1 Introduction

A large majority of the world’s countries are experiencing age structural transition though the pace of this transition varies across nations (UNDESA 2017a; Navaneetham and Dharmalingam 2012). India too has been experiencing an age structural transition due to several factors, including a declining trend in mortality and increasing life expectancy, and of late, a rapid reduction in fertility (Arokiasamy et al. 2012; PRB 2012). Age structural transition is recognised as one of the most remarkable outcomes of demographic transition, which in turn, is affected by a host of socio-economic and demographic factors as well as government policies. Therefore, during the last few years, age structural transition has emerged as one of the most burgeoning demographic issues due to its relevance with regard to the demographic dividend and ageing. Population ageing, that is, an increase in the share of older persons in the population is a profound demographic transformation of the twenty-first century (Rajan 2007). It has significant ramifications for almost all the sectors of society, including labour and financial markets, the demand for goods and services, such as housing, transportation, and social security, health care facilities, family structures, and intergenerational relations (Gulati and Rajan 1999; United Nations 2007, 2015; Alam and Karan 2014). Population ageing is, therefore, an inevitable demographic reality associated with welcome improvements in medical and health facilities (UNFPA 2017).

Thus, ageing is increasingly becoming a pervasive phenomenon in both the developed and developing countries, and India is no exception to this trend. People are living longer, and both the share and the number of older people in the total population are growing rapidly, which can have enormous and multi-faceted socio-economic implications for a country like India (Ortman et al. 2014; Yoshino et al. 2019; UNDESA 2020). The increasing share of the older population will impose new and increasing demands on the health sector as older people face a higher possibility of health risks because of their decreased physiological immunity (Chanana and Talwar 1987; PRB 2012; Irshad et al. 2021). Among other impacts, the changing age-sex structure of the population will necessitate a change in the pattern of production in keeping with the changing demands of the youth, adult, and older population of the country. Industries across the board will also need to respond to this challenge by adjusting their production to meet the rising demand for their products and services. In the wake of the fast-changing demographic scenario in developing countries, the need to meet these challenges on account of an increase in the absolute population aged 60 years and above, cannot be under-estimated. This is particularly true for India, where the old age dependency burden is likely to grow not only due to a decline in the levels of fertility and mortality but also because of out-migration of the working age group population in search of employment in other states of India or outside the country.

Being the world’s second most populated country, India requires special attention of the national and international demographers and policy-makers for carrying out a proper analysis of ageing and its associated challenges, and for preparing policies to face the challenges posed by the rapidly swelling older population before the issue becomes critical (Chanana and Talwar 1987). This study, therefore, efforts to analyse age structural transition taking place in the population of India and its selected 15 major states, and how it has altered the age structure of population of India and its various states from 1961 to 2011. This study explores the process of ageing and associated issues, including trend, pattern and level of ageing as well as of different age indices namely old age dependency ratio, oldest old age dependency ratio, ageing index, sex ratio of older and oldest old population in India and its 15 major states during the last six decades and, thus, contributes to the existing literature on ageing in India. The present study attempts to draw the attention of researchers and policy makers towards the challenges and opportunities associated with age structural transition, demographic window of opportunity, demographic dividend and ageing in India. This study also makes policy recommendations for states with high and low levels of age structural transition. Furthermore, it offers suggestions regarding internal migration and emigration in view of the changing age structure in the country.

1.1 Significance of the study on ageing in India

India, the second most populated country in the world, has experienced a rapid increase in its population, especially after independence. According to the Census of India (2011), the total population of the country is 1210.9 million, which accounts about 17.5% of the world’s total population. During the period 1961–2011, India’s population has experienced rapid demographic changes in fertility, mortality, life expectancy, and its age-sex structure. Life expectancy has increased from 49.7 years in 1970–75 to 69.4 years in 2014–18 (SRS 2020). India’s fertility has reduced from about 6 children per woman in 1960 to 2.2 in 2018, being slightly above the replacement level (West 2018). One of the major consequences of these demographic changes is the remarkable rise in the country’s older and oldest population, which have increased more than four times during the period 1961 to 2011, thereby posing serious challenges for governments and policy-makers to formulate policies related to older people. Moreover, the proportion and number of the aged population is expected to further grow in the coming decade. The rising number of older people will also put pressure on infrastructure, housing, and old-age pensions, and create challenges for the labour market, public benefits, social security, health care systems, and family members who provide a majority of the care to older people with disabilities (Mather et al. 2015; Cotlear 2011). In India, the older population is also particularly vulnerable due to their poor health status (Irshad et al. 2021). About 70% of India’s older population lives in rural areas, primarily engaged in agricultural activities that require physical labour. Some older people, despite being physically fit to work in their later years, do not find employment due to the high unemployment rate in poor and densely populated areas. Besides, females comprise more than 50% of the older population, and since Indian society is patriarchal, few of them own the land and other resources needed to support themselves as they age. Therefore, a majority of older people are likely to remain without income, they will need support either from their families or the government (Chanana and Talwar 1987). However, one of the favourable features of India’s age structural transition is that the proportion of the working age group population has also been increasing along with the older population resulting in the window of opportunity that offers the potential for demographic dividend. This rise in the share of adult population can enhance the rate of economic growth in the country (Aiyar and Mody 2011). However, this window of opportunity will be available only for few decades, as the working age group population will eventually enter the older age groups, resulting in closure of the window of opportunity, leading to an increase in the number and proportion of the older population. India is in the early stage of ageing, and little is known about its socio-economic and health implications (Arokiasamy et al. 2012; Navaneetham and Dharmalingam 2012). It is, therefore, imperative to carry out a proper analysis of aging over a period of time in India and across its various states, and accordingly frame policies to address the problems of the ageing population. Geographically, India is a very large country with vast regional and state-level variations in its demographic landscape. Although the process of ageing is being experienced in all the major states of India, yet it is fast in some states and slow in others, as discussed in the following sections of this paper.

2 Research design

2.1 Objectives of the study

The present paper aims to analyse ageing and age structural transition in India and its selected 15 major states from 1961 to 2011. In doing so, this study focuses on the trends and levels of ageing by analysing various indices of age such as old age dependency ratio, oldest old age dependency ratio, and ageing index, the share of older population in the total population in India, as a whole, and separately in its 15 major states. The study also attempts to analyse sex ratio trends by age groups. Further, an attempt has also been made to demonstrate the age structural transition that has been taking place among the population of India and its major states throughout the study period.

