Dataset Information

Understanding breastfeeding behaviours: a cross-sectional analysis of associated factors in Ireland, the United Kingdom and Australia.

ABSTRACT: Background: Breastfeeding is a complex behaviour relying on a combination of individual mother and infant characteristics, health systems, and family, community and professional support. Optimal breastfeeding in high-income countries is particularly low. Despite having similar sociocultural backgrounds, breastfeeding rates between Ireland, the United Kingdom (UK) and Australia vary, thus there is a need to understand whether this is due to individual, sociocultural or policy differences. This research identifies the between-country differences in infant feeding mode and examines if country differences in feeding mode persist once known individual, behavioural and structural factors are considered using socioecological and person-context models.

Methods: Participants were adult women with at least one infant less than 6?months of age, who completed an online survey (n?=?2047) that was distributed by social media in June 2016. Within-country differences in infant feeding mode ('any breastfeeding' vs. 'no breastfeeding') were examined first before hierarchical multivariable logistic regression was used to determine if country differences in feeding mode persisted after adjusting for known factors associated with breastfeeding.

Results: In this sample, 'any breastfeeding' rates were 89, 71 and 72% in Australia, Ireland and the United Kingdom respectively. Within-country differences were evident in Australia, Ireland and the UK. Four factors showed no association with infant feeding mode in Australia while they did in the other countries (maternal age, income, skin-to-skin contact, support from friends and family). Two factors were unique to Australia: the odds of being in the 'no breastfeeding' group increased when the baby was delivered via caesarean and when not enough breastfeeding information was available after birth. One determinant was unique to Ireland: the odds of being in the 'no breastfeeding' group increased when respondents indicated they were not religious; in the UK this occurred when respondents were living in a town/village. After adjusting for sets of known factors of infant feeding mode based on socioecological and person-context models, country differences remained in hierarchical regressions: the odds of not breastfeeding were higher in both Ireland (AOR 3.3, 95%CI 1.8,6.1) and the United Kingdom (AOR 2.7, 95%CI 1.5, 4.7) compared to Australia.

Conclusions: This study indicates that different levels in the socioecological system are related to infant feeding behaviours. An adequate inter-systems level response would consider the interactions within and between behavioural and structural mechanisms which support breastfeeding behaviour. Optimising infant feeding practices will require an integrated web of interventions that go beyond the individual and focus on addressing factors that will influence families within their communities as they move between systems.

SUBMITTER: Gallegos D

PROVIDER: S-EPMC7709394 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Understanding breastfeeding behaviours: a cross-sectional analysis of associated factors in Ireland, the United Kingdom and Australia.

Gallegos Danielle D Parkinson Joy J Duane Sinead S Domegan Christine C Jansen Elena E Russell-Bennett Rebekah R

International breastfeeding journal 20201202 1

<h4>Background</h4>Breastfeeding is a complex behaviour relying on a combination of individual mother and infant characteristics, health systems, and family, community and professional support. Optimal breastfeeding in high-income countries is particularly low. Despite having similar sociocultural backgrounds, breastfeeding rates between Ireland, the United Kingdom (UK) and Australia vary, thus there is a need to understand whether this is due to individual, sociocultural or policy differences. ...[more]

PMID: 33267900

Similar Datasets

Project description:BackgroundAnxiety about COVID-19 is common. For most people this is an appropriate response to the loss of livelihoods and loved-ones, disruptions to social networks, and uncertainty about the future. However, for others these anxieties relate to contracting the virus itself, a phenomenon termed COVID anxiety. Little is known about the characteristics of people with severe COVID anxiety or the impact it has on their daily lives.MethodsWe conducted a two-phase cross-sectional survey of people aged 18 or over who were living in United Kingdom, self-identified as anxious about COVID-19, and had a score of ≥9 on the Coronavirus Anxiety Scale. We recruited participants nationally through online adverts and locally via primary care services in London. Data on demographic and clinical factors were used in multiple regression modelling to examine the greatest contributors to functional impairment, poor health-related quality of life and protective behaviours in this sample of individuals with severe COVID anxiety.ResultsWe recruited 306 people with severe COVID anxiety between January and September 2021. Most were female (n = 246, 81.2%); they had a median age of 41 (range = 18-83). The majority of participants also had generalised anxiety (n = 270, 91.5%), depression (n = 247, 85.5%), and a quarter (n = 79, 26.3%) reported a physical health condition which put them at increased risk of hospitalisation with COVID-19. Half had severe social dysfunction (n = 151, 52.4%). One in ten reported never leaving their home, one in three washed all items brought into their house, one in five washed their hands constantly, and one in five of those with children reported not sending them to school because of fears of COVID-19. Increasing co-morbid depressive symptoms best explained functional impairment and poor quality of life after controlling for other factors.ConclusionsThis study highlights the high degree of co-occuring mental health problems, and the extent of functional impairment and poor health-related quality of life among people with severe COVID anxiety. Further research is needed to establish the course of severe COVID anxiety as the pandemic progresses, and steps that can be taken to support people who experience this distress.

