Experiences of lifestyle change among women with gestational diabetes mellitus (GDM): A behavioural diagnosis using the COM-B model in a low-income setting

Abstract

BackgroundLifestyle change can reduce the risk of developing type 2 diabetes among women with prior gestational diabetes mellitus (GDM). While understanding women’s lived experiences and views around GDM is critical to the development of behaviour change interventions to reduce this risk, few studies have addressed this issue in low- and middle- income countries. The aim of the study was to explore women’s lived experiences of GDM and the feasibility of sustained lifestyle modification after GDM in a low-income setting.MethodsThis was a descriptive qualitative study on the lived experiences of women with prior GDM, who received antenatal care at a public sector tertiary hospital in Cape Town, South Africa. Nine focus groups and five in-depth interviews were conducted with a total of thirty-five women. Data were analysed using content analysis and the COM-B (Capabilities, Opportunities, Motivations and Behaviour) model to identify factors influencing lifestyle change during and beyond the GDM pregnancy.ResultsThe results suggest that the COM-B model’s concepts of capability (knowledge and skills for behaviour change), opportunity (resources for dietary change and physical activity) and motivation (perception of future diabetes risk) are relevant to lifestyle change among GDM women in South Africa. The results will contribute to the design of a postpartum health system intervention for women with recent GDM.ConclusionOur findings highlight the need for health services to improve counselling and education for women with GDM in South Africa. Support from family and health professionals is essential for women to achieve lifestyle change. The experience of GDM imposed a significant psychological burden on women, which affected motivation for lifestyle change. To achieve long-term lifestyle change, behaviour interventions for women with prior GDM need to address their capability, opportunity and motivation for lifestyle change during and beyond pregnancy.

Perspectives on the psychological and emotional burden of having gestational diabetes amongst low-income women in Cape Town, South Africa

“…A lack of capacity to adhere to recommendations and effectively control their glucose levels also contributed to heightened maternal distress in our study population. As we have reported previously [34], women experience several barriers to implementing lifestyle changes related to socio-economic status including food insecurity and inadequate social support. Psychosocial deprivation associated with low socio-economic status, affects women's capacity for self-management and has been linked to poor prognosis among women with GDM in the UK and France [39,40].…”

“…The interviews explored a range of issues related to GDM and several themes emerging from the data are reported elsewhere [34]. This paper focuses on the emotional and psychological aspects of women's experience of GDM, which emerged as one of the most dominant topics.…”

“…Our findings echo prevalent views around the 'burden' of maternal responsibility and the culture of mother-blaming. Acknowledgement of other contributing factors such as the prevailing physical and social environment [34] is a crucial step towards shared accountability and provision of appropriate support for women with GDM. The study findings have several implications for the management of GDM in South Africa.…”

“…Only one woman in our study reported having postnatal depression following the GDM pregnancy and similar studies from LMIC are still lacking. Postnatal depression may interfere with women's capability and motivation to engage in health behaviour changes [34], further affirming the importance of postnatal follow up, screening and counselling for women with GDM [37,49].…”

Integrating gestational diabetes and type 2 diabetes care into primary health care: Lessons from prevention of mother-to-child transmission of HIV in South Africa - A mixed methods study

“…ATLAS.ti software was used to assist data analysis and management. Interpretation of data was further supported through IINDIAGO team discussions and in relation to other research findings of the project, some of which have already been published [ 17 , 38 ]. Characteristics of participants were analyzed by JCM using SPSS version 24.0.…”