2.2 Sources of data and methodology

The present study employs the population data of the Indian Censuses from 1961 to 2011, covering both India as a whole, and its selected 15 major states. In the present study, the population has been divided into three major age groups, viz. 0–19 years (representing the young population), 20–59 years (signifying the adult population), and 60 years and above (the older population), for analysing the different age indices. Additionally, wherever needed, the oldest old population or the group comprising those aged 80 years and above has been used in the study. This classification has been done keeping in view that in India, a majority of the people up to the age of 19 years are dependent and remain engage in education. Those falling in age group of 20–59 years are considered as the working age group because in a majority of the states, the retirement age is around 60 years, though in the central government for few categories of employees (doctors, teaching faculties etc.) it is 65 years, as also in many developed countries. However, there may also be working people among the older population (60 years and above) and the young population (0–19 years). On the other hand, there may be many non-working people among the adult population (20–59 years) as well. However, in order to analyse the process of age structural transition, in this paper, the population has been divided into the following five major age groups: 0–14 years, 15–39 years, 40–59 years, 60–79 years, and 80+ years.

In addition, for adjusting the data of ‘age not stated’ group, the data have been prorated. The age structural transition from 1961 to 2011 has been exhibited with the help of diagrams. Also, age-sex pyramids have been prepared for all the three categories of states of fast, moderate, and slow ageing. Different indices of age such as old age dependency ratio, oldest old age dependency ratio, ageing index, and sex ratio have been computed for analysing the process of ageing in the country. In this study different age indices have been calculated as follows:

The old age dependency ratio has been computed as the number of persons (P) aged 60 years and above per 100 persons in the age group of 20–59 years.

$$\text{Old Age Dependency Ratio}=\frac{P_{60+}}{P_{20-59}}\times 100$$
(1)

The oldest old age dependency ratio has been calculated as the number of persons aged 80 years and above per 100 persons in the age group of 20–59 years.

$$\text{Oldest Old Age Dependency Ratio}=\frac{P_{80+}}{P_{20-59}}\times 100$$
(2)

The ageing index has been calculated as the number of persons aged 60 years and above per 100 persons in the age group of 0–19 years.

$$\text{Ageing Index}=\frac{P_{60+}}{P_{0-19}}\times 100$$
(3)

The sex ratio has been computed as the number of male population per 100 female population.

$$\text{Sex Ratio}=\frac{\text{Male Population}}{\text{Female Population}}\times 100$$
(4)

In the present study, selected 15 major states include Andhra Pradesh, Gujarat, Bihar, Himachal Pradesh, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Punjab, Haryana, Odisha, Rajasthan, Tamil Nadu, Uttar Pradesh, and West Bengal (Fig. 1). It should also be noted that in the year 2000, the states of Uttar Pradesh, Madhya Pradesh, and Bihar were bifurcated into three new states, namely Uttarakhand, Chhattisgarh, and Jharkhand, respectively. In the Censuses for 2001 and 2011, data were given separately for these three newly created states. However, to make the data comparable with the previous Censuses, the data for these three states have been merged with their parent states, in this paper. It is expected that merging the data of these states with their antecedents will not significantly affect the proportions of the population in different age groups and the calculation of the different age indices because these newly created states are very similar to their parent states with regard to both their demographic and socio-economic characteristics.

Fig. 1
figure 1

Political Divisions of India

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3 Results

3.1 Numbers of older (60 years and above) and oldest old (80 years and above) population

The world’s older population (aged 60 years and above) has more than doubled from 382 million in 1980 to 962 million in 2017. Interestingly, the world’s older population is expected to double again by 2050, when it is projected to reach nearly 2.1 billion (UNDESA 2017b). In India too, the decline in child mortality, and those aged 60 years and above due to a rise in life expectancy and significant reduction in fertility, have led to a sharp rise in the number of older people. Fig. 2 indicates that the number of older people increased tremendously from 24.72 million in 1961 to 104.24 million in 2011. According to the UN estimates, the total older population of India was 125.7 million in 2017, which is likely to reach 316.8 million in 2050 (UNDESA 2017b). This remarkable increase in the older population is expected to pose tremendous economic and health care challenges in the country (James and Goli 2016). According to the Census of India, the total male population aged 60 years and above increased from 12.36 million in 1961 to 51.27 million in 2011. Similarly, the total female population aged 60 years and above went up from 12.36 million in 1961 to 52.97 million in 2011. Thus, in India, among the older people, females have outnumbered males.

Fig. 2
figure 2

Number of Older Population (60+ Population in Million) in India, 1961–2011. (Source: Calculations based on Census of India 1961, 1971, 1981, 1991, 2001, 2011)

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Globally, the total oldest old population (aged 80 years and above) is growing at faster rate than the older persons overall (United Nations 2015). Likewise, in India also, the total oldest old population also registered a substantial increase, from 2.49 million in 1961 to 11.33 million in 2011. Overall, the total oldest old male and female population increased from 1.17 million and 1.32 million, respectively, in 1961 to 5.30 million and 6.03 million, respectively in 2011 (Fig. 3). Thus, it may be observed that since 2001, one of the major features of India’s population has been the feminisation of its older population, which suggests that more females are living as widows with low levels of socio-economic security, and lack other types of support, as a result of which they are more vulnerable as compared to other sections of the population as well as females in the other age groups. The increasing share of India’s older population is accompanied with changing family relationships and limited old-age income and social security, which leads to a variety of socio-economic and health care policy challenges (PRB 2012). It is, therefore, necessary to formulate and properly implement the existing policies dealing with the various needs of the older population of the country.

Fig. 3
figure 3

Number of Oldest Old Population (80+ Population in Million) in India, 1961–2011. (Source: Calculations based on Census of India 1961, 1971, 1981, 1991, 2001, 2011)

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3.2 Levels and trends of the older population: state-level analysis

At the global level, the older population is growing faster than the population of all the younger age groups (Yoshino et al. 2019). In India too, the share of the older population has been continuously increasing, going up from 5.63% in 1961 to 8.61% in 2011 (Table 1). The share of India’s older population is expected to reach 19.1% in 2050 (UNDESA 2017b). At present, although the share of India’s older population seems to be lower than that in the developed countries, in absolute number, it is very large, and in fact, the second highest in the world, which is obviously a matter of great concern for policy-makers. Further, it should also be taken into consideration that geographically, India is one of the largest countries in the world, characterised by extensive social, economic, religious, and physical variations, which directly or indirectly influence the demographic landscape and consequently, the age composition of the population in different parts of the country.

