Fieldworker effects on quality of data collected on sensitive questions in National Family Health Surveys: An analysis based on intimate partner violence in India.

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.

A longitudinal study of incident hypertension and its determinants in Indian adults aged 45 years and older: evidence from nationally representative WHO-SAGE study (2007-2015).

Objectives: Hypertension (HT) is a leading cause of mortality and morbidity in developing countries. This study aimed to estimate the incidence of HT among adults aged 45 years and older in India and its associated risk factors. Methods: This study used longitudinal data from the Indian sample of the first and second waves of the World Health Organization Study on Global Ageing and Adult Health (WHO-SAGE). A bivariate analysis using Pearson's chi-square test was done to examine the associations of individual, lifestyle, and household characteristics with HT status reported in Wave 2. Incident HT changes were analyzed by adjusting for various covariates in the generalized estimating equation (logit link function) with an exchangeable correlation matrix and robust standard errors. Results: The study found that during the 8-year period from 2007 to 2015, the incidence of HT in individuals aged 45 years and over was 20.8%. Pre-hypertensive individuals had an overall incidence rate of 31.1 per 1,000 [95% confidence interval (CI): 26.20-35.9] and a 2.24 times higher odds ratio: 2.24 (95% CI: 1.65-3.03) of developing incident HT compared to those who were normotensive. Adults aged 45 years and older, overweight/obese individuals, and women were more at risk of incident HT. Conclusion: One in five individuals had developed HT over 8 years, with a greater risk of incident HT among women than men. Pre-hypertensive individuals were at a greater risk of developing incident HT compared to normotensive individuals. The study recommends comprehensive and effective management of pre-HT to tackle the burden of HT.

Concurrent Undernutrition and Overnutrition within Indian Families between 2006 and 2021.

Background: The double burden of malnutrition (DBM), characterized by concurrent undernutrition and overnutrition, is a growing global concern. Families share resources and eating behaviors and programs often target households, yet evidence of the DBM at the family level is scarce. Objectives: This study examined trends and inequality in the intrahousehold DBM in India between 2006 and 2021. Methods: Data were from 3 waves of India's National Family Health Survey (NFHS 2006, 2016, and 2021). We examined 3 types of household member (with children aged <5 y) combinations: mother-child (N = 328,039 across 3 waves), father-child, and parent (mother and father)-child (N = 47,139 for each pair). The DBM was defined as one or more individuals with undernutrition (either wasting or stunting in children or underweight in adults) and one or more overweight individuals within the same household. DBM was examined over time, at national and subnational levels, and by residence and wealth. Results: Nearly all DBM was in the form of an overweight parent and an undernourished weight or stunted child. The prevalence of parent-child DBM increased from 15% in 2006 to 26% in 2021. Father-child pairs experienced the most rapid DBM increase, from 12% in 2006 to 22% in 2021, an 83% increase, driven by increasing overweight among men. In 2021, the DBM was highest in North-Eastern and Southern states, and among relatively rich households from urban areas. The increase in the DBM was faster in rural areas and among poor households compared with that in urban areas and rich households. Urban-rural and rich-poor inequalities in the DBM have decreased over time. Conclusions: The intrahousehold DBM has increased over time, affecting 1 in 4 households in India in 2021. Family-based interventions that can simultaneously address child underweight and parent overweight are required to address India's increasing intrahousehold DBM.

Cultural and Contextual Drivers of Triple Burden of Malnutrition among Children in India.

