OBJECTIVE
To identify factors in childhood which might influence the development of obesity in adulthood.


BACKGROUND
The prevalence of obesity is increasing in the UK and other developed countries, in adults and children. The adverse health consequences of adult obesity are well documented, but are less certain for childhood obesity. An association between fatness in adolescence and undesirable socio-economic consequences, such as lower educational attainment and income, has been observed, particularly for women. Childhood factors implicated in the development of adult obesity therefore have far-reaching implications for costs to the health-services and economy.


SEARCH STRATEGY
In order to identify relevant studies, electronic databases--Medline, Embase, CAB abstracts, Psyclit and Sport Discus-were searched from the start date of the database to Spring 1998. The general search structure for electronic databases was (childhood or synonyms) AND (fatness or synonyms) AND (longitudinal or synonyms). Further studies were identified by citations in retrieved papers and by consultation with experts.


INCLUSION CRITERIA
Longitudinal observational studies of healthy children which included measurement of a risk factor in childhood (<18 y), and outcome measure at least 1 y later. Any measure of fatness, leanness or change in fatness or leanness was accepted. Measures of fat distribution were not included. Only studies with participants from an industrialized country were considered, and those concerning minority or special groups, e.g. Pima Indians or children born preterm, were excluded.


FINDINGS
Risk factors for obesity included parental fatness, social factors, birth weight, timing or rate of maturation, physical activity, dietary factors and other behavioural or psychological factors. Offspring of obese parent(s) were consistently seen to be at increased risk of fatness, although few studies have looked at this relationship over longer periods of childhood and into adulthood. The relative contributions of genes and inherited lifestyle factors to the parent-child fatness association remain largely unknown. No clear relationship is reported between socio-economic status (SES) in early life and childhood fatness. However, a strong consistent relationship is observed between low SES in early life and increased fatness in adulthood. Studies investigating SES were generally large but very few considered confounding by parental fatness. Women who change social class (social mobility) show the prevalence of obesity of the class they join, an association which is not present in men. The influence of other social factors such as family size, number of parents at home and childcare have been little researched. There is good evidence from large and reasonably long-term studies for an apparently clear relationship for increased fatness with higher birth weight, but in studies which attempted to address potential confounding by gestational age, parental fatness, or social group, the relationship was less consistent. The relationship between earlier maturation and greater subsequent fatness was investigated in predominantly smaller, but also a few large studies. Again, this relationship appeared to be consistent, but in general, the studies had not investigated whether there was confounding by other factors, including parental fatness, SES, earlier fatness in childhood, or dietary or activity behaviours. Studies investigating the role of diet or activity were generally small, and included diverse methods of risk factor measurement. There was almost no evidence for an influence of activity in infancy on later fatness, and inconsistent but suggestive evidence for a protective effect of activity in childhood on later fatness. No clear evidence for an effect of infant feeding on later fatness emerged, but follow-up to adulthood was rare, with only one study measuring fatness after 7y. Studies investigating diet in childhood were limited and inconc

Childhood predictors of adult obesity: a systematic review.

This article describes the many capabilities offered by the TraMineR toolbox for categorical sequence data. It focuses more specifically on the analysis and rendering of state sequences. Addressed features include the description of sets of sequences by means of transversal aggregated views, the computation of longitudinal characteristics of individual sequences and the measure of pairwise dissimilarities. Special emphasis is put on the multiple ways of visualizing sequences. The core element of the package is the state se- quence object in which we store the set of sequences together with attributes such as the alphabet, state labels and the color palette. The functions can then easily retrieve this information to ensure presentation homogeneity across all printed and graphical displays. The article also demonstrates how TraMineR’s outcomes give access to advanced analyses such as clustering and statistical modeling of sequence data.

