1 Introduction

Food security is the state in which every individual in a family has access to an adequate and nutritionally balanced diet that is culturally appropriate, thereby promoting good health [1]. Socially acceptable methods enable the achievement of this condition. The food supply issue has always been a formidable obstacle for humanity. Global estimates indicate that over 820 million people face food insecurity daily, and over 2 billion people experience inadequate intake of essential micronutrients, significantly impacting their overall health and life expectancy [2]. The prevalence of food insecurity is far more pronounced in developing nations, including India. In the regions of Asia and Africa, which together make up over 92 percent of the global population, undernourishment is prevalent. According to the Food and Agriculture Organisation [3] in 2013, the South Asia region alone comprises over 294.7 million people who experience food insecurity, accounting for almost 35 percent of the global population suffering from undernourishment.

Despite the substantial endeavours made by the public and private sectors to aid impoverished families in meeting their food requirements, about 10 percent of households continue to face challenges in ensuring food security [3]. There exists a population of over three million children that reside in families that are categorised as experiencing “very low food security” [4].

In the context of health hazards, i.e., COVID-19, it is well observed that those belonging to economically disadvantaged segments of society tend to experience the most severe impacts [5, 6]. According to the National Sample Survey Office [7], the majority of small and marginal farmers in India own less than two hectares of land, constituting over 80 percent of this land. Further, a significant portion of the population in rural areas is comprised of landless agricultural labourers, which has the poorest population in the rural population. These statistics highlight the vulnerability of Indian agriculture and the prevalence of food insecurity among the rural population. Amidst the period of enforced confinement, those engaged in farming and agricultural labour have mostly seen a decline in their earnings derived from informal work, rendering them susceptible to financial vulnerability.

The COVID-19 pandemic, characterised by its novel nature and ability to spread between individuals, has had a profound and unprecedented negative influence on healthcare systems worldwide, permeating all facets of human existence [8]. In response, the World Health Organisation [9] (WHO) provided recommendations for implementing preventative measures aimed at mitigating the impact of the disease. In order to mitigate the spread of COVID-19, the Indian government implemented a nationwide lockdown for a duration of 21 days, commencing at midnight on March 25th 2020 and concluding on April 14th, 2020. The Indian government then extended this lockdown until May 31st, 2020. The Central and State Governments have implemented several steps to address health disasters, including thermal screening, testing, social distancing, and the immediate provision of $23.8 billion [10] via direct cash transfers, the public distribution system (PDS), and the Mahatma Gandhi National Rural Employment Guarantee Programme (MGNREGA). The implementation of a countrywide lockdown had a profound impact on several economic operations, particularly the agricultural sector. There have been concerns expressed about the adverse impact of the pandemic on the agricultural sector after the prolongation of restrictions imposed on the mobility of people and vehicles. The study conducted by Kumar et al. [11] in Uttar Pradesh revealed that the absence of migrant labour in certain areas and an excess of workers in others had a significant impact on the harvesting of crops in 2020 (the nationwide lockdown period). This resulted in a decline in agricultural wages in certain areas and an increase in others, along with substantial losses of farm produce. Moreover, the partial closure of rural markets and limited procurement alternatives, coupled with an ample supply of items, resulted in scarcity of food supplies and a significant surge in costs, disproportionately impacting the poor population, especially agricultural labourers.

Hence, the main objective of this study is to assess the food security situation at both the macro and micro levels in order to establish an effective food strategy for rural India as well as other emerging nations with comparable geographical characteristics.