This study examines malnutrition's triple burden, including anaemia, overweight, and stunting, among children aged 6-59 months. Using data from the National Family Health Survey-5 (2019-2021), the study identifies risk factors and assesses their contribution at different levels to existing malnutrition burden. A random intercept multilevel logistic regression model and spatial analysis are employed to identify child, maternal, and household level risk factors for stunting, overweight, and anaemia. The study finds that 34% of children were stunted, 4% were overweight, and 66% were anaemic. Stunting and anaemia prevalence were higher in central and eastern regions, while overweight was more prevalent in the north-eastern and northern regions. At the macro-level, the coexistence of stunting, overweight, and anaemia circumstantiates the triple burden of childhood malnutrition with substantial spatial variation (Moran's I: stunting-0.53, overweight-0.41, and anaemia-0.53). Multilevel analysis reveals that child, maternal, and household variables play a substantial role in determining malnutrition burden in India. The nutritional health is significantly influenced by a wide range of determinants, necessitating multilevel treatments targeting households to address this diverse group of coexisting factors. Given the intra-country spatial heterogeneity, the treatment also needs to be tailor-made for various disaggregated levels.

Clustering of child deaths among families in low and middle-income countries: A meta-analysis.

Background and Aims: Several studies have examined the phenomenon of "death clustering," in which two or more children born to the same mother or from the same family die at an early age. Therefore, a scientific examination of the results is essential to understand how the survival status of the older siblings affects the survival of the younger siblings. By using meta-analysis, this study aims to provide a quantitative synthesis of the results of studies on "child death clustering" in low- and middle-income countries (LMICs). Methods: This study followed the PRISMA-P 2015 guidelines. We used four electronic databases-PubMed, Medline, Scopus, and Google Scholar with search and citation analysis capabilities. Initially, 140 studies were identified, but only 27 met the eligibility criteria eventually. These were studies that had used the death of a previous child as a covariate to determine the survival status of the index child. The heterogeneity and the publication bias of the studies were examined using the Cochran test, I 2 statistic, and Egger's meta-regression test. Results: The pooled estimate of 114 study estimates for LMICs contains some bias. India's 37 study estimates were distributed more or less equally along the middle line, indicating no publication bias, while there was a slight bias in the estimates for Africa, Latin America, and Bangladesh. The odds of experiencing the death of the index child in the selected LMICs were 2.3 times higher for mothers who had lost any prior child as compared to those mothers who had not had any prior child loss. For African mothers, the odds were five times higher, whereas for Indian mothers, the odds were 1.66 times higher. Mothers' characteristics, such as education, occupation, health-seeking behavior, and maternal competence, significantly affect the child's survival status. Conclusion: Achieving the sustainable development goals would not be possible if mothers in countries experiencing high levels of under-five mortality are not provided with better health and nutrition facilities. Mothers who have lost multiple children should be targeted for assistance.

Multimorbidity combinations and their association with functional disabilities among Indian older adults: evidence from Longitudinal Ageing Study in India (LASI).

OBJECTIVE: This study aims to identify the unique multimorbidity combinations (MMCs) and their associations with the functional disability of Indian older adults. Moreover, the population attributable fractions (PAFs) were calculated to assess the potential impact of additional diseases in the nested groups on disability. DESIGN: A cross-sectional data were analysed in this study. SETTING AND PARTICIPANTS: The present study uses data from the first wave of the Longitudinal Ageing Study in India (2017-2018). The sample for the study consists of 27 753 aged 60 years and over. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome variable was functional disability, measured by the combined activities of daily living (ADL)-instrumental activities of daily living (IADL) index. RESULTS: Out of 197 uniquely identified MMCs, the combination of hypertension and high depressive symptoms (HDS) was the most prevalent (10.3%). Overall, all MMCs were associated with increased functional limitation. Specifically, the combination of hypertension, arthritis and HDS was associated with greater ADL-IADL disability than any other MMC. The addition of HDS in group 3 (hypertension and arthritis) (incidence rate ratios (IRR)=1.44; 95% CI 1.26 to 1.64) and the addition of arthritis in group 1 (hypertension, HDS) (IRR=1.48; 95% CI 1.28 to 1.71) and group 2 (hypertension, diabetes) (IRR=1.49; 95% CI 1.22 to 1.82) significantly increases the rates of ADL-IADL disability. The estimated PAFs of the group 1 (hypertension and HDS), group 3 (hypertension and arthritis) and group 4 (arthritis and HDS) for ADL-IADL disability were 22.5% (19.2-25.5), 21.6% (18.7-24.4) and 23.5% (20.6-26.3), respectively. CONCLUSION: The findings from this study underscore the importance of addressing the morbidity combinations which are more disabling than the others in older adults. Understanding the somatic and psychological relevance of the morbidities in functional health is necessary and can help reduce disabilities among older adults.

