INTRODUCTION:

The financial burdens of pregnancy and childbirth, including out-of-pocket (OOP) costs, are closely tied to general health expenditures and socioeconomic, and demographic factors. Due to pandemic-related measures, global health spending has reached approximately 9% to 11% of GDP in recent years. These figures reflect the overall health spending trends. In OECD countries, health expenditure to GDP ratios decreased from 9.7% in 2021 to 9.2% in 2022 but remained above pre-pandemic levels.¹ In many countries, OOP health expenditures make up a significant portion of total health spending, posing financial risks for families. In India, the financial burdens of pregnancy and childbirth are influenced by socioeconomic and demographic factors, healthcare policies, and significant out-of-pocket costs. Health expenditure in India is around 3.2% of GDP, with public health spending making up less than half of the total. Private expenditure, particularly for maternity services, remains substantial.² Pregnancy, though joyous, can impose significant financial burdens on expectant mothers and their families, affecting their well-being. Understanding these socioeconomic and demographic correlates, along with OOP costs, is essential.³ Pandemics, such as COVID-19, exacerbate the financial strain by limiting healthcare access, increasing mental health issues, and worsening socioeconomic inequalities, complicating the financial situation of expectant mothers.⁴ Comprehensive analyses of these factors highlight inequalities and disparities in healthcare access and financial support during pregnancy.⁵

Socioeconomic and demographic factors significantly impact the financial burdens of pregnancy, especially for women in vulnerable groups. Income, education, and location play crucial roles in these costs. Prenatal, delivery and postnatal care expenses strain expectant mothers and families, particularly for those with lower income, limited education, and unstable employment.⁶ Challenges are heightened in rural or underserved areas with limited healthcare access. Identifying and understanding these factors is crucial for effective interventions.⁷ The Government of India and State Governments bear the responsibility of ensuring equitable healthcare access, backed by minimum service standards and effective regulatory mechanisms.⁸

Income level is a key determinant of the financial burden of pregnancy. Lower-income women face greater financial strain due to the high costs of prenatal care, childbirth, and postnatal expenses, which can hinder access to essential healthcare and support during pregnancy. Geographic location is another significant factor influencing these burdens, as the availability of affordable healthcare varies widely across regions. Rural and underserved areas typically have fewer healthcare resources, resulting in higher OOP costs for pregnant women.⁹ Exploring the specific OOP costs incurred by pregnant women is essential for understanding the financial implications of pregnancy. These costs include prenatal care, delivery, postnatal care, and other medical expenses. By analyzing these costs and their variations across different socioeconomic, and demographic groups, areas needing financial support can be identified, and targeted interventions can be developed.¹⁰

Public hospitals alleviate some financial burdens through free or subsidized services, contrasting with the higher OOP costs seen in private hospitals. This disparity emphasizes the need for policy interventions to improve healthcare access and financial support for expectant mothers, particularly in private healthcare settings. Efforts to address the socioeconomic, and demographic correlates are essential for reducing financial challenges and effectively supporting mothers, guiding the development of policies to ensure affordable, quality healthcare.¹¹ In addition to expanding insurance coverage, support programs such as subsidized childcare services and transportation assistance can ease the financial strain on mothers, particularly in underserved or rural regions. These programs help reduce overall pregnancy costs by eliminating barriers to accessing healthcare services. Furthermore, expanding access to affordable prenatal and postnatal care in underserved regions helps minimize geographic disparities in OOP costs, ultimately improving maternal and child health outcomes.¹²

Geographic location plays a crucial role in determining the financial burden of pregnancy. Women in rural or underserved areas face challenges in accessing quality prenatal care, leading to higher OOP costs and potentially influencing their health-seeking behaviors. High OOP costs can result in delays in seeking medical care, fewer prenatal visits, or opting for lower-quality care, all of which negatively affect pregnancy outcomes.¹³ Targeted strategies to alleviate financial burdens are essential for improving health-seeking behaviours and outcomes. Expanding comprehensive insurance coverage and support programs like subsidized childcare and transportation assistance can reduce OOP costs for pregnant women in vulnerable socioeconomic, and demographic groups.¹⁴Additionally, increasing the availability of affordable prenatal and postnatal care in underserved areas helps reduce geographic disparities in healthcare access, ultimately improving pregnancy outcomes. In light of the socioeconomic, demographic insights and out-of-pocket cost implications outlined above, our study aims to evaluate the impact of financial considerations on pregnancy outcomes, with a focus on enhancing healthcare access and support for expectant mothers.

