The Economic Burden of Healthcare Utilisation: Findings from a Health and Well-being Survey in Informal Settlements of Freetown, Sierra Leone

The Economic Burden of Healthcare Utilisation: Findings from a Health and Well-being Survey in Informal Settlements of Freetown, Sierra Leone | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Economic Burden of Healthcare Utilisation: Findings from a Health and Well-being Survey in Informal Settlements of Freetown, Sierra Leone Sullaiman Fullah, Dora Vangahun, Ibrahim Gandi, Sia Morenike Tengbe, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5131613/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Journal of Urban Health → Version 1 posted 3 You are reading this latest preprint version Abstract The fragile health system in Sierra Leone undermines healthcare, leading to substantial patient costs. We aimed to estimate the economic burden and inequalities in healthcare in urban informal settlements in Freetown, Sierra Leone. A cross-sectional survey was conducted in three informal settlements in Freetown in April and May 2023 to collect data on healthcare usage within and outside the boundaries of the informal settlements. Catastrophic expenditures were estimated using the payer’s household budget. Logistic regression explored socio-economic characteristics associated with catastrophic expenditures. Inequalities in healthcare expenditures were assessed through concentration curves and indices. 2,575 participants reported healthcare utilisation. Dwarzark (US$6.9) and Moyiba (US$7.1) had higher costs than Cockle Bay (US$5.5) when utilising healthcare within the communities. Households incurred higher costs when seeking healthcare outside their informal settlements than within (US$14 vs US$ 7). Over half of the households across the settlements incurred catastrophic expenditures when seeking care outside the communities (57%), with the poorest wealth quintile (poorest: 89%; wealthier: 12%) incurring in higher incidence. Attending informal healthcare had a protective effect against catastrophic expenditure for healthcare within the communities. Age +35, residence in Dwarzark and Moyiba and length of residence +4 years were associated with catastrophic expenditures. Healthcare expenditure was progressive in Dwarzark and equally distributed across wealth quintiles in the other communities. Our findings indicate the need to provide accessible, affordable and good-quality healthcare within communities to alleviate the catastrophic costs of healthcare utilisation. The regulation of informal health providers and their integration into the formal health system should be considered. healthcare utilisation informal settlements inequalities catastrophic expenditures costs Figures Figure 1 Figure 2 Introduction The rapid urbanisation has been coupled with the worsening of income inequalities, as the gap between rich and poor is widening consistently across cities in low- and middle-income countries (LMICs) 1 . Within these urban areas in LMICs, many people reside in informal settlements characterised by inadequate housing, insecurity, overcrowding and limited access to basic social amenities and services 2 . In West Africa, Sierra Leone has experienced significant urban population growth. The percentage of the national population residing in urban areas has increased from 21% in 1976 to 43% in 2021, with more than half of these city dwellers (60%) living in informal settlements 3 . Like most cities in LMICs, Freetown lacks coordinated development for healthy urbanisation with insufficient planning and implementation of environmental, housing and transport policies 4 . In addition to the complexities of demographics, urbanisation can be seen as a determinant of health, leading to widening health and well-being inequalities 5 . In an analysis of urban health systems in Ghana, Nigeria, Bangladesh and Nepal, Elsey and colleagues reflected on the fragile health system in these countries and how it can present significant challenges to effective health-seeking behaviour. In this scenario, limited access to quality public services and reliance on the private or informal sector could result in high healthcare costs and catastrophic expenditures for vulnerable urban dwellers 5 . In Sierra Leone, the recently implemented National Emergency Medical Service, aiming to provide a free-of-charge and good quality prehospital service, has improved healthcare access, however, the positive impact has been observed mainly in rural areas 6 . Despite the significant challenges of providing healthcare in the context of rapid urbanisation in LMICs, there needs to be more evidence to support policy and planning to address these challenges, particularly on the extent and nature of healthcare expenditure in informal settlements. In the context of Sierra Leone, the current evidence focuses on the financial burden of surgical care in Freetown and the changes in catastrophic costs in the pre and post-conflict period between 2003 and 2011, a national-level analysis 7,8 . A recent scoping review on the economics of healthcare access for urban informal settlement dwellers in LMICs found a high incidence of catastrophic expenditures (~19%) across wealth quintiles; however, no evidence from Sierra Leone was found 