Comparing socio-economic inequalities in self-reported and undiagnosed hypertension among adults 45 years and over in India: what explains these inequalities?

BACKGROUND: Hypertension (HTN) is a leading cause of mortality and morbidity in developing countries. For India, the hidden burden of undiagnosed hypertension is a major concern. This study aims to assess and explain socio-economic inequalities among self-reported and undiagnosed hypertensives in India. METHODS: The study utilized data from the Longitudinal Aging Study in India (LASI), a nationally-representative survey of more than 72,000 older adults. The study used funnel plots, multivariable logistic regression, concentration indices, and decomposition analysis to explain the socio-economic gap in the prevalence of self-reported and undiagnosed hypertension between the richest and the poorest groups. RESULTS: The prevalence of self-reported and undiagnosed hypertension was 27.4 and 17.8% respectively. Monthly per capita consumption expenditure (MPCE) quintile was positively associated with self-reported hypertension but negatively associated with undiagnosed hypertension. The concentration index for self-reported hypertension was 0.133 (p < 0.001), whereas it was - 0.047 (p < 0.001) for undiagnosed hypertension. Over 50% of the inequalities in self-reported hypertension were explained by the differences in the distribution of the characteristics whereas inequalities remained unexplained for undiagnosed hypertension. Obesity and diabetes were key contributors to pro-rich inequality. CONCLUSIONS: Results imply that self-reported measures underestimate the true prevalence of hypertension and disproportionately affect the poorer MPCE groups. The prevalence of self-reported HTN was higher in the richest group, whereas socio-economic inequality in undiagnosed hypertension was significantly concentrated in the poorest group. As majority of the inequalities remain unexplained in case of undiagnosed hypertension, broader health systems issues including barriers to access to health care may be contributing to inequalities.

Role of seasonality variation in prevalence and trend of childhood wasting in India: An empirical analysis using National Family Health Surveys, 2005-2021.

Background: Wasting develops over a short period and can be reversed with short-term interventions. The prevalence of wasting typically varies from season to season-becoming higher during the monsoon (June to September) season as compared to the winter (October to January) and summer (February to May) seasons every year in a cyclical fashion. However, to the best of our knowledge, using nationally representative demographic surveys to extensively study the impact of the timing of the survey on the results and trends around wasting has not been done so far. Objectives: The goal of this study is to ascertain whether seasonality has an impact on the trend and levels of wasting between NFHS-3 (2005-2006) and NFHS-5 (2019-2021). Methods: The analysis was based on data on 51,555, 259,627, and 232,920 children under 5 years included in NFHS-3, NFHS-4, and NFHS-5 respectively. Multivariable logistic regression analysis and the predicted probabilities approach were employed to examine the effect of the months of interview on the prevalence of wasting. The analysis was conducted for 9 states of India which had data for comparable months to compute wasting levels. Results: We found that at the national level, wasting increased in India by one per cent from NFHS-3 to NFHS-4 but declined by 2% from NFHS-4 to NFHS-5. The results show that seasonality significantly influenced the prevalence of wasting. It was observed that compared to January, the odds of wasting were particularly higher in summer and monsoon seasons, especially in the month of August across all three rounds, indicating the influence of seasonality in the prevalence of wasting in the country. Discussion: The prevalence of wasting in India needs to be interpreted across seasonal changes as seasonality affects many of the variables intrinsically related to child health and nutritional status.

