Factors Influencing Physical Activity Participation among Midlife Immigrant Women: A Systematic Review.
Ping ZouZeest KadriJing ShaoXiyi WangYan LuoHui ZhangAnanya BanerjeePublished in: International journal of environmental research and public health (2021)
Immigrant women are less likely to be physically active and face many barriers to participation in physical activity. This systematic review aims to identify the influencing factors and adaption approaches of physical activity interventions among midlife immigrant women. A systematic literature search was performed using various databases, such as MEDLINE, PsycINFO, and CINAHL, in February 2021. Studies were included if they investigated midlife immigrant women participating in physical activity interventions and were published in an English peer-reviewed journal in or after 2000. Twenty-two papers were included in this review. Guided by the Ecosocial theory, thematic analysis was utilized for data analysis. Among midlife immigrant women, influencing factors associated with physical activity participation included individual factors (a lack of time, current health status, motivation, and a lack of proficiency in various life skills), familial factors (familial support and seasonality), and community factors (social support and neighbourhood environment). The appropriate adaptation of physical activity interventions included adjustments in language, physical activity intensity, physical activity duration, logistical intervention adjustments and other potential technology-based adjustments. The findings can inform community stakeholders, healthcare professionals and researchers to design appropriate physical activity interventions that meet the needs of midlife immigrant women and improve their health outcomes.
Keyphrases
- physical activity
- polycystic ovary syndrome
- systematic review
- body mass index
- pregnancy outcomes
- healthcare
- data analysis
- sleep quality
- randomized controlled trial
- mental health
- type diabetes
- cervical cancer screening
- machine learning
- risk assessment
- high resolution
- climate change
- high intensity
- artificial intelligence