METHODS:

A mixed-method study was conducted, incorporating both quantitative and qualitative components to investigate out-of-pocket expenditures during pregnancy and childbirth, focusing on the socioeconomic, demographic, and reproductive characteristics of women who gave live birth. The study carried out from January 2023 to December 2023, provided an in-depth analysis of factors influencing financial burdens across various months and seasons. Participants were recruited from healthcare facilities and community settings in the Agra district of Uttar Pradesh, India, representing diverse socio-economic backgrounds. From the total population of 76,350 women who gave live birth in the study setting from January 2023 to December 2023, 804 participants showed willingness to participate in the initial survey for sample recruitment. The quantitative segment involved a cross-sectional survey with structured questionnaires covering demographic characteristics, income levels, insurance coverage, and healthcare utilization patterns, as well as out-of-pocket expenses related to prenatal care (e.g., healthcare bills, medications, transportation, and indirect costs like lost wages). For the qualitative aspect, self-administered questionnaires and semi-structured in-depth interviews were used to delve into factors contributing to out-of-pocket expenditures during pregnancy.^14,15

All the health facilities providing prenatal and childbirth services in the Agra district, as well as home deliveries (home), were considered to be the potential source facilities, while the women who gave birth were considered sources of information. The women who gave live birth within one month during the timeframe from January 2023 to December 2023 in the sampled facilities were contemplated as the study population. The facility administration that showed unwillingness for the conduct of the study was excluded from the study. Women with specific medical conditions that could potentially confound the results and those unwilling to participate were also excluded from the study. This study was carried out in both urban and rural areas to ensure a diverse participant pool. By including participants from various settings, the study aimed to capture a wide range of socioeconomic, and demographic groups and geographical locations, enabling a comprehensive analysis of the disparities in health expenditure among pregnant women.¹⁶ From the total population of 76,350 women who gave live birth in the study setting from January 2023 to December 2023, 804 participants showed willingness to participate and were considered for the quantitative study. The total sample size (n) was determined based on the desired confidence level, margin of error, and the estimated proportion of live births, using the standard sampling formula. To ensure representation across various socioeconomic, and demographic segments such as income, education, and geographic location, a stratified random sampling method was employed. The sampling method comprised the participants across three clusters such as home deliveries, private hospital deliveries, and public hospital deliveries. This approach allowed for the selection of participants from different socioeconomic, and demographic backgrounds, ensuring that the study's findings were reflective of the population's diversity.¹⁷ The formula for proportional allocation when using stratified random sampling is:

nh = ------------ x n …………………………………(1)

Where,

nh is the sample size required for stratum h.

Nh is the population size of stratum h (the total number of live births in that stratum).

N is the total population size across all strata.

n is the total sample size required for the entire population.

The formula allocates a portion of the total sample size 𝑛n to each stratum based on the proportion of the population in that stratum, ensuring representation that reflects the true distribution of live births.^18,19

Out of the 804 participants who showed willingness to participate, 125 women gave birth at home, 308 women delivered in private hospitals, and 371 women gave birth in public hospitals. Based on the standard sampling formula and the proportional allocation formula, the total adjusted sample size was 428, which was then allocated to each cluster as 67 samples for home deliveries, 164 samples for private hospital deliveries, and 197 samples for public hospital deliveries. The sample size for each cluster was a proportional allocation based on the proportion of live births in each setting.²⁰ As a mixed methods study, a subset of 50 participants was purposefully selected for the qualitative component of the study. Additionally, those 50 participants were also purposively designated as key informants for the qualitative semi-structured in-depth interviews. This integrated methodology allowed for a comprehensive exploration of the research topic, combining the strengths of quantitative data analysis and qualitative insights from a select group of participants.

An in-house questionnaire (both quantitative and qualitative) was developed based on extensive research needs assessment and with valuable inputs from various experts, including government health officials, administrative officials, hospital administration, and public health officers. The quantitative study questionnaires are designed with clear research objectives in mind and aim to gather specific observations and insights that are crucial for informing decision-making processes. The Likert scale questions and interview questions in our questionnaire for qualitative study have been thoughtfully designed and developed, ensuring their relevance in capturing the targeted qualitative aspects we aim to explore. Careful consideration was given to the response options to offer participants a sufficient level of granularity in expressing their opinions, experiences, or attitudes. It is firmly believed that the questions in our in-house questionnaire are the most appropriate and effective approach for our research objectives.

Prior to the main study, each questionnaire (both quantitative and qualitative) underwent thorough pre-testing and quality checks on 10% of the sample population to ensure reliability and effectiveness. The results from the pre-testing were not included in the main study but were utilized to validate and fine-tune the questionnaire for optimal performance. Data collection was conducted by authors/data collectors using data abstraction formats and self-administered questionnaires, while the principal investigator conducted qualitative semi-structured in-depth interviews. Data collectors received four days of training on the data collection instruments and processes before commencing data collection. Furthermore, two experts from the health department of the district administration reviewed the interview guide for the in-depth interviews to validate its face and content.