Intra-cluster correlations in socio-demographic variables and their implications: An analysis based on large-scale surveys in India.

Individuals who share similar socio-economic and cultural characteristics also share similar health outcomes. Consequently, they have a propensity to cluster together, which results in positive intra-class correlation coefficients (ICCs) in their socio-demographic and behavioural characteristics. In this study, using data from four rounds of the National Family Health Survey (NFHS), we estimated the ICC for selected socio-demographic and behavioural characteristics in rural and urban areas of six states namely Assam, Gujarat, Kerala, Punjab, Uttar Pradesh, and West Bengal. The socio-demographic and behavioural characteristics included religion & caste of the household head, use of contraception & prevalence of anaemia among currently married women and coverage of full immunization services among children aged 12-23 months. ICC was computed at the level ofPrimary Sampling Units (PSUs), that is, villages in rural areas and census enumeration blocks in urban areas. Our research highlights high clustering in terms of religion and caste within PSUs in India. In NFHS-4, the ICCs for religion ranged from the lowest of 0.19 in rural areas of Kerala to the highest of 0.67 in urban areas of West Bengal. For the caste of the household head, the ICCs ranged from the lowest of 0.12 in the urban areas of Punjab to the highest of 0.46 in the rural areas of Assam. In most of the states selected for the study, the values of ICC were higher for the use of family planning methods than for full immunization. The value of ICC for use of contraception was highest for rural areas of Assam (0.15) followed by rural areas of Gujarat (0.13). A higher value of ICC has considerable implications for determining an effective sample size for large-scale surveys. Our findings agree with the fact that for a given cluster size, the higher the value of ICC, the higher is the loss in precision of the estimate. Knowing and taking into account ICCs can be extremely helpful in determining an effective sample size when designing a large-scale demographic and health survey to arrive at estimates of parameters with the desired precision.

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis.

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (p < 0.01). Bivariate analysis suggests that women with two or more infant losses were much less likely to have full immunization (10%) than women with no infant loss (62%), although institutional delivery was high among both groups of women.

Effectiveness of modular approach in ensuring data quality in large-scale surveys: Evidence from National Family Health Survey - 4 (2015-2016).

This study aims to examine the effect of administration of shorter and longer versions of questionnaires on key indicators such as age displacement, birth displacement, age heaping, and skipping questions on antenatal care (ANC) visits and use of contraceptive methods in India using National Family Health Survey (NFHS)-4 data. At the individual level, the effect of the adoption of the shorter and longer versions of the questionnaires on the age displacement of women and children and skipping of the key questions is insignificant. However, the results from the two-level logistic regression model reveal that at the primary sampling unit (PSU) level, work pressure, depending on the number of eligible women in a household, emerges as a confounder in skipping certain questions, namely ANC [1.18 (p < 0.09)] and contraceptive use [AOR = 1.17 (p < 0.05)]. To expand the coverage of NFHS in providing state- and district-level estimates since 2015, the overall sample size was increased from 88,562 households and 89,777 eligible women in 1992-93 to 6,01,509 households and 6,99,686 eligible women in 2015-16. As a strategy to reduce workload and non-sampling errors during the survey, a nested design and modular approach were adopted to provide estimates of maternal and child health indicators at the district/state level and sexual behaviour, HIV/AIDS, and women's empowerment at the state level. It was hypothesised that a longer version of the questionnaire canvassed in the state module may be detrimental to data quality issues. The findings of this study establish the effectiveness of adopting a modular approach in large-scale surveys, depending on the scale of investigation. However, the differential workload calls for expanding the duration of surveys in PSUs, where the number of eligible women is higher. State level variation in the key data quality indicators may be partially explained by differentials in the training of investigators by the agency and use of translators.

Assessing the role of depressive symptoms in the association between social engagement and cognitive functioning among older adults: analysis of cross-sectional data from the Longitudinal Aging Study in India (LASI).

