Birth weight

The “gold standard” measurement of birth weight is the weight recorded in medical notes by clinical staff immediately after delivery. However, obtaining information from routine clinical records is not always feasible. Medical records may be missing, no longer available if the individual was born many years ago or have never existed (e.g. in some low-income settings). Recorded information may also not be available if the individual was born at home, or if delivery occurred outside the country of interest. Therefore, recovery rate of these records is generally low.

Recalled birth weights by mothers and/or fathers (maternal/parental recall) or adult self-reported birth weight are often the only source available. Birth weights recalled by mothers have been found to correlate highly with those found in routine clinical records. However, the accuracy of recall decreases with time since birth.

Selection of data source

Self-reported birth weight can be collected by in person or telephone interviews, by mail survey, electronic questionnaire (which can be self-administered) and the Internet.

Question format

Asking respondents to choose from birth categories rather than reporting birth weight in an open-ended format (e.g. “what was your child’s birth weight?” or “what was your birth weight?”) may increase reporting rates but reduce accuracy and result in loss of power and sensitivity to detect intra-categorical differences.

Example of categories in grams:

  1. Not known
  2. < 2500
  3. 2500 - 2999
  4. 3000 - 3499
  5. 3500 - 3999
  6. > 4000

Units of measure

Ensure to clearly state the unit of the measurement e.g. metric units or imperial scale to avoid discrepancy in recording birth weight. Incorrect conversion may lead to errors. Use units appropriate for the population or ethnic group of interest.

Validation study

When studies rely on self-reported measures, a validation study could help to quantify the potential errors and to calculate correction factors. Ideally, medical records should be used to validate participants’ reporting of birth weight.

Life-course epidemiological studies, investigating the relationship between factors at birth and morbidity and mortality in adult life, often obtain early life data (e.g. birth weight) through self-reported information.

Corrections of self-reported birth weight may be required to derive valid estimates. Heaping or spikiness of reported birth weights, in which respondents show a tendency to round birth weight information to the nearest digit (e.g. 2500 g instead to 2475 g) is one issue which can be addressed by correction. This phenomenon tends to affect the classification of infants in the low birth weight category and it has been frequently observed in retrospective birth weight surveys in less developed countries. To deal with the heaping issue, Boerma et al 1996 [5] and Blanc & Wardlaw 2005 [4] proposed an adjustment procedure on low birth weight estimates in less developed countries.

If birth weight is used as an independent variable, self-reported birth weights may have to be adjusted using birth records when available. The recalled method can also be controlled for, in regression analysis aimed at predicting birth weight outcomes.

Key characteristics of self-reported birth weight methods are outlined in Table A.2.1

Strengths

  1. Cost-effective
  2. Efficient way to obtain the data
  3. Practical tool as it can be included in study questionnaires and be self-administered
  4. Information can be obtained via mail, face-to-face or telephone interviews or the Internet
  5. Can be obtained retrospectively
  6. Low respondent burden
  7. Large number of individuals can be approached
  8. Non-intrusive
  9. It could increase recruitment rates and participation retention, especially by individuals who are reluctant to be measured
  10. No fieldwork required if self-administered or data are collected online

Limitations

  1. Prone to systematic reporting errors by social-demographic characteristics
  2. May not be feasible in certain population where recall bias is high (e.g. in older individuals compared to younger individuals)
  3. Corrections may be necessary at analysis especially when heaping/spikiness occurs (see practical consideration)

Table A.2.1 Characteristics of subjective birth weight methods.

Characteristic Comment
Number of participants High
Relative cost Medium
Participant burden Low
Researcher burden of data collection Low
Researcher burden of coding and data analysis Low
Risk of reactivity bias No
Risk of recall bias Yes
Risk of social desirability bias Yes
Risk of observer bias Yes
Space required Low
Availability High
Suitability for field use High
Participant literacy required Yes, if self-administered
Cognitively demanding Yes

Considerations relating to the use of subjective birth weight methods in specific populations are described in Table A.2.2.

Table A.2.2 Use of subjective birth weight methods in different populations.

Population Comment
Pregnancy
Infancy and lactation
Toddlers and young children
Adolescents
Adults
Older Adults The reliability of self-reported birth weight also decreases in older individuals as they may no longer have access to their mother’s recall, or are unable to accurately remember reports from their mother.
Ethnic groups The accuracy of recalled birth weight varies according to maternal ethnicity and cultural differences (e.g. desirability of large vs small babies could affect reporting).
Other The accuracy of recalled birth weight varies according to socioeconomic status and parity.
The ability to recall birth weight increases with parental education, but decreases with the birth order of the child (first births are recalled more accurately than subsequent births).
  1. Minimal resources are generally required with self-reported parameters as field work may not be necessary
  2. Information can be collected using self-administered questionnaires, mail surveys and the Internet
  3. Standard operating procedures for data entry errors, extreme values, and data cleaning
  4. Statistical knowledge may be required if correction factors are applied to the data

A method specific instrument library is being developed for this section. In the meantime, please refer to the overall instrument library page by clicking here to open in a new page.

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