Table 1 Percentage of Older Population (60+) to Total Population in India and Its Major States, 1961–2011
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In fact, different states of the country are passing through different stages of demographic transition, with which the process of ageing is closely associated. Therefore, significant spatial variations have also been recorded in the levels and proportions of the older population in different states of the country. Table 1 exhibits that the state of Kerala leads various states in the share of the older population. As per Census of India 2011, in Kerala, the share of the older population was 12.61%, increasing from 5.84% in 1961. The rapid ageing of the population in Kerala may be attributed to large scale emigration to other countries, rapid reduction in fertility and lengthening of life expectancy. These transformations positively affected Kerala’s economy, education, and health services, also having a radical impact on its age-sex composition, mortality, and other demographic factors as well. Kerala has the highest literacy rate in India, and the majority of potential employees, who are professional, skilled and technical individuals, either move to other countries or out-migrate to different states within India. There is shortage of unskilled labour in the state. Therefore, presently, Kerala is experiencing large scale unskilled labour in-migration especially from the poor states of the country (Rajan et al. 2020). The Census data reveals that in Kerala the share of inter-state male in-migrants from six under developed states, including West Bengal, Bihar, Rajasthan, Jharkhand, Odisha and Uttar Pradesh increased from 6.26% in 2001 to 18.76% in 2011 (Census of India 2001, 2011). State level differences in age structure has great potential for large scale inter-state migration because the young population has already shown the sign of stabilisation in states like Kerala, Tamil Nadu, Punjab and Goa which have experienced rapid age structural transition, therefore, relative share of labour supply would be from states like Uttar Pradesh, Rajasthan, Bihar, Madhya Pradesh etc. (Navaneetham and Dharmalingam 2012). Therefore, the states with high level of ageing should provide a favourable work environment for inter-state in-migrant workers (UNFPA 2018). In 2020, India was the world’s largest emigrating country, with about 18 million people living abroad, and at the same time the world’s largest recipient of international remittances, with 83.15 USD billion (McAuliffe and Triandafyllidou 2021).

Apart from Kerala, in states such as Tamil Nadu (10.42%), Punjab (10.35%), Himachal Pradesh (10.26%), Maharashtra (9.92%), Odisha (9.52%), Karnataka (9.49%), and Haryana (8.66%), the proportion of the older population to the total population was higher than the national average of 8.61%. Whereas, in states like Bihar (7.37%), Rajasthan (7.49%), Uttar Pradesh (7.85%), Madhya Pradesh (7.87%), Gujarat (7.95%), and West Bengal (8.49%), the proportion of the older population to the total population was lower than the national average, thereby reflecting the slow age structural transition during the study period. Thus, South Indian states such as Kerala and Tamil Nadu, along with the northern states of Punjab and Himachal Pradesh, have been experiencing a fast ageing. In contrast, the ageing is slow in the states of Bihar, Uttar Pradesh, Rajasthan, Madhya Pradesh and Gujarat.

3.3 Socio-economic profile of older persons

India’s older population is not homogenous, rather it has great diversity in terms of rural-urban distribution, marital status, literacy and education levels, economic status, health conditions, and engagement in economic activities. India’s 70.6% older population is concentrated in villages and 29.4% lives in urban areas (Census of India 2011). Females tend to live longer than males because they enjoy higher life expectancy, resulting in a predominately female older population (UNDESA 2019). In 2017, females comprised 54% of the world’s older population and 61% of the oldest old population (UNDESA 2017b). Likewise, India’s older population has higher share of females as they constituted 50.8% of the older population as compared to 49.2% for males, whereas among the oldest old population, females comprised 53.2% as compared of 46.8% for males in 2011. In younger age groups, however, males account for higher shares compared to females. Thus, older male population is more likely to be married while older females are more likely to be widowed (Arokiasamy et al. 2012). As per the Census of India (2011), about one-third of the older population is widowed, and the incidence of widowhood is much higher among females (47.8%) as compared to males (14.61%), which indicate that a higher proportion of older females live without their spouses as compared to their male counterparts. Inadequate financial security is one of the major challenges of India’s older people (Krishnaswamy et al. 2008). Therefore, older people continue to engage in economic activities depending on their health and physical capacity (Chattopadhyay et al. 2022). In 2011, the work participation rates among older males and females were 60.42 and 23.38%, respectively. Among the oldest old male and female population, the work participation rates stood at 34.90 and 10.91%, correspondingly, thereby reflecting significant gender differentials. In India, a majority of the population is engaged in agriculture and the unorganised private sector of the economy, wherein there is no specific age for retirement (Chanana and Talwar 1987). Although remunerative job opportunities decrease with age (Bakshi and Pathak 2016), in India the work participation rate is still high among the older and oldest old people, which may be attributed to the prevalence of economic and social insecurities among them (Krishnaswamy et al. 2008; UNFPA 2012; Goli et al. 2019). Moreover, most of the older people in the country are unable to receive retirement pensions and other benefits that are available to formal sector retirees, and therefore, they have to continue to work even in the older ages (Mahal and Mohanty 2019). In 2011, nearly 12% of the workforce (or about 58 million people) employed in organised sectors were covered under various pensions schemes. Whereas, the remaining 88% of the workforce is primarily working in the unorganised sector (self-employed, daily wage employees, farmers, etc.), with some employed in the organised sector but not mandatorily covered under Organization for Employees’ Provident Funds (EPFO). The EPFO covers employers with 20 or more employees (OECD 2021).

Data from the Longitudinal Ageing Study in India reveals that in India, nearly two-thirds of the older population is engaged in agriculture and allied activities, whereas only 5% are engaged in full-time jobs, and 6% derive benefits from pensions or provident fund schemes (Chattopadhyay et al. 2022). As per the Census of India (2011), only 43.53% of the older population was literate. Among older females, only 28.47% were found to be literate as compared to a corresponding figure of 59.10% among older males. The literacy and education levels were better in the urban areas compared to rural areas. In the rural areas, only 18.42% of the females and 50.52% of the males were literate as compared to corresponding figures of 52.67% for females and 79.60% for males in the urban areas. Further, the level of education among the older people was very low, especially in rural areas, where only 1.34% older population had education up to the graduate level or above as compared to a corresponding figure of 11.16% in urban areas. The disadvantaged condition and vulnerability of females in the older age groups in India may be due to the discrimination and exclusion from education and employment that they face, which are embedded in a deep-rooted cultural and social bias in the country (Singla 2020). Furthermore, the Census data reveals that nearly 5% of the older population and 8.4% of the oldest old population suffered from different kinds of disabilities. These physical disabilities and ill-health among the older people lead to considerable financial burden on their families (Alam and Karan 2014). Besides, in the absence of support from both the family and the government, older people are likely to become more vulnerable with increasing age due to their rising economic dependency, physical immobility, insecurity of health care, and social isolation. It is, thus, imperative to ensure an effective social security system for them (Rajan et al. 2003; Prasad 2011).

