# Water and energy deprivation: Addressing the problem of essential utility services poverty in Mayotte

Dorothée Charlier, Bérangère Legendre, Olivia Ricci

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Dorothée Charlier, Bérangère Legendre, Olivia Ricci. Water and energy deprivation: Addressing the problem of essential utility services poverty in Mayotte. Energy Policy, 2024, 195, pp.114364. 10.1016/j.enpol.2024.114364. hal-05484825

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# Water and energy deprivation: Addressing the problem of essential utility services poverty in Mayotte

Dorothée Charlier<sup>a</sup>, Bérangère Legendre<sup>a</sup>, Olivia Ricci<sup>b,*</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

JEL classification:

O12

Q56

C38

Keywords:

Utility services

Energy poverty

Water poverty

Latent class models

Public policies

Mayotte water crisis

## ABSTRACT

Among the 17 sustainable development goals adopted by the United Nations in 2015 are ensuring “availability and sustainable management of water and sanitation” and “access to modern energy sources”. One problem for Mahorais households is access to safe, clean and affordable essential utility services, such as electricity, water and sewerage. Moreover, Mayotte, a French oversea department, is experiencing an unprecedented drought. The island, which is sinking into a severe water crisis, has been depriving its inhabitants of running water two days out of three since the beginning of September 2023. We define a new concept of utility services poverty (basic utility services deprivation) based on the theoretical capabilities framework of Sen and Nussbaum. Using a latent class model, we identify households that are poor in utility services and characterize four household profiles. One main advantage of this methodology is replicability in many Low and Middle Income Countries’ (LMICs). We demonstrate that access to water is more discriminatory than access to electricity in Mayotte. The top priority in fighting utility services poverty should be access to water and sanitary facilities. Public policies should be implemented not according to income but to facilitate water and energy access and improve basic hygiene conditions notably through social housing.

## 1. Introduction

The 17 sustainable development goals, also called global goals, were adopted by the United Nations in 2015 and are a global call to action to eradicate poverty worldwide. Among them are the two following objectives: “ensure availability and sustainable management of water and sanitation for all (goal 6)” and “ensure access to affordable, reliable, sustainable and modern energy for all (goal 7)”. Worldwide, 46% of individuals do not have access to safely managed sanitation, 29% lack access to basic hygiene and 26% lack safely managed drinking water. Moreover, one-third of the population uses dangerous and inefficient cooking systems, 759 million people lack access to electricity, and the annual energy efficiency rate is equal to 3% and can be improved.<fnref n="1" /> These statistics underscore a pressing need for targeted interventions, particularly in vulnerable regions where utility services poverty, a composite issue encompassing water and energy poverty, exacerbates the plight of the underserved populations.

Energy and water are essential utility services for a decent standard

of living. Water services and sanitation are associated to well-being and improve the ability to benefit from healthcare services and education (Gimelli et al., 2018; Gleick, 1998) and can be a vector of human development (Mehta, 2014). Internationally, the UN recognized the right to access to drinking water (and to sanitation) as a “fundamental human right” in 2010. This right follows directly from “the right to an adequate standard of living”. On July 28, 2010, the United Nations General Assembly adopted a historical resolution recognizing “the right to safe and clean drinking water and sanitation as a human right that is essential for the full enjoyment of life and all human rights” (A/RES/64/292²). Although the right to water was enshrined in 2010, this is not the case for the right to energy.

In the literature, access to water and access to energy are usually treated independently under the concept of energy and water poverty. While there have been abundant studies on energy poverty since the 1980s, the concept of water poverty, initially treated as water scarcity (Dampkjaer and Taylor, 2017), is more recent. It describes both a lack of access to clean water and sanitation and the cost of consumption

<footnote><sup>a</sup> IAE Savoie Mont Blanc, IREGE, 4 Chemin de Bellevue, 74940, Annecy-Le-Vieux, France</footnote>

<footnote><sup>b</sup> Université de la Réunion, CEMOI, 15 Avenue René Cassin, 97715, Sainte-Clotilde, La Réunion, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: dorothee.charlier@univ-smb.fr (D. Charlier), berangere.legendre@univ-smb.fr (B. Legendre), olivia.ricci@univ-reunion.fr (O. Ricci).</footnote>

<footnote n="1">¹ See the webpage: https://sdgs.un.org/goals.</footnote>

<footnote n="2">² Resolution adopted by the General Assembly on 28 July 2010, 64/292. The human right to water and sanitation. A/RES/64/292.</footnote>
(Salameh, 2000). Tsanga Tabi (2021), considers water poverty as the financial difficulties of households in paying their water and sanitation bills. This can be linked to the concept of energy poverty which is recognized as the difficulty to realize essential capabilities due to insufficient access to affordable, reliable, and safe energy services (Day et al., 2016). Energy poverty in High Income Countries (HICs) is a complex phenomenon resulting from a combination of three main factors: low income, energy-inefficient housing and high energy prices (Devalière, 2007; Palmer et al., 2008). These issues are quite different from those identified in Low and Medium Income Countries (LMICs),<fnref n="3" /> where energy poverty usually describes situations in which people have inadequate access to modern energy sources. Few studies have treated fuel and water poverty together (Browne et al., 2018; Fankhauser and Tepic, 2007; Laskari et al., 2016; Martins et al., 2019; Yoon et al., 2019), focusing mainly on affordability issues (Fankhauser and Tepic, 2007). As energy and water are essential needs, it seems relevant to broaden the concept of fuel and water poverty to also address the issue of access to basic utilities services in vulnerable territories.

In this paper, we propose to expand the concept of fuel and water poverty to the concept of utility services poverty by focusing on the case of Mayotte, a French overseas department located in the Indian Ocean close to Madagascar. Since September 2023, Mayotte is going through a serious water crisis and residents have faced unprecedented restrictions. Although the territory of Mayotte does not fit the definition of a LMIC, the characteristics of the territory do not make it a HIC. The median standard of living of the inhabitants of Mayotte is seven times lower than the national level. A large part of the population lives with very few resources: 77% live below the national poverty line, five times more than in metropolitan France (Direction de l'Environnement de l'Aménagement et du Logement de Mayotte, 2017). According to the OECD definition, 36.5% of the Mahorais households are income poor. On Mayotte Island, many households do not have the basic utilities needed to sustain their well-being. The fight against substandard housing is a major challenge in Mayotte: six out of ten homes lack basic sanitary facilities (running water, toilets and showers). In fact, 25.8% of households do not have access to water in housing, 83.8% do not have hot water, and 5% do not have access to electricity in their homes. By providing insights grounded in Mayotte's specificities, this study illuminates the universal challenges of ensuring equitable access to essential utility services in LMICs.

We aim to capture the complex and multidimensional characteristics of utility services poverty. Based on the latest work of Charlier et al. (2021), we go further by examining the need not only for domestic energy services but also for all essential utility services to live a decent life. The main objective of this paper is to develop the concept of utility services poverty by proposing a definition and a quantification of this phenomenon. Drawing on the definition of energy poverty proposed by Day et al. (2016) and on the theoretical capabilities framework developed by Sen and Nussbaum (Nussbaum, 1999, 2003, 2003, 2004, 2011, 2012, 2003; Sen, 1979), we propose a first definition of utility services poverty. Furthermore, we want to identify the households that are utility services poor. To do so, we employ a latent class model (LCM) (Greene and Hensher, 2003). We accurately assess essential utility services poverty using observable objective characteristics. Assuming that objective multivariate variables describing a set of capabilities are observed, we link these variables to the following latent unobserved variable: utility services poverty. The advantage of this methodology is that it provides a scale of utility services poverty in Mayotte and can be re-used on more recent data or similar data in other LMICs. The methodology used, specifically the latent class model, is adaptable and can be applied to similar regions facing comparable challenges, such as

Madagascar and the Comoros.

Finally, it is tempting to think of utility services poverty as a problem of income poverty. As the share of income poor households in Mayotte is significant, we can question the independence of the concept of utility services poverty.

The key contributions of the paper are as follows: 1) we advance the first definition of utility services poverty, and 2) we use an original methodology to identify households that are utility services poor. 3) We provide evidence that households that are utility services poor are not necessarily monetary/income poor, and therefore sometimes do not fall within the scope of the financial assistance offered by the government.

We define utility services poverty as the inability to realize essential "functionings" due to difficulties in access to a set of essential utility services in housing (which could be insufficient access to affordable, reliable and safe basic utility services).

With the LCM, we obtain four distinct household profiles and a utility services poverty scale. We provide evidence that income poor households are not necessarily utility services poor households. In such a context, policies should be implemented not according to income but to facilitate access to water and energy as well as to improve sanitary conditions. We find that households without access to water are more vulnerable to utility services poverty than households without access to energy. To reach the development goals in Mayotte, policies could be implemented in two steps. First, to fight utility services poverty, access to water and sanitary facilities should be prioritized. Second, it is necessary to provide access to electricity for everyone. Better access to social housing can also be a solution to develop decent housing. The significance of this study lies in its critical examination of utility services poverty, particularly within the unique context of Mayotte. Despite its status as a French overseas territory, a distinctive attribute, this study endeavors to enrich the broader discourse on utility services poverty in LMICs. Indeed, Mayotte shares similarities with other small island developing states or territories in analogous geographical settings (Comoros, Madagascar, etc.), grappling with economic vulnerability, environmental hazards, and dependence on a limited range of economic activities. Utilizing a decade-old primary dataset, the latest available for this specific area, this research provides insights into the persistent challenges of access to basic utilities. However, given the rapid environmental changes over the past decade, there is a potential necessity to replicate this study in the coming years to address shifts that could impact the relevance of our findings today. Mayotte has experienced significant changes over the past decade, including increased threats from climate change such as sea-level rise and extreme weather events. These environmental changes have substantial implications for the island's economy and sustainable development. Additionally, immigration from neighboring countries, particularly the Comoros, has dramatically impacted Mayotte's demography and economy, leading to population growth and increased pressure on local resources and services.

The article is organized as follows: In Section 2, we propose a definition of utility services poverty. In Section 3, we present data and descriptive statistics on observable characteristics of utility services poverty in Mayotte. Section 4 presents the latent class model (LCM). Section 5 shows the results. Section 6 offers some concluding remarks and discusses policy implications.

## 2. A proposed definition of utility services poverty

### 2.1. Theoretical background on energy and water poverty

In the literature, energy poverty and water poverty are mainly treated independently. We propose to return to those two streams of the literature and show that in a territory such as Mayotte, these two phenomena should be treated together and combined under the term utility services poverty.

The concept of energy poverty refers to difficulties in obtaining a set

<footnote n="3">³ LMICS corresponds to the World Bank Classification it includes low-income economies, lower-middle income economies, and upper-middle income economies.</footnote>
of essential energy services in housing (Day et al., 2016). While there is a large body of literature on measuring energy poverty, there is no consensus on either a common definition or energy poverty indicators. It is difficult to agree on a satisfactory definition, in part because energy is not an end in itself but is a vehicle by which we can use energy services. It is also difficult to specify a simple criterion for determining whether a level of energy services is acceptable. However, the academic literature has recently begun to highlight the need for a unified theoretical framework for analyzing energy poverty based on Sen's work on poverty. Day et al. (2016) enlarged the concept of energy poverty and conceptualize the relationship among energy, energy services and capabilities framework developed by Amartya Sen and Martha Nussbaum (Nussbaum, 2003, 2011; Nussbaumer et al., 2012; Sen, 1979, 2004). The authors defined energy poverty as "an inability to realize essential capabilities as a direct or indirect result of insufficient access to affordable, reliable and safe energy services, and taking into account available reasonable alternative means of realizing these capabilities" (Day et al., 2016).

