Low infant birth weight

Low infant birth weight is associated with infant mortality and health problems in later life. Infants who have a low birth weight are also likely to spend longer in hospital.

Proportion of low birth weight by country

The United States had the highest proportion of low birth weights, 8.1% in 2015, and the UK the second highest at 6.9%. The proportion of low birth weights in the UK has been stagnant since 2007 at around 7%. Of all the OECD countries, Finland and Iceland have the lowest proportion of low birth weights with 4.2% and 4.4% respectively.

There have been increases over the past twenty years in a number of countries which have been attributed to a number of factors. In Europe, there has been an increase in the number of multiple births, largely due to the increase in fertility treatments, and a general increase in older women giving birth. Both are associated with increased risks of infants born prematurely and/or having a low birth weight.

Improvements in delivery management and care of new-borns have also increased the survival rates of low weight babies (OECD, 2015).

There is evidence to suggest that low birth weight is associated with: mother's age, multiple births, marital status and deprivation (including household income and social class) (Dibben et al, 2008; EURO PERISTAT, 2010). It is likely that a change in one or more of these factors has contributed to the decreasing trend we have seen in the UK since 2003.

Updated May 2017.

About this data

An infant is considered to be of low birth weight if their weight at birth is less than 2,500 grams/5.5 pounds, irrespective of the gestational age of the infant.

The proportion of low birth weight infants is the number of low birth weight births divided by the total number of live births.

National population data mask differences in outcomes across different population groups. Comparisons of different population groups within countries suggest that the proportion of low birth weight infants might also be influenced by differences in education, income and associated living conditions.

Gaps in data series exist because data was not available for these years.


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