# Outcome Comparability and SWOC (Strength-Weakness-Opportunity-Challenges) Analysis of the National Family Health Survey (NFHS) 1 to 5 for Demographic, Maternal and Child Health, and Behavioral Determinants

## TL;DR

This study evaluates the National Family Health Survey (NFHS) data from 1 to 5 to assess its usefulness for improving health programs and achieving global health goals.

## Contribution

The paper introduces a SWOC analysis of NFHS data to identify strengths, weaknesses, opportunities, and challenges for public health policy and program development.

## Key findings

- There was a deviation in sub-criterion identification across NFHS rounds, complicating data use.
- The lowest decline in stunting, wasting, and unmet family planning need was -2.5%, -4.3%, and 1%, respectively.
- Strengths include data quality and new assessment tools, while weaknesses involve unsynchronized survey rounds.

## Abstract

The effective development of health programs requires the practical application of evidence-based strategies, equitable financial allocation, and the integration of operational research into public health actions. These elements are essential for attaining measurable improvements in healthcare systems and population well-being. By aligning research-driven approaches with policy implementation, we can accelerate progress toward achieving Sustainable Development Goal 3 (SDG-3) targets. This study aimed to engage in an in-depth, evidence-based quantitative and qualitative analysis of National Family Health Survey (NFHS) datasets, as well as a category and sub-category-wise comparability assessment of health indicators. Each round of the NFHS outcomes was analyzed for its application towards programmatic development, implementation, and evaluation. Studies analyzed were representative of each of the studied categories, i.e., demography, maternal health, child health, and behavioral pattern. Literature published under the subheads demography (159), maternal health (286), child health (318), and behavioral pattern (94) and indexed on PubMed Central were analyzed for inferential patterned study. This was followed by the outcome comparability and Strength-Weakness-Opportunity-Challenges (SWOC) analysis of trends, emphasis, and applicability. This trend analysis was quantitatively and qualitatively analyzed.

There was a deviation in sub-criterion identification over various rounds, posing challenges to the use of NFHS data with multiple, varied, and rich resources available for healthcare and support. The lowest expected decline per round compared to their previous rounds in stunting, wasting, and unmet need for family planning was -2.5%, -4.3%, and 1%, respectively. In contrast, the lowest increase per round for female sterilization and antenatal care (ANC) was +1.3% and +1%, respectively. Strengths include the quality of data, sub-categorization over NFHS rounds, use of new tools for assessments, and elimination of some parameters. Weakness was illustrated through unsynchronized conduct of rounds, viz., 6, 7, 10, and 5 years' time gap observed in NFHS-1, 2, 3, 4, and 5, respectively. Opportunity of using data for national development initiatives and fulfilling Sustainable Development Goal-3 can be availed to benefit the healthcare-deprived masses. Threats include intrinsic limitations of data collection, processes of outcome measures for addressing upgradation needs, especially of Reproductive, Maternal, Neonatal, Child Health + Adolescents (RMNCH+A), National Programme for Prevention and Control of Non-Communicable Disease (NPNCD), and national nutrition programs. The policy development, programmatic design, intervention implementation, effectiveness assessment, and National Health Program evaluation need stronger, consecutive, and appropriate evidence datasets for public health action. The felt need of public health intervention can be augmented significantly by using NFHS datasets over time while ensuring adaptable, flexible, and resource-friendly mechanisms of action. Triangulating NFHS datasets, programmatic needs, and financial allocations will hence help create user-friendly public health networks.