Charlier et al. (2021) drew on the work of Bouzarovski and Petrova (2015) and Day et al. (2016) to capture the complex and multidimensional characteristics of energy poverty in tropical territories. Like Bouzarovski and Petrova (2015), they showed that in addition to heating issues, fuel poverty should focus on all domestic energy services, including cooling, water heating, and cooking as well as the hygiene, safety and sanitation of dwellings. Moreover, they applied an innovative methodology (LCM) based on the theoretical capabilities framework developed by Sen and the conceptual work of Day et al. (2016) to identify fuel poor households in tropical regions.

The concept of “water poverty” was developed to consider both a lack of access to clean water and sanitation and the cost of consuming water. In 2000, the term “water poverty” was advanced in the literature as an indicator by Salameh (2000). Salameh (2000) described a “*Water Poverty Index*” that was defined as “*the ratio amount of renewable water to the amount required to cover food production and the household uses of one person in one year under the prevailing conditions*”. In the same vein, Sulivan (2002) also provides a Water Poverty Index where water stress, scarcity and socioeconomic variables that reflect poverty are integrated. Feitelson and Chenoweth (2002) emphasized the quality of the water used for domestic purposes and defined water poverty as “*a situation where a nation or region cannot afford the cost of sustainable clean water to all people at all times*”. As mentioned by Yoon et al. (2019), those definitions focused mainly on access to potable water, which is appropriate for LMICs but less appropriate for HICs, where access to water is mainly guaranteed. When referring to water poverty in HICs, the literature refers mainly to the ability of customers to pay their water and sewerage bill(s) (Tsanga Tabi and 2021). Most studies on the affordability of water services have considered a household water poor if its water expenditure related to income exceeds a certain threshold ranking from 3% to 5% (Reynaud, 2008; OECD, 2003). However, this indicator presents a significant problem as in HICs, not all water consumed by households is used to satisfy basic needs but much is used for luxuries (OECD, 2003). Water is a basic right that must be guaranteed to everyone by the public sector. However, basic needs should be distinguished from luxury or superfluous water consumption. Therefore, García-Valiñas et al. (2010) proposed modifying the current water affordability index to consider the theoretical bill for covering basic needs instead of real water bills.

Although access to water and energy are two essential prerequisites for a decent life and for promoting economic development, only a few studies have treated energy and water poverty together as linked objectives (Browne et al., 2018; Fankhauser and Tepic, 2007; Laskari et al., 2016; Martins et al., 2019; Yoon et al., 2019). Some of the studies partially addressing energy and water poverty focused mainly on the affordability issue (Fankhauser and Tepic, 2007). Recently, Alivon & Ricci (2024), assessed the extent of water and energy poverty in Reunion Island using an affordability index and presented the profile of households. It also focused on the most vulnerable households, those affected

by both water and fuel poverty, and outlined the factors contributing to this dual poverty through a bivariate probit model. The econometric study suggested that there was a strong correlation between water and energy poverty. They showed that it is primarily individual characteristics (education level, employment statuses, family composition), rather than equipment and housing quality, that explain the experience of being affected by this dual poverty. Thus, factors highlighted in the literature on energy poverty, such as heating systems, cooking methods, or building quality (Legendre and Ricci, 2015), do not seem to play a role in explaining energy and water poverty in Reunion Island.

## 2.2. *Drawing on the capability framework to provide a definition of utility services poverty*

To characterize the broader concept of utility services poverty in Mayotte, we draw on the theoretical capabilities framework developed by Sen and Nussbaum (Nussbaum, 2003, 2011; Nussbaumer et al., 2012; Sen, 1979, 2004). The capability approach developed by Sen considers human life as a set of doings and beings termed functionings. Functionings vary from escaping morbidity and being in good health to being integrated into a social community, achieving self-respect and receiving recognition for one's work. Sen described functionings in terms of personal achievement, i.e., what a person manages to accomplish or be. Capabilities, on the other hand, refer to the real opportunities or freedoms individuals have to achieve these functionings. According to Sen, poverty can be seen as not having the capabilities to achieve crucial and valued functionings. This concept of capability deprivation was applied to fuel poverty by Day et al. (2016) because it allows a richer comprehension of the phenomenon.

The relevant literature on utility services access and affordability suggests that basic utility services, particularly potable water, improved sanitation and electricity, can impact human health, education, and social interactions as well as women's condition (Howarth et al., 2001; Martins et al., 2019; Njoh et al., 2019). For instance, access to basic utilities in the home has been recognized as being crucial to prevent social exclusion (the inability of a person or group to participate in daily relationships and activities in several areas based on economic, social, cultural, or political grounds) (Howarth et al., 2001). Moreover, Njoh et al. (2019) recently showed that improving access to basic utilities (potable water, improved sanitation and electricity) invariably results in reducing mortality for everyone, including children in Africa. Imelda (2020) show how cleaner energy access and modern cooking modes can improve health and limit premature deaths by diminishing indoor air pollution. Drawing on this literature, we believe that the capability framework developed by Sen is adequate for our study but also for many other LMICs. While a functioning could be “being in good health”, various capabilities are needed to achieve this functioning, including being able to maintain a warm or cool home, being able to cook nutritious meals and store food, and being able to drink potable water. These capabilities require utility services of space heating and cooling, kitchen facilities, sanitation equipment, etc., which require access to clean water and electricity (Fig. 1).

Another functioning could be “being integrated into a social community”, which might require being able to wash oneself and one’s clothes, which are likely to require water and energy services for hot water. It is easily understandable that insufficient access to affordable, reliable and safe essential utility services can result in the inability to realize essential functionings, such as being in good health or being integrated into a social community.

Drawing on the definition of fuel poverty proposed by Day et al. (2016), utility services poverty could be defined as follows: “*The inability to realize essential functionings due to difficulties in satisfying a set of essential utility services in housing*”.
<figure><img src="image_3.png" /><figcaption>Fig. 1. From utility services access to functionings.</figcaption></figure>

## 3. Methodology

### 3.1. Data

To carry out this study, we rely on the 2013–2014 Mayotte housing survey. In this database, information is available on the physical characteristics of the housing stock (size, sanitary comfort, heating, outbuildings), the quality of the housing (condition of the dwelling and the building, noise, exposure, location, environment, neighborhood, security, quality of existing equipment, access to electricity and running water in the house, use of clean energy, and household characteristics). Our database has a total sample size of 2058 households.

To measure income poverty, several methods can be used: the local poverty rate at 60% or 50% of the median living standard and the Sen index. The poverty rate is calculated on the basis of annual household income per unit. It is set at 60% or 50% of the local median standard of living, so we have 36.5% of households in poverty, or 751 individuals below the poverty line (with the 60% standard). If we were to use the national poverty line (metropolitan France), we would have 83% of households in Mayotte below the poverty line.

Sen's index was constructed as an index measuring poverty. Its main advantage is that it takes into account two dimensions simultaneously (Sen, 1976): (i) the poverty rate and (ii) the poverty intensity. Therefore, we use the simplified version of the index, written as follows, since we do not conduct a comparative analysis between countries:

$$S = T \times I = \text{poverty rate} \times \text{poverty intensity}$$

where T is the poverty rate and I is the average poverty gap (intensity) measured relative to the threshold.

$$S = \text{poverty rate} \times \left( \frac{\text{average income of poor households}}{60\% \text{ poverty line}} \right) \times 100$$

Thus, based on the capability framework, we identify some basic utility services provided by the Direction de l'Environnement de l'Aménagement et du Logement de Mayotte (2017). To be qualified as decent housing, a home must have water, a bathtub or a shower and toilets inside the housing to consider that the basic sanitary comfort is respected (Brasset and Deloeuvre, 2016). The classification of basic energy services by the French Ministry and the United Nations (goal for development) combined with the conceptualized relationship between water, energy services and capabilities by Day et al. (2016) helps us to identify items that could be observable characteristics of utility services poverty in Mayotte. Using this theoretical framework and the recommendations of the UN in terms of sustainable goals, we identify 6 items: access to electricity, access to water, the presence of a cooling system to

fight humidity, sanitary facilities (presence of toilets and bathrooms) and the presence of kitchens for cooking with a modern energy source.

### 3.2. Descriptive statistics

The main descriptive statistics are provided in Tables 1a and 1b (Appendix 1). The poverty line was calculated on the basis of income levels in Mayotte and not on the basis of the line that could have been calculated using data from metropolitan France.

The results indicate (Table 1a), that on average approximately 25% of the population does not have access to water in housing. Access to water in housing is highly unequal depending on the type of housing: 92% of households living in hard-wall dwellings have access to water, compared to only 38% of those living in sheet metal houses. Half of households that do not have running water in their home or yard get their supplies from a third party. The other half uses a public hydrant, a well, a cistern or even a stream or river. These public hydrants were set up in the early 2000s to provide quality water and limit the risk of diseases. In addition, when they buy from a third party, half of the households must carry the water collected over 20 m. As for those who must go to other facilities (public hydrant, wells, cisterns), 9 out of 10 must travel more than 20 m. Overall, at least one element of comfort is absent inside in three-quarters of dwellings (toilet, bathroom or shower) to be qualified as decent housing. Fifty percent of Mayotte households do not have a bathroom, more than 60% do not have toilets in their

<table><caption>**Table 1a**
Summary statistics.</caption><thead><tr><th></th><th>N</th><th>Mean</th><th>SD</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td><strong>Utility Services</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cooling system</td><td>2058</td><td>0.169</td><td>0.375</td><td>0</td><td>1</td></tr><tr><td>Water access</td><td>2058</td><td>0.741</td><td>0.438</td><td>0</td><td>1</td></tr><tr><td>Bathroom</td><td>2058</td><td>0.436</td><td>0.496</td><td>0</td><td>1</td></tr><tr><td>Electricity access</td><td>2058</td><td>0.943</td><td>0.233</td><td>0</td><td>1</td></tr><tr><td>Toilet</td><td>2058</td><td>0.409</td><td>0.492</td><td>0</td><td>1</td></tr><tr><td>Kitchen</td><td>2058</td><td>0.713</td><td>0.452</td><td>0</td><td>1</td></tr><tr><td>Energy for cooking:</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Coal & wood</td><td>2058</td><td>0.099</td><td>0.299</td><td>0</td><td>1</td></tr><tr><td>Butane</td><td>2058</td><td>0.746</td><td>0.435</td><td>0</td><td>1</td></tr><tr><td>Electricity</td><td>2058</td><td>0.124</td><td>0.33</td><td>0</td><td>1</td></tr><tr><td>Oil</td><td>2058</td><td>0.191</td><td>0.394</td><td>0</td><td>1</td></tr><tr><td><strong>Monetary Poverty</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Equivalized income</td><td>2058</td><td>7050.982</td><td>9719.735</td><td>0</td><td>94125</td></tr><tr><td>Monetary poor 60%</td><td>2058</td><td>0.365</td><td>0.482</td><td>0</td><td>1</td></tr><tr><td>Monetary poor Sen</td><td>2058</td><td>0.202</td><td>0.402</td><td>0</td><td>1</td></tr><tr><td>Monetary poor 50%</td><td>2058</td><td>0.325</td><td>0.468</td><td>0</td><td>1</td></tr></tbody></table>
dwellings, and 5% do not have access to electricity. In Mayotte, having electricity in your home does not necessarily mean having your own electricity meter. 58% have their own access and approximately 20% of households that do have access to electricity are connected to a neighbor's meter, so those 20% do not have safe access to electricity. Only 16.9% of the households have air conditioning in their houses. As shown by Charlier et al. (2021), air conditioning is important in tropical territories. The climate in Mayotte in summer is very hot and humid; therefore, air conditioning allows reducing humidity which makes dwellings more comfortable and healthier. Thirty percent of the households do not have cooking installations inside their homes, and approximately 10% use wood or coal for cooking, so this population could be exposed to indoor air pollution. Finally, the housing market in Mayotte is split into 2 categories, a market with higher rent and decent housing vs a market with lower rent but with sheet metal housings. On average, a rent costs 320 euros per month and 43% of housing is rented. Steel-metal houses, which very often have several defects, have an average rent of 60 euros per month against 410 euros per month for permanent housing (Brasset and Deloeuvre, 2016). Moreover, access to social housing, despite development policies based on monetary criteria, is still difficult.