3.4 Old age and oldest old age dependency ratio

In the present study, the old age dependency ratio has been computed as the number of persons aged 60 years and above per 100 persons in the age group 20–59 years. Table 2 documents a gradual increase in the old age dependency ratio in India and its major states since 1961. This may be attributed to the rise in number of the older people due to an improvement in health facilities, nutrition, and decline in mortality, all of which have led to a rise in life expectancy. However, increase in the old age dependency ratio indicates that a higher number of older people impose more economic burden upon incomes and revenues generated by a declining pool of working age people and the government as well (Chanana and Talwar 1987; UNFPA 2017; Milovanovic and Smutka 2020). In India, there were about 12 older persons per 100 persons aged 20–59 years in 1961, which rose to about 17 persons in 2011. It is interesting to note that all the major states of India have registered an increase in old age dependency ratio from 1961 to 2011 (Table 2). In 1961, among the major states the old age dependency ratio stood around 11% to 14% but during the subsequent period the fast and moderate ageing sates have recoded greater increase in it. In 2011, the highest dependency ratio was found in Kerala (22.38%) followed by Punjab (19.19%), Himachal Pradesh (18.82%), Maharashtra (18.41%), Odisha (18.22%), Tamil Nadu (18.18%) and Andhra Pradesh (18.14%). In these state, the rising old age dependency is also likely to reverse the demographic benefits of declining child dependency associated with continued lowering of fertility rates (Bhagat 2014). This situation may, adversely affect the economic growth. The country, therefore, needs to introduce more employment-based policies (Chauhan and Arokiasamy 2018) before the demographic window of opportunity closes due to greater share of older population and reduction in the share of working age population. The slow ageing states, whereas, exhibit low old age dependency ratio due to lesser share of older population. Gujarat recorded the lowest dependency ratio (14.91%) which may be attributed higher share of working age population caused by inter-state in-migration in the state attracted by its predominant industrial economy.

Table 2 Trend of Old Age Dependency Ratio in India and Its Major States, 1961–2011
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Similarly, the oldest old age dependency ratio (persons aged 80 years and above per 100 persons aged 20–59 years) has also increased overall in India as well as across its major states. In fact, the oldest old population is the fastest growing segment of the population in India, registering a growth of 4.03% per annum during the decade 2001–2011. Table 3 indicates that in India the oldest old age dependency ratio increased from 1.25% in 1961 to 1.85% in 2011. In 2011, the highest oldest old age dependency ratio was observed in Kerala (2.89%), followed by Himachal Pradesh (2.86%), Punjab (2.54%), Haryana (2.13%), and Uttar Pradesh (2.05%), whereas the lowest oldest old age dependency ratio was found in Bihar (1.44%). Given the improvements in sanitation, nutrition, employment, and health facilities across the country, the number and percentage of the oldest old population are expected to grow rapidly in the coming decades in India, thereby posing serious challenges for the economically active population to support the oldest old age group. This is because not only is the oldest old population the most dependent on the working population, but the health expenses incurred on the former are also very high. A majority of the oldest old population comprises females, who include predominantly widows (69%) and the illiterate (73.83%), with both these groups of women lacking economic security and suffering from various types of disabilities and vulnerabilities. Therefore, the rising old age dependency currently being witnessed in India will demand a higher quantity and quality of geriatric services, and arrangements to facilitate income security and an improved quality of life (Subaiya and Bansod 2011). Besides, the lengthening of life span, is causing stress in families because of the presence of elderly especially suffering from different kind of disabilities (Chaurasia and Srivastava 2020). Thus, sometimes the older people are viewed as liabilities even by their own family members (Chaurasia and Srivastava 2020). It should be noted that in India although the share and number of working age population has also been increasing along with the older population, the growth rate among the latter is much higher than that of the former, which accounts for the rapid rise in the old age dependency ratio in India. The old age dependency burden can be reduced by engaging the older people in different economic activities. This can be accomplished by raising the retirement age in state government jobs, which currently ranges from 56 years in Kerala to 60 years in the majority of other states. Although, for some of the central government employees like doctors, teaching faculties etc. the retirement age is 65 years, in most of other services the retirement age is 60 years which was raised from 58 years in 1998. Therefore, both the central and state governments should raise the retirement age keeping in view the increase in life expectancy. For example, although over the past six decades, despite an increase in life expectancy of more than 30 year, Kerala’s statutory retirement age was only raised by 1 year (Jose and Sekher 2021). On the contrary, in developed world the statutory retirement ages are usually increased to account for ongoing increases in life expectancy (Weber and Loichinger 2022).

Table 3 Trend of Oldest Old Age Dependency Ratio in India and Its Major States, 1961–2011
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3.5 Trend in the ageing index

The ageing index shows the ratio of persons aged 60 years and above per 100 persons under the age of 20 years. The ageing index indirectly represents the economic dimensions of ageing related to allowances and pensions (Bucher 2014). Table 4 presents the aging index in India and in its major states from 1961 to 2011. The table indicates that the ageing index has been continuously increasing over the decades. In India as a whole, the ageing index significantly increased from 11.44% in 1961 to 14.48% in 1991. In 2011, there were about 21 older persons per 100 persons aged 0–19 years. The disparities in the ageing index across the states are quite remarkable. High level age structural transition states recorded the rapid increase in their ageing index compared to the states which experienced moderate and low level age structural transition. For example, Kerala recorded about 40 older persons per 100 persons aged 0–19 years and was followed by Tamil Nadu (32.28%), Himachal Pradesh (29.10%), Punjab (28.94%), Andhra Pradesh (27.70%), and Karnataka (26.50%). These state registered the significant decline in their fertility rate. Traditionally in India, social protection and care for the elderly is mostly rendered by relatives and family members (Wolf et al. 2011; James and Goli 2016). But in a rapidly ageing state like Kerala, Punjab etc. the traditional family support for the elderly is slowly disappearing, as there is lack of young people who can provide care for the elderly in households (Nair 2010; Rajan et al. 2020).

Table 4 Trend of Ageing Index in India and Its Major States, 1961–2011
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On the contrary, due to higher fertility rate and larger share of young population, the ageing index is low in the states of Bihar (15.18%), Rajasthan (16.47%), Uttar Pradesh (16.57%), and Madhya Pradesh (18.14%). Hence, the fast ageing states have recorded a higher ageing index as compared to the moderate and slow ageing states. The rising ageing index in India and in its major states shows that the total number of the older persons per hundred child population increased during the study period. Slow and moderate ageing states are also likely to face a reduction in the number of younger persons who can take care of older persons due to declining fertility and disintegration of joint families as well as out-migration for employment, business, and education (Sathyanarayana et al. 2014; Bakshi and Pathak 2016; Dhillon et al. 2016; Chaurasia and Srivastava 2020).