Regarding the influence of COVID-19 on household food security, there are a minimum of four possible methods by which the ongoing global health crisis may exert its effects. First, the virus’s development or apprehension about its contraction has the potential to reduce activities that generate money. This encompasses both domestic revenue streams and global revenue streams, including remittances. For example, the pandemic is expected to produce a reduction in remittances, which are often seen as crucial for ensuring food security in times of food crises [10, 12]. Second, the implementation of government-imposed measures aimed at mitigating the transmission of the pandemic, such as mobility limitations and lockdown protocols, has resulted in the disruption of various economic activities, thereby leading to a decline in family earnings [13]. Third, the occurrence of disturbances in food systems and subsequent impacts on food supply may significantly impede individuals’ ability to get enough nutrition. Finally, we must acknowledge that disruptions in food systems and their subsequent effects on the food supply can potentially limit individuals’ access to nourishment [14]. According to Laborde et al. [15], the most economically disadvantaged families, who are believed to allocate 70 percent of their total income towards food expenditures, were particularly vulnerable to fluctuations in their income levels.

With these evidence, the novelty of this study is as follows: Firstly, this study represents the first empirical investigation that explores the food security status at a macro-level in Uttar Pradesh during COVID-19, the most populous state in India. Secondly, it also aims to examine the household food security status at a micro-level in the Bundelkhand region, which is considered one of the most underdeveloped region in India, specifically within the context of Uttar Pradesh. Thirdly, this study presents empirical information that elucidates the underlying processes that influence food intake patterns. In addition to the socio-economic and demographic features of the households included in the sample. Finally, this study’s anticipated outputs will aid policymakers in developing effective strategies to improve food security and nutrition outcomes, not only in India but also in other developing nations.

Moreover, this study examines the interconnectedness of COVID-19 and food security at the local level in Bundelkhand, India. The study used a combination of macro- and micro-level data to analyse the current status of food security in the Uttar Pradesh and Bundelkhand region of India. The study utilised macro-level data at the district (macro administrative unit) level to construct a comprehensive food security index that encompasses four key dimensions: availability, accessibility, stability, and utilisation. Additionally, the study has developed a household-level food security index by systematically collecting field survey data from 240 households, utilizing an indicator-based methodology.

2 Methods and materials

2.1 Study area

This study captured micro-observations on food security in the districts of the Bundelkhand region of Uttar Pradesh, India. The socioeconomic characteristics of districts were compared with those of Uttar Pradesh (Table 1). It found that population growth was relatively higher in Jhansi from 2001 to 2021 compared with Uttar Pradesh and Lalitpur, while the population density is relatively lower in Jhansi and Lalitpur (398 and 342 persons/km, respectively) than that of Uttar Pradesh (i.e., 829). The Table 1 indicates that over 40 percent of Jhansi’s population resides in urban areas, compared to only 14.36 percent in Lalitpur. Further, more than 25 percent of the population in Jhansi and Lalitpur belongs to the backward social group and practices Hinduism. As far as food grain productivity is concerned, it was relatively lower in Lalitpur than in Jhansi and Uttar Pradesh. Per capita, net domestic product was also lower in Lalitpur (i.e., $791.98) compared with Jhansi and Uttar Pradesh ($980.66 and $800.77). In totality, economic indicators show that the population belonging to the Jhansi district is relatively in better condition compared with the Lalitpur district [16].

Table 1 Economic indicators of Lalitpur, Jhansi, and Uttar Pradesh.
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2.2 Sampling technique and sample size

To collect field survey data, the current study employs a multistage random sampling technique. A field survey was conducted in August and September 2022. In the first step, the most populous State of India i.e., Uttar Pradesh was selected. In the second step, the Budelkhand region was purposely selected as it has the most backward and food-insecure regions. In the third step, two districts, namely Jhansi and Lalitpur, were selected. In the fourth step, two Development Blocks (administrative units) from each district were selected. In Jhansi district, Mauranipur and Moth Development Blocks were selected, while in Lalitpur district, Talbehat and Mehroni Development Blocks were selected. In the fifth step, one village (micro-administrative unit) from each Development Block was selected. The Larauni village from Mauranipur Development Block, Madpura village from Moth Development Block, Badanpur village from Talbehat Development Blocks, and Manikpur village from Mehroni village were selected.

Lastly, 60 samples from each village were selected. Thus, 1 State, 2 districts, 4 Development Blocks, 4 villages, and 240 samples were selected to elicit household-level information on how COVID-19 impacted the food security status of surveyed farmers.

