Double burden of malnutrition among women of reproductive age: Trends and determinants over the last 15 years in India.

INTRODUCTION: Double burden of malnutrition (DBM) has been recognized by the World Health Organisation (WHO) as an emerging Global Syndemic characterized by the simultaneous occurrence of both undernutrition and overnutrition. Women of the reproductive age group (15 to 49 years) are disproportionately affected by DBM and are at high risk of continuing the intergenerational cycle of malnutrition. This study aims to assess the changing trends and determinants of DBM among women of the reproductive age group in India. MATERIALS AND METHODS: We used data from three rounds of National Family Health Surveys (NFHS-3,4,5) conducted in years 2005-06, 2015-16, and 2019-2021. Descriptive statistics and Poisson regression analysis were done using weights with log link function. RESULTS: The prevalence of anaemia, underweight and overweight/obesity was 57.2%, 18.6% and 24% respectively. The combined burden of underweight and anaemia has declined by 46% (21.6% to 11.7%), whereas the combined burden of overweight/obesity and anaemia has increased by 130% (5.4% to 12.4%) in the past 15 years. The prevalence of DBM, which includes both underweight and overweight/obesity with anaemia was 24.1% in 2021, a decline of 11% in 15 years. Women who were younger, rural, less educated, poor and middle class, and women living in the eastern, western and southern regions of India had higher risk for being underweight with anaemia and lower risk for developing overweight/obesity with anaemia. CONCLUSION: The significant decrease in underweight yet enormous increase in overweight/obesity over the past 15 years with the persistence of anaemia in both ends of the nutritional spectrum is characteristic of the new nutritional reality emphasizing the need to address malnutrition in all its forms. It is critical to consider geography and a population specific, double-duty targeted intervention to holistically address the risk factors associated with DBM and accomplish India's commitment to the global agenda of Sustainable Development Goals-2030.

Trends in prevalence and determinants of severe and moderate anaemia among women of reproductive age during the last 15 years in India.

BACKGROUND: Anaemia is a serious global public health problem that disproportionally affects children, adolescent girls, and women of reproductive age, especially pregnant women. Women of reproductive age are more vulnerable to anaemia, particularly severe and moderate anaemia leads to adverse outcomes among pregnant women. Despite continuous Government efforts, anaemia burden still poses a serious challenge in India. The objective of this study is to assess the trends in prevalence and determinants of severe and moderate anaemia among women of reproductive age between 15 and 49 years. METHOD: We used three rounds of the large-scale National Family Health Survey (NFHS) India, conducted on a representative sample of households using a cross-sectional design across the country in 2005-06, 2015-16 and 2019-2021. We included all the women aged 15 to 49 years in our analysis. We used the same haemoglobin (Hb) cut-off values for all the three rounds of surveys to ensure comparability. Generalized linear regression analyses with log link were done. Survey weights were incorporated in the analysis. RESULTS: The prevalence of severe or moderate Anaemia (SMA) in non-pregnant women was 14.20%, 12.43% and 13.98%; it was 31.11%, 25.98% and 26.66% for pregnant women in 2006, 2016 and 2021 respectively. The decline in SMA prevalence was 1.54% in non-pregnant women, whereas it was 14.30% in pregnant women in 15 years. Women who were poor, and without any formal education had a higher risk for severe and moderate Anaemia. CONCLUSION: Despite the intensive anaemia control program in India, SMA has not declined appreciably in non-pregnant women during the last two decades. Despite the decline, the prevalence of SMA was about 26% in pregnant women which calls for a comprehensive review of the existing anaemia control programmes and there must be targeted programmes for the most vulnerable and high-risk women such as rural, poor and illiterate women of reproductive age to reduce the burden of anaemia among them.

Utility of the lateral flow urine lipoarabinomannan tuberculosis assay in patients with advanced HIV disease at antiretroviral therapy centres in Mumbai, India.