/pdf/analyzing-and-visualizing-state-sequences-in-r-with-traminer-42gncygwun.pdf

Analyzing and Visualizing State Sequences in R with TraMineR

https://orbit.dtu.dk/files/146992779/1_s2.0_S0092867418303751_main.pdf

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal

Comparing text strings in terms of distance functions is a common and fundamental task in many statistical text-processing applications. Thus far, string distance functionality has been somewhat scattered around R and its extension packages, leaving users with inconistent interfaces and encoding handling. The stringdist package was designed to offer a low-level interface to several popular string distance algorithms which have been re-implemented in C for this purpose. The package offers distances based on counting q-grams, edit-based distances, and some lesser known heuristic distance functions. Based on this functionality, the package also offers inexact matching equivalents of R’s native exact matching functions match and %in%.

/pdf/the-stringdist-package-for-approximate-string-matching-4ceetl6ufv.pdf

The stringdist Package for Approximate String Matching

In 1990, the US had the sixth highest female labor participation rate among 22 OECD countries. By 2010 its rank had fallen to seventeenth. We find that the expansion of “family-friendly” p...

https://pubs.aeaweb.org/doi/pdfplus/10.1257/aer.103.3.251

Female Labor Supply: Why Is the United States Falling Behind? †

In this article we define a methodological framework for analyzing the relationship between state sequences and covariates. Inspired by the ANOVA principles, our approach looks at how the covariates explain the discrepancy of the sequences. We use the pairwise dissimilarities between sequences to determine the discrepancy which makes it then possible to develop a series of statistical-significancebased analysis tools. We introduce generalized simple and multi-factor discrepancy-based methods to test for dierences between groups, a pseudo R 2 for measuring the strength of sequence‐covariate associations, a generalized Levene statistic for testing dierences in the within-group discrepancies, as well as tools and plots for studying the evolution of the dierences along the timeframe and a regression tree method for discovering the most significant discriminant covariates and their interactions. In addition, we extend all methods to account for case weights. The scope of the proposed methodological framework is illustrated using a real-world sequence dataset.

/pdf/discrepancy-analysis-of-state-sequences-1duhftaeg5.pdf

Discrepancy Analysis of State Sequences

Factors of change and cumulative factors in self-rated health trajectories: A systematic review

This paper is concerned with the summarization of a set of categorical sequences. More specifically, the problem studied is the determination of the smallest possible number of representative sequences that ensure a given coverage of the whole set, i.e. that have together a given percentage of sequences in their neighbourhood. The proposed heuristic for extracting the representative subset requires as main arguments a pairwise distance matrix, a representativeness criterion and a distance threshold under which two sequences are considered as redundant or, identically, in the neighborhood of each other. It first builds a list of candidates using a representativeness score and then eliminates redundancy. We propose also a visualization tool for rendering the results and quality measures for evaluating them. The proposed tools have been implemented in our TraMineR R package for mining and visualizing sequence data and we demonstrate their efficiency on a real world example from social sciences. The methods are nonetheless by no way limited to social science data and should prove useful in many other domains.

/pdf/extracting-and-rendering-representative-sequences-1tikgnncfb.pdf

Extracting and Rendering Representative Sequences

We explore how recent data mining-based tools developed in domains such as biomedicine or text mining for extracting interesting knowledge from sequence data could be applied to personal life course data. We focus on two types of approaches: 'survival' trees that attempt to partition the data into homogeneous groups regarding their survival characteristics, i.e., the duration until a given event occurs and the mining of typical discriminating episodes. We show how these approaches may fruitfully complement the outcome of more classical event history analyses and single out some specific issues raised by their application to socio-demographic data.

/pdf/mining-event-histories-a-social-science-perspective-3fwgsqmq2e.pdf

Alexis Gabadinho

Papers

Analyzing and Visualizing State Sequences in R with TraMineR

Discrepancy Analysis of State Sequences

Factors of change and cumulative factors in self-rated health trajectories: A systematic review

Extracting and Rendering Representative Sequences

Mining event histories: a social science perspective