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The COVID-19 pandemic has posed an unprecedented public health crisis globally irrespective of age. There is no doubt that the older population (above the age of 60) is the most vulnerable age category due to multiple co-morbidities, which often is not in their favour. Age category, types of co-morbidities and nutritional levels indeed play a pivotal role in determining mortality rates. This paper focuses on Kerala, a southern Indian state and how it maintained low mortality levels due to COVID-19 during the first wave despite being the state with the highest proportion of the older population. The present study argues although the state possessed a robust health system and had an active engagement of the public health sector with its citizens through local governments, it was the state’s meticulous planning, innovative schemes centred around older persons such as reverse quarantine, the prevailing excellent nutritional status among its population and initiatives to ensure good nutrition through food security schemes like ‘essential grocery kits’ and ‘community kitchens’ that helped to develop the body’s resistance to infection and thus played a significant role in flattening the curve for Kerala’s older adult COVID-19 deaths effectively, thereby achieving a high recovery rate and low rates of fatality during the first wave of COVID-19 in Kerala.

Pre–COVID-19 health conditions of older adults in Kerala were analysed through Kerala Ageing Survey (KAS) panel data and Longitudinal Ageing Survey in India (LASI) data. Percentage analysis, Logistic regression method and Cox hazard regression methods were used to analyse the effect of nutritional levels on health and mortality among older adults in Kerala. Publically available COVID-19 data from the Government of Kerala and the Government of India were used to analyse the COVID-19 death rates. In addition, changes in dietary patterns and other preventive measures taken to fight against COVID-19 were investigated through qualitative response.

The study found that nutritional status influences mortality and co-morbidities among older adults in Kerala in the pre-COVID situation. Furthermore, the study found that though nutritional indicators, that is, overweight or obese, significantly increases the risk of comorbid conditions among older adults, good nourishment reduces the risk of all-cause mortality. The study also found that Kerala’s COVID-19 fatality was much lower when compared to India and developed nations like the US, UK and Italy. Even if Kerala is one of the highly COVID-19 affected states, the effective nutritional intervention by the Government of Kerala through its various schemes to build up the general immunity of the state’s citizens, especially high-risk groups; thereby achieving low COVID fatality in the state.

Based on Kerala’s experience, nutritional factors influence the population in building up the body’s resistance to infection against COVID-19. Even though the fatality rate is very low, obesity coupled with non-communicable diseases affects preventive measures of the state. There is an immediate and persuasive need to find new and more efficient clinical studies apart from socio-epidemiological studies, which could play a pivotal role in determining COVID-19 health outcomes.

Keywords ageing, COVID-19, food security, health policy, malnutrition, nutritional status, population density, social isolation, odds ratio, India

First Published December 6, 2021 https://doi.org/10.1177/00469580211059738

INQUIRY: The Journal of Health Care Organization, Provision, and Financing (SAGE)

Economics and Political Weekly Vol. 56, Issue No. 49, 04 Dec, 2021

The NFHS-5 hides more than it reveals on the demographic and health indicators.

Views expressed are personal and do not represent those of the institution/employer of the authors.

The National Family Health Survey (NFHS)-5 is the fifth in a row to offer population and health indicators for Indian states and districts. Having commenced in the early 1990s, over the three decades of periodic enquiry, the NFHS has not only facilitated gauging the trends in population and health para­meters, but also many other programme-related performance indicators. In fact, the most recently held monitoring exercise of the Sustainable Development Goals (SDGs) as well as the assessment of the Multidimensional Poverty Indices for the Indian states and its districts has been largely facilitated by the indicators offered by the latest NFHS. Given the significance and credibility of the indicators offered by consecutive rounds of the NFHS in monitoring the progress on the population and health fronts, the recently released NFHS-5 findings have brought out surprises on the attainment of various targets as well as the progress made on varied domains. Although a range of 131 indicators is offered by this survey, the indicators that received attention relate to the female population sex ratio, the attainment of replacement-level of fertility and the future of the population control policy.