The average annual income in Mayotte is approximately 7000€ per year. The profile of individuals below the local poverty line is essentially the same as that of those below the Sen index except that poor individuals below the Sen index are even poorer than the others and do not have easy access to the resources and energy needed to live. These statistics show, as Sen pointed out, that poverty is not only a monetary issue but also raises the difficulty of achieving functionings. We therefore capture more extreme and multidimensional poverty via the Sen index.

As we mentioned in the introduction, it is tempting to think of utility services poverty as a problem of income poverty. As the share of income poor households in Mayotte is significant, we wonder whether monetary poverty and utility services poverty are distinct (Table 1b, Appendix 1). Therefore, we also examine the data on the non-income poor (Table 2, Appendix 2). Generally, we note that a large number of households do not have the basic resources. In fact, many households do not have access to water and electricity in their homes. Very few households can protect themselves from heat (no insulation in the dwelling, no air conditioning). In addition, poor households live in poor sanitary conditions (even worse than non-poors households). However, there is some diversity within monetary poor households in their access to utility services. For example, among monetary poor households, the percentage with access to water (48.6%) is almost identical to the percentage without access (51.4%).

In terms of cooking methods, while fewer poor households under the Sen index use propane/butane than nonpoor households (45.2% vs. 68.6%), they use more wood and kerosene (14.9% and 33.5% vs. 4.3% and 12.4%). Poor households also appear less dissatisfied with their housing conditions (43.1% of poor households have a positive perceived situation of their dwelling condition as opposed to 22.3% of nonpoor households).

Additionally, on some housing conditions, there are no differences between monetary poor and non-poor households. For example, 24.5% of the households declared that they had humidity problems. This problem is shared equally among poor and nonpoor households.

Thus, even if the manifestations of monetary poverty seem to be noticeable in the conditions of access to utility services and the quality of living conditions, it seems that the profiles of these households are not strictly identical. We will be able to confirm this intuition with the help of our latent class econometric estimation.

We investigate the link between the presence of a kitchen in the dwelling and the cooking method. Butane/propane gas and oil are the two most-used cooking fuels for all households (with or without kitchen facilities). We note that households that do not have a cooking facility use more wood than those that do. More households with kitchen facilities use electricity than those without kitchen facilities (Table 3,

## Appendix 3).

### 3.3. LCM methodology

We want to identify household profiles and know which characteristics are shared by individuals who are utility services poor using latent structural analysis (Lazarsfeld and Henry, 1968). LCM belongs to finite mixture model family (Masyn, 2013) and we use this methodology because there is no formal indicator of utility services poverty. Therefore, we are not able to distinguish a person who is utility services poor from a person who is not simply by applying an existing definition and a measurement tool. However, we know, from both the theoretical framework and the UN guidelines, the characteristics of utility services poverty. This person is deprived of his or her capabilities and therefore will not be able to achieve his or her functionings. Indeed, the dependent variable here, the utility services poverty variable, is assumed to be discrete and unobservable, and the latent class methodology categorizes observations into latent classes using observed variables or indicators (Goodman, 2002).

LCM, like factor analysis, uses iterative procedures based on the maximum likelihood estimation method whose aim is to maximize the likelihood to obtain an optimal solution. Although there are many classification procedures, one of the main advantages of LCM is because this method is based on a probabilistic approach whereas clustering analysis (k-means for instance) is based on a geometric approach defining the clusters according to the Euclidean distances. Moreover, LCM is based on a statistical model (from the population to which the sample belongs) to group individuals (model-based clustering), and allows an objective evaluation of the adequacy of this model to the data through statistical tests i.e. $\chi^2$ on the maximum likelihood ratio (Brusco et al., 2017).

In this study, we want to differentiate profiles that are exclusive and exhaustive, where each individual has membership in exactly one category. This is the assumption of conditional or local independence (Masyn, 2013).<fnref n="4" />

The latent classes relate to latent heterogeneity that varies with manifest variables that explain membership in the class. These manifest variables are related to utility services (access to water, electricity, cooling system, bathroom, kitchen facilities, toilet). These manifest variables should allow latent class homogeneity and latent class separation (Collins and Lanza, 2009). The model is presented in a path diagram in Fig. 2 (Muthén & Muthén, 1998–2011). The methodology is the same as that used in Charlier et al. (2021).

Using a logit discrete choice model allows us to define in which class an individual belongs. We sort individuals into a set of y classes with $y=0,1, ..., r-1$. y is the value observed for $Y_{il}$, the categorical response variable for subject i to item j, with $i=1, ..., n$ and $j=1, ..., J_i$.

$U_i$ is the discrete latent variable (in our case, the utility services poverty variable) for subject i.

Based on the local independence assumption, the given latent class $U_i=u$, the probability of answering $Y_{ij}$ is independent of the probability of answering $Y_{il}$, for $j \neq l$; with $j, l = 1, ..., J$. The manifest distribution of the response vector $Y_i$ is:

$$P(y) = Prob(Y_i = y) = \sum_{u=1}^{k} \pi_u P_u(y)$$

where $\pi_u$ is the weight probability that subject i belongs to class u (with $u = 1, ..., k$):

<footnote n="4">⁴ Local dependence assumption could be related to three issues: bivocality, behaviorally correlated error or Latent heterogeneity. None of these three conditions appear to be problematic in this study. In this line, some robustness checks without cooling and bathroom have been tested to ensure the quality of the results.</footnote>
<figure><img src="image_4.png" /><figcaption>Fig. 2. Path diagram for unconditional LCM of utility services poverty.</figcaption></figure>

$$ \pi_u = p(U_i = \xi_u) = \frac{\exp(\psi_{0u})}{\exp(\psi_{0u})} $$

Subject to

$$ \sum_{u} \pi_{u} = 1; \pi_{u} > 0 $$

where $\xi$ is the value assumed by $U_i$ (support point), $u = 1; \dots; k$

The conditional probability of answering y, given the latent class u, is:

$$ p_{u}(y) = P(Y_{i} = y | U_{i} = \xi_{u}) = \prod_{j=1}^{J_{i}} P(Y_{ij} = y | U_{i} = \xi_{u}) $$

The number of free model parameters is equal to $\pi_u + p_u(y) = (k - 1) + kJ(rj - 1)$.

The LCM is estimated by the maximization of the log-likelihood:

$$ l(\theta) = \sum_{i=1}^{n} \log p(Y_i = y) = \sum_{i=1}^{n} \log \sum_{u=1}^{k} \pi_u p_u(y_i) $$

where $\theta$ is the vector of free model parameters. The log-likelihood $l(\theta)$ may be efficiently maximized through an expectation-maximization (EM) algorithm. This algorithm is based on the complete log-likelihood written as follows:

$$ l^*(\theta) = \sum_{i=1}^{n} \sum_{u=1}^{k} \lambda_{ui} [\log \pi_u + \log p_u(y_i)], $$

where $\lambda_{ui}$ is an indicator equal to 1 if subject i belongs to latent class u and to 0 otherwise. The EM algorithm alternates two steps until convergence in $l(\theta)$: the E-step, which consists of computing the expected value of $l^*(\theta)$ under the current estimates of model parameters, and the M-step, which consists of updating the model parameters by maximizing the expected value of $l^*(\theta)$. The number k of latent classes is not a model parameter, but it has to be fixed a priori. Here, we compare a model with 2 classes to models with 3 and 4 classes. The two class model allows us to discriminate between utility service poor households and non-utility service poor households. This first estimate is based on a traditionally binary approach to poverty: some are utility services poor, and some are not. However, such an approach is often criticized because it assumes that the situation of individuals changes once they pass the poverty threshold. However, we know that reality is more complex, and sometimes being on one side or the other of a poverty/precarity line does not radically change the situation. This is why we introduce the idea that there are also one or more vulnerable classes exposed to one or more exogenous shocks of different natures, putting them at risk of poverty. These sources of vulnerability may be different, which is why we test a 3-class model and then a 4-class model. The final chosen

number of classes is based on information criteria such as the BIC and AIC indexes. These criteria are essential for model selection in statistical analyses, especially when comparing models with different numbers of parameters. The model with the lowest AIC and BIC values is considered the best fit for the data, ensuring a balance between complexity and explanatory power.

After the parameter estimation, each individual i may be allocated to one of the k latent classes on the basis of the highest estimated posterior probability.

$$ \hat{\lambda}_{ui} = \frac{\pi_u \hat{p}_u(y_i)}{\sum_{c=1}^{k} \hat{\pi}_c \hat{p}_c(y_i)} $$

# 4. Results

In a first step, we ensure the quality of the econometric estimation using 2 classes to ensure that we measure utility services poverty (Appendix 4). Second, we compare the models with 2, 3 and 4 classes using AIC and BIC criteria (Appendix 5).

## 4.1. Results for a model with 2 latent classes

Here, we present the results for a binary-class model of utility services poverty in Mayotte in order to identify who is utility services poor and who is not (see Table 4 in Appendix 4).

In Class 1, half of the households have water access and 90% have access to electricity. Only 50% of the households have modern kitchen facilities for cooking. This class, which includes 43.4% of the sample, appears to be the utility services poor. For each criterion used to characterize utility services poverty, households in this class are indeed less well equipped than households in Class 2.

Basically, the utility services sufficient households, identified as Class 2, have access to water and energy (100% of the households have access to electricity and water). This enables us to confirm that there is indeed a utility services deprived class, i.e., a utility services poor class, in which households have common characteristics. Their probability of access to utility services are lower compared to class 2 (as confirmed in Table 4 in appendix).

In a French territory such as Mayotte, the standard of living remains lower than in other departments of the country or in other Western countries. Nevertheless, even if the facilities are underdeveloped, a small part of the population has access to elements of comfort similar to what one would find in overseas departments with higher standards of living. The presence of air conditioning is a good example. Among Class 1 households, 99% do not have air conditioning, while only 62% of Class 2 households do not have air conditioning.

