anthroplus_prevalence {anthroplus} | R Documentation |

Prevalence estimates according to the WHO recommended standard analysis: includes prevalence estimates with corresponding standard errors and confidence intervals, and z-score summary statistics (mean and standard deviation) with most common cut-offs describing the full index distribution (-3, -2, -1, +1, +2, +3), and at disaggregated levels for all available factors (age and sex).

```
anthroplus_prevalence(
sex,
age_in_months = NA_real_,
oedema = "n",
height_in_cm = NA_real_,
weight_in_kg = NA_real_,
sw = NULL,
cluster = NULL,
strata = NULL
)
```

`sex` |
A numeric or text variable containing gender information. If it is numeric, its values must be: 1 for males and 2 for females. If it is character, it must be "m" or "M" for males and "f" or "F" for females. No z-scores will be calculated if sex is missing. |

`age_in_months` |
A numeric variable containing age information; Age-related z-scores will NOT be calculated if age is missing. |

`oedema` |
The values of this character variable must be "n", "N" or "2"
for non-oedema, and "y", "Y", "1" for oedema. Although it
is highly recommended that this variable is provided by the
survey, it is possible to run
the analysis without specifying this variable. If unspecified,
the default vector of all "n" with values considered as
non-oedema is used. Missing values will be
treated as non-oedema. For oedema, weight related z-scores
are NOT calculated (set to missing),
BUT they are treated as being < -3 SD in the weight-related
indicator prevalence ( |

`height_in_cm` |
A numeric variable containing standing height information, which must be in centimeters. Height-related z-scores will not be calculated if missing. |

`weight_in_kg` |
A numeric variable containing body weight information, which must be in kilograms. Weight-related z-scores are not calculated if missing. |

`sw` |
An optional numeric vector containing the sampling weights. If NULL, no sampling weights are used. |

`cluster` |
An optional integer vector representing clusters. If the value is NULL this is treated as a survey without clusters. This is also the case if all values are equal, then it is assumed there are also no clusters. |

`strata` |
An optional integer vector representing strata. Pass NULL to indicate that there are no strata. |

In this function, all available (non-missing and non-flagged) z-score values are used for each indicator-specific prevalence estimation (standard analysis).

Note: the function temporarily sets the `survey`

option
`survey.lonely.psu`

to "adjust" and then restores the original value.
It is a wrapper around the `survey`

package to compute
estimates for the different groups (e.g. by age or sex).

If not all parameter values have equal length, parameter values will be repeated to match the maximum length.

Only cases with age_in_months between 61 (including) and 228 months (including) are used for the analysis. The rest will be ignored.

Returns a data.frame with prevalence estimates for the various groups.

The output data frame includes prevalence estimates with corresponding standard errors and confidence intervals, and z-score summary statistics (mean and standard deviation) with most common cut-offs describing the full index distribution (-3, -2, -1, +1, +2, +3), and at disaggregated levels for all available factors.

The resulting columns are coded with a *prefix*,
*a prevalence indicator* and *a suffix*:

**Prefix:**

- HA
Height-for-age

- WA
Weight-for-age

- BMI
Body-mass-index-for-age

**Prevalence indicator:**

- _3
Prevalence corresponding to < -3 SD

- _2
Prevalence corresponding to < -2 SD

- _1
Prevalence corresponding to < -1 SD

- 1
Prevalence corresponding to > +1 SD

- 2
Prevalence corresponding to > +2 SD

- 3
Prevalence corresponding to > +3 SD

**Suffix:**

- _pop
Weighted sample size

- _unwpop
Unweighted sample size

- _r
Mean/prevalence

- _ll
lower 95% confidence interval limit

- _ul
upper 95% confidence interval limit

- _stdev
Standard Deviation

- _se
Standard error

**For example:**

- HA_r
Height-for-age z-score mean

- WA_stdev
Weight-for-age z-score Standard Deviation

- BMI_2_se
Prevalence of BMI-for-age <-2 SD standard error

- BMI_3_ll
Prevalence of BMI-for-age <-3 SD lower 95% confidence interval limit

Note that weight-for-age results are NA for the groups "All" and the two "Sex" groups, as the indicator is only defined for age in months between 61 and 120.

```
set.seed(1)
prev <- anthroplus_prevalence(
sex = c(1, 2),
age_in_months = rpois(100, 100),
height_in_cm = rnorm(100, 100, 10),
weight_in_kg = rnorm(100, 40, 10)
)
prev[, c(1, 4, 5, 6)]
```

[Package *anthroplus* version 0.9.0 Index]