3.6 Female dominated sex ratio: feminisation of ageing and the associated emerging issues

The sex ratio—traditionally expressed as the number of males per 100 females—is a useful measure for assessing the sex balance among the older population and the resultant trends therein. At the global level, there were 86 males for every 100 females aged 60 years or above in 2015, and 63 males for every 100 females aged 80 years or above (United Nations 2015). Thus, it is obvious that females tend to live longer than males, and this longevity among females imparts them an advantage over males, leading to a predominately female older population (UNDESA 2019). As at the global level, in India too there is dominance of females among the elderly population. In India, as per the Census of India (2011), among the older people, there were only 97 males per 100 females. In 1961, the sex ratio was balanced but it increased to 107 males for 100 females in 1971, and then declined to 104 males per 100 females in 1981, but again increased to 108 males per 100 females. However, in both 2001 and 2011, the sex ratio was found to be 97 males per 100 females. Among the older people, the decline in the sex ratio may be attributed to the differentials in life expectancy of males and females. In the country, females’ life expectancy increased from 49 years in 1970–75 to 70.7 years in 2014–18, whereas correspondingly, the life expectancy for males showed a smaller rise, from 50.5 years to 68.2 years during the same period (SRS 2020).

As per the Census of India (2011), significant variations were observed in sex ratio at the state level. The highest sex ratio of 111 was found in Bihar followed by Uttar Pradesh (108) and Punjab (102). In contrast, in Kerala the sex ratio was as low as 82 males per 100 females. In the country, even among the oldest old population, females dominated over males, as there were only 88 males for every 100 females in this category of the population in 2011. In 1961 the oldest old population’s sex ratio was 89, which increased over the years, and rose to 109 in 1991, though it subsequently declined to 95 in 2001 and 88 in 2011. In 2011, among the oldest old, the lowest sex ratio was found in Kerala (61), whereas, it was as high as 110 in Bihar. The trends pertaining to the sex ratios of the older and oldest old population have been presented in Tables 5 and 6, respectively.

Table 5 Trend of Sex Ratio of Old Population in India and Its Major States, 1961–2011
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Table 6 Trend of Sex Ratio of Oldest Old Population in India and Its Major States, 1961–2011
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In India, the ageing is increasingly becoming a gender issue not only because females enjoy a higher life expectancy than males but also because they are more vulnerable and disadvantaged in multiple ways (Prakash 2003). Therefore, the feminisation of India’s older population is characterised by many problems and challenges, as older females constitute a very vulnerable section of the population. More than 71% of the females are illiterate and nearly 48% are widowed (Census of India 2011). There are also significant differences in widowhood across gender, which may be attributed to the longer life span of females as compared to males, and the general tendency among Indian males to marry females younger than themselves, manifested in the fact that in India, the wives were found to be older than their husbands in less than one percent of the marriages. In addition, higher remarriage rates also prevail among the males (UNDESA 2013; Berkman et al. 2012; Arifin and Ananta 2016; Lin et al. 2020). Single, widowed, poor, and uneducated older females are more vulnerable as compared to their rich and educated married counterparts (Burtless 2013; Alam et al. 2015).

3.7 Age structural transition: state-level analysis from 1961 to 2011

The study of age structural transition has remarkable implications not only for economic development, but several aspects of public policy, consumption pattern and market sectors (Pool 2006). Thus, age structural transition poses many challenges for policy-makers, but at the same time, it also presents potential opportunities (Seniloli 2006; Subaiya and Bansod 2011). The age structural transition is mainly the outcome of declining fertility, reduction in mortality, and increasing survival at older ages, all of which have contributed to the relative shift in the share of different age groups throughout the world, including in India (Pool 2006; UNFPA 2017). After India gained independence in 1947, its mortality rate started declining due to an improvement in various human development indicators, including sanitation, access to health facilities, education, nutrition and employment, among others, but the fertility rate was still significantly high. This situation continued till around the 1980s and resulted in a larger share of the child population. Subsequently, a reduction in the fertility and mortality rates, and increase in life expectancy, along with emigration and internal migration, started altering the age composition of India overall and also individually in its various states. The analysis of age data during last six decades reveals that India has been experiencing an age structural transition, that is, a shift in the age structure, wherein the share of the child population in the total population has been declining while the corresponding shares of the working population and older population have been increasing. In order to analyse the process of age structural transition in the country, the population has been divided into five major age groups, viz., 0–14 years, 15–39 years, 40–59 years, 60–79 years, and 80 years and above. The age structural changes in India’s population from 1961 to 2011 have been delineated in Fig. 4. The figure shows that in India the share of 0–14 years population was 41.04% in 1961 which increased to 42.03% in 1971, however, in the subsequent period it continuously declined to reach 30.87% in 2011. Whereas, the share of 15–59 years (combined share of 15–39 years and 40–59 years) continuously increased from 52.00% in 1971 to 60.52% 2011. This indicates that the share of India’s child population has been declining whereas that of working age population has been increasing over the years since 1971. Population aged 60–79 years showed a continuous increase, from 5.07% in 1961 to 7.67% in 2011. Similarly, the share of the oldest old population (aged 80 years and above) also increased from 0.57% in 1961 to 0.94% in 2011.

Fig. 4
figure 4

Age Structural Transition in India, 1961–2011. (Source: Calculations based on Census of India 1961, 1971, 1981, 1991, 2001, 2011)

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Thus, India is going through a dramatic expansion in its working age group population (West 2018) which is more productive as compared to other age groups and thus offers an opportunity of potential demographic dividend for higher economic growth. This demographic opportunity, however, will gradually diminish after few decades and India may then face serious challenges of older population (Aiyar and Mody 2011; Thakur 2012; Joe et al. 2015). Besides, in India, female’s low work participation rate is also one of the major challenges for potential demographic dividend (Desai 2010). Therefore, in order to reap the benefits emanating from demographic dividend, the government of India and its various states need to generate many more employment opportunities for males and females alike, which is doubtless a major challenge. In the absence of employment opportunities a large share of unemployed population of working age group can turn into an economic disaster (Thakur 2012). Thus, special emphasis should be laid on investing in quality education, providing vocational training, better infrastructure, safeguarding the health of the workforce, women empowerment, especially in the states whose demographic window of opportunity is still not opened (Alam and Karim 2006; Desai 2019; Jain and Goli 2022).

India is the world’s second most populated country and also geographically a very large country with conspicuous socio-economic and demographic inequalities prevailing across its various states. The speed of age structural transition is determined by fertility and mortality rates, life expectancy, and migration, which are, in turn, controlled by diverse social and economic conditions prevailing in different states. Therefore, the age structural transition has not been uniform across the states and striking variations persist due to state-level differentials in the speed of the demographic transition. On the basis of these age structural transitions, all the selected major states of India have been classified into three categories, viz., fast, moderate, and slow age structural transition. A fast age structural transition has been experienced in states of Kerala, Punjab (Fig. 5a), Himachal Pradesh, and Tamil Nadu. These states have witnessed sharp decline in the share of their young population and consequently, greater expansion in the share of the adult population, and share of their older population also increased significantly.

