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Prevalence and determinants of exclusive breastfeeding among lactating mothers in an urban slum, West Tripura: a cross sectional study
Article | IMSEAR | ID: sea-211611
ABSTRACT

Background:

Exclusive breastfeeding is the optimal way to feed children during their first months of life, having important benefits for them and their mothers. Despite of all benefits, the practice of exclusive breastfeeding is quite low and information on influencing factors is limited especially from slum settlements. Objectives was to estimate the prevalence of exclusive breastfeeding and to find out the factors affecting exclusive breastfeeding among lactating mothers in an urban slum, West Tripura.

Methods:

A cross sectional study was conducted among 200 lactating mothers for a period of six months in an urban slum using structured interview schedule. Eligible mothers were selected by sample random sampling technique. Data has been analyzed by SPSS statistical software version 17.

Results:

Majority (43%) of the mothers was aged between 21-25 years and 89% were non working mothers. Among the participants, 55.5% were Hindu by religion, 60% belonged to nuclear family and 43.5% had studied up to primary level. The prevalence of exclusive breastfeeding rate among the study mothers were 60.5%. Only parity, place of delivery and number of antenatal check up were significantly associated with exclusive breastfeeding.

Conclusions:

Exclusive breast feeding (EBF) rate still needs to improve. Community level interventions like awareness programmes on exclusive breastfeeding, health education and behavior change communication among the target group is essential to improve the exclusive breastfeeding rate especially in slum settlements.

Full text: Available Index: IMSEAR (South-East Asia) Type of study: Observational study / Prevalence study / Qualitative research / Risk factors Year: 2019 Type: Article

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Full text: Available Index: IMSEAR (South-East Asia) Type of study: Observational study / Prevalence study / Qualitative research / Risk factors Year: 2019 Type: Article