Access to hygiene facilities is represented by the variables of the presence of a bathroom and toilet in the dwelling. The analysis of these
variables in our estimations confirms our identification of the two categories of population because again, class one seems disadvantaged compared to class two. This suggests that having dignified access to hygiene is more complicated for the 43% of the population included in Class 1. Indeed, among them, 93% do not have a bathroom in the dwelling, and nearly 97% do not even have a toilet. In comparison, these proportions are much less dramatic within Class 2, as 8% have no bathroom in the dwelling, and 10% have no toilet.

The choice of manifest variables, i.e., variables representative of deprivation in utility services, allowed us to clearly discriminate among households according to whether their situation is precarious. The clear identification of two classes with very different characteristics and equipment rates attests to the relevance of the manifest variables selected. Nevertheless, as in any analysis of precariousness and deprivation, one can wonder about the limited nature of a binary classification into poor/precarious versus non-poor/non-precarious. Such a classification suggests that there is a threshold, even if we do not clearly identify it here. However, the very existence of thresholds is frequently criticized, and rightly so. This is why we explore the possibility of a classification into 3 or 4 classes. Beyond the relevance of such an approach in economic terms, statistical tools may or may not confirm that considering more classes is a good choice.

Using the statistics criterion (smaller AIC and BIC values are better) a model with 4 classes is preferred to those with 3 classes. A part of the analysis will involve providing materials to attest that it is meaningful to add an additional class and to provide 4 classes in this analysis (Appendix 5).

## 4.2. Results for 3- and 4-level latent class models

We now observe what happens if we add a third class, a class that would allow us to identify a scale of utility services poverty (see Table 6 in Appendix 6).

27.8% of individuals are expected to be utility services poor (Class 1), 32.4% of individuals are expected to be vulnerable to utility services (Class 2) and 39.8% of individuals are expected to be utility services sufficient (Class 3). These results show that a large share of utility services poor households (previously Class 1 in the 2 latent classes model) fall into the second class. By opening up this third class, we can better identify the poorest households and those that are vulnerable. Vulnerability here means that even if access is seemingly not a problem, using water or accessible energy is not easy, and so individuals seem to remain deprived of capabilities. Individuals, even if they are connected to networks, may not have the means to use these basic services normally and decently. Their deprivation is less severe than that of individuals in Class 1.

Finally, when we add a 4th class, we note that the utility services sufficient class remains the same, but a new class between utility poor and vulnerable households allows us to identify new profiles (Table 7 below).<fnref n="5" /> In Class 1 (utility services poor), the profiles of households are as follows: they do not have access to water, they do not have bathrooms and toilets, 25% do not have access to electricity and 60% do not have kitchen facilities. In Class 2 (utility services vulnerable 1), more than 60% do not have access to water, whereas in Class 3 (utility services vulnerable 2), 100% have access to water. The source of vulnerability for individuals in Class 2 clearly comes from limited access to running water. Households in Class 3 appear to be less well equipped, especially in terms of kitchen and toilet facilities within the dwelling. It is therefore noticeable that even if households have access to electricity, they do not all have access to clean cooking fuels. The common denominator of these 2 vulnerable classes is the almost nonexistence of basic hygiene

facilities, such as bathrooms and toilets, inside their homes. Except in Class 1, access to electricity exists. In contrast, our results show that access to running water is the problematic element in both Class 1 and Class 2. Households in Class 4 (utility services sufficient) still have access to everything.

Finally, to sum up results provided by Tables 7 and 8 in Appendix 7, it is possible to set a profile of utility services poor. These profiles are presented in Table 9 below. We find as a general profile poor household, urban renter households, overcrowded households where the reference person is the woman, often unemployed and not completed high school. What differentiates the vulnerable is the tenure status in housing and the employment status, often active for the least vulnerable.

## 4.3. Comparing utility services poverty and income poverty with the 4-class model

If we meet our utility services poor profiles with income poverty indicators, we can see a progression in income level according to the class. Households in Classes 1 and 2 have lower incomes than those in Classes 3 and 4. However, households with utility services poverty and income poverty do not have exactly the same profile. Moreover, according to our 4-class model, we can see that among the households in Class 1 (utility services poor), who basically have access to nothing, between 30% and 50%, according to the monetary poverty indicators, are not considered monetary poor (see Table 10 in Appendix 9).

In contrast, we find that among the utility services sufficient (Class 4 in our model), between 6% and 14% are considered monetary poor. The fact that utility services poor households are not necessarily income poor households has important policy implications that will be discussed in the next section.

# 5. Conclusions and policy implications

To characterize the broader concept of utility services poverty, we draw on the theoretical capabilities' framework developed by Sen and the conceptual work of Day et al. (2016) to propose a definition of utility services poverty. We define utility services poverty as *"the inability to realize essential functionings due to difficulties in satisfying a set of essential utility services in housing"*. To go further, we mobilize an innovative LCM developed by Charlier et al. (2021) to identify essential utility services poor households in Mayotte. This LCM methodology allows us to accurately assess essential utility services poverty in Mayotte using observable objective characteristics. One of the main advantages of Latent Class Analysis (LCA) is its efficacy in discerning the socio-economic status of individuals by identifying those living in utility services poverty from those who are not. It achieves this by detecting unobservable groups within a population, leveraging observed data. This approach is invaluable in the context of utility services poverty because it goes beyond traditional metrics like income, incorporating a broader spectrum of indicators such as access to water or electricity, kitchen facilities, the presence of cooling systems, and sanitary living conditions. Assuming that objective multivariate variables describing a set of capabilities are observed, we link these variables to the following latent variable: utility services poverty. Here, the methodology enables us to identify different categories of utility services poverty and vulnerability—respectively 2 and then 3—based on these multifaceted attributes, thereby allowing for a deeper understanding of the complex nature of utility poverty. Moreover, this methodology facilitates the development of more precisely targeted policy measures and interventions, aimed at improving the conditions of those most in need, through an informed and strategic understanding of their specific circumstances.

We show that restricting utility services poverty in Mayotte to a binary phenomenon could lead to neglect of the complexity of utility services deprivation. With three and four classes, we highlight a scale of utility services poverty severity. Therefore, policy makers should first

<footnote n="5">⁵ More statistics about the repartition of households into classes and utility services are provided in Table 8 in Appendix 7. This also allows us to confirm the quality of the estimate.</footnote>
<table><caption>**Table 7**
Estimated coefficients and predicted probabilities in a model with 4 latent classes.</caption><thead><tr><th rowspan="2"></th><th colspan="3">Class 1 Utility services poor<br>20.1%</th><th colspan="3">Class 2 Utility services vulnerable 1 –<br>water sanitary<br>13%</th><th colspan="3">Class 3 Utility services vulnerable 2<br>–cooking fuel<br>27.3%</th><th colspan="3">Class 4 Utility services sufficient<br>39.6%</th></tr><tr><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th></tr></thead><tbody><tr><td>0. No access to water</td><td>base outcome</td><td></td><td>0.8744</td><td>base outcome</td><td></td><td>0.6344</td><td>base outcome</td><td></td><td>0</td><td>base outcome</td><td></td><td>0</td></tr><tr><td>1. Access to water</td><td>-1.940 (0.491)***</td><td></td><td>0.1256</td><td>-0.551 (4.266)</td><td></td><td>0.3656</td><td>30.936 (0.494)***</td><td></td><td>1</td><td>31.973 (0.278)***</td><td></td><td>1</td></tr><tr><td>0. No access to electricity</td><td>base outcome</td><td></td><td>0.2495</td><td>base outcome</td><td></td><td>0.0272</td><td>base outcome</td><td></td><td>0.0101</td><td>base outcome</td><td></td><td>0.0022</td></tr><tr><td>1. Access to electricity</td><td>1.101 (0.602)*</td><td></td><td>0.7505</td><td>3.577 (3.448)</td><td></td><td>0.9728</td><td>4.584 (0.899)***</td><td></td><td>0.9899</td><td>6.120 (1.108)***</td><td></td><td>0.9978</td></tr><tr><td>0. No cooling system</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>0.9830</td><td>base outcome</td><td></td><td>0.9734</td><td>base outcome</td><td></td><td>0.5966</td></tr><tr><td>1. Cooling system</td><td>/</td><td>/</td><td>0</td><td>-4.055 (1.548)***</td><td></td><td>0.0170</td><td>-3.602 (0.365)***</td><td></td><td>0.0266</td><td>-0.391 (0.120)***</td><td></td><td>0.4034</td></tr><tr><td>0. No bathroom</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>0.7429</td><td>base outcome</td><td></td><td>0.0746</td></tr><tr><td>1. Bathroom</td><td>/</td><td>/</td><td>0</td><td>-17.730 (1.704)***</td><td></td><td>0</td><td>-1.061 (0.443)**</td><td></td><td>0.2571</td><td>2.518 (1.011)**</td><td></td><td>0.9254</td></tr><tr><td>0. No toilet</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>0.8621</td><td>base outcome</td><td></td><td>0.9906</td><td>base outcome</td><td></td><td></td></tr><tr><td>1. Toilet</td><td>/</td><td>/</td><td>0</td><td>-1.833 (2.256)</td><td></td><td>0.1379</td><td>-4.659 (4.877)</td><td></td><td>0.0094</td><td>3.931 (1.133)***</td><td></td><td>0.9807</td></tr><tr><td>0. No kitchen facilities</td><td>base outcome</td><td></td><td>0.6187</td><td>base outcome</td><td></td><td>0.0905</td><td>base outcome</td><td></td><td>0.4809</td><td>base outcome</td><td></td><td></td></tr><tr><td>1. Kitchen facilities</td><td>-0.484 (1.266)</td><td></td><td>0.3813</td><td>2.308 (1.465)</td><td></td><td>0.9095</td><td>0.076 (0.748)</td><td></td><td>0.5191</td><td>2.971 (0.296)***</td><td></td><td>0.9513</td></tr><tr><td>Obs.</td><td>2058</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Robust standard errors are presented in parentheses.

<table><caption>**Table 9**
Utility services poverty-households' profiles.</caption><thead><tr><th></th><th>Utility services poor</th><th>Utility services vulnerable 1 – water sanitary</th><th>Utility services vulnerable 2 – cooking fuel</th><th>Utility services sufficient</th></tr></thead><tbody><tr><td><strong>Water sanitary</strong></td><td>No access to water<br>No access to sanitation facilities</td><td>Limiting access to drinking water</td><td>Access to water and sanitation facilities</td><td>Access to water and sanitation facilities</td></tr><tr><td><strong>Electricity access</strong></td><td>Poor electricity access</td><td>Limiting electricity access</td><td>Electricity access</td><td>Electricity access</td></tr><tr><td><strong>Cooling system</strong></td><td>No cooling system</td><td>No cooling system</td><td>No cooling system</td><td>Cooling system</td></tr><tr><td><strong>Clean cooking fuel</strong></td><td>No kitchen facilities – fossil fuel for cooking</td><td>Kitchen facilities (in the same proportion than electricity access)</td><td>No kitchen facility – no clean cooking access</td><td>Kitchen facilities</td></tr><tr><td><strong>Households' profile</strong></td><td>Urban<br>Tenant<br>Few active people<br>No diploma<br>Young person of reference<br>Woman as person of reference<br>Overcrowding</td><td>Urban<br>Tenant<br>Many children<br>Few active people<br>No diploma<br>Young person of reference<br>Woman as person of reference<br>Overcrowding</td><td>More rural<br>Homeowner<br>1 active person<br>Man as person of reference<br>Overcrowding</td><td>More rural<br>Homeowner<br>Few children<br>Active people<br>Diploma<br>Man as person of reference<br>Undercrowding</td></tr></tbody></table>

target the most deprived households (in Class 1) and obtain information about who is vulnerable (Classes 2 and 3). The methodology used clearly shows that access to water is therefore more discriminatory than access to electricity in utility services poverty in Mayotte.

