They are mainly focused on health with the aim of characterizing the behavior of variables such as weight, height, and BMI and establishing their relationship with some diseases. Studies to create such tables have been carried out in the school population. The present article is the result of the first phase of a research project consisting of four parts: i systematic review of basic body measurements in children and adolescents aged 2 to 18 years; ii characterization of the morphological profile of this population in Huila, Colombia; iii determination of the growth and development rate of this population; and iv performing a bivariate analysis of the body dimensions of reference for this age range and the sport practiced.
Therefore, the objectives of this review were to identify and synthesize the original research studies on basic body measurements in children and adolescents aged 2 to 18 years, published between and Articles published in English, Spanish and Portuguese were considered. Then, the publication date limit years was specified, and the citations and patents option was unchecked, resulting in studies.
The information regarding the search characteristics is described in Table 1. Table 1 Search characteristics. On the other hand, monographs, dissertations, theses, books, systematic literature reviews or opinions of specialists, such as essays, were excluded. Studies in children and adolescents with special characteristics, syndromes or diseases were also excluded, as well as those that did not describe the age and sex of the population or had a different objective than the one of interest for this review.
Studies that could potentially be analyzed were selected by reading their titles and abstracts. Once the relevant ones were selected, they were examined by reading the full text.
Source: Own elaboration. Figure 1 Flow chart for article selection. To extract data, an application was developed using the relevant information in a Microsoft Excel sheet; this was done by a single investigator. The overall methodological quality of the studies was measured using the critical review forms for quantitative studies, 18 which consider 13 general topics. Based on such topics, 16 items were established form of citation; purposes; rationale; study design; knowledge of the topic and problem; variables; ethical considerations; sampling bias; measurement bias; intervention bias; description of the sample; justification of the sample size; reliability and validity; results; drop-outs; and conclusions and limitations.
Said items were assessed through two response options: meets or does not meet the criteria; the options were assigned a score, 1 or 2, respectively, and if the item was not applicable, NA was checked.
The results of this approximation were expressed as a percentage calculated for each study 19 and the final quality index was the sum of the results in each article divided by the total number of items. The initial search yielded 6 results: 5 from PubMed, from Google Scholar and from Epistemonikos; the latter were obtained through a manual search. Once the studies were analyzed, 6 were excluded after reviewing their title and abstract.
Of the remaining 30 articles, 12 were excluded because they did not meet the inclusion criteria. Finally, 18 articles were included for qualitative analysis Figure 1. The 18 studies included were cross-sectional; in addition, 2 of them were complementary and their methodology had been described in previous studies. The studies totaled participants, 14 in Colombian publications and in international publications Table 2.
No study showed significant sex differences regarding the number of participants. The age range of participants in most of the included studies ranged from 2 to 18 years. Only international studies reported data for each year of age, whereas those carried out in Colombia did it by age group up to 2 years per group ; moreover, the age range of the Colombian population ranged from 5 to 18 years. Table 2 Main characteristics of the included studies. It was observed that the studies were conducted to create anthropometric reference tables to measure the development and physical growth of children and adolescents, some focused on health excess weight, adiposity, etc.
The results are presented in Table 2. The 50 P50 or median percentile was used as a reference to describe the behavior of height, weight, and BMI in the reviewed studies.
Male sex: In Colombia, this population showed a variety in height, especially at the age of At the international level, by the age of 17, it was found that the highest P50 for height in America was in the USA In Europe, the highest P50 was found in Greece Table 3 Median height cm by sex in the reviewed literature.
Female sex: The median height of women in Colombia was At the international level, by the age of 17, it was found that the highest P50 for height in America was in the USA cm , 16 followed by Brazil Male sex: In Colombia, this population showed a variety in weight, especially at the age of Finally, the median weight in the country was At the international level, by the age of 17, it was found that the highest p50 for weight in America was in the USA Table 4 Median weight kg by sex in the reviewed literature.
Female sex: The median weight of Colombian women was 55kg at the age of 17 years. At the international level, by the age of 17, it was found that the highest P50 for weight in America was in the USA Male sex: In Colombia, it was not possible to obtain the median national BMI because the studies conducted in Medellin 23 and Argelia 24 did not report these data.
In Europe, the highest P50 was found in Germany According to the findings, the highest median height was found in European countries, 37 reaching differences of up to 15cm in males and The difference in height among the 3 continents was between 10cm and 15cm in males and 6.
Similarly, in males, height increases of up to 10cm were observed between the ages of 15 and ; in females, this difference was up to 4cm. A decrease in median height was also observed at the end of the 18th year of age, especially in Asian regions such as Korea 33 and Hong Kong 35 0.