2.3 Analytical framework for food security assessment

The current study employs an indicator-based methodology to compute the food security index for the selected districts and households. The indicator approach is widely employed and offers several advantages that have facilitated its extensive use in the planning process and policy communication over time. These advantages include the ability to condense a large amount of intricate information into a manageable format [3, 17], the flexibility to utilise data at various scales, ranging from individual to national levels, for the construction of a food security index, the capacity to employ proxy data when original data is unavailable, the capability to identify, prioritise, and rank food insecure villages in order to identify potential barriers in their development process, and the ability to monitor and evaluate intervention efforts [18, 19].

This study employs differential data in order to compute the food security index, thereby necessitating consideration of the normalisation procedure. Therefore, the current research has used the min–max technique proposed by Singh and Sanatan [20] in order to normalise indicators to a standardised range of (0, 1), taking into consideration their functional association with the dimension of interest, namely food security. The use of the min–max approach may facilitate the streamlining of an intricate dataset related to the nexus of food supply, accessibility, stability, and cost. The strategy has significance in terms of providing information to both the general public and decision-makers on significant issues related to food insecurity [3] as well as the necessary measures to address and mitigate these challenges [21]. Equations 1 and 2 were used to represent indications of the larger-the-better and smaller-the-worse types, respectively.

$$Z_{ij} = \frac{{X_{ij} - Min\left( {X_{ij } } \right)}}{{Max(X_{ij} ) - Min(X_{ij} )}},$$
(1)
$$Z_{ij} = \frac{{Max(X_{ij} ) - X_{ij} }}{{Max(X_{ij} ) - Min(X_{ij} )}},$$
(2)
$$i = 1,2, \ldots .I\;and\;j = 1, 2, \ldots .$$

where \(Z_{ij}\) is the variable index value, \(X_{ij}\) is the actual value, \(Max(X_{ij} )\) and \(Min(X_{ij} )\) is the maximum and minimum value of \(i{\text{th}}\) indicator for the \(j{\text{th}}\) household.

2.3.1 Assigning weight

Given the assignment of appropriate weight for different components is an important issue in the construction of an index, the study has adopted the statistical weight method [22].

$$Wi = \frac{1}{{\mathop \sum \nolimits_{i = 1}^{n} \frac{1}{{\sqrt {Var\left( {Z_{ij} } \right)} }}*\sqrt {Var\left( {Z_{ij} } \right)} }},$$
(3)

where \(Wi\) is the weight of ith indicator, and \(Var\left( {Z_{ij} } \right)\) is variance of standardized value of ith indicator in the districts/household. The calculated weights were used to construct the component index \(P_{{\text{j}}}\) for the ith district/household using Eq. (4).

$${P_{\text{j}}} = \frac{{\sum\nolimits_{{\text{i}} = 1}^{\text{n}} {{Z_{{\text{ij}}}}*{{\text{W}}_{\text{i}}}} }}{{\sum\nolimits_{{\text{i}} = 1}^{\text{n}} {{{\text{w}}_{\text{i}}}} }}\left( {0 < Wi < \sum\limits_{{\text{i}} = 1}^{\text{n}} {{{\text{w}}_{\text{i}}} = 1} } \right).$$
(4)

Finally, the food security index for each district/household is calculated as an average of the food accessibility, food availability, food stability, and food utilization index. Districts with higher index score indicates that it has higher food security. Further, we categorized the homogenous districts under each component into four groups: low (0–25%), medium (26–50%), high (51–75%), and very high (76–100%) based on the quartile estimation.

2.4 Identification of rationale food security indicators

The present study aims to assess the food security status of districts in Uttar Pradesh and survey households using an indicator approach. The study assumes that food security in the surveyed districts consists of four components: food accessibility, food availability, food stability, and food utilisation during the COVID-19 crisis.

