Changes in the analysis of temporal community dynamics data: a 29-year literature review

Trends in ultra-processed food availability and its association with diet-related non-communicable disease health indicators in the Portuguese population

Broad variations in dietary and physical activity patterns are part of nutritional transition concept. An additional nutritional transition has as main characteristic the change of consumption of processed foods for ultra-processed foods (UPF). This study aims to evaluate trends of UPF availability in Portuguese population and its association with diet-related non-communicable diseases (NCD) health indicators. This ecological study used data from the Household Budget Surveys conducted by the National Statistics Institute each 5 years within a national representative sample of households. The percentage of UPF was calculated based on the total daily amount of food and beverages available per capita (in grams). Data from the years 1990, 1995, 2000 and 2005 were used, which were retrieved from DAFNE-Anemos Software. NCD age-standardised mortality, prevalence and incidence were obtained from the Global Burden of Disease database, for the years 2000, 2005, 2010 and 2015. Between 1990 and 2005, the UPF availability increased from 3·9 % to 13·8 %. Over the years, almost all food and beverages categories increased the UPF availability contribution, mainly noticeable for milk, sugar, cereal and meat products. Positive correlations were observed between UPF availability and digestive diseases both in prevalence (r = 0·062; P = 0·037) and incidence (r = 0·005; P = 0·010) measures. Neoplasms incidence also showed positive correlation with UPF availability (r = 0·002; P = 0·012). Trends in UPF availability in Portugal increased exponentially. At the same time, there is a trend towards a decrease in unprocessed and processed food availability. The Portuguese population should be made aware of the health risks resulting from excessive consumption of UPF.

Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample size

Effective and robust ways to describe, quantify, analyse, and test for change in the structure of biological communities over time are essential if ecological research is to contribute substantively towards understanding and managing responses to ongoing environmental changes. Structural changes reflect population dynamics, changes in biomass and relative abundances of taxa, and colonisation and extinction events observed in samples collected through time. Most previous studies of temporal changes in the multivariate datasets that characterise biological communities are based on short time series that are not amenable to data-hungry methods such as multivariate generalised linear models. Here, we present a roadmap for the analysis of temporal change in short-time-series, multivariate, ecological datasets. We discuss appropriate methods and important considerations for using them such as sample size, assumptions, and statistical power. We illustrate these methods with four case-studies analysed using the R data analysis environment.