It naturally follows that policies should be implemented in 2 steps. To fight utility services poverty, priority must be given to access to water and sanitary facilities (fighting disease associated with waste and stagnant water). For example, integrated water and sanitation policies, such as those implemented in various low-income regions, have significantly reduced the incidence of waterborne diseases and improved overall public health outcomes (Hutton and Chase, 2017).

In a second step, public authorities should target electricity access for everyone especially to ensure a clean access to cooking fuels. For instance, the Solar Home Systems program in Bangladesh has provided off-grid solar energy to millions of households, significantly reducing reliance on polluting cooking fuels and improving indoor air quality (Asaduzzaman et al., 2014).

The profile of utility services households also show that a particular attention could be also paid to renters, often poorer with limited access to decent housing. The housing market in Mayotte is split into 2 categories, a market with higher rent and decent housing vs a market with lower rate but with sheet metal housings. At present, the supply of decent social housing with controlled rents is a solution but which is still underdeveloped in the territory and which needs to be consolidated.

The identification of different classes has also shown that an

important share of utility services poor households (between 30% and 50%) are not considered as monetary poor according to three different indicators of monetary poverty. This is problematic in terms of public policy. In fact, many policies to fight fuel and water poverty and to reach goals of development are based on income criteria; if a household is below the income threshold, it is eligible for aid. This means that 33.2% of the utility services poor would not be targeted by the policy if it were based on income criteria. This is also valid among utility service vulnerable households (Classes 2 and 3). Public policies that aim to support only the monetary poor do not solve all the problems of access to utility services. In such a context, policies should be distributed not according to income but according to facilities access and living conditions.

Unfortunately, the identification of utility service poor profiles does not in itself allow us to determine accessibility or equipment thresholds in order to know which households are utility service poor. However, the contribution of this first paper on the identification of the utility service poor concerns above all the philosophy of the policies put in place. Just as Sen has raised the notion of capability to the level of a true theory of poverty, the monetary aspect is absolutely not sufficient to characterize the vulnerabilities of populations. If public policies continue to be based exclusively on thresholds of living standards, part of the means spent miss their goal. Orienting public policies to directly attack the sources of vulnerability, in this case, the issues of access to energy and running water and in a second phase the issues of equipment

<footnote>** p < 0.01.</footnote>

<footnote>** p < 0.05.</footnote>

<footnote>* p < 0.1.</footnote>
and quality of housing and kitchen facilities, seems absolutely essential.

The profiles identified through LCM can be adjusted over time (if data are available) and do not depend on constant threshold measurement. Even though the results are specific to Mayotte, it could be interesting to apply the methodology in other territories and to analyze transitions over time. For instance, if data could be available, such an analysis in Madagascar as well as in Comores, closed to Mayotte, could be relevant to compare the results, particularly with other political contexts (which are not under French supervision). By shedding light on the specific characteristics of Mayotte, this study is bringing to the forefront the common obstacles in achieving equitable access to essential utility services.

Finally, a significant limitation of this analysis lies in the age of the data, even though it is currently the latest wave available. Over the past decade, Mayotte, like other islands, has faced the threat of climate change, including sea-level rise and extreme weather events, which have implications for the economy and sustainable development. Furthermore, immigration from neighboring countries, especially the Comoros, has had a significant impact on Mayotte's demography and economy, contributing to population growth but also putting pressure on local resources and services. In this context, the INSEE (National Institute of Statistics and Economic Studies) has already initiated a new housing survey across French overseas departments and regions, including Mayotte, starting in the coming years. This endeavor is crucial for updating our understanding of the living conditions in Mayotte, offering a contemporary comparison to the 2013 survey, which highlighted significant challenges in housing and utility services. The outcomes of this survey are expected to be instrumental in guiding policy decisions and improving the living standards in Mayotte and other French overseas territories. Future research could focus on two specific directions to deepen the understanding of utility services poverty. First, exploring the intersectionality of utility services poverty with other forms of

deprivation, such as education and health, would offer a more precise view of poverty. Second, future research could investigate the impacts of climate change on utility services access, particularly in vulnerable island regions, to develop adaptive and resilient infrastructure policies.

### CRediT authorship contribution statement

**Dorothée Charlier:** Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Bérangère Legendre:** Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Olivia Ricci:** Writing – review & editing, Writing – original draft, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

### 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.

### Data availability

Data will be made available on request.

### Acknowledgment

We thank Estelle Burnet, research technician, for her help with data management.

## Appendix

### Appendix 1

<table><caption>**Table 1b**
Matrix of correlation</caption><thead><tr><th>Variables</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th><th>(13)</th><th>(14)</th></tr></thead><tbody><tr><td>(1) Cooling system</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(2) Water access</td><td>0.257</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(3) Bathroom</td><td>0.440</td><td>0.520</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(4) Electricity access</td><td>0.111</td><td>0.317</td><td>0.200</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(5) Toilet</td><td>0.479</td><td>0.443</td><td>0.745</td><td>0.188</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(6) Kitchen</td><td>0.252</td><td>0.207</td><td>0.337</td><td>0.176</td><td>0.433</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(7) Coal and Wood</td><td>-0.102</td><td>-0.172</td><td>-0.154</td><td>-0.184</td><td>-0.170</td><td>-0.156</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(8) Butane</td><td>0.207</td><td>0.412</td><td>0.361</td><td>0.322</td><td>0.369</td><td>0.351</td><td>-0.277</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(9) Electricity</td><td>0.184</td><td>0.131</td><td>0.169</td><td>0.093</td><td>0.185</td><td>0.105</td><td>0.013</td><td>0.040</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(10) oil</td><td>-0.200</td><td>-0.299</td><td>-0.294</td><td>-0.172</td><td>-0.324</td><td>-0.148</td><td>0.149</td><td>-0.524</td><td>-0.086</td><td>1.000</td><td></td><td></td><td></td><td></td></tr><tr><td>(11) Income</td><td>0.522</td><td>0.263</td><td>0.418</td><td>0.134</td><td>0.444</td><td>0.221</td><td>-0.114</td><td>0.236</td><td>0.203</td><td>-0.241</td><td>1.000</td><td></td><td></td><td></td></tr><tr><td>(12) Monetary poor 60%</td><td>-0.288</td><td>-0.341</td><td>-0.358</td><td>-0.165</td><td>-0.376</td><td>-0.202</td><td>0.184</td><td>-0.316</td><td>-0.107</td><td>0.283</td><td>-0.489</td><td>1.000</td><td></td><td></td></tr><tr><td>(13) Monetary poor Sen</td><td>-0.201</td><td>-0.294</td><td>-0.284</td><td>-0.178</td><td>-0.276</td><td>-0.171</td><td>0.145</td><td>-0.281</td><td>-0.116</td><td>0.232</td><td>-0.353</td><td>0.664</td><td>1.000</td><td></td></tr><tr><td>(14) Monetary poor 50%</td><td>-0.266</td><td>-0.344</td><td>-0.342</td><td>-0.177</td><td>-0.359</td><td>-0.192</td><td>0.173</td><td>-0.308</td><td>-0.116</td><td>0.288</td><td>-0.458</td><td>0.915</td><td>0.726</td><td>1.000</td></tr></tbody></table>
Appendix 2