OBJECTIVE: The present study aimed to examine the confounding effects of depressive symptoms and the role of gender in the association between social engagement and cognitive functioning among older Indian adults. DESIGN: Large-scale cross-sectional survey data were analysed. SETTING AND PARTICIPANTS: Data from the Longitudinal Aging Study in India (2017-2019) were used in the analysis. The sample included 23 584 individuals aged 60 years and above (11 403 men and 12 181 women). OUTCOME MEASURES: The outcome variable was cognitive functioning, which was based on various measures including immediate and delayed word recall, orientation, executive functioning, arithmetic ability and object naming. Social engagement measure consists of marital status, living arrangement, availability of confidant, and participation in indoor games, and social and cultural functions. The Center for Epidemiological Studies-Depression Scale was used to assess depressive symptoms. RESULTS: Significant gender differences in mean cognition scores (men: 25.8, women: 21.1; on a scale of 0-43) were observed. Two-way stratification between social engagement and depressive symptoms was significantly associated with cognitive functioning after controlling for selected explanatory factors. Older men with a low level of social engagements had significantly poor cognitive functioning (ß=-1.12; 95% CI: -1.53 to -0.72) compared with men with a high level of social engagements. On the other hand, women with a higher level of social engagement performed poorly on cognitive tests (ß=-1.54; 95% CI: -2.11 to -0.98) compared with men with higher social engagements. Three-way stratification between social engagement, gender and depressive symptoms suggests that social engagement's buffering effects are lower in women than in men. The Karlson-Holm-Breen method identified a significant confounding effect of depressive symptoms on the relationship between social engagement and cognitive functioning. CONCLUSION: The positive association of social engagement with cognitive functioning was significantly confounded by depressive symptoms, suggesting the need for maintaining social relations that help improve mental health and cognitive functioning among older adults.

Survey implementation process and interviewer effects on skipping sequence of maternal and child health indicators from National Family Health Survey: An application of cross-classified multilevel model.

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.

Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.

India has adopted a target-based approach to reduce the scourge of child malnourishment. Because the monitoring and evaluation required by this approach relies primarily on large-scale data, a data quality assessment is essential. As field teams are the primary mode of data collection in large-scale surveys, this study attempts to understand their contribution to variations in child anthropometric measures. This research can help disentangle the confounding effects of regions/districts and field teams on the quality of child anthropometric data. The anthropometric z-scores of 2,25,002 children below five years were obtained from the fourth round of India's National Family and Health Survey (NFHS-4), 2015-16. Unadjusted and adjusted standard deviations (SD) of the anthropometric measures were estimated to assess the variations in measurements. In addition, a cross-classified multilevel model (CCMM) approach was adopted to estimate the contribution of geographical regions/districts and teams to variations in anthropometric measures. The unadjusted SDs of the measures of stunting, wasting, and underweight were 1.7, 1.4, and 1.2, respectively. The SD of stunting was above the World Health Organisation threshold (0.8-1.2), as well as the Demographic and Health Survey mark. After adjusting for team-level characteristics, the SDs of all three measures reduced marginally, indicating that team-level workload had a marginal but significant role in explaining the variations in anthropometric z-scores. The CCMM showed that the maximum contribution to variations in anthropometric z-scores came from community-level (Primary Sampling Unit (PSU)) characteristics. Team-level characteristics had a higher contribution to variations in anthropometric z-scores than district-level attributes. Variations in measurement were higher for child height than weight. The present study decomposes the effects of district- and team-level factors and highlights the nuances of introducing teams as a level of analysis in multilevel modelling. Population size, density, and terrain variations between PSUs should be considered when allocating field teams in large-scale surveys.

An association between multi-morbidity and depressive symptoms among Indian adults based on propensity score matching.