Though age–sex composition of population along with other information collected from the households form the fundamental basis of the NFHS-5, the basic indicators like sex ratio and age composition based on this survey may not be the best alternative to the census enumeration. The NFHS-5 (2019–21) findings highlight a feminine population sex ratio of 1,020 when compared to the 991 obtained in the NFHS-4 (2015–16)—a 29 points improvement in just five years. In the absence of a 2021 Census, the 2011 Census reported 940 females per 1,000 males—an 80 points improvement in 10 years. This improvement once acknowledged can have its own interpretation in the improved status of women to gendered advantage. However, before jumping to conclusions on this improved sex ratio shifting from a masculine to a feminine one, we should revisit the results from varied perspectives. The main objective of the earlier four rounds of the NFHS as well the current one is to provide high-quality data on reproductive health and family welfare indicators and not on the population sex ratio. The overall sex ratio of the NFHS-5 need not necessarily be taken on its face value. Further, the recent experience of fertility transition has implication for the number of children with a skewed sex composition and the skewed presence of elderly individuals in the surveyed households. Given these complexities, a survey-based population sex ratio being feminine need not be highlighted to comment on its popular derivatives. We have to wait for the 2022 Census to examine the overall sex ratio.

The second most important highlight has been the attainment of a total fertility rate (TFR) of 2.0, implying a below replacement level of fertility for the Indian population. While the TFR is a marker of fertility decline and the success of long-standing antenatal policies, its implication for population replacement has a lag given the momentum of population growth on the one hand and the characteristic differential on the other. The aggregate low fertility may well be a reality, but its distribution represents infertility on one extreme and fertility level above this norm on the other. Though Kerala achieved a replacement level of fertility as early as 1987, it is expected to stabilise around 2030. Hence, the attainment of below replacement level of fertility would perhaps have its implication for population growth and composition in terms of attaining stabilisation following a sustained low fertility for a while. Apart from celebrating this success, it is pertinent to recognise strategies to mitigate consequences of low fertility as well. With low fertility, the experience of infertility is on a rise and needs attention, and at the same time, the implication of low fertility on the emergence of future inequality (particularly owing to differential endowments among children and families) should also be a matter of concern. Given the economic gradient of fertility differential and clusters of fertility above the low fertility normative, its inequality derivatives are imminent.

Apart from these two indicators, a host of indicators concerning maternal and child health, nutrition, women’s autonomy, gender-based violence along with the use of tobacco and alcohol are also obtained. A significant share of these indicators display an improvement over the last survey figures offering optimism regarding the success of government programmes as well as the changing population health environment at large. Many of these indicators as defined are simple headcount ratios for varying denominators, making their comparison across situations questionable, given the magnitude of the phenomenon on the one hand and the attained level of success on the other. Besides the national-level comparison of trends, the same across states and districts would perhaps require greater caution to comment on improvement/deterioration overlooking the raised concern mentioned above. Further, these indicators may also have a compositional structure in terms of various characteristics with a range of vulnerability differences that would be masked in these aggregates and may have a bearing on their progress towards their betterment. Such cautions are necessary, given the tendency of using this information base for the assessment of progress towards betterment.

On the whole, the generation of the host of indicators at a disaggregated level with characteristic differences is quite encouraging in terms of gauging performances and progress, but many of these indicators will have the limitation of being defined in a dichotomous construct with their characteristics and compositional differences that will compromise their robust comparison.

Rajan, S. I., Sivadasan, T. M., Jayanth, R. S. S., & Batra, P. (2021). Household Pandemic Response: The Socioeconomic Impact of COVID-19 on Migrant Households in India. Asian Economics Letters3(Early View). https://doi.org/10.46557/001c.25382

The urban-rural divide in India has been the cause of labour flow to Indian cities, which have historically witnessed an insufficiency in planning. Moreover, widening social inequalities exacerbate the living conditions in Indian cities, pushing migrant labourers from rural areas to the margins of urban spaces. Public policymakers have long turned a blind eye to migrants, denying them essential social security. This study attempts to review how these factors have made urban space unwelcome to migrants from rural areas, edging them to a state of inability to sustain themselves, especially amidst the COVID-19 pandemic. It is also an attempt to re-evaluate the status of urbanization. The government imposed a sudden lockdown in 2020 to mitigate the effects of the COVID-19 outbreak, leading to a massive exodus of migrants from cities back to their homes. The study also seeks to account for the significance of economic planning and social security with regard to migrant labour