BACKGROUND: People with Advanced HIV Disease (AHD) are at higher risk of TB coinfection and mortality. However, there are challenges in TB diagnosis with the currently recommended diagnostic tools. WHO recommends lateral flow urine lipoarabinomannan (LF-LAM) assay to assist TB diagnosis among AHD patients. We assessed the utility and acceptability of using urine LF-LAM assay for TB diagnosis among patients at public Antiretroviral Therapy (ART) Centres in Mumbai. METHODS: The cross-sectional study was conducted among adult AHD patients accessing care from 17 ART centres during November,2020-June, 2021. Urine LF-LAM was offered as routine care for eligible patients in combination with standard diagnostic tests. We calculated the proportion of positive LF-LAM results by CD4 categories and TB symptoms and performed multivariable logistic regression to determine the factors associated with LF-LAM positivity. RESULTS: Among 2,390 patients, the majority (74.5%) had CD4 between 101-200 cells/mm3. The mean age was 43.7 years (SD:10.6), 68.6% were male, 8.4% had TB symptoms and 88.0% were on ART. The overall proportion of patients with urine LF-LAM positive results was 6.4%. Among PLHIV with CD4≤100 cells/mm3, the positivity was 43.0% and 7.7% in symptomatic and asymptomatic patients, respectively. Among PLHIV with a CD4>100 cells/mm3, the positivity was 26.7% and 2.7% in symptomatic and asymptomatic patients respectively. Urine LF-LAM positivity was higher among inpatients, ART naïve, patients on treatment for <6 months, symptomatic and in WHO clinical stage III/IV of HIV disease as compared to the reference categories. We detected an additional 131 TB cases with urine LF-LAM in combination with the standard diagnostic tests. CONCLUSION: The study demonstrated the utility of urine LF-LAM for TB diagnosis among AHD patients and the simple, user-friendly test was acceptable as part of routine care. Inclusion of urine LF-LAM test in the current diagnostic algorithm may facilitate early TB diagnosis among AHD patients.

The clinical demand and supply of blood in India: A National level estimation study.

BACKGROUND: Estimating the clinical demand for blood and components arising in a health facility is crucial to ensure timely availability of blood. This study aims to estimate disease-specific clinical demand, supply and utilization of whole blood and components in India. METHODS: We conducted a national level cross-sectional study in five randomly selected states from five regions of the country. We included 251 public and private facilities representing primary, secondary and tertiary care facilities. We collected annual disease-specific demand, supply and utilization of blood and components using a structured tool. We estimated the national demand by extrapolating the study data (demand and beds) to the total number of estimated beds in the country. FINDINGS: According to the study, the total clinical demand of 251 health facilities with 51,562 beds was 474,627 whole blood units. Based on this, the clinical demand for India was estimated at 14·6 million whole blood units (95 CI: 14·59-14·62), an equivalent of 36·3 donations per 1,000 eligible populations, which will address whole blood and component requirement. The medicine specialty accounted for 6·0 million units (41·2%), followed by surgery 4·1 million (27·9%), obstetrics and gynecology 3·3 million (22·4%) and pediatrics 1·2 million (8·5%) units. The supply was 93% which is equivalent to 33·8 donations against the demand. CONCLUSION: The study indicated a demand and supply gap of 2.5 donations per 1,000 eligible persons which is around one million units. The gap emphasises the need for sustained and concerted efforts from all stakeholders and for increasing the awareness about repeat voluntary non-remunerated blood donation (VNRBD); optimizing the availability of blood components through efficient blood component separation units; promoting modern principles of patient blood management and strengthening capacities of human resources in the blood transfusion system in India.

A review of legal, regulatory, and policy aspects of blood transfusion services in India: Issues, challenges, and opportunities.

BACKGROUND: Blood transfusion services (BTS) in India have progressed significantly during the last three decades. However, there is still inequity in the availability and access to blood due to various demand and supply-side issues. Appropriate laws, regulations, policies, and guidelines are critical to ensure universal access to blood. AIMS AND OBJECTIVES: This article aims to review the evolution and current status of legal, regulatory, and policy framework and analyses the issues, challenges, and opportunities for improvement of BTS in India. METHODS: This article is based on an extensive review of currently available literature and government documents. RESULTS: The review highlights the gaps and challenges in terms of licensing, safety and quality, voluntary blood donations, the organization of BTS, access to services, and regulatory bodies. The findings emphasize the need for a coordinated response by either the National Blood Transfusion Council or a newly established autonomous "National Blood Authority" consisting of technical, administrative, and legal experts which must be exclusively responsible for regulating the BTS. As adherence to quality management systems in blood banks is not a mandatory requirement, it recommends a legal measure to ensure mandatory quality assurance in blood banks and storage centers. Towards ensuring efficiency and universal access to blood, this article recommends evidence-based criteria for establishing new blood banks to avoid skewed distribution of blood banks, component separation facilities, and blood storage centers. CONCLUSION: The review emphasizes the need for periodic reviews and updates of the legal, regulatory and policy framework, considering the rapid developments and technical advancements with increasingly complex systems and processes in transfusion medicine.

Assessment of Performance of Blood Banks in India: A National Level Cross Sectional Study.