Keeping in view the cascade of disturbances caused by the co-existence of multi-morbidity and depression among aged population, this study aims to ascertain the independent impact of multi-morbidity as a risk factor for the development of depressive symptoms among adults living in India. The present study utilizes data from the nationally representative survey "Longitudinal Ageing Study in India" (LASI, Wave-1, 2017-2018). The eligible sample size was 62,244 adults aged 45 years and above. Descriptive statistics along with bivariate analysis was used to understand the prevalence of depressive symptoms. Further, binary logistic regression and Propensity Score Matching (PSM) methods were applied to examine the independent effect of multi-morbidity on depressive symptoms while controlling the selected background characteristics. Overall, around one-third respondents had at least one chronic disease and one-fifth had multi-morbidity. The most prevalent chronic disease reported in the sampled population was hypertension followed by diabetes and joint disease. It is observed that older adults with multiple chronic diseases had 77% higher odds of having depressive symptoms as compared to those without a history of chronic disease in the multivariable logistic regression model. Results obtained from PSM indicate that the risk of having depressive symptoms was 3.7% higher for adults with multi- morbidity. Depressive symptom was identified to be associated with a wider range of multiple physical health problems and people with multi-morbidity are at a higher risk of having depressive symptoms. It is imperative that multi-morbidity can be used as a screener for identifying people with depressive symptoms.

Sterilization incentives and associated regret among ever married women in India, NFHS, 2015-16.

OBJECTIVE: Sterilization is the only family planning method that involves relatively large amount compensation. So, the study attempts to examine the role of incentives received against the sterilization procedures on the reporting of sterilization regret in India. METHODS: The study used data from the fourth round of National Family Health Survey, 2015-16, which gathered the information on sterilization regret from 1,94,207 ever-married women. Multivariate logistic analysis and predicted probabilities approach was used to study the effect of compensation received on the sterilization regret in India. RESULTS: Results show that women who have received compensation were 33% less likely to report sterilization regret. It was found that 70% of women who undergone sterilization in public facility didn't incur any expenditure, rather received incentives. It is observed that women who had undergone operation in private facility spent a large amount than women who had done their operation in public facility. The regret in the private facility mainly results from high out of pocket expenditure on sterilization procedures. Around eight percent of women regretted getting sterilized in a private hospital and received some compensation amount, vis a vis the six percent who regretted undergoing sterilization in public facility and received compensation. CONCLUSION: The study calls for a need to standardize the cost of sterilization procedure in India's health facilities. A good alternative for reducing the cost could be Public-Private Partnership.

Validity of self-reported hypertension in India: Evidence from nationally representative survey of adult population over 45 years.

Self-reported measures of health, in the context of developed countries, are well-researched and commonly regarded as reliable predictors of the underlying health of the population. However, the validity of these measures is under-researched and questionable in the context of low- and middle-income countries. The authors used Longitudinal Ageing Study in India (LASI) survey data from India to compare self-reported hypertension with biometrically-measured hypertension. The results are reported in terms of sensitivity, specificity, and kappa as a measure of agreement. Logistic regression was undertaken to examine the characteristics of those who were unaware of their hypertensive status. Our analysis showed a low sensitivity of 56% and a high specificity of 90.5%. Agreement between self-reported data and biometric measurement of hypertension was observed to be moderate (κ = 0.48). Large variations were observed among states and sub-groups. The odds of false negative reporting of hypertension were lower in the individuals with higher age, high education, and greater wealth status. The authors conclude that self-reported hypertension has important limitations and may be a source of systematic bias. It is recommended that planning and policy-making in India be based more on an objective assessment of hypertension.

The trends of female sterilization in India: an age period cohort analysis approach.