The study examines labour force participation, occupational changes and unemployment levels of Indian return emigrants at the time of leaving from their country of destination and after return to the country of origin. Further, this article extends the debate on the socioeconomic level of return migrants, post their return, in comparison to the non-migrants. The data from the 64th round of the National Sample Survey (NSS), which is the latest available data on return migration, has been utilised for this study to explore the pre- and post-return migration statuses. The result shows that the occupational changes are substantially different in the pre- and postreturn phases. Meanwhile, the labour force participation ratio is seen to have significantly declined among the return migrants. In addition, unemployment ratio is seen to be significantly higher for both pre- and post-return periods while economic level of return migrants is observed to be better than non-migrants. However, among the return migrants, the poorest are most likely to return than the richest and the category of middle class five times more likely to than richest. The study concludes that return migrants drastically suffered from unemployment and financial problems after return to the country of origin. As a way of addressing these issues, some appropriate policy levels indicated by this analysis are discussed.

Although it is the world’s largest recipient of remittances, India lacks information about the investment behavior of its remittance receiving households. Using data from Reserve Bank of India and the Tobit analysis, this paper examines how remittances, different household and migrant characteristics have affected both the propensity to invest and the amount of investment by the remittance receiving households. The findings have significant implications for policy purposes. For example, government programs can create incentives for older migrants to have more remittance transfers. Remittance money used for children’s education could be matched to create robust flow of educational investments.

Based on our survey conducted in Tamil Nadu, this paper analyses the characteristics of Indian migrant nurses and the factors influencing their migration. India is considered the second largest exporter of nurses after the Philippines. Many Indian nurses have migrated to work in OECD countries, the Gulf countries and some ASEAN countries. While Indian nurses are migrating overseas to fill shortages at their destinations, India has itself been suffering from an acute scarcity of nurses since its independence in 1947. Therefore, the large scale of nurse migration is a serious threat to the Indian healthcare system. The results of the survey imply that international migration by nurses can be explained in part by the gap between the private sector and the public sector in terms of salary and working environment. Since the impact of social status on the migration decisions of nurses has lessened, economic factors are the crucial determinant of international migration of nurses. Policy intervention in this area is the necessary first step to solving this long-standing problem. The priority in any policies formulated should be given to nurses working in the private sector whose salaries are considerably lower than those in the public sector and whose voices are unheard.

The article examines the role of large scale migration surveys in understanding that future. Focusing on the example of Kerala, the article highlights the role of the Kerala Migration Survey (KMS) which has provided data on stocks of emigrants, return emigrants, cost of migration, use of remittances and migration corridors since 1998 The article shows how the Government of Kerala effectively utilized this data to manage the spread of the pandemic and its subsequent socio-economic impact on individuals, communities and society and organize policies and programs as well as to prepare for eventual return migrants for their integration and rehabilitation. Given that the KMS model has been successfully replicated in some of the major states in India, we proposed the KMS model to be replicated nationwide as an India Migration Survey and globally, given the challenges to come in terms of new emerging trends and patterns of migration in post-pandemic world.

Emigration by skilled and semi-skilled workers from India to the Middle East is a strategy for better economic returns. Families rarely accompany migrants. Drawing insights from primary data gathered from intensive fieldwork in Sivaganga district, Tamil Nadu, this article attempts to understand the psychological consequences on the wives left behind. A mixed sampling method was used to derive the sample size. Analysis of variance (ANOVA) and Pearson’s chi-square tests were mainly used for quantitative analysis supplemented by qualitative methods. The results indicated that wives considered loneliness the most significant psychological problem arising from their husbands’ absence. Stress was also caused by financial problems and the necessity of taking on additional roles in the family.