Factors associated with women's healthcare decision-making during and after pregnancy in urban slums in Mumbai, India: a cross-sectional analysis

• Main Authors: Neha Batura (Author), Stavros Poupakis (Author), Sushmita Das (Author), Ujwala Bapat (Author), Glyn Alcock (Author), Jolene Skordis (Author), Hassan Haghparast-Bidgoli (Author), Shanti Pantvaidya (Author), David Osrin (Author)
• Format: Book
• Published: BMC, 2022-04-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12889-022-13216-7; 1471-2458
• Keywords: Agency; Healthcare utilisation; Maternal health; India; Public aspects of medicine; RA1-1270
• Source: BMC Public Health, Vol 22, Iss 1, Pp 1-7 (2022)

Abstract Background Understanding factors associated with women's healthcare decision-making during and after pregnancy is important. While there is considerable evidence related to general determinants of women's decision-making abilities or agency, there is little evidence on factors associated with women's decision-making abilities or agency with regards to health care (henceforth, health agency), especially for antenatal and postnatal care. We assessed women's health agency during and after pregnancy in slums in Mumbai, India, and examined factors associated with increased participation in healthcare decisions. Methods Cross-sectional data were collected from 2,630 women who gave birth and lived in 48 slums in Mumbai. A health agency module was developed to assess participation in healthcare decision-making during and after pregnancy. Linear regression analysis was used to examine factors associated with increased health agency. Results Around two-thirds of women made decisions about perinatal care by themselves or jointly with their husband, leaving about one-third outside the decision-making process. Participation increased with age, secondary and higher education, and paid employment, but decreased with age at marriage and household size. The strongest associations were with age and household size, each accounting for about a 0.2 standard deviation difference in health agency score for each one standard deviation change (although in different directions). Similar differences were observed for those in paid employment compared to those who were not, and for those with higher education compared to those with no schooling. Conclusion Exclusion of women from maternal healthcare decision-making threatens the effectiveness of health interventions. Factors such as age, employment, education, and household size need to be considered when designing health interventions targeting new mothers living in challenging conditions, such as urban slums in low- and middle-income countries.