Are livelihoods of slum dwellers sustainable and secure in developing economies? Evidences from Lucknow, Uttar Pradesh in India

Abstract

Objectives

We adopted the Sustainable Livelihood Security (SLS) approach to assess the living conditions of slum dwellers in Lucknow, Uttar Pradesh, India. Keeping the urban poor at the centre, we attempted to bring out the multidimensional nature of poverty and explored various aspects of the livelihood of slum dwellers.

Methods

We surveyed 900 households from both notified and non-notified slums of Lucknow city to construct the SLS index, keeping the social, economic, infrastructural, health, and micro-environmental aspects of slum dwellers in the background. We collected data based on the household approach of the UN and the neighbourhood approach of the Government of India and aggregated the weighted index values under various sub-components to construct a composite index.

Results

The results suggested that the index values were low for both types of slum dwellers in Lucknow city specifically in the economic, infrastructural, and micro-environmental aspects. The results also showed that ‘non-notified slum dwellers’ were much more deficient in all the dimensions compared to their ‘notified’ counterparts. The livelihood condition of the marginalized households (backward castes and minorities) was especially precarious and vulnerable.

Conclusion

The findings reveal the existence of a high level of informality of livelihood of the urban poor in terms of housing, employment, health, and other basic amenities, and demonstrate that their livelihood condition is characterized by a low assets base, and poor strategies to overcome exigencies and risks.

Recommendations

This paper recommends enactment of an urban employment guarantee act, conducting of sabhas (meetings) at the ward level on a regular basis to promote awareness, and notification of non-notified slums to notified slums on regular basis for the overall development of slum dwellers.

Highlights

(for Review)

• •Study revisited Sustainable Livelihood Security an integrated and multidisciplinary framework of urban slums in India.
• •Study addressed gaps by incorporating health and micro-environmental aspects to address livelihood issue of slum dwellers.
• •The grass-root level results confirmed that ‘non-notified slum dwellers’ were deficient in terms of socio, economic, infrastructural, health and micro-environmental aspects compared to their counterparts of ‘notified dwellers’.
• •This paper suggested specific action and policies for the overall development of slum dwellers.

1. Introduction

The manifestation of slums in urban centres is an outcome of numerous exogenous and indigenous factors - such as inadequate investment in basic urban infrastructure, poor economic diversification, and ad - hoc urban governance system - right since the colonial period in the developing and under developed nations, specifically in Africa, South America, and Asia [1,2]. During the colonial period, the British feared that urbanization by granting property rights (security of tenure) to migrants would foster anti-colonial solidarities. Therefore, they preferred sojourners and temporary labour and adopted strong racial discrimination in most of the historical cities of Africa like Nairobi (Kenya), Dar-es-Salam (Tanzania), and Rhodesia (Zimbabwe) and in the North Indian cities like Allahabad, Varanasi, Kanpur, Lucknow, and Delhi [3,4]. At the same time, frequent drought, high inflation and high interest rates, and low prices of agricultural products led to a huge agrarian migration to the urban areas, which resulted in the creation of a large number of slums during the post-independence period.

Studies have observed that the formation of slums and the deprivation faced by the slum population are due to: poor intergenerational socio-economic conditions [5], an unstable linkage between urban population growth and economic growth [6], poverty trap, policy trap and low investment equilibrium trap [7], land and housing market failure induced by demographic, economic, or institutional factors, and a disjointed process of modernization [1]. In post-independence India, the prominent reasons for the development of slums and the subsequent deprivation, especially in the recent decades, include the large-scale rural to urban migration and the settling of the poor near industrial or construction projects on urban land owned mostly by the government [8], the development of informal leadership in slums to catalyze the demand for the basic needs of the slum dwellers, and the resultant political mobilization through voting [9].

According to the UN-Habitat's estimates, in 2016, about 16% of world's total population and 30% of its urban population lived in slums [10]. The proportions of slum population to urban population in Sub-Saharan Africa, South Asia, and South East Asia are much larger (56%, 31%, and 29% respectively) [1]. Despite numerous efforts to prevent further slum formation, the absolute number of slums has increased over time [11]. Many well-known slums, viz. Dharavi in Mumbai, India (around 1 million population), Orangi in Karachi, Pakistan (>1 million population), Kibera in Nairobi (0.7–1 million population), and Neza/Chalco/Itza in Mexico City (>1 million population) are situated in the developing nations and are continuously growing in size. There has been a continuous growth in the overall slum population in recent decades in India [12]. In 2011–12, with a decadal growth of 25%, the country's total slum population stood at around 65.49 million (nearly 17.2%) out of a total urban population of 377 million. Of this, 63% and 37% of total slum households were in notified and non-notified slums respectively [12].1

The living conditions of slum households are poor due to the following factors. First, low security of tenure, poor quality of housing units and other infrastructure, poor neighbourhood, and location are significant factors [[13], [14], [15]]. Since there is an underestimation of the slum population and urban poverty based on the Census definition of slum in India, there is inadequate resource allocation for slum improvement. This adversely affects health outcomes and accessibility of basic amenities [16,17]. Second, infrequent notifications of slums and inadequate improvement in the security of tenure (de facto) have worsened the quality of infrastructure, housing structures, and basic amenities within the households [18]. Third, deprivation or denial of basic services (which are essential for human health and survival) or prevalence of multiple deprivations or multidimensional poverty in non-notified slum households is much higher than in notified slums in various cities in India due to the lack of de jure security [19,20].

The existing literature on slums focuses on understanding either the extent of possession of basic amenities, assets, and infrastructure or on the relative levels of need for and deprivation of living conditions. These studies mostly take an actor-oriented perspective on different development schemes [21] and largely use quantifiable indicators to make policy prescriptions. The living conditions of slum populations, however, are beset by numerous other challenges such as poor education, health and employment i.e., multidimensional poverty [[22], [23], [24]]; gender inequality [25]; social isolation [26]; urban informality and subaltern urbanism [[27], [28], [29], [30]] and poor environment [31,32]. In sum, the poor livelihood conditions of slum dwellers are determined by a combination of numerous complex phenomena. With this background, this paper intends to take an integrated and multidimensional perspective to explore the sustainable livelihood conditions of slum dwellers along the lines of the ‘Urban Sustainable Development Goals’ of the UN.

1.1. Understanding sustainable livelihood security (SLS) for slum households

The World Commission on Environment and Development (WCED) developed the concept of Sustainable Livelihood Security (SLS) in 1987 as an integrated concept consisting of livelihood, security, and sustainability.2 According to this concept, ‘a household may be enabled to gain sustainable livelihood security in many ways: through the ownership of land, livestock, or trees; through the right to grazing, fishing, hunting, or gathering; through stable employment with adequate remuneration; or through varied repertoires of activities’ [33].

The concept was modified in early 1990s by Chambers and Conway as follows: ‘A livelihood comprises the capabilities, assets (stores, resources, claims, and access), and activities required for a means of living: a livelihood is sustainable which can cope with and recover from stress and shocks, maintain or enhance its capabilities and assets, and provides sustainable livelihood opportunities for the next generations, and which contributes net benefits to other livelihoods at the local and global levels and in the short and long run’ [34].

The scope was further modified and broadened by Scoones [35] of IDS, Ashley and Carney [36] of the British' Department for International Development (DFID), and Krantz [37] of the Swedish International Development Agency (SIDA). However, these institutions adopted no unified approach to assess sustainable livelihood (SL) of poor people across countries. For instance, Chambers and Conway [34] identified three fundamental determinants of SL, namely capabilities, equity, and sustainability. On the other hand, Scoones [35] argued that ‘sustainable livelihoods are achieved through access to a range of livelihood resources viz. natural, economic, human, and social capitals which are combined in the pursuit of different livelihood strategies (agricultural intensification or extensification, livelihood diversification and migration)’. Ashely and Carney [36] emphasized that the SL approach necessarily addresses the environmental, social, economic, and institutional aspects of sustainability. Therefore, livelihood becomes sustainable and secure when it addresses the multi-faceted nature of poverty such as vulnerability, assets, and strategies of the poor and prescribes the role of institutions and processes to control poverty in the short and long run [[37], [38], [39]].

Although initially, these concepts had their focus on rural areas, they began to be used in both peri-urban and urban contexts subsequently [40]. The livelihood security of slum dwellers has been defined as adequate and sustainable in terms of income and resources to meet basic needs, including adequate access to food, potable water, health facilities, educational opportunities, and housing. In other words, SLS embodies three fundamental attributes: (i) possession of human capabilities (education, skills, health, and psychological orientation); (ii) access to tangible and intangible assets (social, physical, natural, and economic capital), and (iii) existence of economic activities for a regular source of income. The interaction among these attributes leads to the sustainable pursuit of livelihood security of a household.

In recent decades, studies on slum areas have focussed on various issues such as asset management, different kinds of capital, effect of women's employment on poverty reduction, governance and political participation, and vulnerability. Moser's Assets Vulnerability Framework speaks about livelihoods in terms of assets (labour, human capital, productive assets, and social capital) and emphasizes that capabilities of the poor population can be enhanced to improve their use of resources and reduce their vulnerability [41]. Kantor [25] observed that women's participation in paid or unpaid economic activities had little influence on below poverty line (BPL) households in the slums of Lucknow, Uttar Pradesh, India. The human asset development study carried out in Dhaka argued that among the slum dwellers of Dhaka, accessibility of infrastructure and access to capacity building and professional training were significantly low and poor [42]. Likewise, a study on the slum dwellers of Visakhapatnam, Andhra Pradesh in India confirmed that income, employment, housing conditions, education, health, demographic characteristics, and accessibility to basic amenities were quite inadequate in the city [43]. All these studies have directly or indirectly highlighted that providing a strong base of physical, natural, human, financial, and social capital to low income households can reduce their risks to a secure livelihood and enable them to escape poverty.

However, the existing studies on slums carried out in developing countries using the SLS approach have failed to incorporate numerous fundamental variables in their respective frameworks. For example, the role of social indicators such as family size, social discrimination, overcrowding, violence and insecurity, is inadequately explained. Likewise, the discussion on the importance of micro environmental variables, such as existence of drainage, sewerage and waste disposal systems, and elimination of water logging in slum areas is almost negligible. These facilities are supposed to be provided by institutions or urban governments. The slum dwellers barely have any control over these facilities, however, when these facilities are absent, the livelihoods of slum dwellers get adversely affected. Therefore, in view of the gaps in the existing literature, we framed many sub-components such as social, economic, infrastructural, health, and micro-environmental aspects under the SLS and added many new variables under each sub-component.

1.2. Issues with the definitions of a slum

The term ‘slum’ is outlandishly amorphous, loosely deployed, and interchangeably used with many other terms [15]. Nonetheless, there has been a significant progress globally in the definition of a slum, starting from a very narrow definition in18123 to a much broader definition (liberal approach4) by the UN-Habitat in The Challenge of Slums in 2003 [2]. The UN-Habitat's (2003) definition of a slum takes a household-level approach to identify and enumerate slum households and the associated household level problems. In addition, it makes recommendations for subsequent planning and policy implementation. It addresses measurable parameters such as improved water and sanitation, durability of housing, sufficient living space and security of tenure for operational purposes [31]. This definition has advantages in identifying household-level basic amenities and various socio-economic deprivations among them [16].

Contrary to the household-level approach, the Government of India has adopted the neighbourhood approach to identify and enumerate slums [17,20]. This approach identifies a slum as an aggregate representation of multiple households. To elucidate the difference between the two approaches, consider this example: If a government provides subsidy to build a toilet, it is a household-level intervention, whereas, if the government connects toilets with the city's sewer system, it is considered neighbourhood-level policy [44]. However, the neighbourhood approach fails to capture the heterogeneity in the living conditions of households based on their socio-economic and demographic characteristics, whereas the household-level approach adopted by the UN has this advantage [17]. The enumeration of non-notified slums by the National Sample Survey Organisation (NSSO) [12] in India, however, is quite inclusive as the minimum threshold for identifying a settlement as a slum is 20 households. Furthermore, the definition used by the NSSO captures both inter-slum (notified and non-notified) and intra-slum (among households) deprivations [45]. While, inter-slum deprivations exist due to the lack of legal entitlement to a non-notified slum, intra-slum deprivations take place due to the neighbourhood approach. Given its advantages, this study adopted the NSSO's definition to identify slum households in two categories: notified and non-notified.

The present study is designed to assess the sustainable livelihood security (SLS) status of notified and non-notified slum dwellers in a middle-range city of three million population known as Lucknow, the capital city of Uttar Pradesh in India. A comprehensive field survey was conducted in the city to elicit information on social, economic, infrastructural, health and micro-environmental factors to understand their interrelationships. This paper is organized into five sections. Section one describes the reasons for the manifestation of slums, the poor living conditions, and the deprivations in urban slums, examines the origin and development of the debate under the sustainable livelihood security framework, and describes the issues with the definitions of a slum. Section two provides details about the study area, the data collection methods, and the methods of estimation. Section three analyses the results. Section four deals with the discussion. Finally, section five contains the conclusion and makes a few recommendations.

2. Research methods

2.1. Study area

Lucknow is situated on the banks of the river Gomti between 26,°51′ north latitude and 80,°36’ east longitude in Uttar Pradesh, India. It has a high level of urban agglomeration in terms of. density of population, infrastructure, business and commerce. It is one of the most developed cities of Uttar Pradesh and has good connectivity (rail, road and air) to other major cities in the country. As per Census of India, 2011 [46], Lucknow is the third most populated city and the second largest district in terms of number of households (8.6 lakh households) in Uttar Pradesh.

The growth of slums in Lucknow is historical and the slums have spread through the process of urbanization for generations. More than 56% of slums are more than 50 years old, underlining the fact that many of them were developed before independence and during the early years of the post-independence period [47]. The Census of India, 2011 [46] revealed that the total slum population of Uttar Pradesh was 6.24 million (14% of state's urban population), while that of Lucknow was 0.773 million (26% of city's urban population). Considering its huge concentration of slum population, the Lucknow district, having six administrative zones comprising 110 wards, was selected as the study area (Fig. 1).

Fig. 1.

Map of the study area.

2.2. Sampling design, size and data collection

A multistage sampling method was adopted to assess the livelihood security status of the notified and non-notified slum dwellers in Lucknow city of India. In the first stage, the district of Lucknow was identified purposefully from among the 75 districts (a local administrative unit) of Uttar Pradesh, since the district's slum population was significantly high. In the second stage, all the six administrative zones of the district were covered for selection of slums. In the third stage, the probability proportional to size (PPS) approach was adopted to select the slums (nearly 3.4% of total number of slums in each zone).

The choice of specific slums was purposive looking into the nature of slums. Hence, four slums from Zone 1, five from Zone 2, four from Zone 3, one from Zone 4, three from Zone 5, and four from Zone 6 were selected. In the fourth stage, 148 households from Zone 1, 168 from Zone 2, 150 from Zone 3, 116 from Zone 4, 151 from Zone 5, and 167 from Zone 6 were surveyed. In this stage, a systematic sampling frame was adopted by choosing every third household from each slum. Thus, a total of 900 households were selected for the field survey, of which 54% households were from notified slums and 46% from non-notified slums. The selected households were well-represented in terms of social, economic and religious characteristics.

2.3. Constructing sustainable livelihood security index (SLSI)

A Sustainable Livelihood Security Index (SLSI) was estimated for the notified and non-notified slums based on the Sustainable Livelihood Security (SLS) approach developed by numerous scholarly studies [19,[48], [49], [50], [51], [52], [53]]. SLSI is basically a generalization process of the relative condition of individual entities and as such estimates the relative performance of each entity taking into account the whole universe. SLSI is a holistic, flexible, and inter-disciplinary approach which, in this study, integrated various sub-components such as social security index (SSI), economic security index (ESI), infrastructure security index (ISI), health security index (HSI), and micro environment security index (MESI).

2.3.1. Normalization of indicators

The study used different kinds of data to develop an SLSI for the notified and non-notified slums with different scales. It was a prerequisite to rescale the data for normalization based on the methods adopted by Singh and Nayak [50], and Nayak and Singh [54] to estimate the index. The process of normalization was undertaken to reduce the variability that could arise due to the presence of extreme values, eliminate units (as the values were expressed in different units), and enhance the comparability of the variables. Based on the nature of the data, the min-max method was adopted to standardize all indicators into a common range (0, 1), depending on their functional relationship with the sub-components [55,56].

The min-max method can help simplify a complex array of information on social, economic, infrastructural, health, and micro-environment securities and their nexus with sustainable livelihood security. Another major advantage of this method that it can capture livelihood security at any scale, that is, at the household, slum, district, state, and country levels. This makes the method vital for informing the public and the decision-makers about the key livelihood insecurity issues. Equations (1), (2)) shown below were used for larger-the-better and smaller-the-worse type indicators, respectively, to normalize the data.

$$Y_{ij}=\frac{K_{ij}-{\mathit{Min}(X}_{ij})}{{\mathit{Max}(X}_{ij})-{\mathit{Min}(X}_{ij})}$$ (1)

$$Y_{ij}=\frac{{{\mathit{Max}(X}_{ij})-K}_{ij}}{{\mathit{Max}(X}_{ij})-{\mathit{Min}(X}_{ij})}$$ (2)

Where, $Y_{ij}$ is the index for the ith indicator related to the jth slum, while $K_{ij}$ is the actual/observed value of the ith indicator of the jth slum. ${\mathit{Max}(X}_{ij}\left)and{\mathit{Min}(X}_{ij}\right)$ are the maximum and minimum values in the distribution, respectively, of the ith indicator among the jth slums. When, an indicator had a positive relationship with its respective sub-component, then equation (1) was employed, while when an indicator had a negative relationship with its respective sub-component, then equation (2) was used.

2.3.2. Assigning weights to the indicators

Assignment of weights and aggregation of the weighted index values were two vital and conceptually complex issues that were addressed before integrating the indicators into the composite index [57]. Weights indicate the relative contribution of indicators in influencing the overall performance of a dimension and the possible trade-off among the factors towards the ultimate policy objective [49]. The selection and assignment of weights makes a significant difference to the final ranking of entities. The following technique was used to calculate the weight of each indicator.

$$\left[{\mathrm{W}}_{\mathrm{i}}=\frac{k}{\sqrt{\mathrm{V}\mathrm{a}\mathrm{r}\left(Y_{ij}\right)}}\right]$$ (3)

$$\mathrm{W}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e},\left[\mathrm{K}=\frac{1}{\left\{\sum _{i=1}^I\frac{1}{\sqrt{\mathrm{V}\mathrm{a}\mathrm{r}\left(Y_{ij}\right)}}\right\}}\right]$$ (4)

Where weight ($W_i)$ is (0<W > 1 and ${\sum }_{i=1}^m{W}_i=1)$ that is assigned to the ith variable. $Var\left(Y_{ij}\right)$ has statistical variation across the standardized indices for all variables.

2.3.3. Estimating sustainable livelihood security index (SLSI)

Two steps were adopted to estimate the sustainable livelihood index. In the first step, the index values of all the indicators under each sub-component were estimated for both notified and non-notified slum households. To estimate the value of each indicator, the standardized value of each indicator was multiplied by its respective absolute weight (as calculated in equations (3), (4))). Next, the index values of various indicators under each sub-component were estimated through the additive aggregation method. In the aggregation process, the values of indices of all the sub-components covering both notified and non-notified slums were estimated by using the following formula [58].

$$\mathrm{S}\mathrm{S}\mathrm{I}={\mathrm{W}}_{1\mathrm{X}}*{\mathrm{X}}_{1\mathrm{J}}+{\mathrm{W}}_{2\mathrm{X}}*{\mathrm{X}}_{2\mathrm{J}}+{\mathrm{W}}_{3\mathrm{X}}{\mathrm{X}}_{3\mathrm{J}}+{\mathrm{W}}_{4\mathrm{X}}*{\mathrm{X}}_{4\mathrm{J}}+\dots ..+\mathrm{W}{}_{12\mathrm{X}}*\mathrm{X}{}_{12\mathrm{J}}$$ (5)

$$\mathrm{E}\mathrm{S}\mathrm{I}={\mathrm{W}}_{1\mathrm{X}}*{\mathrm{X}}_{1\mathrm{J}}+{\mathrm{W}}_{2\mathrm{X}}*{\mathrm{X}}_{2\mathrm{J}}+{\mathrm{W}}_{3\mathrm{X}}*{\mathrm{X}}_{3\mathrm{J}}+{\mathrm{W}}_{4\mathrm{X}}*{\mathrm{X}}_{4\mathrm{J}}+\dots \dots \dots +{\mathrm{W}}_{9\mathrm{X}}*{\mathrm{X}}_{9\mathrm{X}}$$ (6)

$$\mathrm{I}\mathrm{S}\mathrm{I}={\mathrm{W}}_{1\mathrm{X}}*{\mathrm{X}}_{1\mathrm{J}}+{\mathrm{W}}_{2\mathrm{X}}*{\mathrm{X}}_{2\mathrm{J}}+{\mathrm{W}}_{3\mathrm{X}}*{\mathrm{X}}_{3\mathrm{J}}+{\mathrm{W}}_{4\mathrm{X}}*{\mathrm{X}}_{4\mathrm{J}}+\dots \dots {\dots }_{+}{\mathrm{W}}_{7\mathrm{X}}*\mathrm{X}{}_{7\mathrm{J}}$$ (7)

$$\mathrm{H}\mathrm{S}\mathrm{I}={\mathrm{W}}_{1\mathrm{X}}*{\mathrm{X}}_{1\mathrm{J}}+{\mathrm{W}}_{2\mathrm{X}}*{\mathrm{X}}_{2\mathrm{J}}+{\mathrm{W}}_{3\mathrm{X}}*{\mathrm{X}}_{3\mathrm{J}}+{\mathrm{W}}_{4\mathrm{X}}*{\mathrm{X}}_{4\mathrm{J}}+\dots \dots \dots +{\mathrm{W}}_{14\mathrm{X}}*{\mathrm{X}}_{14}\mathrm{J}$$ (8)

$$\mathrm{M}\mathrm{E}\mathrm{S}\mathrm{I}={\mathrm{W}}_{1\mathrm{X}}*{\mathrm{X}}_{1\mathrm{J}}+{\mathrm{W}}_{2\mathrm{X}}*{\mathrm{X}}_{2\mathrm{J}}+{\mathrm{W}}_{3\mathrm{X}}*{\mathrm{X}}_{3\mathrm{J}}+{\mathrm{W}}_{4\mathrm{X}}*{\mathrm{X}}_{4\mathrm{J}}+{\mathrm{W}}_{5\mathrm{X}}*{\mathrm{X}}_{5\mathrm{J}}$$ (9)

In the second step, once the values of the sub-components had been estimated, the value of the SLSI was calculated by taking the average values of all the sub-components through the following formula.

$$\mathrm{S}\mathrm{L}\mathrm{S}\mathrm{I}=\frac{\sum \left(SSI+ESI+ISI+HSI+MESI\right)}{5}$$ (10)

Where, SLSI is the final index value of all the sub-components.5 An index value close to zero (0) shows a lower livelihood security status, whereas an index value close to one (1) shows a higher livelihood security. Based on the above, a total of 47 indicators were selected and then segregated into five dimensions under the ‘sustainable livelihood security’ framework of slum households. The origin, significance, and description of each variable is analyzed in detail in Table 1. The sub-components are associated with numerous vulnerabilities, adaptation strategies and livelihood outcomes. Fig. 2 depicts the linkages among the different livelihood sub-components, vulnerabilities and risks, adaptation strategies, and livelihood outcomes of the slum households. The details are explained in the discussion section.

Table 1.

Details of rational indicators for sustainable livelihood security index.

Sub-components of Livelihood Security	Indicators	Description	Functional Relationship with SLSI	Source (s)	Mean			t statistics of difference
					Notified	Non-notified	Overall
Social Security Indicators	Family size (nos.)	Large family size in an over-crowded slum adversely affects the livelihood security.	–	[59]	5.39	5.01	5.21	2.79*
	Literacy rate (%)	Higher educational level leads to better employment prospects and livelihood.	+	[60]	65.72	45.84	57.11	13.10*
	Female literacy rate (%)	An educated female can get a job and earn respect in the society and contribute positively to the livelihood security.	+	[60]	59.89	42.54	52.28	7.77*
	Literacy rate (%) of children below 14 years	Slum dwellers are not able to send their children for better education due to low income.	+	[60]	89.02	64.27	76.40	8.99*
	Female-headed households (%)	Female-headed households are highly susceptible in urban settlements and face several constraints to living with dignity.	–	[25]	31.54	24.40	28.22	2.38**
	Social discrimination (%)	Social vulnerabilities, institutional discrimination and structural violence are not sufficiently addressed by international or local governments in third world cities, which affects the marginalized communities living in slums to a higher extent.	–	[30]	58.51	50.96	55.00	2.27**
	Population belonging to backward social group (SC, ST & OBC) (in %)	Modern urban crises emerge in the form of sharp social divisions, creating urban informality or poverty. Majority of people living in slums belong to backward social groups.	–	[28]	81.05	79.42	80.32	1.04**
	Sex-ratio (number of female members per one hundred male members)	Gender equality is a prerequisite for sustainable development. A higher equality in the sex ratio represents higher sustainable livelihood security.	+	[25]	89.09	91.67	90.23	−0.49NS
	Distance between school and living areas (in meters)	It is expected that schools closer to slum settlements lead to a better access to education.	–	[60]	1850.20	2060.76	1948	−1.46NS
	Population facing insecurity and violence (%)	Crimes against women are relatively higher in urban slums than in the organized urban settlements. This leads to a low level of livelihood security among slum dwellers.	–	[32]	24.48	29.43	26.78	−1.67***
	Population perceiving living areas as crowded (%)	A higher population density with limited access to infrastructure and common property resources makes the slums over-crowded, leading to low livelihood security.	–	[32]	58.71	54.78	56.89	1.18NS
	Religion	Hindus are considered majority and other religions minority. Some groups based on religion or ethnicity are vulnerable to shocks and stress.	+	[38]	78	63	71	5.03*
Economic Security Indicators	Ownership of house (%)	Owning a house is the most significant factor for SLS as it is automatically attached with numerous government facilities to slum dwellers.	+	[18]	81.54	42.34	63.33	−13.30*
	Ownership of an all season house (%)	An all season house provides protection from heavy rain, heat and cold-waves and offers an additional layer of livelihood security that other types of houses do not. It is an important asset for the urban poor for shelter and productive or income generating purposes	+	[54]	38.00	10.00	25.11	10.06
	Ownership of a dilapidated house (jhuggi, jhompri and semi-pakka house) %	. Living in a dilapidated house exposes slum households to health hazard, violence and social isolation. It affects their livelihood adversely.	–	[41]	62.00	90.00	74.89	10.06*
	Income (in INR)	Higher income leads to higher livelihood security and vice-versa.	+	[61]	11228.63	8394.62	9912.39	5.56*
	Workforce participation rate (%)	Higher workforce participation rate leads to higher and a consistent level of income to households eventually resulting in a higher level of SLS.	+	[61]	36.63	39.28	37.86	−2.02**
	Women's workforce participation rate (%)	Higher female workforce participation is one of the most important coping strategies for enhancing household income.	+	[38]	25.11	25.08	25.14	0.08NS
	Monthly consumption expenditure on non-durable goods (in INR)	Higher consumption expenditure on non-durable goods shows households are well-aware of nutritional security, which leads to higher livelihood security.	+	[57]	5515.35	5515.35	5078.66	6.95*
	Households availing subsidized food grains (%)	Accessibility to subsidized food grains is an official targeted programme for promoting livelihood of the urban poor.	+	[38]	69.02	53.52	62.00	4.76*
	Population having membership of self-help group (%)	Self-help groups in urban unorganized settlements provide credit at low interest rates and make a positive contribution to livelihood security.	+	[54]	23.24	24.64	23.89	−0.49NS
Infrastructure Security Indicators	Access to safe drinking water (%)	Safe drinking water prevents diseases and reduces health expenditure, leading to higher livelihood security.	+	[62]	80.29	71.29	76.11	3.17*
	Access to latrine (%)	Access to latrine provides extra health-safety and better livelihood security.	+	[63]	68.88	33.01	52.22	−11.49*
	Access to bathroom (%)	Access to bathroom is vital especially, for women and contributes positively to the livelihood security.	+	[62]	61.62	26.56	45.33	−11.24*
	Access to all-season roads (%)	All-season roads provide last-mile connectivity and are very important to the working class. They provide an additional layer of livelihood security.	+	[15]	64.11	38.04	52.00	−8.0770*
	Access to power supply (%)	Electricity opens up new employment opportunities, enhances work efficiency and eventually leads to higher livelihood security.	+	[17]	80.91	26.08	55.44	−19.74*
	Access to formal banking services (%)	Banking services help the households to get credit at low interest rates and hence lead to higher livelihood security.	+	[18]	13.90	16.27	15.00 |	−0.99NS
	Access to clean energy for cooking (%)	Use of clean energy is vital to environment and health of women, which leads to higher livelihood security.	+	[16]	72.82	70.10	71.56	0.90NS
Health Security Indicators	Households washing hands regularly (%)	Hand-washing reduces the risk of diseases and improves the degree of livelihood security.	+	[62]	96.89	93.54	95.33	−2.37**
	Households treating drinking water regularly (%)	Regular treatment of drinking water reduces water-borne diseases and enhances livelihood.	+	[62]	5.60	8.13	6.78	−1.51***
	Households using mosquito net and other preventive measures (%)	Use of mosquito nets and other preventive measures prevents dwellers from malaria and other diseases, enabling them to have better livelihoods.	+	[64]	88.79	78.01	83.91	4.33*
	Regular consumption of intoxicating substances (%)	Regular intoxication through substances such as pan, bidi, tobacco, ganja, toddy, liquor etc increase diseases and eventually reduces livelihood.	–	[61]	70.12	74.64	72.22	1.51***
	Distance to government hospital from living areas (kms)	Less distance to government hospital means better access to government health services and higher health security.	–	[54]	2.74	2.52	2.64	3.40*
	Access to government health services (%)	Greater access to government health services results in low spending and higher livelihood security.	+	[64]	29.88	23.44	26.89	−2.17*
	Access to other hospitals and doctors (private, unregistered etc.) (%)	Slum dwellers consult private doctors for acute ailments due to convenience, or to save time.	+	[64]	70.12	76.56	73.11	2.17*
	Access to emergency transport services (%)	Access to emergency transport services like ambulance is a deciding factor for the survival of a patient. Better access leads to higher livelihood security.	+	[65]	22.41	22.25	22.33 |	0.05NS
	Perception of facing distress and anxiety (%)	Overcrowding, inadequate resources and unemployment cause distress and anxiety and lead to lower livelihood security.	–	[59]	31.12	23.68	27.67	2.49*
	Chronic Illness (%)	Slum dwellers are more prone to chronicle illnesses, which leads to high health expenditure, poor health, and low livelihood security.	–	[61]	18.88	13.88	16.56	2.02**
	Health cost on both acute and chronic diseases (in INR)	Higher health cost reduces livelihood of households.	–	[54]	1959.15	1331.20	1665.98	2.28**
	Out of pocket expenditure (OOPE) (%)	Higher level of OOPE reduces livelihood security of households.	–	[66]	28.26	28.98	28.60	−0.147NS
	Catastrophic health expenditure (%)	Higher level of catastrophic health expenditure makes the livelihood worse.	–	[66]	54.55	51.61	53.17	0.53NS
	Child malnutrition rate (%)	Lower child malnutrition rate leads to higher livelihood security.	–	[67]	30.71	39.47	34.78	−2.76*
Micro Environment Security Indicators	Access to drainage system (%)	Close drainage system reduces the incidence of mosquito induced (vector borne) diseases, leading to a higher livelihood security in nearby slums.	+	[61]	70.54	39.95	56.33	−9.69*
	Connectivity of sewerage line to latrine (%)	Better and efficient connection of latrine to main sewerage system provides a safety net to slum dwellers from various diseases, leading to higher livelihood security.	+	[61]	53.11	26.32	40.67	8.47*
	Access to garbage disposal system (%)	Better and sustainable disposal of garbage is an integral part of higher livelihood security.	+	[68]	33.61	6.94	21.22	−10.31*
	Water logging in rainy season (%)	Water-logging in the rainy season provides a suitable environment for the development of diseases like malaria and diarrhea, leading to lower livelihood security.	–	[61]	75.73	83.73	79.44	2.97*
	Governmental efforts to control mosquitoes (%)	A robust mechanism of urban local bodies to control mosquitoes leads to a better livelihood.	+	[54]	19.50	14.83	17.33	−1.85***

Source: Field Survey Data, 2018.

Fig. 2.

Livelihood strategy framework of Lucknow slums.

3. Results

3.1. Social security index (SSI)

Table 2 reveals that non-notified slum dwellers are relatively worse off compared to notified slum dwellers (SSI_non-notified = 0.516 versus SSI_notified = 0.617). The index values of family size, literacy rate, female literacy rate, literacy rate of children below 14 years, and distance between school and living areas for notified slum dwellers are higher than those for non-notified dwellers, reflecting relatively better mean values and a higher SSI. A high mean of population size (5.21 persons in all slums), coupled with low literacy rates, especially among children below 14 years and women, is a significant factor behind moderate social security.

Table 2.

Index values of various sub-components for notified and non-notified slums.

Indicators	Weight	Notified	Non-Notified	Overall
Social Security Index (SSI)
Family size	10	0.063	0.039	0.051
Literacy rate	8	0.060	0.030	0.045
Female literacy rate	9	0.065	0.038	0.051
Literacy rate of children below 14 years	8	0.068	0.040	0.054
Female-headed households	9	0.046	0.054	0.050
Social discrimination	7	0.043	0.067	0.055
Population belonging to backward social groups (SC, ST & OBC)	7	0.024	0.031	0.028
Sex-ratio	8	0.030	0.039	0.034
Distance between school and living areas	8	0.040	0.028	0.034
Population facing insecurity and violence	9	0.073	0.054	0.063
Population perceiving living conditions as crowded	10	0.050	0.057	0.054
Religion	7	0.055	0.039	0.047
Social Security Index		0.617	0.516	0.567
Economic Security Index (ESI)
Ownership of house	9	0.077	0.036	0.056
Have all-season house	7	0.065	0.020	0.042
Having dilapidated house (jhuggi, jhompri and semi-pakka house)	11	0.053	0.011	0.032
Household income	12	0.060	0.019	0.040
Workforce participation rate (WPR)	11	0.019	0.040	0.030
Women's workforce participation rate	13	0.031	0.030	0.031
Consumption expenditure on non-durable goods	12	0.068	0.022	0.045
Households availing subsidized food grains	10	0.064	0.031	0.048
Population having membership of self-help groups	17	0.045	0.046	0.046
Economic Security Index		0.483	0.256	0.370
Infrastructure Security Index (ISI)
Access to safe drinking water	16	0.100	0.069	0.084
Access to latrine	13	0.023	0.069	0.046
Access to bathroom	12	0.027	0.073	0.050
Access to all season road	14	0.076	0.063	0.069
Access to power supply	12	0.102	0.037	0.070
Access to formal banking services	15	0.053	0.069	0.061
Use of clean energy for cooking	19	0.112	0.091	0.102
Infrastructure Security index		0.493	0.471	0.482
Health Security Index (HIS)
Households washing hands regularly	6	0.059	0.044	0.051
Households treating drinking water regularly	7	0.011	0.010	0.011
Households using mosquito nets and other preventive measures	6	0.048	0.028	0.038
Families intoxicated regularly	8	0.049	0.040	0.045
Distance to government hospital from living areas (kms)	7	0.018	0.031	0.025
Access to government health services	6	0.040	0.032	0.036
Access to other hospitals and doctors (private, unregistered, etc.)	5	0.014	0.023	0.018
Access to emergency transport services	7	0.029	0.028	0.028
Perception of facing distress and anxiety	9	0.048	0.057	0.052
Families having chronic diseases	9	0.028	0.025	0.026
Health cost including both acute and chronic diseases	7	0.034	0.043	0.039
Out- of-pocket expenditure (OOPE)	8	0.059	0.047	0.053
Families facing catastrophic health expenditure	7	0.040	0.033	0.037
Child malnutrition rate	6	0.031	0.024	0.027
Health Security Index		0.508	0.464	0.486
Micro Environment Security Index (MESI)
Access to close drainage	17	0.117	0.069	0.093
Connectivity of sewerage line to latrine	19	0.086	0.052	0.069
Access to garbage disposal facility	22	0.080	0.023	0.052
Existence of water logging in rainy season	20	0.119	0.151	0.135
Governmental efforts to control mosquitoes and flies	22	0.143	0.097	0.120
Micro- Environment Security Index		0.545	0.392	0.469

Source: Field Survey, 2018.

Table 1 demonstrates that about 57% of all slum population is literate. Among non-notified slum dwellers, only 46% of the population is literate. Most slum dwellers do not send their children to school as they are unaware of the importance of education and have low income, and low consumption. High drop-out rates are one of the significant reasons for the low literacy rates among children below 14 years and, consequently, for the addition of a high number of child workers to the informal sector of the economy.

Slum dwellers, who are mostly from the Scheduled Castes (SC) and Scheduled Tribes (ST) population, face social discrimination, live in unhygienic conditions, do low-paying jobs, and are at the bottom of the employment hierarchy as they are involved in the cleaning of the city's solid and liquid waste systems. Furthermore, they live in overcrowded (high density of population and a number of people living in one room) informal settlements and are, often, victims of crime and violence, especially women and children.

3.2. Economic security index (ESI)

With a value of 0.37 (Table 2), the ESI delineates the poor economic conditions of the notified and non-notified slum dwellers. It also shows that the values of all the indicators are higher for notified slum dwellers compared to non-notified slum dwellers (ESI_notified=0.483 versus ESI_non-notified = 0.256). Non-notified slum dwellers have a lower mean monthly income and a lower non-durable consumption expenditure compared to notified slum dwellers (Table 1). Only 42% of non-notified slum dwellers own a house, of whom, only 29% have a pucca (concrete) house. As a consequence, the slum dwellers living on rent frequently face eviction by private builders or house owners. Most of the slum dwellers engage in low-wage employment as only 8% of the total population has a regular job. The workforce participation rate (WPR) in the slums of Lucknow is much lower (38%) compared to the urban sector (both slums and non-slums) of Lucknow city (nearly 46%). The WPR in the slums of Lucknow is also much lower compared to the corresponding figure (45%) for all of India, covering both rural and urban areas in 2018 [69]. A relatively low WPR, coupled with low monthly income, results in a very low monthly non-durable and durable consumption expenditure. The evidence gathered from the field survey reveals that non-notified slum dwellers in the study area are discriminated against in the urban labour market due to the irregular and unorganized nature of, and low wage provision in the labour market.

3.3. Infrastructure security index (ISI)

Safe drinking water, sanitation and hygiene, electricity, and cooking gas are some of the most important amenities for a decent livelihood. However, people living in the slums of Lucknow are deprived of most of these basic amenities as can be inferred from the ISI value of 0.48 for all the slum dwellers (Table 2). The values of most of the public goods such as drinking water, all-season roads, electricity and cooking gas (which are formally provided) are higher for notified slums than for non-notified slums. Nearly, 76% of households have piped water supplied to them by the municipality/urban local body either directly to their dwelling or to a yard/plot. However, the water supply is irregular, erratic (only 4–6 h), and qualitatively poor. As a consequence, a parallel water market has developed, whereby private suppliers provide water to slum dwellers in return for a payment. This situation, where the poorest population of the society is forced to purchase the most essential commodity for its survival, indicates government failure.

Latrine and bathroom facilities are also inadequate, more so in non-notified slums compared to notified slums (Table 1). Many slum dwellers do not use toilets due to the non-availability of water, lack of connection with the sewerage system, and various behavioural factors. They avoid public latrines too as these tend to be costlier, do not have subsidized card facilities, and come with other inconveniences such as having to stand in long queues. Therefore, almost two-thirds of non-notified slum dwellers and one-third of notified slum dwellers defecate in the open. As far as bathroom facility is concerned, only one fourth of the non-notified slum dwellers have it. As a consequence, they either do not bathe regularly or are compelled to walk long distances for a bath. Access to a regular power supply, formal banking facilities, and clean energy for cooking is low, inadequate and inferior.

3.4. Health security index (HSI)

Numerous water contaminated diseases (typhoid, jaundice, and cholera), faecal/sludge induced water-borne diseases (diarrhea), scanty water induced diseases (skin and eye infection), vector-borne diseases (malaria and dengue), and poor hygiene induced diseases (abdominal pain) are widely prevalent among slum dwellers, especially children, aging population, and women. Cross connections between leaky drinking water pipelines and sewerage lines cause drinking water to become contaminated with bacteria and induce faecal diseases. In all of the slums, more than one-third of the total families had at least one ailment during the survey period. The number of acute and chronic illnesses in non-notified slums was much higher compared with notified slums.

Though public health services are affordable, only about a fourth of slum dwellers avail them due to inconvenience or long waiting time. Private health facilities, on the other hand, are costly. Besides, slum dwellers often get victimized by a variety of non-professional medical practitioners operating in the private sector. Only one fifth of slum dwellers have access to emergency transport services (ambulance). Almost 29% of the consumption expenditure of households is spent in the form of out-of-pocket expenditure (OOPE) on health and more than half of all households face catastrophic health expenditure. Almost one third of children are malnourished. Table 2 demonstrates that when all the indicators are combined, the overall health security index score for non-notified slums (0.46) is less than that for notified slums (0.51).

3.5. Micro environment security index (MESI)

The slum dwellers suffer greatly due to the lack of micro-environmental facilities. There is a poor drainage system, insufficient/non-existing sewerage connection, non-existing garbage disposal facilities, insufficient motorable roads, and poor institutional facilities for controlling mosquitoes and flies. Blocked drains, the consequent water-logging of roads, and encroachment of water into the dwellings are common problems during the rainy season. There is no place for people to dispose of their domestic garbage, whereas municipal garbage or garbage from other residential areas is disposed of near the slums. As a consequence, a large number of illnesses are noticed in these areas.

The sanitation systems of only about a half of all households are connected with the sewerage system or any form of drainage system. The drainage system of nearly 80% households gets blocked during the rainy season; 83% households are severely affected by mosquitoes and flies; only 21% households have a garbage disposal facility. Overall, with a value of 0.46, the MESI is significantly poor and inadequate for both non-notified and notified slums (Table 2). Non-notified slums have a substantially lower MESI score (0.392) than notified slum (0.545). This reflects that non-notified slums have a lower score for each indicator than notified slums.

3.6. Sustainable livelihood security index (SLSI)

Using equation (10), we found that the slums dwellers in the city of Lucknow have a low level of livelihood security index (with a value of 0.476, which is even less than 0.5) (Table 3). Overall, notified slums have a higher SLSI than non-notified slums (0.53 versus 0.42), confirming that people living in notified slums have better access to most facilities for their livelihood compared with their counterparts living in non-notified slums. Vulnerability in terms of insecurity, violence, overcrowding; low wage and income; poor and insufficient safe drinking water, sanitation, electricity and cooking gas; and out-of-pocket health expenditure and catastrophic health expenditure are high for all households. The index values of all the sub-components for both notified and non-notified slum are presented in a spider diagram (Fig. 3). The scale of the diagram ranges from 0 (worst livelihood) at the centre of the diagram to 0.7 (best livelihood) on the margin of the diagram, with 0.1 unit of increment. Fig. 3 demonstrates that notified slum dwellers are better-off (green colour) on all sub-components than non-notified slum dwellers (yellow colour).

Table 3.

Sustainable livelihood security index for notified and non-notified slums.

Sub-components	Notified	Non-Notified	Overall
Social Security Index	0.617	0.516	0.567
Economic Security Index	0.483	0.256	0.370
Infrastructure Security Index	0.493	0.481	0.487
Health Security Index	0.508	0.464	0.486
Micro Environment Security Index	0.545	0.394	0.470
Sustainable Livelihood Security Index	0.529	0.423	0.476

Source: Field Survey, 2018.

Fig. 3.

Sustainable livelihood spider diagram for notified and non-notified slum dwellers.

4. Discussion

4.1. Low level of tangible and intangible assets base

In this study, we built a sustainable livelihood security index to explore the multidimensionality of livelihoods in the slums of Lucknow. Our results demonstrate that slum dwellers have accessibility to numerous tangible and intangible assets. However, their access to tangible assets such as durable and non-durable food stocks, drinking water, and sanitation are inadequate and in poor form. In addition, they don't own most of the assets but have a negotiated relationship with them to a certain extent [34]. For instance, education, employment, ownership of house, electricity, all-season roads, formal banking, public health facilities, and sewerage, drainage and waste disposal systems are certainly not easily accessible to slum dwellers due to numerous challenges.

Our findings further show the prevalence of institutional failure to deliver micro-environmental facilities to slum dwellers. Consequently, people in slums live in unhygienic conditions and suffer from heavy pollution load due to poor disposal of human excreta and grey-water, prevalence of seasonal problems such as water-logging, and poor management of solid waste. These observations are corroborated by the findings of Dianati et al. [67], Azevedo et al. [68], Katukiza et al. [70].

Non-notified slum dwellers, Muslims and other minority communities, and backward castes (OBCs and SCs) households have low ownership of houses, including all-season houses, and low access to regular income and formal banking. Their access to intangible assets in the form of claims (demands and appeals) is mostly poor, as they are used as a vote bank with a lot of aspirations for political mobilization [9]. The slum dwellers are also poor in social connectedness in terms of strong relationships with friends, families, and communities, which plays an enormous role in helping individuals escape from poverty [26].

4.2. Inadequate adoptive strategies

Slum dwellers devise strategies to meet exigencies, risks and shocks but they tend to be inadequate. For example, boosting women's work participation rate [71] and membership in self-help groups (SHG) are important coping mechanisms to supplement family income and promote household based entrepreneurship. However, these mechanism are inadequate as only a fourth of the total workforce is made up of women, who work for low wages in the informal sector.

Many dwellers do not send their children to school (nearly 25% of children below 14 years are illiterate) due to their inability to pay the fee and instead make the children start working at an early age to boost the family income. This compulsion prevents the children from earning adequate incomes and leading a better life in the future [72]. Notified slum dwellers are well-aware of seasonal diseases and the problem of water-logging in the rainy season. To deal with these problems, they adopt coping strategies like using mosquito nets, washing hands before eating, and using treated drinking water to avoid malaria, diarrhea and other water-borne diseases. Non-notified slum dwellers, on the other hand, adopt such measures to a lesser extent.

Governmental efforts to provide subsidized food-grains to poor families are significant. However, our results show that two-thirds of all slum households and almost half of non-notified slum households are unable to access subsidized food-grains due to institutional and practical barriers.

4.3. High level of vulnerability and low positive outcomes

Our findings reveal that a majority of slum dwellers live in dilapidated houses in an overcrowded environment, have inadequate access to drinking water, sanitation, public health, education, and community facilities, or face a combination of these factors. All of this is detrimental to their safety, health, and morale and eventually, results in high level of vulnerability of the slum dwellers. Our findings in terms of insufficient access of slum dwellers to various tangible and intangible assets; and the resultant consequences are in line with the results of Moser [41], Uddin et al. [42], Parvin [43], Banerjee et al. [59], Banerjee and Goswami [60], Dianati et al. [67], Ezeh et al. [73], Wood and Salway [74]. Our results also indicate that the overall livelihood security of non-notified slum dwellers is much worse compared with that of notified slum dwellers as the former have minimal access to basic amenities, employment opportunities, health facilities, and micro-environmental amenities. These results are comparable with the findings of Sajjad [19], Nolan et al. [20], Subbaraman et al. [45], Murthy [75], Krishna [76]. The reason behind this disparity is mainly the legal bottlenecks associated with the property rights of non-notified slum dwellers. The deprivation or denial of basic services (which are essential for human health and survival) is much higher in non-notified slum households due to the lack of de jure and de facto security of the slum community, which consequently makes them go ‘off the map’.

Our results also highlight that the vulnerability is higher for minorities (Muslims and other religions) and other backward castes. This reflects in terms of their low literacy rates, overcrowding, residence in dilapidated and rented houses, employment in the informal sector at low wages, low levels of income, and higher health expenditure (out-of-pocket expenditure and catastrophic health expenditure); all of these observations are in tune with the findings of earlier studies [ 61, 62]. A majority of the Hindu households belonging to backward castes face high levels of discrimination, insecurity, and violence as well.

4.4. Interrelationship among assets, strategies and outcomes

Our findings indicate that poor human capital in terms of education, skills, and access to health services result in poor financial capital in the form of low work participation rate in low-paying jobs, lowest position in organizational hierarchy of professional structure in terms of respect and dignity, and a high prevalence of chronic diseases and malnutrition among children. These findings are substantiated by established evidences that well-educated households have a better capacity to upgrade their living conditions due to higher incomes and a greater ownership of home appliances [41,77].

The cause-and-effect relationship become circular in nature as the conditions affect one another for generations. For example, slum dwellers do not send their children to school due to their unawareness of the importance of education, and their low income and low consumption. It is believed that a large family size means more working members in the family and, therefore, a higher income for the household. However, the household remains in a low base category of income and consumption, which then affects the next generation's access to better and higher education [ 23].

High drop-out rates are one of the significant reasons for the low literacy rates among children below 14 years and, consequently, for the addition of a high number of child workers to the informal sector. This kind of a poor livelihood outcome leads to a vicious cycle for generations. This point was raised conceptually by Marx et al. [7], whereby they argued that urban poverty is preferable to rural poverty. However, slum areas are growing rapidly and many urban households are also trapped in slums for generation.

4.5. Advantages and limitations

This study's use of the SLS approach to assess the living conditions of slum dwellers, keeping the social, economic, infrastructural, health, and environmental aspects of their livelihood in the background, has many advantages over previous studies that assessed poverty, unemployment, or deprivation of basic amenities in slums in fragmented ways. The present study differs from those studies in the following ways.

First, it placed the urban poor (low-income settlements) at the centre and explored the multidimensional nature of poverty, which is commonly neglected [22,38]. Second, it tried to bring out the complex nature of vulnerability, assets base, strategies (to withstand risks, minor shocks and other exigencies), outcomes and their inter-relationships. Third, the study significantly captured both inter- and intra-slum deprivations by adopting the household and the neighbourhood approaches by employing multiple indicators. Fourth, the study used primary data from a household survey to construct SLSI. This approach helped avoid the loopholes associated with the use of secondary data [48]. Besides, this framework can be replicated at the district and state levels. Fifth, many new indicators were added under each sub-components to address the multidimensionality of livelihoods, which reflects the novelty of the framework. Finally, this study provided snapshots of livelihoods of urban slum dwellers in a robust manner despite having usual limitations such as bias due to recall period for collection of data on variables such as consumption expenditure, income, chronic diseases, health expenditure and access to government and private health services. The paper suggests the inclusion of issues such as role of community, cultural norms, and domestic violence in future studies in the livelihood framework.

5. Conclusion and policy prescription

The slums of Lucknow are a suitable illustration of the conditions of subaltern urbanism in the global south, where millions of people live in informality [27,29,32]. This study underlined the existence of various spheres of informality of livelihood of the urban poor in terms of housing, employment, health, drinking water, and other basic amenities. Along with these, it demonstrated inequities in access to various public amenities due to legal constraints, especially for non-notified slum dwellers, which eventually violates human rights on spatial practices of informal or marginalized geographies. All these above facilities are becoming the limits for the recognition of slum dwellers.

We highlighted that the livelihood condition of slum dwellers is characterized by a low assets base, and poor strategies to overcome exigencies and risks, which puts the slum dwellers in a highly vulnerable position. Households belonging to backward castes and minority communities face an even higher level of vulnerability with low positive outcomes in many forms, though the difference within their respective categories is not very sharp. It is argued that the urban poor as a social deviant group are associated with a poor social, economic, and political structure and live with sustained inequality and exploitation. The actual social, economic, infrastructural, environmental, and health vulnerabilities of the slum people are much worse compared to what evidences based on scientific estimates such as per capita income, HDI, poverty, and inequality suggest [30]. The definition of slum used in India, which is based on the neighbourhood approach, fails to capture the heterogeneity in the living conditions of slum households. The sustainable development model based on this approach neglects local needs based development and urban planning, social connectedness and community living, and sense of belonging.

We propose a set of policies to address the precarious livelihood conditions of slum dwellers. The first proposal is to implement a National Urban Employment Guarantee Scheme (NUEGS) with a minimum number of days and minimum wages, which certainly would push urban employment, especially among the urban poor living in the slums. It can be offered to both skilled and unskilled labourers the way the Kerala Ayyakali Urban Employment Guarantee Scheme did recently. The scheme could promote public works like roads, parks, vegetable markets, etc. and green works such as plantations, waste management and pollution control methods. Ensuring a minimum income for slum dwellers would certainly develop their base of social assets and the income of the future generations.

The second proposal is to generate awareness of various public provisions among the slum population to enhance their overall access to and claims (intangible assets) from the urban local bodies (ULBs) to break the low equilibrium trap in the slums. Regularly conducting sabhas (meetings) at the ward level to address the local problems can strengthen their capabilities in the urban local bodies.

The third and the final proposal is to grant land tenure and land rights to slum dwellers to reduce their risk of eviction, to enable them to access credit from the formal market for opening small or petty businesses, and to educate their children. Notification of non-notified slums at regular intervals is the best way to address this issue.

Funding

The authors acknowledge ICSSR, New Delhi, for its financial support towards a larger study conducted earlier.

Declarations

Author contribution statement

Sanantan Nayak: Conceived and designed the analysis; Contributed analysis tools or data; Wrote the paper.

Surendra Singh Jatav: Analyzed and interpreted the data; Wrote the paper.

Data availability statement

Data will be made available on request.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.