The paradox of declining fertility and declining contraceptive use in India: An artefact of survey design?

•Ensuring data quality in large scale surveys is challenging.•The trend and pattern of declining fertility and declining contraceptive use in India is puzzling.•Interview privacy setting and interviewer effect can partially explain the anomaly.•Large scale surveys impose severe demands on survey supervision and ability to ensure privacy.•Innovative ways of data collection for sensitive issues can be explored for proper reporting.

Precarity in a Time of Uncertainty: Gendered Employment Patterns during the Covid-19 Lockdown in India.

India implemented one of the world's most stringent lockdowns in response to the COVID-19 crisis. This paper examines whether the impacts of the lockdown on employment differed by gender in areas surrounding Delhi. An ongoing monthly employment survey between March 2019 and May 2020 allows for comparison in employment before and after the lockdown. Estimates based on random-effects logistic regression models show that for men, the predicted probability of employment declined from 0.88 to 0.57, while that for women fell from 0.34 to 0.22. Women's concentration in self-employment may be one of the reasons why women's employment was somewhat protected. However, when we look only at wage workers, we find that women experienced greater job losses than men with predicted employment probability for wage employment for men declining by 40 percent compared to 72 percent for women.

Impact evaluation of a community engagement intervention in improving childhood immunization coverage: a cluster randomized controlled trial in Assam, India.

BACKGROUND: To improve immunization coverage, most interventions that are part of the national immunization program in India address supply-side challenges. But, there is growing evidence that addressing demand-side factors can potentially contribute to improvement in childhood vaccination coverage in low- and middle-income countries. Participatory engagement of communities can address demand-side barriers while also mobilizing the community to advocate for better service delivery. The objective of this study is to evaluate the impact of a novel community engagement approach in improving immunization coverage. In our proposed intervention, we go a step beyond merely engaging the community and strive towards increasing 'ownership' by the communities. METHODS/DESIGN: We adopt a cluster randomized design with two groups to evaluate the intervention in Assam, a state in the northeast region of India. To recruit villages and participants at baseline, we used a two-stage stratified random sampling method. We stratified villages; our unit of randomization, based on census data and randomly selected villages from each of the four strata. At the second-stage, we selected random sub-sample of eligible households (having children in the age group of 6-23 months) from each selected village. The study uses a repeated cross sectional design where we track the same sampled villages but draw independent random samples of households at baseline and endline. Total number of villages required for the study is 180 with 15 eligible HHs from each village. Post-baseline survey, we adopt a stratified randomization strategy to achieve better balance in intervention and control groups, leveraging information from the extensive baseline survey. DISCUSSION: The proposed intervention can help identify barriers to vaccination at the local level and potentially lead to more sustainable solutions over the long term. Our sampling design, sample size calculation, and randomization strategy address internal validity of our evaluation design. We believe that it would allow us to causally relate any observed changes in immunization coverage to the intervention. TRIAL REGISTRATION: The trial has been registered on 7th February, 2017 under the Clinical Trials Registry- India (CTRI), hosted at the ICMR's National Institute of Medical Statistics, having registration number CTRI/2017/02/007792 . This is the original study protocol.

Neighborhood heterogeneity in health and well-being among the elderly in India - Evidence from Study on global AGEing and adult health (SAGE).

We establish a rationale for a multilevel approach in examining health among older adults. Using data on a nationally representative sample of 6560 Indian adults aged 50 years and older, we examine the extent of contextual variation between neighborhoods, after accounting for the compositional effect of individuals' background characteristics, across multiple dimensions of elderly health. The variance apportioned to neighborhoods in null intercept-only models varied widely across different health outcomes examined in the elderly - while neighborhoods accounted for only 4% of the total variation in high blood pressure at exam, 23% of the total variation in self-rated poor quality of life could be attributed to neighborhood-level differences. In models that accounted for state, place of residence, and demographic and socioeconomic characteristics of individuals, the contribution of neighborhood to the total variation for most health outcomes was attenuated (2-11%) but persisted to exist. Our findings underscore the importance of neighborhoods in studying the health and well-being of the elderly in India.

Vaccination coverage in India: a small area estimation approach.

Information on population health indicators in India come from a number of surveys that vary in periodicity, scope and detail. In the case of immunization, the most recent coverage indicators are derived from the first round of Annual Health Survey (AHS-1, 2010-11), but these were conducted only in 9 of 35 states and union territories. The most recent national surveys of immunization coverage were conducted in 2009 (Coverage Evaluation Survey) by UNICEF. Therefore, reliable immunization coverage data for the entire country since 2009 is lacking. We used an established approach of small area estimation to predict coverage rates of several vaccinations for the remaining 26 states (not covered by AHS-1) in 2011. In our method, we considered a linear mixed model that combines data from five cross sectional surveys representing five different time points. Our model encompasses sampling error of the survey estimates, area specific random effects, autocorrelated area by time random effects and hence, borrows strength across areas and time points both. Model-based estimates for 2011 are almost identical to the AHS-1 estimates for the nine states, suggesting that our model provides reliable prediction of vaccination coverage as AHS-1 estimates are highly precise because of their large sample size. Results indicate that coverage inequality between rural and urban areas has been reduced significantly for most states in India. The National Rural Health Mission has had both supply side and demand side effects on the immunization programme in rural India. In combination, these effects may have contributed to the reduction of vaccination coverage gaps between urban and rural areas.