India lacks comprehensive information about blood transfusion systems, which could help ensure universal access to safe blood through evidence-based strategies and programs. We conducted the first national assessment of blood bank systems, services, practices, and performance in India. We conducted a cross-sectional survey of all 2626 blood banks and assessed the administrative, technical, and quality aspects in 2016. In addition to descriptive analysis, we compared the means of different variables using independent t-test or ANOVA and a generalized linear model. We performed linear regression analysis between the collection of blood per 100 people and the number of blood banks per million people. The disaggregated mean score of quality management system and overall performance are presented by different groups. Besides, we graded the performance based on tertile classification, as low, medium and high-performance blood banks. Of the 2493 blood banks that participated in the study, most were public (38%) or not-for-profit(38%), and 51% had component separation facilities. Of the 11.65 million units of blood collected annually, 72% was through voluntary blood donation. There were 2.2 blood banks per one million people, collecting around one unit per 100 persons annually with wide variation between states. The mean overall performance score was 62(95% confidence interval [CI]:61.6-62.5), and the mean quality management system score was 57.4(95% CI:56.8-58.0), with significant variation across different categories of blood banks. This assessment provides critical information for developing evidence-based policies, programs, and monitoring systems to improve the performance of blood transfusion services in India.

A national level estimation of population need for blood in India.

BACKGROUND: The population need for blood is the total volume required to transfuse all the individuals who need transfusion in a defined population over a defined period. The clinical demand will arise when people with a disease or condition who require transfusion, access healthcare services, and subsequently the clinicians request blood. Essentially, the conversion of need to demand must be maximum to avoid preventable mortality and morbidity. The study estimated the population need for blood in India. METHODS: The methodology included a comprehensive literature review to determine the diseases and conditions requiring transfusion, the population at risk, and prevalence or incidence; and Delphi method to estimate the percentage of people requiring transfusion, and the quantum. RESULTS: The estimated annual population need was 26.2 million units (95% CI; 17.9-38.0) of whole blood to address the need for red cells and other components after the separation process. The need for medical conditions was 11.0 million units (95% CI:8.7-14.7), followed by surgery 6.6 million (95% CI:3.8-10.0), pediatrics 5.0 million (95% CI:3.5-7.0), and obstetrics and gynecology 3.6 million units (95% CI:1.9-6.2). The gap between need and demand which depends upon the access and efficiency of healthcare service provision was estimated at 13 million units. CONCLUSION: The study brings evidence to highlight the gap between need and demand and the importance of addressing it. It cannot be just the responsibility of blood transfusion or health systems, it requires a multi-sectoral approach to address the barriers affecting the conversion of need to clinical demand for blood.

Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models.

BACKGROUND: Ever since the Coronavirus disease (COVID-19) outbreak emerged in China, there has been several attempts to predict the epidemic across the world with varying degrees of accuracy and reliability. This paper aims to carry out a short-term projection of new cases; forecast the maximum number of active cases for India and selected high-incidence states; and evaluate the impact of three weeks lock down period using different models. METHODS: We used Logistic growth curve model for short term prediction; SIR models to forecast the maximum number of active cases and peak time; and Time Interrupted Regression model to evaluate the impact of lockdown and other interventions. RESULTS: The predicted cumulative number of cases for India was 58,912 (95% CI: 57,960, 59,853) by May 08, 2020 and the observed number of cases was 59,695. The model predicts a cumulative number of 1,02,974 (95% CI: 1,01,987, 1,03,904) cases by May 22, 2020. As per SIR model, the maximum number of active cases is projected to be 57,449 on May 18, 2020. The time interrupted regression model indicates a decrease of about 149 daily new cases after the lock down period, which is statistically not significant. CONCLUSION: The Logistic growth curve model predicts accurately the short-term scenario for India and high incidence states. The prediction through SIR model may be used for planning and prepare the health systems. The study also suggests that there is no evidence to conclude that there is a positive impact of lockdown in terms of reduction in new cases.

Modelling of reproduction number for COVID-19 in India and high incidence states.

BACKGROUND: Since the onset of the COVID-19 in China, forecasting and projections of the epidemic based on epidemiological models have been in the centre stage. Researchers have used various models to predict the maximum extent of the number of cases and the time of peak. This yielded varying numbers. This paper aims to estimate the effective reproduction number (R) for COVID-19 over time using incident number of cases that are reported by the government. METHODS: Exponential Growth method to estimate basic reproduction rate R0, and Time dependent method to calculate the effective reproduction number (dynamic) were used. "R0" package in R software was used to estimate these statistics. RESULTS: The basic reproduction number (R0) for India was estimated at 1.379 (95% CI: 1.375, 1.384). This was 1.450 (1.441, 1.460) for Maharashtra, 1.444 (1.430, 1.460) for Gujarat, 1.297 (1.284, 1.310) for Delhi and 1.405 (1.389, 1.421) for Tamil Nadu. In India, the R at the first week from March 2-8, 2020 was 3.2. It remained around 2 units for three weeks, from March 9-29, 2020. After March 2020, it started declining and reached around 1.3 in the following week suggesting a stabilisation of the transmissibility rate. CONCLUSION: The study estimated a baseline R0 of 1.379 for India. It also showed that the R was getting stabilised from first week of April (with an average R of 1.29), despite the increase in March. This suggested that in due course there will be a reversal of epidemic. However, these analyses should be revised periodically.

