Decision letter | A century of trends in adult human height

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A century of trends in adult human height

Decision letter

Affiliation details

Eduardo Franco, Reviewing editor, McGill University, Canada

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your work entitled "The height of the world – A century of trends in adult human height" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by Eduardo Franco, as a Reviewing Editor, and Prabhat Jha, as the Senior Editor. M Dawn Teare, a Member of eLife's Board of Reviewing Editors served as one of the reviewers and agreed to reveal her identity.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This paper is a substantial and impressive report submitted on behalf of the NCD Risk Factor Collaboration. It represents a huge and extremely valuable new assemblage of data, including adult height measurements for around 15.4 million individuals born between 1896 and 1996 from 178 countries around the globe. Never before has such comprehensive data on stature been brought together, bearing on trends and differentials across the globe in health, nutrition, economy, and anthropometry. This collaborative group has published several papers now using this methodology, tackling a different health outcome in each paper. Here the health outcome is adult height and the team has systematically collected adult height measurements from 1450 studies from 178 countries for adults born between 1896 and 1996 and used a hierarchical Bayesian model to analyse trends over 100 years. Adult height lends itself nicely to this sort of analysis as the assumption is that height is pretty constant after 18, whereas weight (and hence BMI) is a much less stable measurement.

Essential revisions:

Structure and Organization:

The paper is difficult to read and some investment in visualisation tools would greatly enhance its value. The maps after the References section are very nice and easy to fit into the article in a pdf form. However, the country by gender plots need to be made a bit more accessible as these are the more interesting results summarizing the trends.

Please revise the Abstract and Introduction with due attention to providing factual material only. 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. Finding “no indication of convergence across countries” in mean adult heights is hardly news.

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 178 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 165 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.

Data Analysis:

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., 2011 and Finucane et al., 2014 for details of the model, but the Bayesian models in those references pertain to systolic blood pressure and to health status, not to heights. Heights pose many different issues, particularly when only 70 of the 178 countries have data for cohorts born before 1920 and 22 of 200 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.

Please provide details on the Bayesian model regarding the following:

A) growth curves by age;

B) the “linear and non-linear” trends in mean age over time;

C) non-normality at younger and older ages;

D) variability in standard deviations and its relationship to the homogeneity or heterogeneity of each measured population;

E) smoothing (B-splines?);

F) covariance structures within region by age and time;

G) sample information with regard to measurement scales in centimeters or inches, with or without shoes (or unknown), degree of rounding, etc.

DOI: http://dx.doi.org/10.7554/eLife.13410.018