Exploring the Perceived Barriers to Following a Mediterranean Style Diet in Childbearing Age: A Qualitative Study.
Harriet KretowiczVanora A HundleyFotini TsofliouPublished in: Nutrients (2018)
A considerable amount of research has focused on interventions in pregnancy to promote health in current and future generations. This has yielded inconsistent results and focus has turned towards improving health in the preconception period. Promotion of healthy dietary patterns similar to a Mediterranean diet in the preconception years has been suggested as a dietary strategy to prevent maternal obesity and optimize offspring health. However, it is uncertain whether adoption is acceptable in women of childbearing age. This qualitative study aims to investigate the perceived barriers to following a Mediterranean diet in women of childbearing age. Semi-structured focus groups were used to generate deep insights to be used to guide the development of a future intervention. Nulliparous women aged between 20 and 47 years were recruited (n = 20). Six focus groups were digitally audio recorded and transcribed verbatim by the researcher. Thematic analysis was used to analyze data, which occurred in parallel with data collection to ascertain when data saturation was reached. Five core themes were identified: Mediterranean diet features, perceived benefits, existing dietary behavior and knowledge, practical factors, and information source. The present study highlights that a Mediterranean diet is acceptable to childbearing-aged women, and the insights generated will be helpful in developing an intervention to promote Mediterranean diet adoption.
Keyphrases
- pregnancy outcomes
- mental health
- polycystic ovary syndrome
- electronic health record
- healthcare
- physical activity
- public health
- depressive symptoms
- health information
- social support
- randomized controlled trial
- insulin resistance
- weight loss
- cervical cancer screening
- big data
- pregnant women
- type diabetes
- breast cancer risk
- metabolic syndrome
- health promotion
- machine learning
- high fat diet
- social media
- preterm birth
- climate change
- deep learning