<table><caption>**Table 2**
Summary statistics by monetary poverty</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Sample means (n = 2058)</th><th colspan="4">Monetary poor 60%</th><th colspan="4">Monetary poor Sen index</th></tr><tr><th>%</th><th colspan="2">Nonpoor (n = 1307)</th><th colspan="2">Poor (n = 751)</th><th>%</th><th colspan="2">Nonpoor (n = 1642)</th><th colspan="2">Poor (n = 416)</th></tr><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td><strong>Dwelling characteristics</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Wall material</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sheet metal</td><td>33.9</td><td>21.5</td><td>281</td><td>55.5</td><td>417</td><td>26.9</td><td>441</td><td>61.8</td><td>257</td><td></td><td></td></tr><tr><td>Hard (stone, brick, breeze block)</td><td>61.9</td><td>73.8</td><td>964</td><td>41.4</td><td>311</td><td>68.7</td><td>1128</td><td>35.3</td><td>147</td><td></td><td></td></tr><tr><td>Semihard (coated earth, lime)</td><td>3.0</td><td>3.7</td><td>48</td><td>1.9</td><td>14</td><td>3.2</td><td>53</td><td>2.2</td><td>9</td><td></td><td></td></tr><tr><td>Vegetal, wood, earth</td><td>1.5</td><td>0.83</td><td>17</td><td>0.73</td><td>15</td><td>1.17</td><td>24</td><td>0.39</td><td>8</td><td></td><td></td></tr><tr><td><strong>Floor material</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Clay</td><td>7.6</td><td>4</td><td>50</td><td>14.2</td><td>106</td><td>5.9</td><td>97</td><td>14.2</td><td>59</td><td></td><td></td></tr><tr><td>Cement</td><td>27.5</td><td>24.9</td><td>323</td><td>32.1</td><td>240</td><td>26.5</td><td>433</td><td>31.3</td><td>130</td><td></td><td></td></tr><tr><td>Tile</td><td>40.6</td><td>54.5</td><td>708</td><td>16.6</td><td>124</td><td>47.5</td><td>775</td><td>13.7</td><td>57</td><td></td><td></td></tr><tr><td>Plastic coating</td><td>24.0</td><td>16.6</td><td>216</td><td>36.8</td><td>275</td><td>19.8</td><td>324</td><td>40.2</td><td>167</td><td></td><td></td></tr><tr><td>Other</td><td>0.3</td><td>0.2</td><td>3</td><td>0.4</td><td>3</td><td>0.2</td><td>4</td><td>0.5</td><td>2</td><td></td><td></td></tr><tr><td><strong>Roof material</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Vegetal</td><td>0.1</td><td>1.1</td><td>3</td><td>0.4</td><td>3</td><td>0.1</td><td>3</td><td>0.7</td><td>3</td><td></td><td></td></tr><tr><td>Sheet metal</td><td>58.0</td><td>47.7</td><td>620</td><td>75.8</td><td>567</td><td>52.7</td><td>861</td><td>78.6</td><td>326</td><td></td><td></td></tr><tr><td>Cement</td><td>41.8</td><td>52.1</td><td>677</td><td>23.8</td><td>178</td><td>47.1</td><td>769</td><td>20.7</td><td>86</td><td></td><td></td></tr><tr><td><strong>Humidity</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>24.5</td><td>25.0</td><td>256</td><td>23.1</td><td>77</td><td>25.0</td><td>300</td><td>20.8</td><td>33</td><td></td><td></td></tr><tr><td>No</td><td>75.5</td><td>75.0</td><td>770</td><td>77.0</td><td>257</td><td>75.0</td><td>901</td><td>79.2</td><td>126</td><td></td><td></td></tr><tr><td><strong>Water infiltration or flooding in the home</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>32.4</td><td>26.4</td><td>345</td><td>42.9</td><td>322</td><td>29.3</td><td>481</td><td>44.7</td><td>186</td><td></td><td></td></tr><tr><td><strong>Cooling system</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes. entire dwelling</td><td>3.3</td><td>4.7</td><td>62</td><td>0.7</td><td>5</td><td>3.9</td><td>64</td><td>0.7</td><td>3</td><td></td><td></td></tr><tr><td>Yes. just a room</td><td>13.6</td><td>20.4</td><td>266</td><td>2.0</td><td>15</td><td>16.8</td><td>276</td><td>1.2</td><td>5</td><td></td><td></td></tr><tr><td>No</td><td>83.1</td><td>74.9</td><td>979</td><td>97.3</td><td>731</td><td>79.3</td><td>1302</td><td>98.1</td><td>408</td><td></td><td></td></tr><tr><td><strong>Housing condition (as perceived by the household)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Very good</td><td>8.6</td><td>10.2</td><td>134</td><td>5.2</td><td>39</td><td>4.3</td><td>18</td><td>9.4</td><td>155</td><td></td><td></td></tr><tr><td>Good</td><td>37.1</td><td>36.9</td><td>482</td><td>19.4</td><td>146</td><td>18</td><td>75</td><td>33.7</td><td>553</td><td></td><td></td></tr><tr><td>Medium</td><td>36.2</td><td>38.4</td><td>502</td><td>38.6</td><td>290</td><td>37.7</td><td>157</td><td>38.7</td><td>635</td><td></td><td></td></tr><tr><td>Bad</td><td>14.3</td><td>9.1</td><td>119</td><td>21.7</td><td>163</td><td>22.4</td><td>93</td><td>11.5</td><td>189</td><td></td><td></td></tr><tr><td>Very bad</td><td>3.8</td><td>5.4</td><td>70</td><td>15.1</td><td>113</td><td>17.6</td><td>73</td><td>6.7</td><td>110</td><td></td><td></td></tr><tr><td><strong>Access to water and sanitary facilities</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Access to water</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>74.2</td><td>85.5</td><td>1117</td><td>54.5</td><td>409</td><td>80.6</td><td>1324</td><td>48.6</td><td>202</td><td></td><td></td></tr><tr><td><strong>Access to hot water</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>16.2</td><td>20.9</td><td>233</td><td>3.7</td><td>15</td><td>18.4</td><td>243</td><td>2.5</td><td>5</td><td></td><td></td></tr><tr><td><strong>Means of water supply used</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Water intake at a third party</td><td>18.1</td><td>26.3</td><td>50</td><td>13.5</td><td>46</td><td>22</td><td>70</td><td>12.1</td><td>26</td><td></td><td></td></tr><tr><td>Hydrant in the yard</td><td>8.5</td><td>10.5</td><td>20</td><td>7.3</td><td>25</td><td>10.1</td><td>32</td><td>6.1</td><td>13</td><td></td><td></td></tr><tr><td>Public hydrant</td><td>38.5</td><td>36.8</td><td>70</td><td>39.5</td><td>135</td><td>40.3</td><td>128</td><td>36</td><td>77</td><td></td><td></td></tr><tr><td>Hydrant of a family member</td><td>17.1</td><td>15.8</td><td>30</td><td>17.8</td><td>61</td><td>16.4</td><td>52</td><td>18.2</td><td>39</td><td></td><td></td></tr><tr><td>Well, cistern</td><td>7.7</td><td>5.8</td><td>11</td><td>8.8</td><td>30</td><td>5</td><td>16</td><td>11.7</td><td>25</td><td></td><td></td></tr><tr><td>Other (river, water course, etc./)</td><td>10.1</td><td>4.8</td><td>9</td><td>13.2</td><td>45</td><td>6.3</td><td>20</td><td>15.9</td><td>34</td><td></td><td></td></tr><tr><td><strong>Household has a bathroom (shower, bath)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>43.6</td><td>57.1</td><td>746</td><td>20.2</td><td>152</td><td>50.7</td><td>833</td><td>15.6</td><td>65</td><td></td><td></td></tr><tr><td><strong>Household suffers from water deprivation</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes, in the dry season</td><td>1.4</td><td>0.8</td><td>10</td><td>2.5</td><td>19</td><td>1.2</td><td>20</td><td>2.2</td><td>9</td><td></td><td></td></tr><tr><td>Yes, in the rainy season</td><td>1.0</td><td>0.5</td><td>7</td><td>1.7</td><td>13</td><td>0.7</td><td>11</td><td>2.2</td><td>9</td><td></td><td></td></tr><tr><td>Yes, in all seasons</td><td>9.3</td><td>7.9</td><td>103</td><td>11.9</td><td>89</td><td>8.2</td><td>135</td><td>13.7</td><td>57</td><td></td><td></td></tr><tr><td><strong>Household has a toilet in the home</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes, inside</td><td>24.3</td><td>54.9</td><td>717</td><td>16.5</td><td>124</td><td>47.7</td><td>783</td><td>13.9</td><td>58</td><td></td><td></td></tr><tr><td>No, outside</td><td>16.6</td><td>31.5</td><td>412</td><td>53.7</td><td>403</td><td>35.6</td><td>585</td><td>55.3</td><td>230</td><td></td><td></td></tr><tr><td>No</td><td>39.6</td><td>13.6</td><td>178</td><td>29.8</td><td>224</td><td>16.7</td><td>274</td><td>30.8</td><td>128</td><td></td><td></td></tr><tr><td><strong>Access to electricity</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Electricity access</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>74.3</td><td>83.1</td><td>836</td><td>64.6</td><td>485</td><td>83.6</td><td>1372</td><td>60.1</td><td>250</td><td></td><td></td></tr><tr><td>Yes, connected to another home's meter</td><td>18.7</td><td>13.2</td><td>133</td><td>24.6</td><td>185</td><td>12.8</td><td>210</td><td>24.8</td><td>103</td><td></td><td></td></tr><tr><td>No</td><td>7.00</td><td>3.7</td><td>37</td><td>10.8</td><td>81</td><td>36.5</td><td>60</td><td>13.9</td><td>58</td><td></td><td></td></tr><tr><td><strong>Safety of the electrical installation of the dwelling</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Protected installation</td><td>44.9</td><td>53.8</td><td>684</td><td>27.8</td><td>186</td><td>49.4</td><td>782</td><td>24.6</td><td>88</td><td></td><td></td></tr><tr><td>Installation with unprotected wires</td><td>47.0</td><td>41.2</td><td>523</td><td>58.1</td><td>389</td><td>44.1</td><td>697</td><td>60.1</td><td>215</td><td></td><td></td></tr><tr><td>Unprotected installation</td><td>8.1</td><td>5</td><td>63</td><td>14.2</td><td>95</td><td>6.5</td><td>103</td><td>15.4</td><td>55</td><td></td><td></td></tr><tr><td><strong>Kitchen facilities</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Household has a place for cooking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>71.3</td><td>49.7</td><td>1023</td><td>21.6</td><td>445</td><td>60.0</td><td>1235</td><td>11.3</td><td>232</td><td></td><td></td></tr><tr><td><strong>Kitchen surface area</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Less than 4 m²</td><td>23.0</td><td>20</td><td>151</td><td>34.7</td><td>66</td><td>21.5</td><td>183</td><td>36.6</td><td>34</td><td></td><td></td></tr><tr><td>From 4 m² to 7 m²</td><td>36.9</td><td>35.5</td><td>268</td><td>42.6</td><td>81</td><td>36</td><td>307</td><td>45.2</td><td>42</td><td></td><td></td></tr></tbody></table>

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<table><caption>**Table 2 (continued)**</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Sample means (n = 2058)</th><th colspan="4">Monetary poor 60%</th><th colspan="4">Monetary poor Sen index</th></tr><tr><th>%</th><th colspan="2">Nonpoor (n = 1307)</th><th colspan="2">Poor (n = 751)</th><th>%</th><th colspan="2">Nonpoor (n = 1642)</th><th colspan="2">Poor (n = 416)</th></tr><tr><th></th><th></th><th></th><th colspan="2">Obs</th><th colspan="2">Obs</th><th>%</th><th colspan="2">Obs</th><th colspan="2">Obs</th></tr></thead><tbody><tr><td>From 7 m² to 12 m²</td><td>25.1</td><td>27.7</td><td>209</td><td>14.7</td><td>28</td><td>26.4</td><td>225</td><td>12.9</td><td>12</td><td></td></tr><tr><td>Greater than 12 m²</td><td>15.0</td><td>16.8</td><td>127</td><td>7.9</td><td>15</td><td>16.1</td><td>137</td><td>5.4</td><td>5</td><td></td></tr><tr><td><strong>Energy for cooking</strong></td><td></td><td></td><td><strong>1307</strong></td><td></td><td><strong>751</strong></td><td></td><td><strong>1642</strong></td><td></td><td><strong>416</strong></td><td></td></tr><tr><td>Butane, propane, tank</td><td>74.6</td><td>85</td><td>1111</td><td>56.5</td><td>424</td><td>68.6</td><td>1326</td><td>45.2</td><td>209</td><td></td></tr><tr><td>Oil</td><td>19.1</td><td>10.7</td><td>140</td><td>33.8</td><td>254</td><td>12.4</td><td>239</td><td>33.5</td><td>155</td><td></td></tr><tr><td>Electricity</td><td>12.4</td><td>15.1</td><td>197</td><td>7.7</td><td>58</td><td>12.2</td><td>235</td><td>4.3</td><td>20</td><td></td></tr><tr><td>Wood</td><td>7.4</td><td>2.8</td><td>36</td><td>15.6</td><td>117</td><td>4.3</td><td>84</td><td>14.9</td><td>69</td><td></td></tr><tr><td>Coal</td><td>2.9</td><td>3.3</td><td>43</td><td>2.1</td><td>16</td><td>2.6</td><td>50</td><td>1.9</td><td>9</td><td></td></tr><tr><td><strong>Households' profile</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Rural (less than 5000 inhabitants)</td><td>8.02</td><td>5.78</td><td>119</td><td>2.24</td><td>46</td><td>6.85</td><td>141</td><td>1.17</td><td>24</td><td></td></tr><tr><td>Number of children</td><td>2.02</td><td>1.45</td><td>1307</td><td>2.77</td><td>751</td><td>1.93</td><td>1642</td><td>2.38</td><td>416</td><td></td></tr><tr><td>Number of active (employed) persons</td><td>1.05</td><td>0.63</td><td>1307</td><td>1.30</td><td>751</td><td>0.48</td><td>1642</td><td>1.20</td><td>416</td><td></td></tr><tr><td>Homeowner</td><td>56.56</td><td>38.68</td><td>796</td><td>17.88</td><td>368</td><td>47.81</td><td>984</td><td>8.75</td><td>180</td><td></td></tr><tr><td>Age (head of household) - years</td><td>43.3</td><td>44.55</td><td>1307</td><td>41.07</td><td>751</td><td>44.23</td><td>1642</td><td>39.55</td><td>416</td><td></td></tr><tr><td>Level of diploma > bac</td><td>9.00</td><td>8.84</td><td>182</td><td>0.15</td><td>3</td><td>8.89</td><td>183</td><td>0.10</td><td>2</td><td></td></tr><tr><td>Person of reference is a man</td><td>59.48</td><td>41.50</td><td>854</td><td>17.98</td><td>370</td><td>49.85</td><td>1026</td><td>9.62</td><td>198</td><td></td></tr><tr><td>Person of reference is foreign</td><td>36.30</td><td>13.12</td><td>270</td><td>23.18</td><td>477</td><td>21.87</td><td>450</td><td>14.43</td><td>297</td><td></td></tr><tr><td><strong>Housing population index*</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Undercrowding</td><td>24.59</td><td>21.38</td><td>440</td><td>3.21</td><td>66</td><td>23.08</td><td>475</td><td>1.51</td><td>31</td><td></td></tr><tr><td>Normal housing population</td><td>20.55</td><td>15.60</td><td>321</td><td>4.96</td><td>102</td><td>17.74</td><td>365</td><td>2.82</td><td>58</td><td></td></tr><tr><td>Overcrowding</td><td>54.86</td><td>26.53</td><td>546</td><td>28.33</td><td>583</td><td>38.97</td><td>802</td><td>15.89</td><td>327</td><td></td></tr></tbody></table>

Note.