9 . To address the gap in evidence on healthcare costs to informal settlement dwellers, this study aims to assess the economic burden and inequalities in healthcare utilisation in three informal settlements in Freetown, Sierra Leone. Methodology Study setting Sierra Leone is a low-income country in West Africa with a Gross Domestic Product (GDP) per capita of $1,931 in 2022 10 According to the latest estimate from the World Bank, 26% of the country's population lived below the poverty line (defined as $2.15 a day in terms of purchasing power parity) in 2018 11 . In Freetown, the capital city, estimates indicate that average monthly expenses for an individual range from US$185 to US$500 12 . However, these figures vary significantly across different areas of the city, depending on location, lifestyle, and personal needs. In addition, in 2015, 35% of Freetown's population was living below the multidimensional poverty line. Only 22% of residents have access to improved private sanitation facilities, and 3% of urban households have access to piped indoor drinking water. Additionally, 39% of households rely on public taps, and only 40% of the city’s waste is collected 13 . The community profiling and enumeration research in Freetown indicated the existence of 68 informal settlements, 36% of all settlements in the city, and high population density in these settings, which increased from 1,360 people per square kilometre in 2004 to 2,154 in 2015. The study also noted that the population growth occurred mainly in settlements on the coast and hillsides where residents are exposed to water and sanitation-related diseases, coastal floods, fire and landslides 14 . The health and well-being survey reported in this article occurred in three urban informal settlements in Freetown: Cockle Bay, Moyiba and Dwarzark. Box 1 shows the main characteristics of the study sites. Study design and data collection procedures The content and design of this study drew on findings from qualitative studies conducted in the same informal settlements investigating the community members’ perspectives on health and well-being. During the qualitative study, community residents in the study areas revealed the vulnerability to health risks such as the poor WASH facilities, lack of health centres in Cockle Bay and the underserved peripheral health units in Dwarzark and Moyiba, precarious livelihoods, exposure to disasters, high costs to access healthcare and lack of safety compounded the health risks and wellbeing of residents 15–17 . Having understood the intersection of health risks in these settlements, we wanted to quantify the qualitative findings, which informed the development of survey tools to ascertain a wider perspective of the issues that emerged from the qualitative study. We conducted a cross-sectional survey from April to May 2023 to investigate service delivery, healthcare utilisation, environmental risks, and well-being priorities in those informal settlements. The survey questions were developed based on the priorities identified during the qualitative research across the study sites. These were access and barriers to services (water, sanitation, and healthcare), environmental health risks/vulnerabilities (disasters, safety and security, livelihoods), and well-being priorities. We collected data on household income, out-of-pocket expenditure (OOPE, direct medical costs: medicines, consultation fees and tests; direct non-medical costs: transport and food) to utilise healthcare within and outside the informal settlements' boundaries, and the type of healthcare utilised. The survey sections are indicated in Box 2. All findings have been published in the Survey report 18 . The RedCap tool was applied to collect data online and offline. The survey team was recruited based on their familiarity with the communities' geography and landscape and understanding of the local context. Data was collected face-to-face by co-researchers and community mobilisers in the informal settlements included in this study. Co-researchers were residents in the study sites, recruited since the project's inception. They were actively engaged in the research to ensure the full participation of communities throughout the various phases of the research process. Community mobilisers were recruited purposely to facilitate the data collection due to the huge volume of the sample size. They were responsible for community engagement, data collection and dissemination of the study findings to promote local utilisation/application of project components/outputs.The survey team underwent a 4-day training program covering using the participant information sheet and consent form and selecting households based on the survey's sampling framework. They were also trained to familiarise themselves with the survey tool, use the redcap, and troubleshoot if they faced any problems. The survey tool was tested in a pilot survey of 150 households across the three communities in March 2023. The research team held a workshop in Sierra Leone, attended by all community mobilisers and co-researchers, to discuss the challenges faced during the pilot survey and the necessary improvements in the tool to enhance its accuracy.We collected data on the last visit to healthcare by any household member in