Fig. 5
figure 5

a Fast Age Structural Transition States: Age Structural Transition in Kerala and Punjab, 1961–2011. b Moderate Age Structural Transition States: Age Structural Transition in Karnataka and Odisha, 1961–2011. c Slow Age Structural Transition States: Age Structural Transition in Uttar Pradesh and Bihar, 1961–2011. (Source: Calculations based on Census of India 1961, 1971, 1981, 1991, 2001, 2011)

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The share of 0–14 years population has been continuously declining in Kerala and Punjab since 1961, and in Tamil Nadu and Himachal Pradesh since 1971. Among all the states of the country in 2011, Kerala recorded the lowest share of 0–14 years population (23.47%) closely followed by Tamil Nadu (23.59%), Punjab (25.58%) and Himachal Pradesh (25.90%). Conversely, the share of population in 15–59 years age group has been continuously increasing in Kerala and Punjab since 1961, and in Tamil Nadu and Himachal Pradesh since 1971. In 2011, the highest share of population in 15–59 years age group was recorded in Tamil Nadu (65.99%) while in Kerala, Punjab and Himachal Pradesh the share of this age group stood around 64%. In these states, the older population accounted more than 10% of their respective total population, highest being in Kerala (12.56%). The states at high level of age structural transition namely Kerala, Tamil Nadu, Punjab and Himachal Pradesh recorded early decline in fertility, are almost near the end of their demographic window of opportunity (Desai 2019). While a moderate age structural transition (Fig. 5b) has been observed in states of Andhra Pradesh, Karnataka, Maharashtra, Odisha, and Haryana. In 2011, in these states the share of 0–14 years age group varied from about 26% to nearly 30%. Whereas 15–59 years age group constituted about 61 to 64%, while the share of the older population comprised between 8 and10%. These states are likely to experience the expansion in their working age population for few more decades in view of decline in their child population. Whereas, Uttar Pradesh, Bihar, Madhya Pradesh, Rajasthan and Gujarat have experienced slow age structural transition (Fig. 5c). Among these states, the share of 0–14 years population was as high as 39.26% in Bihar, followed by Uttar Pradesh (35.74%), Rajasthan (34.75%), Madhya Pradesh (33.13%). On the contrary, the share of 15–59 years age group varied from 53.37% (in Bihar) to 63.07% (in Gujarat). In these states, the older population comprised less than 8% of their respective population.

Thus, age structure in the northern, central, and eastern states of India is dominated by younger population due to the high fertility and mortality (Subaiya and Bansod 2014). In these states, the level of the young age dependency is also very high, as they have very large shares of the young population. However, the share of their young population has been declining slowly during the study period. In the states with moderate and slow age structural transition the shares of the working age population have been increasing slowly. While in the states with fast age structural transition and fast ageing, the share of working age population is very high but expected to decline very soon. Therefore, the bulge in working age population will be especially experienced in slow-demographic transition states which are going through slow age structural transition. Thus, how India earns the remainder of its demographic dividend is mainly dependent on the social and economic performance of the states like Uttar Pradesh, Bihar, Madhya Pradesh, Rajasthan, Gujarat, etc. as they comprise very large proportion of the county’s total population and they have low share of older population and their child population is more likely to decline in coming decades (Thakur 2012).

3.8 Population pyramids of India and the selected states

Age-sex pyramids have also been prepared for understanding the changes in the age-sex structure of population of India and its selected major states in each of the fast, moderate, and slow ageing categories for the selected years. During the last six decades, India and its states have recorded spectacular changes in their age-sex pyramids. However, these changes are more noticeable in some states than in others. In 1961, India’s age-sex pyramid was triangular in shape with a broad base composed of the young population, which significantly narrowed in 2011, as seen in Fig. 6. Yet, it is still triangular in shape, illustrating the declining share of the working and older population in each successive age group and a pointed top, which may be attributed to the above replacement level fertility in India (Wolf et al. 2011).

Fig. 6
figure 6

Age Sex Pyramids of India from 1961 to 2011. (Source: Calculations based on Census of India 1961, 1971, 1981, 1991, 2001, 2011)

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India’s rapidly ageing states have recorded very pronounced changes in the shapes of their age-sex pyramids. For instance, Kerala has experienced a faster age structural transition and ageing as compared to the other states, and therefore, spectacular changes can be observed in its age-sex pyramid from 1961 to 2011. In 1961, Kerala had a very broad base of its age-sex pyramid, representing a higher share of the younger population tapering upward, with a decreasing share of each successive age group to a pointed top, which was common in all the agricultural societies in the past. Of course, for major period of human history, population pyramid remained bottom-heavy pyramid, with children representing nearly one half and this type of pyramid is found even today in many developing countries (Bengtsson and Scott 2010; Herlofson and Hagestad 2011). In 2011, the age-sex pyramid of Kerala acquired nearly a rectangular shape, depicting a shrinking base and expanding middle and top portions of the pyramid (Fig. 7). The rectangular shape of Kerala’s population pyramid may be attributed to the rapid decline in its fertility rate. In fact, Kerala attained replacement fertility rate of 2.1 children per woman in 1988, besides a significant increase in life expectancy (Arifin 2006; Martin 2021).

Fig. 7
figure 7

Age-Sex Pyramids of Kerala in 1961 and 2011: An Example of Fast Ageing State. (Source: Calculations based on Census of India 1961, 2011)

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Other examples of the fast ageing states are Tamil Nadu, Punjab and Himachal Pradesh. In these states, though the bases of their respective age-sex pyramids have shrunk and the middle parts have broadened but they are tapering upwards with a pointed top, and therefore, their age-sex pyramids are quite different from Kerala’s age-sex pyramid, which, as mentioned earlier, is increasingly becoming rectangular in shape. On the contrary, Karnataka (as seen in Fig. 8), Odisha, Maharashtra, and Andhra Pradesh represent the moderate ageing states. The bases of the age-sex pyramids of these states were also very broad in 1961, which have been narrowing during the subsequent periods. In 2011, their bases showed significant narrowing, while the middle parts started widening due to a considerable increase in the shares of their adult population. In contrast, the age-sex pyramids of the slow ageing states such as Uttar Pradesh (as seen in Fig. 9), Bihar, Rajasthan, Madhya Pradesh and Gujarat are still triangular in shape, with a wide base representing a higher share of the young population and declining share of the working age population in each successive age group tapering upward with a pointed top, manifesting a low proportion of the older population. The shapes of the age-sex pyramids in India’s various states are expected to exhibit significant transformations in the coming decades due to the notable ongoing improvements in health care services and life expectancy, and decline in birth rates and death rates. Although at present, India has a very large share of the population in the working age group, the quality of its human resources is one of the poorest in Asia, despite the intellectual brilliance exhibited by the country’s elite population (West 2018).