The utilization of a robust study design such as quantitative and qualitative, diverse participant pool, and meticulous sampling technique facilitated a comprehensive exploration of the socioeconomic, demographic, and reproductive characteristics of pregnant women and the nuances of out-of-pocket expenditures during pregnancy. These methodological considerations enabled the identification of disparities in health expenditure among different socioeconomic, and demographic groups and the formulation of targeted recommendations for reducing the financial burden on expectant mothers.^21-23

ANALYSIS AND STATISTICS:

The analysis was performed in aggregate, and descriptive parameters such as frequency, mean, and standard deviation (SD) were calculated for different variables. To investigate the potential association between socioeconomic, and demographic variables and the choice of availing healthcare services from either public or private providers, or at home, a chi-square test was conducted using GraphPad Prism® Version 5.01 statistical software, with p-value ≤ 0.05 considered statistically significant. In the Likert scale method employed in the qualitative study, respondents were asked to rate their level of agreement or disagreement with each statement (total of 13 factors) using a 5-point scale from 1 to 5. The scale ranged from “1 - Strongly Disagree” to “5 - Strongly Agree”. Participants were instructed to select the response option that best represented their viewpoint. Based on the specific values of each response, the mean scores and standard deviations for each factor were computed. The analysis and interpretation of participant responses were used to evaluate the factors contributing to impaired public service utilization and out-of-pocket expenditure burden. Data from in-depth interviews were subjected to a thematic analysis approach. Key themes such as contributing factors and suggestions for reducing out-of-pocket expenditures (OOPE) were manually reviewed and handled.

RESULTS:

The obtained data provided valuable information into the socioeconomic, demographic, and reproductive characteristics of the participants, shedding light on the determinants of out-of-pocket expenditures during pregnancy. The findings revealed a diverse participant pool in terms of geographical area, age, education, income, employment, marital status, pregnancy, and childbirth history, offering a comprehensive representation of women who gave live birth from varied backgrounds.

QUANTITATIVE FINDINGS:

Socioeconomic, Demographic, and Geographic Variables:

The study encompassed pregnant women from both urban and rural areas, ensuring a diverse geographical representation. The participants' ages ranged from 18 to 40 years, with varying levels of education and income. Employment status varied, with participants encompassing various occupational roles. Marital status also varied, capturing the experiences of married, single, and divorced women. Additionally, a range of parity and gestational ages allowed for a comprehensive analysis of reproductive characteristics.

The Chi-square tests conducted on various socioeconomic, demographic, and geographic variables across three clusters of delivery locations (Home, Private Hospital, and Public Hospital) aimed at understanding its association with the financial burdens of pregnancy and related healthcare. The socioeconomic, demographic, and geographic variables across three clusters of delivery locations are shown in Table 1, along with the p values for differences. The study focused on 67 home deliveries, 164 private hospital deliveries, and 194 public hospital deliveries. There were no statistically significant differences in marital status and self-occupation regarding the choice of availing services from the healthcare sector for childbirth. However, factors such as residence, age, gravida, level of education, occupation of husband/guardian, monthly family income, distance to the health facility, and the number of hospital visits during pregnancy were significantly associated with differences in the choice of availing maternity-related healthcare services between the private sector, public sector, and non-healthcare sector (home).

Financial and Healthcare Utilization Variables:

The analysis of financial and healthcare utilization variables across the three clusters of women who gave live birth within the study setting revealed significant variations in expenditures, and the data are shown in Table 2. Public hospitals typically do not charge for consultations, diagnostics, and monthly medications, while private hospitals impose fees on all participants in varying amounts, which cannot be avoided. The distribution of OPD visits/consultation charges per visit varied widely, with the private hospitals incurring charges ranging from less than 500 INR to over 1000 INR. Lab and radiology expenditures similarly showed a diverse range, with some private hospital-delivered participants incurring significant expenditures exceeding 10,000 INR for lab tests and up to 10,000 INR for radiology services. Moreover, newborn care expenditures, nutritional expenses, and other expenses ranged significantly, especially for the women participants of private hospital deliveries. Regarding healthcare support, the presence of ASHA visits during pregnancy and the receipt of Janani Suraksha Yojana (JSY) benefits were documented, with varying proportions of participants receiving these services. Lastly, the source of money for expenditure was diversified, including daily wages, farming, government aid, insurance, loans, salaries, savings, and business income. These findings highlight the significant financial burden and diverse healthcare utilization experiences among the women participants in the study.

The analysis revealed distinct differences in financial burden and healthcare utilization among the participants who gave birth at home, in private hospitals, and public hospitals within the study setting. It is important to note that the participants who gave birth at home incurred negligible financial expenses compared to those who delivered in private or public hospitals. However, the healthcare utilization aspects for home deliveries were considered significantly poorer, marked by fewer OPD visits, minimal lab and radiology expenditures, and lower nutritional and medication costs. This lack of healthcare utilization is associated with increased risks for both the mother and newborn, highlighting potential gaps in accessing essential maternal healthcare services. Despite not facing considerable financial burdens, the absence of adequate medical support and supervision during home deliveries underscores the critical need for improving maternal healthcare outreach and ensuring safe delivery practices. These findings emphasize the importance of enhancing healthcare utilization to mitigate associated risks and improve outcomes for mothers and newborns in home birth settings.

Qualitative Findings:

Perceived factors contributing to the burden of OOPE on pregnancy and related healthcare expenses

All respondents were provided with questionnaires containing thirteen factors believed to affect service utilization and the financial burden of out-of-pocket expenses on pregnancy and related healthcare. Responses were evaluated using a 5-point Likert scale. The most common perceived factors contributing were "Inadequate government maternity care facilities lead to a reliance on more expensive private services" – 3.88 (1.18) [Mean (SD)], "Rising costs of prenatal and postnatal care services create a significant financial strain" – 3.76 (1.16), "Limited availability of essential medicines and supplies in government hospitals leads to additional costs" – 3.70 (1.28), and " Low real monthly disposable income worsens the financial impact of pregnancy-related expenses" - 3.64 (1.41). The mean score of all the responses on different contributing factors is shown in Table 3.

Qualitative semi-structured in-depth interview findings:

In-depth interviews were carried out with all qualitative study participants (n = 50), and responses were gathered. The interviews focused on three main areas: factors that contribute to impaired public service utilization, strategies for improving the burden of OOPE on pregnancy-related expenses, and suggestions to the government/policymakers in reducing the burden of OOPE on pregnancy-related expenses.

Factors that contribute to impaired public service utilization:

The key informants highlighted several contributing factors, such as prolonged wait times at OPD and drug counters, insufficient infrastructure in government hospitals, and the lack of branded medicines in these facilities. They also pointed out that misconceptions regarding the quality of services in public health facilities play a significant role in hindering service utilization.

Strategies for improving the burden of OOPE on pregnancy-related expenses:

Key informants were asked for their insights on strategies to enhance facility-level approaches to alleviate the burden of out-of-pocket expenses. Suggestions included enhancing government facility infrastructure and capacity, augmenting staffing and equipment to minimize long waiting times, and lessen dependence on private services. Also, some of the key informants mentioned offering more financial counselling services to help families understand and navigate their medical bills, and explaining available government subsidies and how to apply for them.

Suggestions to the Government/policymakers in reducing the burden of OOPE on pregnancy-related expenses:

The respondents were asked to provide suggestions to the government or policymakers on how to improve service utilization and reduce the OOPE. Increasing funding for maternal healthcare in public hospitals to ensure that all essential services and medications are available free of charge. They also suggested that policies should be implemented to regulate and control the costs of prenatal and postnatal services in private hospitals, ensuring they are affordable. This could include setting a maximum price cap on certain necessary services and procedures. Some of the key informants mentioned that introducing government subsidies specifically tailored to pregnancy-related healthcare costs could directly alleviate the financial burden on households. These targeted financial supports could make a substantial difference in ensuring equitable access to quality maternity care without incurring excessive out-of-pocket expenses.

Table 1: Descriptive Statistics on the Socioeconomic, Demographic, and Geographic factors across three clusters of women who gave live birth in the study setting (January 2023 to December 2023), Agra District, Uttar Pradesh, India

Variable	Home N (%) n=67	Private N (%) n=164	Public N (%) n=197	Chi-square statistic (χ²) and P value*
Residence
Urban	3 (4.5)	143 (87.2)	111 (56.3)	137.7 and <0.0001
Rural	64 (95.5)	21 (12.8)	86 (43.7)	137.7 and <0.0001
Age
18-25	35 (52.2)	109 (66.5)	122 (62)	19.53 and 0.0034
26-35	28 (41.8)	55 (33.5)	73 (37)
36-45	4 (6)	0 (0)	1 (0.5)
>45	0 (0)	0 (0)	1 (0.5)
Gravida
Primigravida	8 (12)	77 (47)	48 (24.4)	34.89 and <0.0001
Multigravida	59 (88)	87 (53)	149 (75.6)	34.89 and <0.0001
Level of Education
None	14 (20.9)	15 (9.2)	13 (6.6)	21.64 and 0.0014
High School or Below	33 (49.3)	63 (38.4)	104 (52.8)
Higher Secondary or Diploma	18 (26.8)	75 (45.7)	73 (37)
Degree/Graduates or Above	2 (3)	11 (6.7)	7 (3.6)
Marital Status
Married	66 (98.5)	163 (99.4)	195 (99)	1.90 and 0.7541^ns
Widowed	1 (1.5)	1 (0.6)	1 (0.5)
Divorced	0 (0)	0 (0)	1 (0.5)
Occupation of Husband/Guardian
Casual Labour	19 (28.4)	12 (7.3)	70 (35.5)	140.3 and <0.0001
Cultivator	36 (53.7)	28 (17.1)	86 (43.7)
Employed (Salaried)	0 (0)	66 (40.2)	18 (9.1)
Employed (Self)	12 (17.9)	58 (35.4)	23 (11.7)
Occupation (Self)
Casual Labour	8 (11.9)	17 (10.4)	16 (8.1)	17.55 and 0.0631^ns
Cultivator	11 (16.4)	9 (5.5)	23 (11.7)
Home Maker	48 (71.7)	123 (75)	147 (74.6)
Employed (Salaried)	0 (0)	7 (4.3)	2 (1)
Employed (Self)	0 (0)	3 (1.8)	2 (1)
Student	0 (0)	5 (3)	7 (3.6)
Monthly Family Income
<5000 INR	39 (58.2)	24 (14.6)	57 (28.9)	154.8 and <0.0001
5001-10000 INR	18 (26.9)	18 (11)	99 (50.3)
10001-15000 INR	8 (11.9)	65 (39.6)	18 (9.1)
>15000 INR	2 (3)	57 (34.8)	23 (11.7)
Distance to Health Facility
Up to 5 KM	32 (47.8)	25 (15.2)	50 (25.4)	26.85 and <0.0001
More than 5 KM	35 (52.2)	139 (84.8)	147 (74.6)	26.85 and <0.0001
No. of Visits to Hospital During Pregnancy
None	25 (37.3)	0 (0)	0 (0)	201.3 and <0.0001
One or two	22 (32.8)	22 (13.4)	19 (9.6)
Three	15 (22.4)	58 (35.4)	117 (59.4)
Four and more	5 (7.5)	84 (51.2)	61 (31)

*𝑃 value ≤ 0.05 was considered statistically significant, ns – non-significant

N-Frequency, %-Percentage, n-total respondents in the respective category, INR-Indian Rupee currency

Table 2: Financial and Healthcare Utilization variables across three clusters of women who gave live birth in the study setting (January 2023 to December 2023), Agra District, Uttar Pradesh, India

Variables	Type of Hospital for Availing Health Service
Variables	Home N (%) n=67	Private N (%) n=164	Public N (%) n=197
OPD Visits/Consultation Charges Per Visit
Free of Charge/NA	25 (37.3)	0 (0)	173 (87.8)
<500 INR	42 (62.7)	103 (62.8)	16 (8.1)
501-1000 INR	0 (0)	42 (25.6)	8 (4.1)
>1000 INR	0 (0)	19 (11.6)	0 (0)
Lab Expenditure
Free of Charge/NA	30 (44.8)	0 (0)	153 (77.7)
<1000 INR	28 (41.8)	45 (27.4)	31 (15.7)
1001-5000 INR	9 (13.4)	85 (51.8)	13 (6.6)
5001-10000 INR	0 (0)	28 (17.1)	0 (0)
>10000 INR	0 (0)	6 (3.7)	0 (0)
Radiology Expenditure
Free of Charge/NA	29 (43.3)	0 (0)	149 (75.6)
<1000 INR	38 (56.7)	24 (14.6)	17 (8.6)
1001-5000 INR	0 (0)	125 (76.2)	24 (12.2)
5001-10000 INR	0 (0)	15 (9.2)	7 (3.6)
Transportation Expenditure
Free of Charge/NA	49 (73.1)	0 (0)	27 (13.7)
<500 INR	13 (19.4)	56 (34.1)	152 (77.2)
501-1000 INR	5 (7.5)	67 (40.9)	8 (4.1)
1001-2000 INR	0 (0)	29 (17.7)	7 (3.5)
>2000 INR	0 (0)	12 (7.3)	3 (1.5)
Monthly Medicine Expenses
Free of Charge	61 (91)	0 (0)	172 (87.3)
<500 INR	6 (9)	80 (48.8)	11 (5.6)
501-1000 INR	0 (0)	34 (20.7)	8 (4.1)
1001-2000 INR	0 (0)	22 (13.4)	6 (3)
>2000 INR	0 (0)	28 (17.1)	0 (0)
Newborn Care Expenditure
Free of Charge	0 (0)	9 (5.5)	174 (88.3)
<1000 INR	0 (0)	91 (55.5)	11 (5.6)
1001-4000 INR	0 (0)	38 (23.1)	8 (4.1)
4001-10000 INR	0 (0)	26 (15.9)	3 (1.5)
>10000 INR	0 (0)	0 (0)	1 (0.5)
Nutrition Expenditure
Free of Charge/NA	38 (56.7)	49 (29.9)	115 (58.4)
<1000 INR	15 (22.4)	24 (14.6)	56 (28.4)
1001-5000 INR	11 (16.4)	67 (40.9)	17 (8.6)
>5000 INR	3 (4.5)	24 (14.6)	9 (4.6)
Other Expenses
NA	28 (41.8)	0 (0)	0 (0)
<500 INR	17 (25.4)	120 (73.2)	144 (73.1)
500-1000 INR	12 (17.9)	20 (12.2)	34 (17.3)
1001-2000 INR	10 (14.9)	17 (10.3)	13 (6.6)
>2000 INR	0 (0)	7 (4.3)	6 (3)
ASHA Visit during Pregnancy
Yes	37 (55.2)	162 (98.8)	197 (100)
No	30 (44.8)	2 (1.2)	0 (0)
Janani Suraksha Yojana (JSY) Benefits
Yes	0 (0)	86 (52.4)	170 (86.3)
No	67 (100)	78 (47.6)	27 (13.7)
Source of Money on Expenditure
Daily Wages	27 (40.3)	15 (9.2)	16 (8.1)
Farming	30 (44.8)	28 (17.1)	32 (16.2)
Government Aid	0 (0)	45 (27.4)	124 (62.9)
Insurance	0 (0)	4 (2.4)	0 (0)
Loan	10 (14.9)	5 (3)	2 (1.1)
Salary	0 (0)	34 (20.7)	3 (1.5)
Savings	0 (0)	17 (10.4)	20 (10.2)
Business	0 (0)	16 (9.8)	0 (0)

N-Frequency, %-Percentage, n-total respondents in the respective category, INR-Indian Rupee currency, OPD-Out Patient Department, NA-Not Applicable

Table 3: Perceived factors contributing to the burden of OOPE on pregnancy and related healthcare expenses in the study setting (January 2023 to December 2023), Agra District, Uttar Pradesh, India (n=50)

S. No	Contributing Factors	Frequency (%)					Mean (SD)
S. No	Contributing Factors	SD	D	N	A	SA	Mean (SD)
1	Rising costs of prenatal and postnatal care services create a significant financial strain	1 (4)	2 (4)	3 (5)	4 (24)	5 (13)	3.76 (1.16)
2	Rising inflation increases the overall cost of pregnancy-related healthcare	1 (16)	2 (1)	3 (7)	4 (21)	5 (5)	2.96 (1.46)
3	Government spending on prenatal, delivery, and postnatal care is insufficient	1 (10)	2 (4)	3 (12)	4 (20)	5 (4)	3.08 (1.26)
4	Prescriptions often include high-cost branded maternity drugs and supplies that are expensive	1 (16)	2 (8)	3 (7)	4 (10)	5 (9)	2.76 (1.52)
5	Limited availability of essential medicines and supplies in government hospitals leads to additional costs	1 (7)	2 (2)	3 (3)	4 (25)	5 (13)	3.7 (1.28)
6	Utilization of government maternity medical services is poor due to perceived inadequacies	1 (10)	2 (6)	3 (4)	4 (14)	5 (16)	3.4 (1.52)
7	Inadequate government maternity care facilities lead to a reliance on more expensive private services	1 (3)	2 (5)	3 (5)	4 (19)	5 (18)	3.88 (1.18)
8	Government schemes targeting the reduction of OOPE for maternity care are not sufficient	1 (15)	2 (6)	3 (10)	4 (12)	5 (7)	2.8 (1.44)
9	Government schemes for reducing OOPE in maternity care are not effectively reaching the target population	1 (10)	2 (6)	3 (3)	4 (21)	5 (10)	3.3 (1.43)
10	Most pregnant women do not have sufficient health insurance coverage to cover pregnancy-related expenses	1 (13)	2 (6)	3 (5)	4 (12)	5 (14)	3.16 (1.58)
11	Private maternity medical services are perceived to offer better quality of care compared to public services	1 (13)	2 (8)	3 (4)	4 (12)	5 (13)	3.08 (1.57)
12	Dependence on private maternity services, which are more costly, significantly contributes to OOPE	1 (23)	2 (8)	3 (4)	4 (10)	5 (5)	2.32 (1.46)
13	Low real monthly disposable income worsens the financial impact of pregnancy-related expenses	1 (8)	2 (3)	3 (5)	4 (17)	5 (17)	3.64 (1.41)

SD-Strongly Disagree, D-Disagree, N-Neutral, A-Agree, SA-Strongly Agree, Mean (SD)- Mean (Standard Deviation)

Response scores ranged from Strongly Agree (5) to Strongly Disagree (1)

DISCUSSION:

In this study, the quantitative analysis unveiled significant correlations between various socioeconomic, demographic geographic factors and out-of-pocket costs during pregnancy and related healthcare.²⁴ It was found that factors such as education, income, and geographic location were closely associated with the level of financial burden experienced by pregnant women.²⁵ Higher educational attainment and income were linked to lower out-of-pocket expenses, highlighting the influence of socioeconomic status on health expenditure during pregnancy. Furthermore, the analysis identified disparities in out-of-pocket costs between urban and rural areas, underscoring the need for targeted interventions to address the financial challenges faced by pregnant women in different geographic locations.^26,27

Out-of-pocket expenditure (OOPE) in India remains high, accounting for about 63% of the total health spending, which is significantly above the global average. Public healthcare infrastructure is often overburdened and underfunded, leading many people to turn to private clinics where fees are higher. Health insurance coverage is limited, leaving most outpatient costs to be paid directly by individuals. Additionally, the cost of medicines and diagnostic services remains high due to insufficient government regulation, which increases the financial burden on households.²⁸ Efforts to expand public healthcare infrastructure, increasing awareness and penetration of government health insurance schemes like Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), and regulating the cost of essential medicines and diagnostics could reduce OOPE in the future. Additionally, the initiatives by the government of India to distribute generic medicines at affordable prices have created a wave of competition in the industry. By making essential medications more affordable and accessible, the promotion of generic drugs aligns with the overarching goal of lowering healthcare costs for the general public.²⁹

This study’s findings illuminate the complex interplay between socioeconomic, demographic, and geographic factors and the financial burdens associated with pregnancy and related healthcare, particularly as they relate to out-of-pocket costs and the choice of delivery location. Age, gravida status, education level, occupation of husband/guardian, distance to health facilities, and the number of hospital visits during pregnancy emerge as significant determinants in the financial decision-making process for delivery locations. These factors can influence not only the direct costs, such as fees for delivery services but also indirect costs including transportation and additional hospital visits. The absence of significant associations with marital status and the respondent's occupation suggests that the direct costs of delivery and related healthcare services might be more universally challenging, regardless of these factors. However, the husband's occupation's near-significant association with delivery location choice hints at the influence of household income or financial stability on such decisions.

The significant association between delivery location choice and distance to health facilities, as well as the number of hospital visits, underlines the critical role of accessibility and the need for frequent healthcare interventions in shaping the financial burdens of pregnancy. This points towards a need for policy interventions that could include improving transportation infrastructure, reducing travel costs for pregnant women, and enhancing insurance coverage or financial support for those requiring frequent medical attention. In terms of health insurance, our quantitative and qualitative findings showed a very low portion of patients on health insurance, which is overall 2.4% in whole sampled participants, and it is one of the significant perceived contributing factors in escalating the OOPE issues. Concerning the issue of financial inequality, pregnant women who had lower household incomes were subject to higher financial burdens. The government should prioritize advancing the promotion of comprehensive health insurance schemes. Understanding all these dynamics is crucial for designing effective policies and interventions aimed at minimizing the financial burdens of pregnancy.³

The financial variables analyzed in this study underscore the diverse and significant financial burdens associated with pregnancy, reflecting both direct healthcare costs and broader socioeconomic and demographic factors influencing out-of-pocket expenses. In the case of public vs. private healthcare, public hospitals play a crucial role in alleviating financial burdens through free or subsidized services, including JSY benefits, radiology, and newborn care. However, the presence of significant out-of-pocket costs in private hospitals highlights disparities in access to affordable care. In terms of socioeconomic and demographic correlations, variations in financial burdens across different types of expenditures suggest that factors, such as income, education, and geographic location, significantly influence healthcare choices and the associated costs. For instance, transportation and nutrition expenses reveal underlying disparities in access to care and support services. Lastly, on policy implications, the findings highlight the need for targeted policy interventions to address the financial barriers faced by expecting mothers, especially in private healthcare settings. Expanding coverage for essential services, increasing the availability of free or subsidized care, and addressing indirect costs like transportation and nutrition could significantly reduce the financial stress on families.

In parallel, the qualitative analysis provided rich insights into the nuanced experiences of pregnant women with out-of-pocket expenditures. Themes such as emotional distress and coping strategies emerged from the interviews, emphasizing the multifaceted impact of financial strain on expectant mothers. The qualitative findings complemented the quantitative results by providing a deeper understanding of the practical and emotional implications of out-of-pocket costs, thereby contributing to a comprehensive depiction of the financial challenges faced during pregnancy.^30,31

The inadequacy of government maternity care facilities, which often results in a dependence on costly private services, is a concerning issue that can exacerbate the financial burden on expectant mothers. This reliance on private services is driven by the perceived lack of quality and accessibility in public healthcare institutions, leading to increased expenditure for individuals seeking maternal healthcare services. Also, the rising costs associated with prenatal and postnatal care services further compound the financial strain on families, particularly those with limited resources, which can significantly impact the financial well-being of individuals and families, especially when combined with the limited availability of essential medicines and supplies in government hospitals. The additional costs incurred due to the necessity of sourcing these items from private providers further escalate the overall financial burden. Moreover, the low real monthly disposable income among individuals facing pregnancy-related expenses intensifies the economic challenges they encounter.

Key informants highlighted critical factors contributing to impaired public service utilization, emphasizing the need for infrastructure improvements, better staffing, and dispelling misconceptions about service quality in public health facilities. Strategies proposed by informants centered on enhancing government facility capabilities, offering financial counselling, and advocating for more comprehensive government subsidies to alleviate the burden of out-of-pocket expenses on pregnancy-related healthcare costs. Overall, the integrated analysis of both quantitative and qualitative data allowed for a comprehensive exploration of the determinants of out-of-pocket costs during pregnancy. The findings underscore the complexity of factors influencing health expenditure and highlight the critical need for targeted interventions to alleviate the financial burden on expectant mothers, ultimately improving maternal and child health outcomes.²⁷

STRENGTHS AND LIMITATIONS OF THE STUDY:

The study exhibits several strengths, including comprehensive data collection through structured questionnaires and semi-structured interviews, ensuring a detailed exploration of socioeconomic, and demographic profiles and the impact of out-of-pocket expenses on health-seeking behaviours. The representative sample derived through stratified random sampling, comprising participants from various delivery settings, enhances the sample's representativeness. The integration of quantitative and qualitative analyses provides a nuanced understanding of the relationship between socioeconomic, demographic characteristics, and financial variables, offering valuable insights into out-of-pocket costs during pregnancy and childbirth. The inclusion of pregnant women from diverse urban and rural backgrounds amplifies the generalizability of findings. However, the study is limited by self-reporting bias and geographical focus, which pose limitations despite its valuable insights. Notably, the study's narrow focus on service utilization and out-of-pocket expenses in public and private hospitals may warrant further exploration of quality and outcomes in private healthcare settings.

CONCLUSION:

The comprehensive analysis of both quantitative and qualitative data has yielded valuable insights into the determinants of out-of-pocket costs during pregnancy and childbirth, shedding light on the financial burden experienced by expectant mothers among diverse socioeconomic and demographic profiles. These findings revealed notable trends and correlations between various socioeconomic, and demographic factors and healthcare expenditure, providing a nuanced understanding of the factors influencing health costs during pregnancy. The integration of structured questionnaires and semi-structured interviews enabled a deeper exploration of the emotional and practical implications of financial strain on pregnant women, especially across different geographic locations. The study's outcomes will form a crucial foundation for developing targeted interventions to alleviate the financial burden on expectant mothers and enhance maternal and child health outcomes. By emphasizing the financial challenges associated with pregnancy, this research underscores the importance of comprehensive policy measures to ensure equitable access to essential care and support across healthcare settings.

ETHICAL CONSIDERATIONS:

The study addressed ethical considerations in various aspects of its design and implementation. Ethical approval was obtained from the Agra district hospitals in compliance with the declaration of the Chief Medical Officer of the Agra district administration (Ref No: CMO/AGRA HO/08/2022/02). Furthermore, permission from each study facility’s administration was obtained to conduct the study, ensuring adherence to ethical guidelines. The participants were provided with clear and comprehensive information about the study, ensuring transparency and informed consent. Their personal information was treated with utmost confidentiality and was solely used for the purpose of the study. Informed consent was obtained in writing from each participant, emphasizing their autonomy to withdraw from the study at any point. The confidentiality of the participants was maintained by using codes rather than personal identifiers in all data collection and analysis processes. This rigorous approach to confidentiality and ethical standards underscores the commitment to upholding the rights and well-being of the study participants.

ACKNOWLEDGMENTS:

The authors acknowledge the Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology, Varanasi, Uttar Pradesh, India, for their support and encouragement in completing this project. The authors express gratitude to the study participants, including health professionals, study facility administrations, and the Agra district administration, for their necessary support.

FUNDING:

There was no funding source at any level of the project. So, the project was entirely non-funded. All expenses were borne by the authors themself.

CONFLICT OF INTERESTS:

All authors declare that they have no competing interests.

DATA AVAILABILITY:

The datasets used and analyzed during the study are available upon reasonable request.

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Received on 04.06.2024 Revised on 09.09.2024

Accepted on 13.11.2024 Published on 24.12.2024

Available online from December 27, 2024

Research J. Pharmacy and Technology. 2024;17(12):5713-5723.

DOI: 10.52711/0974-360X.2024.00870