NAME

WHO::GrowthReference::Table - Lookup height/weight in the WHO growth chart (a.k.a. growth reference, growth standards)

VERSION

This document describes version 0.012 of WHO::GrowthReference::Table (from Perl distribution WHO-GrowthReference-Table), released on 2022-06-07.

SYNOPSIS

use WHO::GrowthReference::Table qw(get_who_growth_reference);

# get mean height & weight of a 3-year old girl

my $res = get_who_growth_reference(gender => "F", dob => time() - 3*365.25*86400);
# => [200, "OK", {
#      age => "36.0 month(s)",
#      height_mean => 95.034, # cm
#      weight_mean => 13.9,   # kg
#      height_P01  => ..., # height at 0.1% percentile
#      height_P1   => ..., # height at 1% percentile
#      height_Z-3  => ..., # height at -3 SD
#      height_Z-2  => ..., # height at -2 SD
#      ...
#     }]

# you have a 3.5-year old boy weighing at 14.8kg and with a height of 102cm,
# calculate the percentiles

my $res = get_who_growth_reference(gender => "M", dob => time() - 3.5*365.25*86400, weight=>14.8, height=>102);
# => [200, "OK", {
#      age => "42.0 month(s)",
#      height_mean => 99.844, # cm
#      height_percentile => 70.2, # your boy's height is above world average, about 70.2% of boys of the same age are shorter than your boy
#      height_zscore => ...,
#      weight_mean => 15.3,   # kg
#      weight_percentile => 39.6, # your boy's weight is below world average, about 39.6% of boys of the same age weigh less than your boy
#      weight_zscore => ...,
#      height_P01 => ...,
#      ...
#      height_potential => ...,
#      height_potential_Z0 => ...,
#      weight_potential_10y => ...,
#      weight_potential_10y_Z0 => ...,
#     }]

DESCRIPTION

FUNCTIONS

get_who_growth_reference

Usage:

get_who_growth_reference(%args) -> [$status_code, $reason, $payload, \%result_meta]

Lookup height/weight in the WHO growth chart (a.k.a. growth reference, growth standards).

Examples:

• Get weight/height information for a boy that is born on May 4, 2017:

  get_who_growth_reference(gender => "M", dob => "2017-05-04");

  Result:

  [
    200,
    "OK",
    {
      age           => "61.0 month(s)",
      bmi_mean      => 15.264,
      bmi_P01       => 12.041,
      bmi_P1        => 12.72,
      bmi_P10       => 13.764,
      bmi_P15       => 14.03,
      bmi_P25       => 14.441,
      bmi_P3        => 13.148,
      bmi_P5        => 13.384,
      bmi_P50       => 15.264,
      bmi_P75       => 16.172,
      bmi_P85       => 16.7,
      bmi_P90       => 17.074,
      bmi_P95       => 17.656,
      bmi_P97       => 18.052,
      bmi_P99       => 18.845,
      bmi_P999      => 20.355,
      bmi_SD0       => 15.264,
      bmi_SD1       => 16.645,
      bmi_SD1neg    => 14.071,
      bmi_SD2       => 18.259,
      bmi_SD2neg    => 13.031,
      bmi_SD3       => 20.166,
      bmi_SD3neg    => 12.118,
      bmi_SD4       => 22.072,
      bmi_SD4neg    => 11.204,
      gender        => "M",
      height_mean   => 110.265,
      height_P01    => 96.076,
      height_P1     => 99.583,
      height_P10    => 104.381,
      height_P15    => 105.506,
      height_P25    => 107.168,
      height_P3     => 101.629,
      height_P5     => 102.712,
      height_P50    => 110.265,
      height_P75    => 113.362,
      height_P85    => 115.023,
      height_P90    => 116.149,
      height_P95    => 117.817,
      height_P97    => 118.9,
      height_P99    => 120.946,
      height_P999   => 124.453,
      height_SD0    => 110.265,
      height_SD1    => 114.856,
      height_SD1neg => 105.673,
      height_SD2    => 119.448,
      height_SD2neg => 101.082,
      height_SD3    => 124.039,
      height_SD3neg => 96.49,
      height_SD4    => 128.63,
      height_SD4neg => 91.899,
      weight_mean   => 18.506,
      weight_P01    => 12.581,
      weight_P1     => 13.802,
      weight_P10    => 15.711,
      weight_P15    => 16.204,
      weight_P25    => 16.967,
      weight_P3     => 14.58,
      weight_P5     => 15.013,
      weight_P50    => 18.506,
      weight_P75    => 20.216,
      weight_P85    => 21.212,
      weight_P90    => 21.92,
      weight_P95    => 23.023,
      weight_P97    => 23.774,
      weight_P99    => 25.276,
      weight_P999   => 28.126,
      weight_SD0    => 18.506,
      weight_SD1    => 21.109,
      weight_SD1neg => 16.279,
      weight_SD2    => 24.165,
      weight_SD2neg => 14.367,
      weight_SD3    => 27.77,
      weight_SD3neg => 12.718,
      weight_SD4    => 31.375,
      weight_SD4neg => 11.07,
    },
    {
      "func.raw_weight" => [
        61,
        -0.2026,
        18.5057,
        0.12988,
        12.581,
        13.802,
        14.58,
        15.013,
        15.711,
        16.204,
        16.967,
        18.506,
        20.216,
        21.212,
        21.92,
        23.023,
        23.774,
        25.276,
        28.126,
      ],
    },
  ]

