# **Box 1. Child anthropometry data issues**

As an important caveat, available estimates of child undernutrition rates, including the statistics discussed in this review, may be biased due to missing or invalid child anthropometry data. Thus, the results of any analysis—whether of patterns, trends, or correlates—may be artifacts of the data rather than real phenomena.

Missing data can take four forms: (a) the survey was not conducted because the intended household was unavailable, (b) the survey was not conducted because the intended household refused to participate in the survey, (c) the intended household participated in the survey but refused child anthropometry measurement, or (d) the child anthropometry measurements were invalid. Not all household surveys perform fielding or statistical adjustments for the different forms of missing data. Furthermore, not all household survey reports present comprehensive, detailed information on the extent of missing data.

Based on statistics we could extract from household survey reports and nutrition studies, the missing data problem seems severe, especially in certain parts of the country. For example, in the 2011 NNS, household survey nonresponse rates (that is, missing data forms (a) and (b) divided by the original household sample size) are as high as 9% in Balochistan and 16% in KPK. In the 2012–13 DHS, the rate of missing or invalid anthropometry data (that is, missing data forms (c) and (d) divided by the number of eligible children in surveyed households) is 19%. In the same survey, for Balochistan, 20% of eligible children in surveyed households have missing anthropometry data, and 59% of children who were measured have invalid anthropometry data.

In terms of other evidence, Arif et al. (2014) note that the 2010 Pakistan Panel Household Survey (PPHS), which covered 16 districts across the four provinces, failed to gather height and weight data for about one-third and one-fifth of eligible children, respectively. Likewise, Ibrahim (1999) notes that the 1990–91 DHS did not measure 31% of eligible children. The main reasons for the missing measurement are: the mother refusing (30% of cases), the child not being present (20%), and the child refusing (18%). Ibrahim states that mothers refused measurement of their children mainly due to fears derived from traditional superstition that the survey team could cast an ‘evil eye’ on their children.

The missing data rates are worryingly high in absolute terms, but the magnitude of the problem is underscored when compared to other countries in the region. For example, in the 2014 DHS for Bangladesh, the household survey nonresponse rate is 4% and the missing anthropometry data rate is 6%. In addition, the missing data rates for Pakistan indicate that the problem extends more widely than for low-population areas such as Balochistan.

More investigation is needed into the direction of the potential bias in child undernutrition rates due to missing data. Data may be unavailable to assess the nature of the bias due to missing households in the survey sample, but the data gathered in the survey could be used to assess the nature of the bias due to missing or invalid child anthropometry data for surveyed households. The 2012–13 DHS report points to the presence of bias, stating that the extent of missing or invalid anthropometry data is associated with child age, maternal and household characteristics, <u>and province of residence.</u>