To develop a food accessibility index, accessibility of the local market, access to necessary goods for daily consumption, accessibility of all seasonal roads, price stability, and food inflation, access to ration cards, accessibility of free rations under the Pradhan Mantri Garib Kalyan Yojna (PMGKY), and accessibility of mid-day meal indicators were considered (Table 2). For instance, access to a midday meal ensured the nutritional security of children. Likewise, a mismatch between food prices and wages results in lower food accessibility [23].

Table 2 Rational indicators for household’s food security.
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As far as the food availability component of food security is concerned, this study considered six indicators, namely the availability of fertile land, farmers responses to farm productivity decline, supplementation and low-cost food for children, adult and child skipped food due to the non-availability of food, and surveyed households hungry but didn’t eat due to the non-availability of food (Table 2). For instance, fertile land resulted in higher farm productivity and ensured food availability throughout the year [24]. Similarly, the perception of farmers of declining farm productivity gives a signal that the degree of food availability has declined over the years, and it is assumed that it is negatively associated with the food availability index [3].

Further, to develop the food stability index, eight indicators were used, namely irrigated land, use of chemical fertiliser, crop diversification, irregularities in rainfall, access to electricity, awareness of food prices in local markets, awareness of the minimum support price, and storage capacity (Table 2). For instance, irrigation is a major determinant of higher farm productivity. Hence, irrigation ensured food stability in the system [20]. Likewise, the majority of Indian farming systems are closely linked with southwest monsoon rainfall distribution. Higher variability in rainfall results in lower food stability in the system and will be responsible for lower households’ food security [3].

Lastly, a food utilisation index was developed using seven indicators: awareness of a balanced diet, household’s ability to afford balanced food, inclusion of meat and eggs in the diet, weight loss, cutting the size of children’s meals, consultation with government officials on nutrition status, and participation in nutrition diet programmes (Table 2). For example, awareness of a balanced diet gives signals for better nutritional status in households. Households aware of a balanced diet consume nutritious food to cope with health disasters like COVID-19 [6, 11]. This resulted in higher food utilization and food security than the others. Additionally, stunting is a sign of malnutrition. It also gives a signal that households are not eating enough food. This resulted in lower food utilisation and food security status [23].

3 Results

3.1 Assessing the food security status of districts in Uttar Pradesh

By using Eqs. 1 and 2 and the data mentioned in Table 2, district-wise food availability, food accessibility, food stability, food utilisation, and food security indices were calculated (Table 3). The results show that about 68 percent of districts fall under the medium category, followed by 6.67 percent in the low category, 21.33 percent in the high category, and only 4 percent in the very high category as far as the food availability index is concerned. The study is also calculated the food accessibility index for all 75 districts of Uttar Pradesh using the indicators mentioned in Table 2. The results show that more than 85 percent of districts fall into the high food accessibility category, while only 13.33 percent fall into the medium category. Further, the calculated the food stability index results show that nearly 90 percent of districts fall into the medium category, whereas only 5.33 percent fall into the low category. Furthermore, the food utilisation index results show that out of 75 districts, 47 fall under the high category, while 26 fall under the very high category. Furthermore, about 51 districts out of 75 fall into the high category, while 24 fall into the medium category as far as food security index is concerned.

Table 3 Categorization of districts based on the index scores.
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3.2 Region wise food security status

Based on the portfolio of indicators (Table 2), it was discovered that 50 percent of the population in the Bundelkhand region has poor food security (Table 4). On the contrary, very high food security was found in the western region. The Bundelkhand region is historically backward in terms of income and sources of livelihood and faces recurrent drought every year [21], while the western region has fertile land, improved irrigation sources, and relatively more non-farm employment opportunities [26, 27]. Furthermore, districts in the eastern region are constantly flooded, and the majority of the population relies on agriculture because non-farm employment opportunities are scarce, as shown in Table 4, which shows that nine districts in the region have low food security.

Table 4 Region wise status of food security status.
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3.3 Micro-level information on the impact of COVID-19 on food security

The information gathered at the micro-level reflects households’ perceptions, constraints, and opportunities regarding various aspects of the phenomena being studied. The existence of such a repository of information and proof greatly aids both the harmonization of ancient practices with contemporary scientific understanding and the development and execution of adaptation procedures [28].

In order to understand its significance, several researchers have attempted to examine and quantify the various repercussions of COVID-19 on food security and nutritional status. According to Nechifor et al. [29], 1.3 percent of families in sub-Saharan Africa, particularly in rural regions, do not consume the required calories to maintain food security status. The results also highlighted the fact that Kenya’s food security is still at risk as the global pandemic spreads. There was a decrease in food security among rural families in southern Iran during the COVID-19 pandemic [30]. A study conducted by Ceballos et al. [31] highlighted that rising costs, falling earnings, and limited availability at local markets all contributed to a reduction in rural families’ food security and food variety during COVID-19. Furthermore, Rahman et al. [32] discovered that COVID-19 will increase poverty, malnutrition, and income for backward population and those working in the informal sector because the government has imposed a nationwide lockdown. Quarantine, mobility, and social limitations all influenced agro-food systems, supply-value chains, and market levels.

3.4 Socioeconomic characteristics of surveyed farmers

The socioeconomic characteristics show the risk-aversion behaviour of farmers. Table 5 shows that the number of poor households in Manikpur village, Lalitpur district, is more variable than in other surveyed villages. Manikpur village had about 36.75 percent of households living below the poverty line (BPL), compared to only 26.25 percent in Larauni village of Jhansi district. Larauni village had the highest average household land size, while Manikpur village in Lalitpur district had the lowest. About 44.75 percent of households in Manikpur village belong to the backward social group. The study  observes that the majority of surveyed households are young. The average age varies from 30 years in Manikpur to 42 years in Madpura. The mean income also varies from $292.50 in Manikpur to $339.31 in Larauni. Access to basic amenities shows that households in Manikpur village have the least access compared to those in Larauni village. For instance, about 12.35 percent of households belonging to the Larauni village don’t have all seasonal houses, while about 27.75 percent of households belonging to the Manikpur village don’t have all seasonal houses.

Table 5 Socioeconomic characteristics of sample households.
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3.5 Farmers’ perception on COVID-19

Farmers’ perception of COVID-19 shows their risk-aversion capacity to deal with the pandemic. The non-availability of effective medicine for COVID-19 is a serious issue to deal with. Therefore, ex-ante and ex-post adaptation strategies are vital to combating the pandemic. Ex-ante adaptation strategies like health insurance, consultation with doctors, and a balanced diet have not only helped in containing the spread but also reduced the risk of community spread, while ex-post adaptation strategies like self-quarantine and COVID-19 testing have reduced health expenditure.

As far as ex-ante adaptation strategies are concerned, about 15 percent of households have taken health insurance, 56 percent of households have consulted with doctors on COVID-19, and about 35 percent of households have taken a balanced diet (Fig. 1). Likewise, as far as ex-post adaptation strategies are concerned, about 68 percent of households have tested positive for COVID-19 and about 95 percent of households’ self-quarantine to cope with the COVID-19 health disaster.

Fig. 1
figure 1

(Source: Field Survey Data, 2022)

Households perception of COVID-19

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3.6 Food accessibility index (FASI)

Table 6 presents the food accessibility index and its indicators. The calculated food accessibility index shows that households belonging to the Manikpur village have relatively less access to resources to access food, while households belonging to the Larauni village have relatively higher food accessibility among the surveyed villages. The cross-indicator analysis shows that the highest access to local markets, access to daily needs goods, access to all seasonal roads, and access to midday meals were the main contributing factors for higher food accessibility in Larauni village compared with Manikpur village. Approximately 62 percent of households in Larauni village have access to the local market, compared to just 41 percent in Manikpur village. More than 72 percent of households in Larauni village have access to necessary goods for daily consumption expenditure, compared to only 55 percent in Manikpur village. Furthermore, about 85 percent of households in Larauni village have access to all seasonal roads, compared to only 58 percent. Similarly, about 82 percent of children get a midday meal from the Larauni village, while only 78 percent get a midday meal from the Manikpur village.

Table 6 Village wise food accessibility index.
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3.7 Food availability index (FAI)

Table 7 displays a village-based food availability index. The results show that households belonging to the Larauni village have relatively higher food accessibility (i.e., a 0.603 index score) compared with households belonging to the Manikpur village (i.e., a 0.500 index score). The cross-indicator analysis shows that relatively higher perceived farm productivity loss, supplementation and low-cost food for children, food skips due to non-availability of food, and hunger but not eating food due to non-availability of food were the main influencing factors for lower food availability in Manikpur village compared with Larauni village.

Table 7 Village wise food availability index.
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3.8 Food stability index (FSBI)

Table 8 shows that households belonging to the Larauni village (i.e., 0.513 index score) have relatively higher food stability compared with households belonging to the Manikpur village (i.e., 0.402 index score). The cross-indicator analysis shows that higher fertile land, use of chemical fertiliser, crop diversification, awareness of food prices in the local market, access to the minimum support price, and storage capacity were the main influencing factors for higher food stability in Larauni village compared with Manikpur village. About 28 percent of households reported they have fertile land suitable for wheat production with assured irrigation facilities, while households belonging to the Manikpur village have only 15.8 percent fertile land. Furthermore, about 85 percent of households in Larauni village use chemical fertiliser to increase farm productivity, compared to only 65 percent in Manikpur village. About 21 percent of households in the Larauni village have diversified their cropping patterns, compared to only 15 percent in the Manikpur village. Furthermore, about 60 percent of households in the Larauni village were aware of food prices in the local market, compared to only 48 percent in the Manikpur village. Nearly half of the households in Larauni village were aware of the minimum support price, whereas only 33 percent of households in Manikpur village were aware of the minimum support price. Finally, about 22.5 percent of households in Larauni village have storage capacity to store farm produce, resulting in higher farm returns, compared to only 15.5 percent in Manikpur village. In total, households in Larauni village have a more stable food system, whereas those in Manikpur village have a relatively less stable food system.

Table 8 Village wise food stability index.
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3.9 Food utilization index (FUI)

Table 9 shows the food utilisation index for the surveyed villages. The calculated food utilisation indices for different villages show that households belonging to the Larauni village were relatively more likely to utilise their food resources to ensure food security compared with households belonging to the Manikpur village. The cross-indicator analysis shows that higher awareness of balance diet, taking meat and eggs to meet nutritional requirements of the body, consultation with government officials on balance diet, and participation in nutrition diet programmes were the main contributing factors responsible for higher food utilisation in households belonging to the Larauni village compared with households belonging to the Manikpur village. We observed that approximately 45 percent of Larauni village households were aware of a balanced diet, compared to only 35 percent of Manikpur village households. Furthermore, about 29 percent of households in Larauni village were able to afford balanced food, compared to only 19 percent in Manikpur village. Furthermore, about 26 percent of households in Larauni village have consulted with nutrition experts on a balanced diet, compared to only 15 percent in Manikpur village. Likewise, about 18 percent of households belonging to the Larauni village have attended the nutrition diet programme, while only 9 percent of households belonging to the Manikpur village have attended the nutrition diet programme.

Table 9 Village wise food utilization index.
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3.10 Food security index (FSI)

Table 10 depicts the village-wise food security status of the surveyed village. The findings indicate that households in the Larauni village of Jhansi district were highly food secure, whereas those in the Manikpur village of Lalitpur district were less food secure. The cross-component analysis shows that higher food accessibility, availability, stability, and utilisation have resulted in higher food security for households belonging to the Larauni village, while lower food accessibility, availability, stability, and utilisation have resulted in households belonging to the Manikpur village.

Table 10 Village wise food security index.
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3.11 Validation of food security index with its components

Table 11 shows the validation of the Food Security Index along with its four components, i.e., accessibility, availability, stability, and utilization. Spearman’s correlation coefficients reveal that food security is positively associated with its four components, as the value lies closer to + 1, as shown in the table. It strongly reflects that food security depends on food availability, accessibility, stability, and utilization, and also has a significant association with its components.