* The housing population index characterizes the degree of occupancy of the dwelling, by comparison between the number of rooms it has and the number of rooms necessary for the household.

## Appendix 3

<table><caption>**Table 3**
Use of different energy types, according to the presence of a kitchen facility</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="5">Energy for cooking</th><th rowspan="2">Total</th></tr><tr><th>Butane/propane</th><th>Electricity</th><th>Wood</th><th>Coal</th><th>Oil</th></tr></thead><tbody><tr><td rowspan="3">Has a kitchen facility (open kitchen, gas stove, kitchen utensils ...)</td><td>No</td><td>50.5%</td><td>6.9%</td><td>14.7%</td><td>2.9%</td><td>28.3%</td><td>28.7%</td></tr><tr><td>Yes</td><td>84.3%</td><td>14.6%</td><td>4.5%</td><td>2.9%</td><td>15.5%</td><td>71.3%</td></tr><tr><td>Total</td><td>74.6%</td><td>12.4%</td><td>7.4%</td><td>2.9%</td><td>19.1%</td><td>100%</td></tr></tbody></table>

## Appendix 4

<table><caption>**Table 4**
Estimated coefficients and predicted probabilities in a model with 2 latent classes</caption><thead><tr><th rowspan="2"></th><th colspan="3">Class 1 Utility services poor</th><th colspan="3">Class 2 Utility services sufficient</th></tr><tr><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th></tr></thead><tbody><tr><td>0. No access to water</td><td>base outcome</td><td></td><td>0.4568</td><td>base outcome</td><td></td><td>9.07e-12</td></tr><tr><td>1. Access to water</td><td>0.173</td><td>(0.068)**</td><td>0.5432</td><td>25.426</td><td>(0.965)***</td><td>1</td></tr><tr><td>0. No access to electricity</td><td>base outcome</td><td></td><td>0.1013</td><td>base outcome</td><td></td><td>3.84e-08</td></tr><tr><td>1. Access to electricity</td><td>2.183<sup>a</sup></td><td>(0.100)***</td><td>0.8987</td><td>17.075</td><td>(7.607)**</td><td>1</td></tr><tr><td>0. No cooling system</td><td>base outcome</td><td></td><td>0.9924</td><td>base outcome</td><td></td><td>0.06204</td></tr><tr><td>1. Cooling system</td><td>-4.873</td><td>(0.415)***</td><td>0.0076</td><td>-0.491</td><td>(0.076)***</td><td>0.3796</td></tr><tr><td>0. No bathroom</td><td>base outcome</td><td></td><td>0.9313</td><td>base outcome</td><td></td><td>0.0843</td></tr><tr><td>1. Bathroom</td><td>-2.607</td><td>(0.187)***</td><td>0.0687</td><td>2.384</td><td>(0.144)***</td><td>0.9156</td></tr><tr><td>0. No toilet</td><td>base outcome</td><td></td><td>0.9678</td><td>base outcome</td><td></td><td>0.1007</td></tr><tr><td>1. Toilet</td><td>-3.402</td><td>(0.207)***</td><td>0.0322</td><td>2.190</td><td>(0.186)***</td><td>0.8993</td></tr><tr><td>0. No kitchen facilities</td><td>base outcome</td><td></td><td>0.4629</td><td>base outcome</td><td></td><td>0.0569</td></tr><tr><td>1. Kitchen facilities</td><td>0.149</td><td>(0.060)***</td><td>0.5371</td><td>2.807</td><td>(0.179)***</td><td>0.9430</td></tr><tr><td>Observations</td><td>2058</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Robust standard errors are presented in parentheses.

*p* < 0.1 Note: aThe probability of being in Class 1 increases if households have electricity access compared with those without electricity access.

*** p < 0.01.

** p < 0.05.
Appendix 5

<table><caption>**Table 5**
Comparison of models</caption><thead><tr><th></th><th></th><th>AIC</th><th>BIC</th><th>LL</th><th>df</th></tr></thead><tbody><tr><td>Model 1</td><td>2 classes</td><td>10219.24</td><td>10292.42</td><td>-5096.619</td><td>13</td></tr><tr><td>Model 2</td><td>3 classes</td><td>10009.43</td><td>10110.76</td><td>-4986.714</td><td>18</td></tr><tr><td>Model 3</td><td>4 classes</td><td>9981.925</td><td>10117.03</td><td>-4966.962</td><td>24</td></tr></tbody></table>

Appendix 6

<table><caption>**Table 6**
Estimated coefficients and predicted probabilities in 3 latent classes model</caption><thead><tr><th rowspan="2"></th><th colspan="3">Class 1 Utility services poor<br>27.8%</th><th colspan="3">Class 2 Utility services vulnerable<br>32.4%</th><th colspan="3">Class 3 Utility services sufficient<br>39.8%</th></tr><tr><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th><th>Coeff.</th><th>Std. Err.</th><th>Margin</th></tr></thead><tbody><tr><td>0. No access to water</td><td>base outcome</td><td></td><td>0.9143</td><td>base outcome</td><td></td><td>0.0124</td><td>base outcome</td><td></td><td>0.0013</td></tr><tr><td>1. Access to water</td><td>-2.368</td><td>(1.345)*</td><td>0.0857</td><td>4.377</td><td>(0.717)***</td><td>0.9876</td><td>6.661</td><td>(1.080)***</td><td>0.9987</td></tr><tr><td>0. No access to electricity</td><td>base outcome</td><td></td><td>0.1851</td><td>base outcome</td><td></td><td>0.0165</td><td>base outcome</td><td></td><td>0.0015</td></tr><tr><td>1. Access to electricity</td><td>1.482</td><td>(0.114)***</td><td>0.8149</td><td>4.088</td><td>(1.269)***</td><td>0.9835</td><td>6.511</td><td>(2.833)**</td><td>0.9985</td></tr><tr><td>0. No cooling system</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>0.9711</td><td>base outcome</td><td></td><td>0.5992</td></tr><tr><td>1. Cooling system</td><td>/</td><td>/</td><td>0</td><td>-3.516</td><td>(0.302)***</td><td>0.0289</td><td>-0.402</td><td>(0.100)***</td><td>0.4008</td></tr><tr><td>0. No bathroom</td><td>base outcome</td><td></td><td>1</td><td>base outcome</td><td></td><td>0.7759</td><td>base outcome</td><td></td><td>0.0872</td></tr><tr><td>1. Bathroom</td><td>/</td><td>/</td><td>0</td><td>-1.242</td><td>(0.152)***</td><td>0.2241</td><td>2.348</td><td>(0.269)***</td><td>0.9128</td></tr><tr><td>0. No toilet</td><td>base outcome</td><td></td><td>0.9632</td><td>base outcome</td><td></td><td>0.9811</td><td>base outcome</td><td></td><td>0.0158</td></tr><tr><td>1. Toilet</td><td>-3.264</td><td>(0.235)***</td><td>0.0368</td><td>-3.949</td><td>(2.400)</td><td>0.0189</td><td>4.133</td><td>(0.690)***</td><td>0.9842</td></tr><tr><td>0. No kitchen facilities</td><td>base outcome</td><td></td><td>0.4507</td><td>base outcome</td><td></td><td>0.4422</td><td>base outcome</td><td></td><td>0.0461</td></tr><tr><td>1. Kitchen facilities</td><td>0.0198</td><td>(0.094)**</td><td>0.5493</td><td>0.232</td><td>(0.092)**</td><td>0.5578</td><td>3.030</td><td>(0.307)***</td><td>0.9539</td></tr><tr><td>Observations</td><td colspan="3">2058</td><td colspan="3"></td><td colspan="3"></td></tr></tbody></table>

Robust standard errors are presented in parentheses.

Appendix 7

<table><caption>**Table 8**
Summary statistics by utility services poverty</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Sample means (n = 2058)</th><th colspan="4">Utility services poverty</th></tr><tr><th>Poor<br>Class 1 (n = 289)</th><th>Vulnerable 1<br>Class 2 (n = 260)</th><th>Vulnerable 2<br>Class 3 (n = 685)</th><th>Nonpoor<br>Class 4 (n = 824)</th></tr></thead><tbody><tr><td><strong>Housing conditions</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Wall material</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sheet metal</td><td>33.9</td><td>11.0</td><td>10.0</td><td>12.4</td><td>0.5</td></tr><tr><td>Hard (stone. brick. breeze) %</td><td>61.9</td><td>2.6</td><td>2.4</td><td>18.8</td><td>38.1</td></tr><tr><td>Semihard (coated earth. lime) %</td><td>3.0</td><td>0.2</td><td>0.1</td><td>1.8</td><td>1.0</td></tr><tr><td>Vegetal. wood. Earth %</td><td>1.5</td><td>0.6</td><td>0.3</td><td>0.4</td><td>0.2</td></tr><tr><td><strong>Floor material</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Clay %</td><td>7.6</td><td>3.4</td><td>1.9</td><td>2.3</td><td>0.1</td></tr><tr><td>Cement %</td><td>27.5</td><td>3.7</td><td>3.0</td><td>15.5</td><td>5.2</td></tr><tr><td>Tile %</td><td>40.6</td><td>0.8</td><td>1.1</td><td>6.5</td><td>32.3</td></tr><tr><td>Plastic coating %</td><td>24.0</td><td>6.1</td><td>6.6</td><td>8.9</td><td>2.3</td></tr><tr><td>Other %</td><td>0.3</td><td>0.1</td><td>0.1</td><td>0.2</td><td>0</td></tr><tr><td><strong>Roof material</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Vegetal %</td><td>0.1</td><td>0</td><td>0</td><td>0.1</td><td>0</td></tr><tr><td>Sheet metal %</td><td>58.0</td><td>12.5</td><td>10.7</td><td>23.9</td><td>10.8</td></tr><tr><td>Cement %</td><td>41.8</td><td>1.5</td><td>1.9</td><td>9.4</td><td>29.1</td></tr><tr><td><strong>Humidity</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>24.5</td><td>1.1</td><td>0.9</td><td>7.3</td><td>15.2</td></tr><tr><td>No %</td><td>75.5</td><td>3.5</td><td>3.2</td><td>24.3</td><td>44.6</td></tr><tr><td><strong>Water infiltration or flooding in the home</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>32.4</td><td>6.5</td><td>55</td><td>10.5</td><td>9.9</td></tr><tr><td>No %</td><td>67.6</td><td>7.5</td><td>7.1</td><td>22.8</td><td>30.1</td></tr></tbody></table>