Weight differences were up to 12kg in men and up to 3kg in women. These variations depended on age 16 , 27 , 32 and were greater in males. At the country level, for the male sex, Greece 27 had the highest median height, while the USA 16 had the highest median BMI and weight. In contrast, in Peru, 26 the lowest median height and weight were found in both sexes, while the lowest P50 for BMI were in Argentina 26 for men and Hong Kong 35 for women.
Based on this information, the scope of this type of morphological studies in the development of health and anthropometric issues is evident, especially in the field of sports, as differences in the variables analyzed height, weight, and BMI at certain ages are described, which allow identifying and creating the profile of basic body measurements at an historical moment.
For example, in Asia, an increase of 1. Furthermore, an increase of 0. Concerning weight, the comparison of these same studies 35 , 38 showed an increase of gr in males and a decrease of gr in females over a period of 15 years. The tallest average height of women in the world can be found in Latvia and Netherlands, in both of which the average height is more than 5 feet 6 inches.
But most of the surveys result in the above-described height for women being ideal, at least in the eyes of most men, and you fall barely under this category. Moreover, there are hundreds of models of this height, and this is a height that is often praised. As it is sometimes more about the personality than about the height. Hopefully, this article was helpful in answering some of your height-related questions. As they stand, the findings listed in the Abstract and Introduction would hardly justify publication.
They are tidbits, engaging the curiosity of readers and showing off the scope of the assembled data, but not settling open questions of theoretical interest. Everyone knows that nutritional status across the world has not converged to some common level. The paper has a number of strengths that do not come across in the Abstract. They have systematically searched for sampled measured data rather than self-reports; they have collected a large amount of data on women and have data from countries.
This means that the work is a substantial step up from other studies of trends in height. I think the paper is too short. Please explain the BMI analysis referred to in Figure 6. The main text and figures are valuable. The pages of Supplementary Information, in contrast, do not belong in the publication. The lists of NCD Risk Factor Collaborators and the long table of data sources belong on a Project Website with hyperlink pointers in the article, or perhaps as a separate appendix hosted in the journal.
Some details of the validation study might reasonably belong an appendix, but the validation study as it stands is not entirely convincing. The uncertainties of importance relate to the out-of-sample-range extrapolations to timeframes and countries without datasets, whereas the cross-validation mainly measures success at within-sample-range interpolations within sets of times and cases where relevant datasets are available.
What is the specification of the Bayesian model in use here for filling in missing data and extrapolating back into the past and outward to nations with limited sets of direct measurements?
The paper directs readers to Danaei et al. Heights pose many different issues, particularly when only 70 of the countries have data for cohorts born before and 22 of countries for which estimates are generated have no data at all. Presumably, the model here incorporates features needed for application to heights, but nothing is spelled out. Toward the end of this review is a list of some of the model features that would seem important to describe.
In what form and under what arrangements are these data to be made available to the wider community of researchers? Is the creation of a data resource for heights along the lines of the Human Mortality Database and the Human Fertility Database underway? This question arises not only with regard to compliance with data-sharing requirements of eLife and other top journals, but also with regard to the wide range of scientific questions that could be addressed with these data.
What is already treated in this paper hardly scratches the surface. D variability in standard deviations and its relationship to the homogeneity or heterogeneity of each measured population;. G sample information with regard to measurement scales in centimeters or inches, with or without shoes or unknown , degree of rounding, etc.
As the reviewer has correctly pointed out, with countries, this figure would be best suited to a dynamic visualisation. We would be happy to finalise the specifics with the Editors and the production team. We have done as suggested for Abstract. The Introduction contains only a concise summary of current literature in the field, and the contribution of the paper; to the best of our ability, it is entirely factual.
We would be happy to provide more information in this paper if it is deemed informative to repeat the materials here. We request to keep the list of data sources because it is increasingly the norm in presenting global health estimates to state the data sources used in the analysis soon to become a part of reporting guidelines.
Therefore, we request to be allowed to include the full list of authors especially given that eLife is published online.
The validation analysis is entirely out of sample validation. We removed data for specific countries i. NCD-RisC is a data pooling analysis that uses secondary data. Some of our data are from public sources and we would be happy to point others to the relevant sites for these sources, or provide the data.
Other sources are provided either by specific scientists or national health agencies. For these, we will be happy to provide contact information of the data provider for requests to be made.
We do not model individual height, for which non-normality may be an issue. Rather our analysis models mean height of the population, and its distribution across countries and health surveys. We also considered and have used elsewhere Stevens et al, ; Finucane et al. The results of the current analysis were not sensitive to choice, confirming that the normal prior appropriately described the distribution of mean height.