Table 11 Validation of food security index.
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4 Discussion

4.1 Food security assessment: an application of indicator approach

Food security may be evaluated in three main ways: via the use of simulation approach [33], through the use of dietary intake approach [34], and through the use of indicators approach. Researchers frequently use the simulated data approach to make predictions on global food security. They have assessed and predicted food security using large-scale data, primarily at the national level. The main benefit of this approach is its ability to predict the future food security scenario. Altering assumptions about factors like population increase, arable agricultural land availability, water resource availability, and technology scale might provide new projections. This approach’s findings may be applicable to international food policy. The measurement of food security at the individual and household levels also often uses the dietary intake technique. The estimate leaves out the issue of food stability in favour of a greater emphasis on nutritional safety. The dietary approach cannot evaluate food security at the district or state levels. Food security was measured by surveying families in the Bundelkhand region of Uttar Pradesh; however, this research used complicated and varied data to do so. As a result, we can best estimate our data using an indicator-based strategy. There are a number of benefits to using indicators in the planning process and policy communication, including the flexibility to use data from any level (individual, household, village, district, state, and country) in the creation of a food security index and the flexibility to use proxy data in place of original data if the latter is unavailable. In addition, the indicator technique may be used to quickly create knowledge that can be used to help tailor interventions to certain farm types and geographic locations, where they are more likely to have a positive impact on the farm’s socioeconomic standing.

4.2 Risk aversion strategies and COVID-19

The findings of this study suggest that households in the Bundelkhand region employ various livelihood strategies, including crop diversification, seeking advice from nutritional experts, and diversifying their occupational patterns. These strategies have implications for their ability to respond to changes in agronomic management practices and climate shocks, which in turn affect their food security. Putting together food security scenario analysis and farm typological assessment could be a useful tool for agricultural planners who want to see how different development interventions will work before they happen. This approach allows for the identification of optimal choices among different development alternatives. Despite being a simplified representation of farm family livelihood choices, the use of typologies and indicators together appears to be a valuable heuristic tool for examining and evaluating food security patterns across various simulated scenarios. This research represents the inaugural endeavour to integrate secondary data and field survey data in order to assess the food security condition of several districts and survey farmers within the COVID-19 epidemic. Farmers have effectively used their indigenous knowledge and interpersonal networks to improve effectively address the issue of food security. The centrally controlled Pradhan Mantri Garib Kanyan Yojna (PMGKY) has significantly contributed to food security by offering free rations to eligible families.

4.3 Dietary quality implications of the COVID-19 pandemic

This section aims to analyse the impact of the COVID-19 pandemic on dietary quality, with a specific emphasis on the consumption patterns of seven food products that are rich in essential nutrients. Figure 2 presents a comparison of the frequency of intake, specifically above 10 times/month, of the aforementioned food categories by respondents both before and after the COVID-19 crisis. There exists a substantial disparity in the frequency of food group consumption reported by the respondents before and during the epidemic. For example, it was observed that before the COVID-19 pandemic, around 56 percent of households regularly included fruits in their dietary habits. However, in the COVID-19 era, this percentage decreased to 32 percent as fewer families consumed fruits. In a comparative analysis, it was shown that during a typical era, a significant majority of families, over 80 percent, regularly included vegetables in their dietary intake. However, in the context of the COVID-19 pandemic, this proportion declined substantially, with only 46 percent of families maintaining a consistent consumption of vegetables. In contrast, indigenous botanicals have seen a significant increase in use. In the pre-pandemic era, a mere 25 percent of families included local herbs in their daily dietary practices as a means to sustain their nutritional well-being. However, in the midst of the COVID-19 pandemic, there has been a notable surge in the intake of local herbs, with around 78 percent of homes now partaking in this dietary practice. According to Fig. 2, there was an approximate 50 percent decrease in the number of participants who reported frequent consumption across the seven specified categories during the pandemic. The potential causes of this phenomenon may be attributed to limited affordability or constrained market access resulting from various constraints. Darnton-Hill and Cogill [35], as well as Harris et al. [36], have also documented comparable results in India. According to the findings, families exhibited a preference for safeguarding their intake of basic foods rather than opting for costlier but more nutritionally packed food options. The aforementioned situation is a matter of concern since some food categories play a crucial role in providing essential micronutrients necessary for maintaining good health. Moreover, estimations indicate that more than two billion individuals globally are currently experiencing deficiencies in micronutrients [37].

