Implementing a large-scale survey involves a string of intricate procedures exposed to numerous types of survey errors. Uniform and systematic training protocols, comprehensive survey manuals, and multilayer supervision during survey implementation help reduce survey errors, providing a consistent fieldwork environment that should not result in any variation in the quality of data collected across interviewers and teams. With this background, the present study attempts to delineate the effect of field investigator (FI) teams and survey implementation design on the selected outcomes. Data on four of the bigger Empowered Action Group (EAG) states of India, namely Uttar Pradesh, Madhya Pradesh, Bihar, and Rajasthan, were obtained from the fourth round of the National Family Health Survey (NFHS-4) for analysis. A fixed-effect binary logistic regression model was used to assess the effect of FI teams and survey implementation design on the selected outcomes. To study the variation in the outcome variables at the interviewer level, a cross-classified multilevel model was used. Since one interviewer had worked in more than one primary sampling unit (PSU) & district and did not follow a perfect hierarchical structure, the cross-classified multilevel model was deemed suitable. In addition, since NFHS-4 used a two-stage stratified sampling design, two-level weights were adjusted for the models to compute unbiased estimates. This study demonstrated the presence of interviewer-level variation in the selected outcomes at both inter- and intra-field agencies across the selected states. The interviewer-level intra-class correlation coefficient (ICC) for women who had not availed antenatal care (ANC) was the highest for eastern Madhya Pradesh (0.23) and central Uttar Pradesh (0.20). For ‘immunisation card not seen’, Rajasthan (0.16) and western Uttar Pradesh (0.13) had higher interviewer-level ICC. Interviewer-level variations were insignificant for women who gave birth at home across all regions of Uttar Pradesh. Eastern Madhya Pradesh, Rajasthan, and Bihar showed higher interviewer-level variation across the selected outcomes, underlining the critical role of agencies and skilled interviewers in different survey implementation designs. The analysis highlights non-uniform adherence to survey protocols, which implies that not all interviewers and agencies performed in a similar manner in the field. This study recommends a refined mechanism for field implementation and supervision, including focused training on the challenges faced by FIs, random vigilance, and morale building. In addition, examining interviewer-level characteristics, field challenges, and field agency effects may also highlight the roots of interviewer-level variation in the data. However, based on the interviewer's performance in the field, the present study offers an intriguing insight into interviewer-level variations in the quality of data.

National Family Health Survey (NFHS) has played a pivotal role in formulating policies and programs by providing nationally representative data on a wide range of monitoring and impact evaluation indicators in population, health and nutrition. However, due to measurement errors resulting in misreporting, the collection of accurate data on sensitive issues in sample surveys has always been a matter of concern. This study examines the fieldworker effect on the reporting of physical, sexual, and emotional Intimate Partner Violence (IPV) using fifth round of NFHS (2019-21) data in India. The cross-classified multi-level model was used to examine the fieldworker's effect on the reporting of IPV. The fieldworker effect accounted for around 32% of total variation in the reporting of intimate partner violence. The fieldworker's effect varied from 26% to 41 % for physical violence, 29% to 33% for emotional IPV and 30%–36% for sexual IPV. It was observed that variation due to fieldworker for non-sensitive outcomes was negligible.Of total variation, only 1.6% for information related to ever attending school, 4.8% for ever given birth, 5% for currently pregnant and 8.5% for information on ever terminated pregnancy was being explained by the fieldworker. Our results indicate a significant fieldworker influence on the likelihood of reporting intimate partner violence, underlining the need for an increased understanding of the impact of fieldworkers on data outputs, especially—but not exclusively—when queries contain delicate or stigmatized themes. This study highlights the importance of providing extra guidance and special training to the fieldworkers when collecting sensitive information related to IPV.

Non‐communicable diseases (NCDs) account for a major portion of morbidity and mortality worldwide, with older persons being especially vulnerable due to age‐related health concerns. The burden of chronic diseases among India's aging population is understudied, particularly in terms of gender and age differences. The study utilized data from the Longitudinal Ageing Study in India (LASI), wave 1 (2017–18), comprising a sample of 66,606 older adults aged 45 years and above. We performed a Mmultivariable logistic regression analysis to examine the age‐gender differences in the prevalence and patterns of nine chronic diseases, namely hypertension, diabetes, cancer, chronic heart disease, stroke, psychiatric disorders, chronic lung disease, bone and joint diseases, and high cholesterol among older adults after adjusting for various socio‐demographic and lifestyle factors. Compared to male respondents, female older respondents were less likely to have diabetes and stroke (in the 45–59 and 60–69 years age groups), chronic lung diseases (in the 45–59 years age group), and chronic heart diseases (in the 60–69 years age group). Conversely, in the 70 years and above age group, older female respondents had higher odds of having hypertension and bone and joint diseases compared to male respondents. The current study revealed significant gender and age‐related differences in the prevalence and odds of all the nine selected diseases even adjusted for potential confounding factors. The findings highlight how urgently age‐ and gender‐specific treatments are needed to reduce inequities in chronic diseases, boost positive health outcomes, and improve the quality of life for India's aging populations.