Is BCG associated with reduced incidence of COVID-19? A meta-regression of global data from 160 countries.

BACKGROUND: Global research is running towards to find a vaccine to stop the threat of the COVID-19. The Bacillus Calmette-Guérin (BCG) vaccine that prevents severe forms of tuberculosis is getting more attention in this scenario. The objective of our study was to determine the association between BCG vaccine coverage and incidence of COVID-19 at a national-level across the Globe. METHODS: The data of 160 countries were included in the study. Meta-regression was done to estimate the difference in the incidence of COVID-19 cases between countries with BCG vaccination coverage. BCG coverage was categorized as ≤70%, >70% and no vaccination. The analyses were carried out by adjusting for factors such as population density, income group, latitude, and percentage of the total population under age groups 15-64 and above 65 years of each country. RESULTS: The countries that had ≤70% coverage of BCG vaccine reported 6.5 (95% CI: -8.4 to -4.5) less COVID-19 infections per 10,000 population as compared to countries that reported no coverage. Those that had >70% coverage reported 10.1 (95% CI: -11.4 to -8.7) less infections per 10,000 population compared to those with no BCG countries. CONCLUSION: Our analysis suggests that BCG is associated with reduced COVID-19 infections if the BCG vaccine coverage is over 70%. The region-wise analyses also suggested similar findings, except the Middle East and North African region.

Who is dying from COVID-19 and when? An Analysis of fatalities in Tamil Nadu, India.

BACKGROUND: As the number of COVID-19 cases continues to rise, public health efforts must focus on preventing avoidable fatalities. Understanding the demographic and clinical characteristics of deceased COVID-19 patients; and estimation of time-interval between symptom onset, hospital admission and death could inform public health interventions focusing on preventing mortality due to COVID-19. METHODS: We obtained COVID-19 death summaries from the official dashboard of the Government of Tamil Nadu, between 10th May and July 10, 2020. Of the 1783 deaths, we included 1761 cases for analysis. RESULTS: The mean age of the deceased was 62.5 years (SD: 13.7). The crude death rate was 2.44 per 100,000 population; the age-specific death rate was 22.72 among above 75 years and 0.02 among less than 14 years, and it was higher among men (3.5 vs 1.4 per 100,000 population). Around 85% reported having any one or more comorbidities; Diabetes (62%), hypertension (49.2%) and CAD (17.5%) were the commonly reported comorbidities. The median time interval between symptom onset and hospital admission was 4 days (IQR: 2, 7); admission and death was 4 days (IQR: 2, 7) with a significant difference between the type of admitting hospital. One-fourth of (24.2%) deaths occurred within a day of hospital admission. CONCLUSION: Elderly, male, people living in densely populated areas and people with underlying comorbidities die disproportionately due to COVID-19. While shorter time-interval between symptom onset and admission is essential, the relatively short time interval between admission and death is a concern and the possible reasons must be evaluated and addressed to reduce avoidable mortality.

Demystifying the varying case fatality rates (CFR) of COVID-19 in India: Lessons learned and future directions.

INTRODUCTION: At the end of the second week of June 2020, the SARS-CoV-2 responsible for COVID-19 infected above 7.5 million people and killed over 400,000 worldwide. Estimation of case fatality rate (CFR) and determining the associated factors are critical for developing targeted interventions. METHODOLOGY: The state-level adjusted case fatality rate (aCFR) was estimated by dividing the cumulative number of deaths on a given day by the cumulative number confirmed cases 8 days before, which is the average time-lag between diagnosis and death. We conducted fractional regression analysis to determine the predictors of aCFR. RESULTS: As of 13 June 2020, India reported 225 COVID-19 cases per million population (95% CI:224-226); 6.48 deaths per million population (95% CI:6.34-6.61) and an aCFR of 3.88% (95% CI:3.81-3.97) with wide variation between states. High proportion of urban population and population above 60 years were significantly associated with increased aCFR (p=0.08, p=0.05), whereas, high literacy rate and high proportion of women were associated with reduced aCFR (p<0.001, p=0.03). The higher number of cases per million population (p=0.001), prevalence of diabetes and hypertension (p=0.012), cardiovascular diseases (p=0.05), and any cancer (p<0.001) were significantly associated with increased aCFR. The performance of state health systems and proportion of public health expenditure were not associated with aCFR. CONCLUSIONS: Socio-demographic factors and burden of non-communicable diseases (NCDs) were found to be the predictors of aCFR. Focused strategies that would ensure early identification, testing and effective targeting of non-literate, elderly, urban population and people with comorbidities are critical to control the pandemic and fatalities.