Fig. 8
figure 8

Age-Sex Pyramids of Karnataka in 1961 and 2011: An Example of Moderate Ageing State. (Source: Calculations based on Census of India 1961, 2011)

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Fig. 9
figure 9

Age-Sex Pyramids of Uttar Pradesh in 1961 and 2011: An Example of Slow Ageing State. (Source: Calculations based on Census of India 1961, 2011)

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4 Discussion

The present paper reveals that during the last six decades, the number and percentage of the older and oldest old population have significantly increased in India, thereby posing new challenges for the government and policy-makers to provide healthcare services, old age homes, elderly-friendly infrastructures, and socio-economic security, among other things, for the older population. An analysis of India’s health care system, social security, and employment scenario suggests that the country is not fully prepared to face the future challenges emerging from these unprecedented age structural and demographic transitions (Rajan et al. 2003; Mohanty and Panda 2022). Nearly three-quarters of India’s older population is concentrated in rural areas, which have highly inadequate health care facilities, especially for older people (Alam and Karan 2014). Albeit, India faced a very serious crisis pertaining to availability and access to health care facilities during the second wave of Coronavirus pandemic starting in April 2021. In India the older people are expected to experience remarkable financial problems and poverty for requiring health care which is mainly paid for out-of-pocket money (Lee et al. 2017). Illness among the older people is linked to loss of income. Besides, elderly care is increasingly becoming more expensive with increasing life expectancy. Generally, families have been main source of economic and social support to the older people (Prasad 2007; Bloom et al. 2010). But, due to the disintegration of joint families and out-migration of the adult population, along with the rising engagement of younger women in employment and education, the availability of caregivers for older people is likely to decline (Sathyanarayana et al. 2014; Bakshi and Pathak 2016; Dhillon et al. 2016; Chaurasia and Srivastava 2020).

Although the ageing process is being experienced in all major states of India, the pace of ageing shows contrasting spatial variations across the states. Since various states of India are passing through different stages of demographic transition due to their varying birth rates, death rates, and life expectancy, as well as differentials in terms of socio-economic development and health care facilities, thus, some states have been experiencing more rapid ageing than others. As has been pointed out earlier in this paper, the pace of ageing is faster in the South Indian states along with two northern states of Punjab and Himachal Pradesh, whereas the other North Indian states such as Bihar, Uttar Pradesh, Rajasthan, and Madhya Pradesh, are experiencing slow ageing. The states of Karnataka, Maharashtra, Andhra Pradesh, and Odisha, on the contrary, are experiencing a moderate level of ageing. It has been observed that when population age rapidly, governments are often less prepared to face and mitigate the concomitant impacts of this ageing process, which can adversely affect economic growth, socio-economic security, and the housing as well as health status of the older population (UNFPA 2017; Hong and Ekapirak 2019). Therefore, the existing social policies for the older population need to be examined critically, followed by their suitable redesigning (NSO 2021).

Interestingly, at the global level, among the older people, females outnumber males (UNDESA 2017a). In India too, since 2001, one of the chief characteristics of the older population has been its feminisation, that is, a rise in the ratio of females among older people. However, the feminisation of India’s older population is characterised by a high prevalence of illiteracy, greater economic dependence, higher incidence of widowhood and poor health among the older women (Alam and Karan 2014). Historically, females who have experienced widowhood have been socially more vulnerable and poorer than other females (Burtless 2013; Alam et al. 2015; Munnell et al. 2020). Besides, because of the patriarchal set-up prevalent in Indian society, a majority of the females are financially and physically dependent on their male counterparts, due to which older females face a higher risk of poverty as compared to older males (Singla 2020; Vlachantoni 2019; WHO 2015; UN-ESCAP 2017). As per the NSS 75th Round (2017–18), in the rural and urban areas of India, 66 and 68% of the older females, respectively, are fully financially dependent on others. Meanwhile, the partially dependent among the older females accounted for 24 and 21%, respectively, in the rural and urban areas of the country (NSO 2021). In India, such a higher old age economic dependency of females as compared to males is generally an extension of their dependency in the adult age group (Bhagat and Unisa 2006).

In India, due to an increase in the number of the older population, the old age dependency ratio and the oldest old age dependency ratio have shown a marked increase during the study period. However, the levels of the old age dependency ratio and the oldest old age dependency ratio have been increasing at varying rates and thus have differed across the states. Again, the rapidly ageing southern states, along with Punjab and Himachal Pradesh, have higher levels of old age dependency ratio as compared to the northern states, thereby indicating a higher burden on the working population for meeting the economic and health care needs of their older population. A similar pattern can also be observed in the level of the ageing index across the different states of the country. Thus, keeping in view the declining trend of fertility and mortality, and increase in life expectancy, the ageing index is expected to further rise in the coming decades. A rising ageing index indicates that there will be fewer younger people available in the country to support the older population (Subaiya and Bansod 2014). Rising share of older population will also affect the pattern of economic behavior and economic well-being of the older population because the elderly in India, as elsewhere too, consume more economic resources than they produce through labour. The occurrence of chronic diseases and disabilities lead to significant expenditure on health care thereby enhancing their economic dependency (Panruti et al. 2015; Dommaraju 2016; Yoshino et al. 2019). Thus, in the country older people face considerable economic insecurity. Therefore, some policy-makers are emphasising the need for retaining a higher number of older persons in the labour market as it reduces the economic burden of older population (Ingham et al. 2009; Bloom et al. 2010; Dhillon and Ladusingh 2013). However, it should be noted that in India as a whole, the old age dependency ratio and the oldest old age dependency ratio have been increasing along with an increase in the share of the working population and decline in the share of the child population.

The present study also reveals that India as a whole, and its major states individually have been experiencing an age structural transition, as indicated by the considerable changes that have taken place in the shares of the child, adult, and older population from 1961 to 2011. As a result of the age structural transition, the share of the child population has fallen significantly whereas the share of the adult and older population has increased during the study period. Such a transition in the age structure of the population has profound ramifications on the socio-economic progress and demographic landscape of the country (Navaneetham 2002). India’s southern states, along with Punjab and Himachal Pradesh, are ahead of other states in their demographic transition in terms of fertility, mortality and life expectancy and have, therefore, been experiencing more rapid age structural transition and ageing than other states (Navaneetham 2002; Subaiya and Bansod 2014). Due to these variations in the pace and timing of the age structural transition across the states, India will have the window of demographic opportunity for a longer duration that many countries could not enjoy. Therefore, India does not have to deal with a sudden labour supply at a single point of time in all parts of the country indicating longer period of age structural transition which may provide India with an opportunity to reap the benefits of its demographic dividend for a longer period of time. Kerala, Tamil Nadu, Punjab and Himachal Pradesh have experienced high level of age structural transition and, therefore, have almost approached the end of the demographic window of opportunity, while it has just opened in most of the northern and central states (Navaneetham and Dharmalingam 2012; Kumar 2013) and yet to open in north-eastern states.

