health, Wellbeing and Aging (SABE) Study, a representative sample of older residents (60 years and older) of São Paulo, Brazil. Multinomial logistic analysis was performed to identify individual factors associated with the occurrence and place of falls, and multilevel multinomial analysis to identify contextual effects (green areas, violence, presence of slums and income inequality).

Application of poultry processing industry waste: a strategy for vegetation growth in degraded soil.

The disposal of poultry processing industry waste into the environment without proper care, can cause contamination. Agricultural monitored application is an alternative for disposal, considering its high amount of organic matter and its potential as a soil fertilizer. This study aimed to evaluate the potential of poultry processing industry waste to improve the conditions of a degraded soil from a desertification hotspot, contributing to leguminous tree seedlings growth.

[Effects of aquatic physical exercise on the kinematic gait pattern in patients with Parkinson's disease: a pilot study].

AIM. To determine the effects of an aquatic-based physical exercise program on gait parameters of patients with Parkinson's disease (PD). PATIENTS AND METHODS.