• Get weight/height information for a 6.5yo girl:

  get_who_growth_reference(gender => "F", age => "6.5y");

  Result:

  [
    200,
    "OK",
    {
      age           => "78.0 month(s)",
      bmi_mean      => 15.32,
      bmi_P01       => 11.645,
      bmi_P1        => 12.365,
      bmi_P10       => 13.525,
      bmi_P15       => 13.832,
      bmi_P25       => 14.315,
      bmi_P3        => 12.832,
      bmi_P5        => 13.096,
      bmi_P50       => 15.32,
      bmi_P75       => 16.492,
      bmi_P85       => 17.206,
      bmi_P90       => 17.728,
      bmi_P95       => 18.57,
      bmi_P97       => 19.165,
      bmi_P99       => 20.41,
      bmi_P999      => 23.013,
      bmi_SD0       => 15.32,
      bmi_SD1       => 17.131,
      bmi_SD1neg    => 13.879,
      bmi_SD2       => 19.482,
      bmi_SD2neg    => 12.704,
      bmi_SD3       => 22.668,
      bmi_SD3neg    => 11.725,
      bmi_SD4       => 25.855,
      bmi_SD4neg    => 10.746,
      gender        => "F",
      height_mean   => 117.977,
      height_P01    => 101.611,
      height_P1     => 105.657,
      height_P10    => 111.19,
      height_P15    => 112.488,
      height_P25    => 114.405,
      height_P3     => 108.016,
      height_P5     => 109.266,
      height_P50    => 117.977,
      height_P75    => 121.549,
      height_P85    => 123.466,
      height_P90    => 124.764,
      height_P95    => 126.688,
      height_P97    => 127.938,
      height_P99    => 130.297,
      height_P999   => 134.343,
      height_SD0    => 117.977,
      height_SD1    => 123.273,
      height_SD1neg => 112.681,
      height_SD2    => 128.569,
      height_SD2neg => 107.385,
      height_SD3    => 133.865,
      height_SD3neg => 102.089,
      height_SD4    => 139.161,
      height_SD4neg => 96.793,
      weight_mean   => 21.227,
      weight_P01    => 13.932,
      weight_P1     => 15.333,
      weight_P10    => 17.626,
      weight_P15    => 18.239,
      weight_P25    => 19.206,
      weight_P3     => 16.252,
      weight_P5     => 16.773,
      weight_P50    => 21.227,
      weight_P75    => 23.591,
      weight_P85    => 25.028,
      weight_P90    => 26.077,
      weight_P95    => 27.761,
      weight_P97    => 28.945,
      weight_P99    => 31.399,
      weight_P999   => 36.41,
      weight_SD0    => 21.227,
      weight_SD1    => 24.877,
      weight_SD1neg => 18.333,
      weight_SD2    => 29.572,
      weight_SD2neg => 15.998,
      weight_SD3    => 35.757,
      weight_SD3neg => 14.087,
      weight_SD4    => 41.942,
      weight_SD4neg => 12.175,
    },
    {
      "func.raw_weight" => [
        78,
        -0.5185,
        21.2274,
        0.1523,
        13.932,
        15.333,
        16.252,
        16.773,
        17.626,
        18.239,
        19.206,
        21.227,
        23.591,
        25.028,
        26.077,
        27.761,
        28.945,
        31.399,
        36.41,
      ],
    },
  ]

• See percentiles/z-scores for a 6yo boy weighing 17kg and having a height of 102cm:

  get_who_growth_reference(gender => "M", age => "6y", height => 102, weight => 17);

  Result:

  [
    200,
    "OK",
    {
      age                  => "72.0 month(s)",
      bmi                  => 16.3398692810458,
      bmi_mean             => 15.306,
      bmi_P01              => 12.066,
      bmi_P1               => 12.733,
      bmi_P10              => 13.773,
      bmi_P15              => 14.042,
      bmi_P25              => 14.459,
      bmi_P3               => 13.157,
      bmi_P5               => 13.393,
      bmi_P50              => 15.306,
      bmi_P75              => 16.258,
      bmi_P85              => 16.819,
      bmi_P90              => 17.221,
      bmi_P95              => 17.854,
      bmi_P97              => 18.291,
      bmi_P99              => 19.176,
      bmi_P999             => 20.91,
      bmi_percentile       => 76.4593454731863,
      bmi_SD0              => 15.306,
      bmi_SD1              => 16.761,
      bmi_SD1neg           => 14.083,
      bmi_SD2              => 18.52,
      bmi_SD2neg           => 13.04,
      bmi_SD3              => 20.689,
      bmi_SD3neg           => 12.141,
      bmi_SD4              => 22.858,
      bmi_SD4neg           => 11.242,
      bmi_zscore           => 0.71056307975653,
      gender               => "M",
      height_mean          => 115.951,
      height_P01           => 100.726,
      height_P1            => 104.49,
      height_P10           => 109.637,
      height_P15           => 110.845,
      height_P25           => 112.628,
      height_P3            => 106.685,
      height_P5            => 107.847,
      height_P50           => 115.951,
      height_P75           => 119.274,
      height_P85           => 121.057,
      height_P90           => 122.265,
      height_P95           => 124.055,
      height_P97           => 125.217,
      height_P99           => 127.412,
      height_P999          => 131.176,
      height_percentile    => 0.404622741764081,
      height_potential     => 155.876968650372,
      height_potential_SD0 => 176.543,
      height_SD0           => 115.951,
      height_SD1           => 120.878,
      height_SD1neg        => 111.024,
      height_SD2           => 125.804,
      height_SD2neg        => 106.097,
      height_SD3           => 130.731,
      height_SD3neg        => 101.171,
      height_SD4           => 135.658,
      height_SD4neg        => 96.244,
      height_zscore        => -2.83170929760455,
      weight_mean          => 20.514,
      weight_P01           => 13.913,
      weight_P1            => 15.248,
      weight_P10           => 17.361,
      weight_P15           => 17.912,
      weight_P25           => 18.768,
      weight_P3            => 16.105,
      weight_P5            => 16.585,
      weight_P50           => 20.514,
      weight_P75           => 22.48,
      weight_P85           => 23.637,
      weight_P90           => 24.467,
      weight_P95           => 25.767,
      weight_P97           => 26.661,
      weight_P99           => 28.464,
      weight_P999          => 31.948,
      weight_percentile    => 7.67396907216494,
      weight_SD0           => 20.514,
      weight_SD1           => 23.517,
      weight_SD1neg        => 17.996,
      weight_SD2           => 27.129,
      weight_SD2neg        => 15.87,
      weight_SD3           => 31.508,
      weight_SD3neg        => 14.063,
      weight_SD4           => 35.888,
      weight_SD4neg        => 12.256,
      weight_zscore        => -1.46848541862653,
    },
    {
      "func.raw_weight" => [
        72,
        -0.318,
        20.5137,
        0.13372,
        13.913,
        15.248,
        16.105,
        16.585,
        17.361,
        17.912,
        18.768,
        20.514,
        22.48,
        23.637,
        24.467,
        25.767,
        26.661,
        28.464,
        31.948,
      ],
    },
  ]

Caveats:

Currently the z-zcore line values (e.g. height_Z1, height_Z-1, etc) are calculated using linear interpolation.

This function is not exported by default, but exportable.

Arguments ('*' denotes required arguments):

• age => duration

• dob => date

• gender* => str

• height => float

  Specify height to calculate percentile.

• now => date

  Assume now is this date, instead of current date.

• weight => float

  Specify weight to calculate percentile.

Returns an enveloped result (an array).

First element ($status_code) is an integer containing HTTP-like status code (200 means OK, 4xx caller error, 5xx function error). Second element ($reason) is a string containing error message, or something like "OK" if status is 200. Third element ($payload) is the actual result, but usually not present when enveloped result is an error response ($status_code is not 2xx). Fourth element (%result_meta) is called result metadata and is optional, a hash that contains extra information, much like how HTTP response headers provide additional metadata.

Return value: (any)

HOMEPAGE

Please visit the project's homepage at https://metacpan.org/release/WHO-GrowthReference-Table.

SOURCE

Source repository is at https://github.com/perlancar/perl-WHO-GrowthReference-Table.

SEE ALSO

WHO::GrowthReference::GenChart uses this module to make growth charts.

For CLI frontends for this module and more, see App::WHOGrowthReferenceUtils.

Source data is from http://www.who.int/childgrowth/standards/en/. Note that CDC also publishes growth standards; I might write CDC::GrowthReference::Table too someday.

AUTHOR

perlancar <perlancar@cpan.org>

CONTRIBUTING

To contribute, you can send patches by email/via RT, or send pull requests on GitHub.

Most of the time, you don't need to build the distribution yourself. You can simply modify the code, then test via:

% prove -l

If you want to build the distribution (e.g. to try to install it locally on your system), you can install Dist::Zilla, Dist::Zilla::PluginBundle::Author::PERLANCAR, and sometimes one or two other Dist::Zilla plugin and/or Pod::Weaver::Plugin. Any additional steps required beyond that are considered a bug and can be reported to me.

COPYRIGHT AND LICENSE

This software is copyright (c) 2022, 2021, 2018 by perlancar <perlancar@cpan.org>.

This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.

BUGS

Please report any bugs or feature requests on the bugtracker website https://rt.cpan.org/Public/Dist/Display.html?Name=WHO-GrowthReference-Table

When submitting a bug or request, please include a test-file or a patch to an existing test-file that illustrates the bug or desired feature.

cpanm WHO::GrowthReference::Table

perl -MCPAN -e shell
install WHO::GrowthReference::Table