In India demographic window of opportunity has slowly opened since 1981 (Mitra and Nagarajan 2005: Bhagat and Kumar 2011; Aiyar and Mody 2011; Kumar 2013) due to decline in the share of child population and an increase in the share of working age population especially in the South Indian states including, Kerala, Tamil Nadu, Goa, etc. along with two North Indian states of Punjab and Himachal Pradesh. In fact, India’s accelerated economic growth rates from 1981 to 2011 may partially be attributed to greater share of working age population in these states (Aiyar and Mody 2011; Thakur 2012). It should, however, be noted that the southern states account for a smaller share of India’s population as a majority of the population is concentrated in the northern states, which are passing through a slow age structural transition and are expected to supply the lion’s share of country’s working population within and across the national border. After 2001, highly populated states of North India, including Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh started registering a decline in their child population and an increase in the share of their working age population. Whereas, the share of older population is still low in these states. As a result in the country the effective demographic window of opportunity has opened since 2011 (Jain and Goli 2022). However, in these northern states namely Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, etc. a very large proportion of the population is still illiterate, unemployed and poorer than in South Indian states. These states can play a major role in the higher economic growth of the country. Therefore, in order to reap the benefits of demographic window of opportunity for potential demographic dividend, the country needs to focus on human resource development of these North Indian states which constitute major proportion of India’s population and are experiencing slow age structural transition.

As an increase in the human capital of working age population enhances economic growth (Philipov et al. 2014), India should prioritise the development of its existing human capital through improvements in education, health and decent employment (Maity and Sinha 2021). Besides, creation of trained workforce, productive employment, better infrastructure, female work participation can also play major role in the development human capital and thus, realisation of demographic dividend (Desai 2010; Jain and Goli 2022). Demographic window of opportunity will not last long as increasing share of the working population will be offset by rising share of older population (Wolf et al. 2011; Bhagat 2014). Various scholars have estimated that India’s working population may increase until about 2035 to 2050 (Mitra and Nagarajan 2005; Bhagat and Kumar 2011; Jain and Goli 2022).

Unfortunately, in India the levels of education and skill development of the adult population are far from satisfactory (James and Goli 2016; Chauhan and Arokiasamy 2018). Albeit, India has one of the lowest proportions of trained adult population in the world, and consequently, the country will not be able to reap the full benefits of its demographic dividend (West 2018), especially also because millions of people are illiterate, a significant proportion of the educated adult population is unemployed and poverty is widespread in both the rural and urban areas.

Furthermore, while female labour participation is a key indicator of women’s economic contributions and engagement in the development process, its low level is also a major constraint for realising the demographic dividend to its fullest extent (Desai 2010; UNFPA 2018). However, in the present time of globalization, females’ access to education has increased and these females can significantly contribute in the economic development through their greater access to remunerative employment (Luke and Munshi 2011; Desai 2014). Raising female labour force participation can significantly accelerate India’s economic growth. However, in order to enhance females’ work participation rate, it is essential to expand their employment options and reducing their labour market disadvantages (Desai 2010; Sorsa 2015). Thus, at present, providing employment to the adult population in India has emerged as the biggest challenge both at the national level as well as at the level of its various states. Therefore, the central government and the governments of the various states need to formulate policies that will enable engaging its increasing adult population in the workforce and also in meeting the multifold needs of its rising older population.

5 Conclusion and policy implications

This study reveals that India’s population has been experiencing age structural transition which has brought significant changes in its age composition during 1961 to 2011. The number and share of older population have increased significantly since 1961, and are expected to grow further in the near future as the older population is growing faster than other age groups. Interestingly, among the older people, females outnumber males. The growth in the number of older population has raised the ageing index, old age dependency ratio, and oldest old age dependency ratio, resulting in a greater burden of the older population on the working age population. After 1971, the share of India’s child population continued to fall while the working age population increased. However, the pace of age structural transition and ageing varies across states due to remarkable variations in fertility, mortality, life expectancy, migration as well as other socio-economic and demographic conditions prevailing there. The age structural transition and ageing have been fast in South Indian states along with Punjab and Himachal Pradesh as compared to the North Indian states like Bihar, Uttar Pradesh, Madhya Pradesh, Rajasthan and Gujarat which are passing through slow age structural transition and ageing. While moderate age structural transition and ageing has been recorded in Andhra Pradesh, Karnataka, Maharashtra, Odisha, and Haryana. Thus, various states of the country are at different stages of age structural transition and it has led to a demographic window of opportunity reflected in the demographic dividend, the benefits of this demographic dividend should be fully reaped before it ends due to shifting of working age population into the older age group. However, India’s demographic window of opportunity is expected to remain open for a relatively longer duration due to the differentials in the age structural transition in various states of the country. India’s age structural transition, thus, offers great potential for the economic development and also poses serious challenges to be addressed within a limited time span through effective policy intervention. The finding of this study indicates that India will experience major expansion in its working age population due to age structural transition in highly populated states of North India. Unfortunately, in these states a very large proportion of population is illiterate, or has low level of education, unemployment rate is very high not only among illiterate but among educated people as well. Females’ literacy, level of education and employment as well as health conditions are very disappointing.

In view of the changing age structure across the states, a large labour supply is expected to occur from North Indian states towards South Indian states. However, migrants face several problems in their destinations states because their rights are not effectively protected. Moreover, sometimes there is violence against the migrants in many states. Therefore, migrants’ issues should be properly addressed in the destination states. Interestingly, due to the vast size of the working age population and a lack of employment possibilities, India has emerged as the world’s the largest supplier of adult emigrants while also emerging as the world’s largest recipient of foreign remittances. However, most of the emigrants are unskilled and semi-skilled workers especially moving towards the Gulf countries. As a result, enough skill and training should be provided prior to emigration so that these emigrants can earn higher wages overseas and send more remittances to the country.

Health crises experienced during the second wave of Coronavirus pandemic, and women health conditions indicate the inadequate health infrastructure and poor access to health care facilities in the India. In view of these challenges associated with age structural transition, this study, therefore, suggests for effective policy implementation in employment, education and health sector with particular focus on the states with low level of age structural transition. The central and state governments must equip the youths with a high quality of education and skill development, and provide them adequate employment opportunities and access to affordable health care facilities. Special efforts should be made to improve female’s education, work participation, access to affordable health care services particularly in less developed sates in order to reap full benefits of the demographic dividend, leading to higher economic growth, social development, and prosperity in the country. States with high level of age structural transition and ageing need to focus on ensuring the socio-economic security of their increasing older population, old age related health care facilities etc. In these states, as the share of working population is expected to decline while the life expectancy has risen significantly and many older people are physically fit to work in the older ages. Therefore, the central and state governments should consider raising the retirement age of all the employees.