In India, sterilisation is the most frequent method of modern contraception, and is primarily used by women. The contemporaneous assessment of sterilisation literature focuses only on trends and patterns that are limited to socioeconomic considerations, ignoring the cohort and period issues. No study has employed Age Period Cohort (APC) analysis to highlight the effect of APC on a particular outcome to yet. We have used maximum entropy method modelling to analyse the individual influence of APC on female sterilisation in India using the four rounds of the National Family Health Survey (NFHS). While the older group had higher sterilisation rates than the younger cohort, the age effects were found to have a standard inverted U-shaped curve, with women sterilising in their mid-30s as the might have completed their desire family size. The analysis found high rural-urban differentials in utilising female sterilisation, highlighting the relevance of education and empowerment in contraceptive decision-making among the educated one. Female sterilisation has become less common among Muslims in India over time, and among uneducated women, and it has shifted to later ages with each succeeding period. This was determined to be concerning in terms of India's future fertility. Since 1947, the government has implemented numerous policies to provide women with a variety of contraceptive options; however, the dominance of female sterilisation throughout all periods demonstrates that the government's efforts to provide temporary methods were futile.

Infant mortality and death clustering at the district level in India: A Bayesian approach.

This study assessed the clustering of and spatial variations in infant mortality between districts in selected states of India using a Bayesian geoadditive model. The study utilized 10 years of retrospective birth history of women from the fourth round of NFHS-4 (2015-16). Findings suggest, except Kerala, there was a significant amount of clustering of infant deaths in families in the selected Indian states. The maximum impact of clustering was observed in Assam, followed by Madhya Pradesh, Bihar, Uttarakhand, and Uttar Pradesh. The estimated residual spatial effect was statistically significant in all the states, with the maximum effect being in Assam and Chhattisgarh. The risk of infant death in Assam was higher in the north-eastern districts and lower in the southern districts of the state. Mother's age at child birth had a nonlinear effect on infant death in all the states, although significant effects were observed only in Bihar and Assam. In both of these states, mother's age at child birth had a "U-shape," showing that the risk of infant death was higher at both earlier and later ages of mother's reproductive period. With the exception of Kerala, all the other selected states in the study had an "elongated L shaped" pattern, showing that in the early ages of the reproductive period, the risk of infant death was very high and that it gradually decreased with age and remained constant thereafter. In Kerala, mother's age at child birth was a straight line, implying that the risk of infant death was constant across the reproductive age of women. In order to keep infant mortality at a low level and to achieve better maternal and child health outcomes, the government needs to target families experiencing multiple infant deaths. In addition, programs must take into consideration the prevailing state-specific spatial heterogeneity in infant deaths and factors like mother's age at child birth.

Role of maternal and child health services on the uptake of contraceptive use in India: A reproductive calendar approach.

BACKGROUND: According to the latest round of National Family Health Survey-4 (NFHS (2015-16)) maternal and child health care (MCH) services improved drastically compared to NFHS-3. Previous studies have established that the uptake of MCH services increases the likelihood of early adoption of contraceptives among women. So, our study aims to examine if the early initiation of contraceptive has proportionately improved with the recent increase in MCH services. METHODS: This study used the reproductive calendar of NFHS-4, 2015-16, to evaluate contraceptive initiation within 12 months after the last birth among 1,36,962 currently married women in India. A complementary log-log regression model was created to examine the link between the time of initiation of contraception and MCH care at the national level. RESULTS: It was found that only a quarter of women within 12 months from last birth have adopted the modern contraceptive method. Among those majority of the females adopted sterilization mostly at the time of birth. The multivariable model identified, that the period of initiation of contraceptive depends on the gender composition of children and access to MCH services. It was found that the odds of early initiation of contraceptive use was higher when a women have only son (AOR = 1.15,95% CI- 1.22, 1.18) compared to women with only daughter. Also, it was found that women who have availed MCH services were more likely to adopt contraceptives earlier. CONCLUSION: The number of women availing MCH services has increased in India, but it did not result in a proportional increase in initiation of contraception after childbirth. Facilitating family planning services alongside MCH services will be beneficial in low-resource settings. It is a golden opportunity to educate and encourage women for early adoption of contraceptive.