Project description:BackgroundBreastfeeding has the most profound impact on infant health and wellness, and also have significant implications for the mother. The duration of the breastfeeding determines the infant's protection from malnutrition and other common infectious diseases; consequently, the World Health Organization (WHO) recommends exclusive breastfeeding (EBF) six months, followed by gradual weaning and breastfeeding until the baby is two years old. In Pakistan, the practice of breastfeeding is heavily dependent upon certain demographic, economic, social, and biological factors, which ultimately impact the quality of care provided to the infant and their health. The aim of this paper, therefore, is to measure the impact of these factors on the exclusive breastfeeding duration in Pakistan.MethodsThe data for the study has been collected from Pakistan Demographic and Health Survey (PDHS) for the year 2017-18. Binary logistic regression model and survival analysis are used to determine the relationship between the independent and dependent variables.ResultsWe use a binary logistic regression to estimate the effect of each factor on the duration of EBF. The binary logistic regression finds significant relationships between region, maternal education, wealth index, size of a child, watching television, delivery by cesarean, and maternal age and EBF. We then use log-likelihood, AIC, BIC criteria to determine if a parametric or non-parametric model would provide a better fit; based on these results we fit an Inverse Gaussian (Weibull) distribution for the survival analysis. These results show that there are more significant factors associated with EBF duration in parametric survival analysis than in the binary logistic regression results. Thus, the survival analysis is a better method for predicting the relationship between the duration of EBF and its factors. Furthermore, logically EBF is designated to be done for six months which would not be properly gauged with a binary response variable.ConclusionsThe results of this study provide proof that exclusive breastfeeding is a common practice among women in Pakistan, and to improve the quality of post-natal care, health policy in the country needs to focus on the existing demographic and social factors which are found significant in this study.

Project description:BackgroundChanging population-level exposure to modifiable risk factors is a key driver of changing cancer incidence. Understanding these changes is therefore vital when prioritising risk-reduction policies, in order to have the biggest impact on reducing cancer incidence. UK figures on the number of risk factor-attributable cancers are updated here to reflect changing behaviour as assessed in representative national surveys, and new epidemiological evidence. Figures are also presented by UK constituent country because prevalence of risk factor exposure varies between them.MethodsPopulation attributable fractions (PAFs) were calculated for combinations of risk factor and cancer type with sufficient/convincing evidence of a causal association. Relative risks (RRs) were drawn from meta-analyses of cohort studies where possible. Prevalence of exposure to risk factors was obtained from nationally representative population surveys. Cancer incidence data for 2015 were sourced from national data releases and, where needed, personal communications. PAF calculations were stratified by age, sex and risk factor exposure level and then combined to create summary PAFs by cancer type, sex and country.ResultsNearly four in ten (37.7%) cancer cases in 2015 in the UK were attributable to known risk factors. The proportion was around two percentage points higher in UK males (38.6%) than in UK females (36.8%). Comparing UK countries, the attributable proportion was highest in Scotland (41.5% for persons) and lowest in England (37.3% for persons). Tobacco smoking contributed by far the largest proportion of attributable cancer cases, followed by overweight/obesity, accounting for 15.1% and 6.3%, respectively, of all cases in the UK in 2015. For 10 cancer types, including two of the five most common cancer types in the UK (lung cancer and melanoma skin cancer), more than 70% of UK cancer cases were attributable to known risk factors.ConclusionTobacco and overweight/obesity remain the top contributors of attributable cancer cases. Tobacco smoking has the highest PAF because it greatly increases cancer risk and has a large number of cancer types associated with it. Overweight/obesity has the second-highest PAF because it affects a high proportion of the UK population and is also linked with many cancer types. Public health policy may seek to mitigate the level of harm associated with exposure or reduce exposure levels-both approaches may effectively impact cancer incidence. Differences in PAFs between countries and sexes are primarily due to varying prevalence of exposure to risk factors and varying proportions of specific cancer types. This variation in turn is affected by socio-demographic differences which drive differences in exposure to theoretically avoidable 'lifestyle' factors. PAFs at UK country level have not been available previously and they should be used by policymakers in devolved nations. PAFs are estimates based on the best available data, limitations in those data would generally bias toward underestimation of PAFs. Regular collection of risk factor exposure prevalence data which corresponds with epidemiological evidence is vital for analyses like this and should remain a priority for the UK Government and devolved Administrations.

Dataset Information

Understanding breastfeeding behaviours: a cross-sectional analysis of associated factors in Ireland, the United Kingdom and Australia.

Publications

Understanding breastfeeding behaviours: a cross-sectional analysis of associated factors in Ireland, the United Kingdom and Australia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets