Health status statistics: Morbidity
Newborns with low birth weight (percentage)
Rationale for use
The low birth weight rate in a population is a good indicator of a public health problem that includes long-term maternal malnutrition, ill health and poor health care. On an individual basis, low birth weight is an important predictor of newborn health and survival.
Percentage of live born infants with birth weight less than 2 500g in a given time period.
Low birth weight may be subdivided into very low birth weight (less than 1 500 g) and extremely low birth weight (less than 1 000 g).
Birth weight is the first weight of the foetus or newborn obtained after birth. For live births, birth weight should ideally be measured within the first hour of life before significant postnatal weight loss has occurred and actual weight should be recorded to the degree of accuracy to which it is measured.
Low birth weight is defined as less than 2500 g (up to and including 2499 g).
Live birth refers to the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of the pregnancy, which, after such separation, breathes or shows any other evidence of life - e.g. beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles - whether or not the umbilical cord has been cut or the placenta is attached. Each product of such a birth is considered live born.
Age-specific mortality rates among children and infants are calculated from birth and death data derived from vital registration, census, and/or household surveys:
Vital registration: Number of deaths by age and numbers of births and children in each age group are used to calculate age specific rates. This system provides annual data.
Census and surveys: An indirect method is used based on questions to each woman of reproductive age as to how many children she has ever born and how many are still alive. The Brass method and model life tables are then used to obtain an estimate of under-5 mortality.
Surveys: A direct method is used based on birth history - a series of detailed questions on each child a woman has given birth to during her lifetime. To reduce sampling errors, the estimates are generally presented as period rates, for five or 10 years preceding the survey.
Methods of estimation
Empirical data from different sources are consolidated to obtain estimates of the level and trend in under-5 mortality by fitting a curve to the observed mortality points. However, to obtain the best possible estimates, judgement needs to be made on data quality and how representative it is of the population. Recent statistics based on data availability in most countries are point estimates dated by at least 3-4 years which need to be projected forward in order to obtain estimates of under-5 mortality for the current year.
By sex, location (urban/rural, major regions/provinces) and socio-economic characteristics (e.g. mother's education, wealth quintile). Often disaggregated under-5 mortality rates are presented for 10-year periods because of the rapid increase in sampling error if multiple categories are used. Censuses and surveys provide such detail; vital registration data usually does not include socio-economic variables but can provide the other disaggregations.
Trends in child mortality in the developing world: 1960 to 1996
The World Health Report 2005 - make every mother and child count
The State of the World's Children 2005 - Childhood under threat
- Demographic and Health Surveys (DHS)
- WHOSIS Mortality Database (Vital registration data)
- UNICEF (statistics and MICS)
Even though many countries have collected information on child mortality in recent years, the high demand for very recent child mortality trend information is difficult to meet through household surveys. High quality of vital registration systems (completeness of registration) and high quality of survey or census data collection are crucial - WHO does estimate the level of underestimation of vital registration systems and there clearly is substantial variation in data quality and consistency across countries.