Fig. 2
figure 2

(Source: Field Survey, 2022)

Dietary diversity during COVID-19 and normal periods

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5 Conclusion

This study has used quantitative systems analysis methodologies to evaluate the effects of the COVID-19 pandemic on the food security of families surveyed in Bundelkhand, an area in India characterised by significant socioeconomic challenges. The COVID-19 epidemic and the implementation of mobility restrictions have had a significant influence on the food security of families. This impact is seen in two main ways: firstly, via price fluctuations caused by supply-side constraints, and secondly, through the reduction of wages resulting from increased unemployment and loss of earnings. The findings indicate a deterioration in both food security and nutritional quality among the families surveyed in the Jhansi and Lalitpur districts of the Bundelkhand area during the COVID-19 pandemic, as compared to the pre-pandemic era. The aforementioned factors may be attributed to the decline or decrease in earnings, limited market accessibility resulting from travel limitations, and diminished buying capacity. Households in the sample population depend on market mechanisms for their livelihood, and any imposed limitations have a direct impact on their financial resources.

These impacts would manifest differently depending on the pre-existing livelihood choices and degree of agricultural diversification among the sampled families. Farmers that have strategically expanded their income-generating portfolio by including additional sources of revenue exhibit a relatively lower degree of food insecurity in the face of the COVID-19 pandemic. This study illustrates the integration of district-level (macro) data and household-level (micro) data to identify the most food-insecure locations within the region. Therefore, this study has used a comparable methodology to identify areas experiencing food insecurity in other agro-climatic zones of India. This would enable a more comprehensive assessment and targeted implementation of food security development policies, not only in Uttar Pradesh but also in other regions where similar agricultural systems are prevalent.

6 Policy recommendations

Based on the aforementioned findings, the current research suggests numerous solutions to improve income stability, guarantee food accessibility, and aid in livelihood recovery following a pandemic like the current COVID-19 crisis. The first step is the government’s implementation of structural modifications in social security programmes that include adaptable packages in response to social security concerns, as well as food security programmes that account for emergency situations, serving as a readily available contingency plan. Further, the facilitation and use of savings and borrowing potential, particularly among individuals with low incomes and rural families, would provide avenues for accessing funds and revitalising enterprises and lives in the aftermath of a crisis. Finally, it is crucial to establish systems that guarantee the resilience and continuity of food supply chains, with a particular focus on those that provide access to foods with high nutritional value.

7 Limitations of the study

Although efforts were made to assess the food security situation in the districts of Uttar Pradesh and gather field survey data to analyse the influence of COVID-19 on the food security status of selected families, it is important to note that the data used in this research was derived from geographical sources. Spatial–temporal data has the potential to improve outcomes and facilitate monitoring of food policy initiatives. This study has gathered a total of 240 samples from two distinct regions. Therefore, the findings can only extrapolate to the Bundelkhand area or other locations with comparable features. Nevertheless, the data presented in this study offers valuable insights into the first consequences of the COVID-19 problem. Future research endeavours might further expand upon and enhance these findings by using representative and longitudinal samples or other survey methodologies. Further, it is critical to improve readiness for future health hazards and establish effective monitoring and surveillance systems to address the recent surge in COVID-19 cases. Moreover, a comprehensive strategy that includes the coordination and extension of healthcare facilities, as well as a better understanding of emerging phenomena, is essential in order to avoid another catastrophe.