Civil registration of births and deaths underpins people’s legal identity, access to essential services, and evidence-based policy. Over the last two decades, the expansion of the National Health Mission (NHM) and the dramatic increase in institutional deliveries have created new opportunities to link maternal healthcare with critical event documentation. Primary health centres (PHCs) and community health centres (CHCs), which are frequently the initial point of contact for rural households, are emerging as important places for birthing and registration. Despite their expanding importance, the particular role of these grassroots facilities in birth registration results has not been thoroughly investigated. This study addresses that gap by assessing their role in increasing registration coverage among children under the age of five. We analyzed nationally representative data from the National Family Health Survey rounds 4 (2015–2016) and 5 (2019–2021). This study focused on children under five, examining the association between place of delivery and registration status. Descriptive analysis and multivariable logistic regression estimated the odds of registration across delivery settings. Pooled data from both survey rounds captured temporal shifts, and predicted probabilities were calculated for institutional deliveries, adjusting for socio-demographic covariates. The proportion of institutional births occurring in PHCs and CHCs rose from 30.5% to 34.7% between the two survey rounds. Registration among children delivered in these facilities increased from 80.8% to 90.2%, the highest gain among all delivery settings. Regression analysis showed that births in PHCs/CHCs were associated with 38% higher odds of being registered compared to private facilities. States designating PHCs and CHCs as official registrars, such as Delhi, Rajasthan, and Uttar Pradesh, reported the greatest improvements. Lower-level government health facilities are not only advancing safe delivery but also acting as pivotal nodes for civil registration. Their dual function creates a scalable model for integrating healthcare with legal identity creation, supporting equity and accelerating progress toward Sustainable Development Goal 16.9.

An accurate and efficient sampling design plays a vital role in ensuring the reliability, validity, and representativeness of data collected through large-scale surveys. As survey research and data science have developed, the ways of planning and carrying out sampling have steadily evolved to keep up with new challenges and technologies. This study presents a comprehensive systematic analysis of the evolution of sampling design, exploring global trends, methodological developments, and thematic progressions within this essential field. Drawing on 262 publications published between 1979 and 2024, the research maps the trajectory of scholarly contributions, highlighting both established and emerging areas of interest. The analysis of country contributions demonstrates long-standing leadership from particular high-output nations, as well as increased engagement from developing countries. Thematic findings highlight a consistent increase in scholarly output over recent decades, with a focus on methodological issues such as variance estimates, sampling weights, and probabilistic design techniques. Network, factorial, and trend studies demonstrate these concepts' interconnection and changing importance within the subject. This study not only synthesizes decades of academic discourse but also underscores the need for continuous methodological refinement to address the complexities of modern data environments. The findings offer valuable direction for future research and contribute to strengthening the foundations of survey methodology.

Background and Aims: Fertility and child mortality are critical public health indicators in India, directly influencing health policy, planning, and intervention effectiveness. The relationship between declining fertility and decreasing child mortality has been widely debated. This study aims to estimate and compare fertility and child mortality rates at the district level using data from the National Family Health Survey (NFHS) rounds 4 and 5, with a focus on understanding regional trends and their implications for health interventions. Methods: The study investigates four key demographic indicators: Total Fertility Rate (TFR), Neonatal Mortality Rate (NMR), Infant Mortality Rate (IMR), and Under‐Five Mortality Rate (U5MR). Fertility and child mortality rates were estimated using Bayesian methods, aligned with Demographic and Health Survey (DHS) standards. Fertility rates were computed in two stages: first, birth history data were transformed into table of birth, followed by the calculation of fertility rates through Poisson regression models at the district level. Results: Between 2015–16 and 2019–21, the number of districts with a TFR below 1.6 increased from 21 to 166, while number of districts with a TFR between 1.6 and 2.1 remained stable at 328. Additionally, the number of districts with an NMR under 10 per 1,000 live births grew from 79 to 140. The study found a strong association between the reduction in child mortality and the decline in fertility rates. Conclusion: This study suggests that addressing regional variations in fertility and child mortality rates could enhance the effectiveness of health interventions in India. Policymakers should prioritize expanding access to family planning and maternal‐child health services. The availability of district‐level data will support more targeted and effective health policies tailored to local needs.