As mentioned above, the analysis and modelling are of the mean height, so the only relevant standard deviation is the standard error of the sample means.
Standard errors were computed together with sample means when NCD-RisC members re-analysed each data source.
The standard deviations of each data source study are reflected in the standard errors used in specifying the distribution of the sample means. The covariance between different birth cohorts i. Formally, the auto-regressive model induces a particular precision inverse covariance structure for cohorts within a country and the induced covariance is therefore the inverse of that.
The linear and non-linear components of this auto-regressive structure, as well as its intercept, are modelled hierarchically so the effects for each country borrow from the region to the extent that the data suggest that countries within a region have similar levels and trends across cohort.
This induces covariance between countries within a region, even if not modelled explicitly. Such hierarchical structure is a standard strategy for accounting for dependence in statistical modelling. Nonetheless, the use of an age model introduces dependence in height over age. A few data sources were in inches or meters and were converted to centimetres, which is of course an entirely deterministic calculation. To our knowledge, self-report is the single most important source of bias in adult height data.
A major strength of our paper is the exclusive use of measured data and the exclusion of self-reported height. Removal of shoes is a part of the standard protocol of health and nutrition surveys Madden et al, We have nonetheless stated measurement error as a potential limitation of population-based data Discussion, sixth paragraph. Semiparametric Bayesian density estimation with disparate data sources: a meta-analysis of global childhood undernutrition.
J Am Stat Assoc ; : Madden AM, Smith S. Body composition and morphological assessment of nutritional status in adults: a review of anthropometric variables.
J Hum Nutr Diet ; 29 1 : The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. This article is distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use and redistribution provided that the original author and source are credited.
Article citation count generated by polling the highest count across the following sources: Crossref , Scopus , PubMed Central. A large scale study reveals how human height has changed in the last years. Identifying environmentally responsive genetic loci where DNA methylation is associated with coronary heart disease CHD may reveal novel pathways or therapeutic targets for CHD.
We did a nested case-control study comprising incident CHD cases and matched controls who were identified from the 10 year follow-up of the China Kadoorie Biobank. We performed the single cytosine-phosphate-guanine CpG site association analysis and network approach to identify CHD-associated CpG sites and co-methylation gene module.
After quality control, participants mean age Mediation analyses revealed Methylation level at the promoter region of SNX30 was associated with blood pressure and subsequent risk of CHD, with the mediating proportion to be 7. Network analysis revealed a co-methylation module associated with CHD.
We identified novel blood methylation alterations associated with incident CHD in the Asian population and provided evidence of the possible role of epigenetic regulations in the smoking- and blood pressure-related pathways to CHD risk. Simulating nationwide realistic individual movements with a detailed geographical structure can help optimise public health policies. However, existing tools have limited resolution or can only account for a limited number of agents. We introduce Epidemap, a new framework that can capture the daily movement of more than 60 million people in a country at a building-level resolution in a realistic and computationally efficient way.
By applying it to the case of an infectious disease spreading in France, we uncover hitherto neglected effects, such as the emergence of two distinct peaks in the daily number of cases or the importance of local density in the timing of arrival of the epidemic. Finally, we show that the importance of super-spreading events strongly varies over time.
Cited Views , Annotations Open annotations. The current annotation count on this page is being calculated. Cite this article as: eLife ;5:e doi: Figure 1. Download asset Open asset. Figure 2.
Figure 3. Figure 4. Figure 5. Figure 6. Figure 7. Figure 8. Figure 9. Figure Data sources were included in the NCD-RisC database if: measured data on height, weight, waist circumference, or hip circumference were available; study participants were five years of age and older; data were collected using a probabilistic sampling method with a defined sampling frame; data were representative of the general population at the national, subnational, or community level; data were from the countries and territories listed in Supplementary file 1.
We excluded data sources on population subgroups whose anthropometric status may differ systematically from the general population, including: studies that had included or excluded people based on their health status or cardiovascular risk; ethnic minorities; specific educational, occupational, or socioeconomic subgroups of the population; and those recruited through health facilities, with the exception noted below. Clarke P Sastry N Duffy D Ailshire J Accuracy of self-reported versus measured weight over adolescence and young adulthood: findings from the national longitudinal study of adolescent health , American Journal of Epidemiology — Emerging Risk Factors Collaboration Adult height and the risk of cause-specific death and vascular morbidity in 1 million people: individual participant meta-analysis International Journal of Epidemiology 41 — Fisher RA XV.
Komlos J Baur M From the tallest to one of the fattest: the enigmatic fate of the American population in the 20th century Economics and Human Biology 2 —
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