Discussion
Maternal mortality remains a global health concern with anaemia as a significant contributing factor. Earlier research has highlighted that multipronged approach can reduce the burden of maternal mortality. Worldwide anaemia is identified, as the leading cause of maternal mortality in numerous regions. Globally, more than 500 million women between the ages of 15 and 49 were affected by anaemia in 2019. Anaemia is a crucial health problem among pregnant women in India, including the state of Karnataka. Preterm birth, low birth weight, and maternal and fetal morbidity and mortality were all enhanced by maternal anaemia. Iron deficiency is more prevalent than anaemia, and it frequently emerges during early pregnancy, even in women who have sufficient iron scores at starting stage of pregnancy.12 According to the data from the NFHS-5 conducted in 2019–2021, prevalence of anaemia in women of reproductive age was 29.9%. The prevalence was 29.6% for non-pregnant women of reproductive age, whereas it was 36.5% for pregnant women. While the prevalence of anaemia among women of reproductive age has decreased significantly internationally since 2000, it has remained steady among pregnant women.13
It is important to note that these figures can change over time, and continuous efforts are needed to improve maternal health and reduce the risk of anaemia-related complications during pregnancy. Iron-deficiency anaemia and folate-deficiency megaloblastic anaemia are the most prevalent types of anaemia during pregnancy. The latter is more common in women who have insufficient dietary intake and do not receive adequate prenatal iron and folate supplements.14 A study carried out in Mekele town Ethiopia, in 2014 found that parity, meal frequency, dietary variety and meat consumption significantly affected pregnant women’s anaemia.15 These findings underscore the importance of government initiatives such as POSHAN Abhiyaan, National Nutrition Strategy and Anaemia Mukt Bharath launched during 2018 in India aimed to reduce anaemia prevalence among vulnerable groups. Karnataka’s Anaemia Muktha Poustika Karnataka aligns with national guidelines to address anaemia locally, highlighting the need for ongoing targeted polices, especially in rural and marginalised areas.16
Our study has attempted to look into the spatial dimension of maternal deaths attributed to anaemia with the aim of uncovering geographic patterns and identifying high-risk areas. Existing studies often lack spatial granularity, hindering the identification of localised risk factors and specific targeted interventions in these areas. By employing spatial analysis techniques, we seek to provide GIS insights that are essential and crucial for formulation of policies and specific targeted interventions. The results revealed that, districts differed in the percentage of maternal fatalities related to anaemia, with some districts of Karnataka reporting high prevalence of anaemia-related maternal deaths. The study presented areal interpolation tool in mapping of underlying risk of anaemia in maternal deaths for Karnataka state (figure 2) and the highest risks were noticed in northwest, middle and southwest regions.
In the first objective, temporal trend of maternal deaths attributed to anaemia yields a declining trend as various programmes were implemented between 2018 and 2020 including the iron and folic acid supplementation programme, village health and nutrition day, national iron+ initiative and anaemia Mukt Bharat.17 However, the years 2020–2021 and 2021–2022 have seen arise, probably the impact of COVID-19 pandemic, which has disrupted the healthcare system worldwide, including challenges to essential antenatal care services. Several studies conducted to study the impact of COVID-19 pandemic on maternal health and barriers faced by pregnant women to access healthcare during pandemic observed that pandemic resulted in deteriorated maternal and fetal outcomes on a global scale, with an upsurge in maternal deaths, stillbirths, ruptures ectopic pregnancies and maternal depression. Notably, there was a significant variation in certain outcomes between regions with abundant resources and those with limited resources.18–21 Despite the immediate impact of sickness, the COVID-19 pandemic exacerbated and amplified the already existing socioeconomic and health disparities.22 The global lockdowns, movement restrictions, fear of infection, healthcare system strain have led to destruction in antenatal services, thereby reducing the number of clinical visits or delay in seeking the screening and treatment for anaemia from healthcare centres. As the pandemic situation came under control by the end of 2022, the health services stabilised and the antenatal services were also re-established with due time.