(continued on next page)

<footnote>*** $p < 0.01$.</footnote>

<footnote>** $p < 0.05$.</footnote>

<footnote>* $p < 0.1$.</footnote>
<table><caption>**Table 8 (continued)**</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Sample means (n = 2058)</th><th colspan="4">Utility services poverty</th></tr><tr><th>Poor<br>Class 1 (n = 289)</th><th>Vulnerable 1<br>Class 2 (n = 260)</th><th>Vulnerable 2<br>Class 3 (n = 685)</th><th>Nonpoor<br>Class 4 (n = 824)</th></tr></thead><tbody><tr><td><strong>Cooling system</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes, entire dwelling %</td><td>3.3</td><td>0.0</td><td>16.0</td><td>0.2</td><td>3.0</td></tr><tr><td>Yes, just a room %</td><td>13.6</td><td>0.0</td><td>10.1</td><td>0.5</td><td>13.0</td></tr><tr><td>No %</td><td>83.1</td><td>14.0</td><td>3.8</td><td>32.5</td><td>40.0</td></tr><tr><td><strong>Housing condition (as perceived by the household)</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Very good %</td><td>8.6</td><td>0.8</td><td>16.0</td><td>1.7</td><td>5.8</td></tr><tr><td>Good %</td><td>37.1</td><td>2.2</td><td>10.1</td><td>9.1</td><td>22.8</td></tr><tr><td>Medium %</td><td>36.2</td><td>5.3</td><td>3.8</td><td>16.0</td><td>9.8</td></tr><tr><td>Bad %</td><td>14.3</td><td>4.4</td><td></td><td>5.0</td><td>1.4</td></tr><tr><td>Very bad %</td><td>3.8</td><td>1.3</td><td>16.0</td><td>1.6</td><td>0.3</td></tr><tr><td><strong>Water facilities</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Access to water</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>74.2</td><td>0.8</td><td></td><td>33.3</td><td>40.0</td></tr><tr><td>No %</td><td>25.8</td><td>13.2</td><td>16.0</td><td>0</td><td>0</td></tr><tr><td><strong>Access to hot water</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>16.2</td><td>0</td><td>3.8</td><td>0.3</td><td>15.9</td></tr><tr><td>No %</td><td>83.8</td><td>1.1</td><td></td><td>44.6</td><td>38.1</td></tr><tr><td><strong>Means of water supply used</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Water intake at a third party %</td><td>18.1</td><td>7.5</td><td>10.1</td><td>-</td><td>-</td></tr><tr><td>Hydrant in the yard %</td><td>8.5</td><td>4.3</td><td>3.8</td><td>-</td><td>-</td></tr><tr><td>Public hydrant %</td><td>38.5</td><td>22.6</td><td>16.0</td><td>-</td><td>-</td></tr><tr><td>Hydrant of a family member %</td><td>17.1</td><td>7.0</td><td>10.1</td><td>-</td><td>-</td></tr><tr><td>Well, cistern %</td><td>7.7</td><td>4.0</td><td>3.8</td><td>-</td><td>-</td></tr><tr><td>Other (river, water course, etc./) %</td><td>10.1</td><td>5.8</td><td></td><td>-</td><td>-</td></tr><tr><td><strong>Household has a bathroom (shower, bath</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>43.6</td><td>0</td><td>0.2</td><td>7.3</td><td>36.3</td></tr><tr><td>No %</td><td>56.4</td><td>14.0</td><td></td><td>26.0</td><td>3.7</td></tr><tr><td><strong>Household suffers from water deprivation</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes, in the dry season %</td><td>1.4</td><td>0.5</td><td>4.2</td><td>0.3</td><td>0.2</td></tr><tr><td>Yes, in the rainy season %</td><td>1.0</td><td>0.2</td><td>0.5</td><td>0.2</td><td>0.2</td></tr><tr><td>Yes, in all seasons %</td><td>9.3</td><td>2.2</td><td>0.2</td><td>2.4</td><td>3.3</td></tr><tr><td><strong>Household has a toilet in home</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes, inside %</td><td>24.3</td><td>0</td><td>8.0</td><td>0.1</td><td>23.6</td></tr><tr><td>No, outside %</td><td>16.6</td><td>0</td><td>5.2</td><td>0</td><td>16.1</td></tr><tr><td>No %</td><td>39.6</td><td>7.6</td><td>0.9</td><td>23.7</td><td>0.3</td></tr><tr><td><strong>Electricity</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Electricity access</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>74.3</td><td>4.0</td><td>12.5</td><td>31.4</td><td>31.5</td></tr><tr><td>Yes, connected to another home's meter %</td><td>18.7</td><td>6.0</td><td>0.2</td><td>5.0</td><td>1.1</td></tr><tr><td>No %</td><td>7.00</td><td>6.6</td><td></td><td>0.1</td><td>0.1</td></tr><tr><td><strong>Safety of the electrical installation of the dwelling</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Protected installation %</td><td>44.9</td><td>1.9</td><td>4.2</td><td>10.0</td><td>29.7</td></tr><tr><td>Installation with unprotected wires %</td><td>47.0</td><td>6.1</td><td>0.5</td><td>21.0</td><td>11.1</td></tr><tr><td>Unprotected installation %</td><td>8.1</td><td>1.1</td><td>0.2</td><td>35.2</td><td>42.4</td></tr><tr><td><strong>Kitchen facilities</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Household has a place for cooking</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes %</td><td>71.3</td><td>2.1</td><td>12.5</td><td>18.6</td><td>38.1</td></tr><tr><td>No %</td><td>28.7</td><td>12.0</td><td>0.2</td><td>14.7</td><td>1.9</td></tr><tr><td><strong>Kitchen surface area</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Less than 4 m² %</td><td>23.0</td><td>1.0</td><td>3.2</td><td>7.1</td><td>11.8</td></tr><tr><td>From 4 m² to 7 m² %</td><td>36.9</td><td>0.3</td><td>4.2</td><td>6.8</td><td>25.6</td></tr><tr><td>From 7 m² to 12 m² %</td><td>25.1</td><td>0.1</td><td>0.5</td><td>2.2</td><td>22.2</td></tr><tr><td>Greater than 12 m² %</td><td>15.0</td><td>0.0</td><td>0.2</td><td>1.3</td><td>13.5</td></tr><tr><td><strong>Energy for cooking</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Butane, propane tank %</td><td>74.6</td><td>3.7</td><td>8.0</td><td>25.1</td><td>37.8</td></tr><tr><td>Oil %</td><td>19.1</td><td>5.3</td><td>5.2</td><td>7.2</td><td>1.4</td></tr><tr><td>Electricity %</td><td>12.4</td><td>0.4</td><td>0.9</td><td>3.1</td><td>8.0</td></tr><tr><td>Wood %</td><td>7.4</td><td>3.4</td><td>1.3</td><td>2.3</td><td>0.4</td></tr><tr><td>Coal %</td><td>2.9</td><td>0.2</td><td>0.1</td><td>1.3</td><td>1.1</td></tr><tr><td><strong>Households' profile</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Rural (less than 5000 inhabitants) %</td><td>8.02</td><td>0.87</td><td>0.44</td><td>2.33</td><td>4.37</td></tr><tr><td>Number of children</td><td>2.02</td><td>2.06</td><td>2.67</td><td>2.02</td><td>1.8</td></tr><tr><td>Number of active (employed) persons</td><td>1.05</td><td>0.53</td><td>0.73</td><td>0.93</td><td>1.44</td></tr><tr><td>Homeowner %</td><td>56.56</td><td>6.07</td><td>7.24</td><td>18.3</td><td>25.0</td></tr><tr><td>Age (head of household) - years</td><td>43.3</td><td>36.9</td><td>39.3</td><td>44.9</td><td>45.5</td></tr><tr><td>Level of diploma > bac %</td><td>9.00</td><td>0.15</td><td>0.10</td><td>0.68</td><td>8.07</td></tr><tr><td>Person of reference is a man %</td><td>59.48</td><td>6.66</td><td>8.45</td><td>19.29</td><td>25.07</td></tr><tr><td>Person of reference is foreign</td><td>36.30</td><td>9.77</td><td>8.79</td><td>12.93</td><td>4.81</td></tr><tr><td>Housing population index<sup>a</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Undercrowding %</td><td>24.59</td><td>0.53</td><td>0.58</td><td>3.35</td><td>20.12</td></tr><tr><td>Normal housing population %</td><td>20.55</td><td>1.65</td><td>1.36</td><td>7.29</td><td>10.25</td></tr><tr><td>Overcrowding %</td><td>54.86</td><td>10.40</td><td>12.15</td><td>22.64</td><td>9.67</td></tr></tbody></table>

Note.
* The housing population index characterizes the degree of occupancy of the dwelling, by comparison between the number of rooms it has and the number of rooms necessary for the household.

## Appendix 9

<table><caption>**Table 10**
Results – comparisons of utility services poor and monetary poor (4 classes model)</caption><thead><tr><th rowspan="3"></th><th colspan="4">Monetary poor 60%</th><th colspan="4">Monetary poor 50%</th><th colspan="4">Monetary poor Sen index</th><th rowspan="2">Income</th><th rowspan="2">Total</th></tr><tr><th colspan="2">No</th><th colspan="2">Yes</th><th colspan="2">No</th><th colspan="2">Yes</th><th colspan="2">No</th><th colspan="2">Yes</th></tr><tr><th>Obs</th><th>%</th><th>Obs</th><th>%</th><th>Obs</th><th>%</th><th>Obs</th><th>%</th><th>Obs</th><th>%</th><th>Obs</th><th>%</th><th>Euros</th><th>Obs</th></tr></thead><tbody><tr><td>Class 1<br>Utility services poor</td><td>96</td><td>33.2</td><td>193</td><td>66.8</td><td>105</td><td>36.3</td><td>184</td><td>63.7</td><td>152</td><td>52.6</td><td>137</td><td>47.4</td><td>2657</td><td>289</td></tr><tr><td>Class 2<br>Utility services vulnerable 1</td><td>98</td><td>37.7</td><td>162</td><td>62.3</td><td>11</td><td>43.5</td><td>147</td><td>56.5</td><td>17</td><td>66.5</td><td>87</td><td>33.5</td><td>2690</td><td>260</td></tr><tr><td>Class 3<br>Utility services vulnerable 2</td><td>405</td><td>61.5</td><td>280</td><td>42.5</td><td>443</td><td>67.3</td><td>242</td><td>36.7</td><td>542</td><td>82.3</td><td>143</td><td>21.7</td><td>4197</td><td>658</td></tr><tr><td>Class 4<br>Utility services sufficient</td><td>708</td><td>85.9</td><td>116</td><td>14.1</td><td>72</td><td>88.5</td><td>95</td><td>11.5</td><td>775</td><td>94.1</td><td>49</td><td>5.9</td><td>12340</td><td>824</td></tr><tr><td>Total</td><td>1307</td><td></td><td>751</td><td></td><td>1390</td><td></td><td>668</td><td></td><td>1642</td><td></td><td>416</td><td></td><td></td><td>2058</td></tr></tbody></table>

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