While the burden of anaemia on maternal deaths has decreased on yearly basis, individual districts displayed variation across different years. Even though the burden of maternal anaemia has reduced in Karnataka, it remained high in certain regions or districts that clearly indicated the spatial disparities. The factors associated with maternal mortality were region or space-specific, and the use of geospatial analysis in maternal mortality and morbidity is still limited.23 Those districts identified as high-risk areas in the year 2017–2018 has shown decline in the subsequent year, probably reasons could be the multisectoral approach of the government initiatives. The number of districts that have been identified with more than 15% of maternal deaths attributed to anaemia was more than 10 in 2020–2021, this was probably because of the impact of COVID-19 pandemic, which disrupted the healthcare services as mentioned above. Once the system had been established, we saw a static percentage of maternal deaths attributed to anaemia of 7.7% during 2021–2022. Further, districts like Chikkamagaluru, Dakshina Kannada, Gadag and Udupi reported zero maternal death attributed to anaemia throughout the study period. Similar to our study, study conducted in Ethiopia aimed to observe that over one third of pregnant women were anaemic and the prevalence varied among Ethiopian administrative zones.24 Another study in Kenya showed that the accurate mapping of maternal health outcomes using routinely collected data was important for addressing subcountry disparities.25
Given the greater precision and detail afforded by areal interpolation compared with traditional thematic mapping, we opted to continue our analysis using areal interpolation methods. This technique has identified the regions near the districts of Bidar, Bagalkot, Bellary, Davangere, Kodagu and Haveri as the very highest risk areas and vulnerable populations while Gadag, Udupi, Dakshina Kannada, Chikkamagaluru and Chitradurga showed least risks. Sociodemographic characteristics identified in the NFHS 5 survey such as the high prevalence of anaemia among pregnant women (40%–60%), low body mass index among women (12%–25%), low levels of education (39%–58%), early marriage (12%–28%) and low coverage of health insurance schemes (15%–20%) were crucial factors. Additionally, lower rates of consumption of iron folic acid (IFA) supplementation among pregnant women for 180 days (16%–30%) underscore potential challenges. These factors collectively may contribute to MMA in high-risk districts. This insight for public health practice has facilitated evidence-based decision-making, where the policy-makers can design specific targeted interventions for these areas considering the local sociocultural background of the vulnerable population and allocate the resources efficiently, monitor the impact of this public health programme over the period.
According to the NFHS-5 study, pregnant women’s anaemia was most prevalent in Bidar, Chitradurga, Dharwad, Gadag, Haveri, Kalaburagi, Kodagu, Koppal, Raichur, Vijayapura and Yadgir. Further, to add the percentage of pregnant women who took IFA for at least 100 days during pregnancy was between 32% and 45% and for at least 180 days was between 15% and 25%.26–28 This could have led to a higher proportion of maternal deaths attributed to anaemia in these areas, thus, our study results correlate with the NFHS-5 survey. Similar study carried out in Tanzania using inverse distance weighted interpolation method found geographical differences in patterns of death.29 Another study conducted in Mozambique used spatial zero-inflated models where maps were used to highlight areas with increased or decreased mortality rate and such areas were found in south and north of Mozambique.30
Very few studies have focused on the spatial analysis of maternal anaemia in India, particularly in Karnataka. Furthermore, among the limited studies conducted in Karnataka, especially on maternal anaemia, we were able to identify this particular study conducted in North Karnataka focusing on anaemia in pregnant women. Study included 500 pregnant women and results from the study revealed that 93.4% were urban dwellers and sociodemographic parameters like age, residence, family size, education level and family income, with the exception of religion, seemed to be strongly associated with anaemia.31 According to research conducted in 2008, there was a statistically significant difference between the anaemia prevalence between employed women and homemakers.32 There was a variation in the distribution of anaemia in lower-income groups. Anaemia prevalence and economic growth were negatively associated at the national level. Education, money, occupation (such as agricultural labourers) and place of living all had an impact on anaemia societal patterns. Anaemia is typically a sign of socioeconomic deprivation; those with the lowest levels of education and income were most likely to be exposed to risk factors for anaemia and its after-effects.
Geospatial analysis offers numerous advantages over traditional methods in analysing maternal deaths. By providing a spatial perspective, integrating multiple data sources, identifying high-risk populations, enabling real-time decision-making and improving data communication, geospatial analysis has the potential to transform maternal healthcare. Geospatial analysis is a tool, which helps in decision-making for policy-makers by identifying geographically high maternal mortality and priority area.33 Areal interpolation along with the thematic mapping, has shown variations in the burden of MMA. Moreover, areal interpolation enables the integration of diverse data sources fostering collaboration across multiple sectors and the need for interdisciplinary approach to enhance the effectiveness of public health efforts, address the health disparities in combating anaemia and improve the overall health outcomes of pregnancy.