the last month before the interview. Due to the strong informality in the job market in Freetown, the participants were asked to provide their income data daily, weekly, or monthly. Costs were collected in the local currency, Sierra Leone Leones and converted to US$ (1 SLE=0.044 USD), applying the average exchange rate from OANDA website (www.oanda.com) during the data collection period (April-May, 2023). Sample size calculation and sampling The informal settlements were selected purposively to ensure maximum variation in context and to understand their spatial and social diversities. The sample size was determined based on the proportion of households facing barriers to accessing health services, estimated to be 0.47 from a pilot survey conducted before the survey. A margin of error of 0.03, a design effect of 10 to account for convenience sampling, a critical value of 0.05 (95% confidence interval), and a non-response rate of 10% were applied in the sample size calculation. The final sample was determined to be 4,884 households, considered large enough to estimate other health and well-being indicators within the desired precision. The following formula was used to calculate the sample size: Where: n = required sample size p = proportion of households facing barriers to accessing health services (0.47) deff = design effect (10) d = margin of error (0.03) z21−α2 = critical value for the standard normal distribution corresponding to a Type 1 error rate of a two-tailed test (1.96). NR = Non-response rate (0.10) A hybrid sampling technique comprising probability and non-probability approaches was employed in household selection due to the lack of a sample frame of all households in the study sites. Probability sampling was employed proportionally to allocate the number of households to each informal settlement based on estimated populations from 2018 13 . This approach resulted in a sample of 1,251 households in Cockle Bay, 2,312 in Moyiba, and 1,321 in Dwarzark. Within each settlement, the number of households was equally allocated to different settlement zones (Cockle Bay: 313 households per zone x 4 zones, Moyiba: 232 households per zone x 10 zones and Dwarzark: 111 households per zone x 12 zones). In each zone, a random household along the chosen direction pointing outwards from an identified landmark was selected as a starting point for interviews. Landmarks used (e.g., mosques, cinemas, community centres and water points) and settlement boundaries were identified during a GIS mapping study 19 . The next step involved selecting the closest household to the one randomly chosen and interviewed if inclusion criteria requirements were met. The process was repeated interactively until the boundary of the zone was reached. This ensured that the households sampled were representative of the community population. Data was collected by interviewing every i th household in each direction from the landmark, with k th value determined by dividing the number of sampled households in each zone by the number of landmarks. One consenting adult (18 years and older), either the head of the household or the most senior household member, was selected for the interview. Data analysis Mean with 95% confidence intervals (CIs) and median costs with interquartile ranges (IQR) of healthcare utilisation were estimated by cost type (direct medical, direct non-medical) per informal settlement and healthcare location (within and outside the community). The incidence (%) of catastrophic expenditures was also estimated using the payer’s household budget. We converted the daily and weekly incomes into monthly income by multiplying them by 27 working days or four weeks. The number of working days a month (27) for daily income workers was established based on the reports from Women in Informal Employment Globalizing and Organizing (WIGO) and the International Labour Organization (ILO) 20–22 . We adopted 10% and 20% threshold levels to estimate catastrophic expenditures within and outside the communities across wealth quintiles and communities. Wealth quintiles were calculated according to the monthly income reported by respondents. Inequalities in healthcare expenditures were computed by determining concentration curves and indices for healthcare utilisation. The concentration curve displayed the share of healthcare costs by the cumulative population ranked in wealth quintiles. A concentration curve placed below the line of equity indicates higher costs amongst the wealthier (progressivity), whilst curves above the equity line indicate higher costs amongst the poorest (regressivity). The concentration indices were calculated to measure the magnitude of inequities in healthcare expenditures. The indices vary from -1 to 1, with negative values indicating healthcare expenditures concentrated amongst the poorest and positive values indicating expenditures concentrated amongst the wealthiest 23 . Data analysis was performed using Stata version 15. Frequency distributions and descriptive statistics were calculated. Chained multiple imputation (Royston, 2005) estimated missing cost data. Ten multiple imputed data sets with five iterations were generated and defined according to the percentage of missing data in healthcare utilisation 24 . ANOVA (Bonferroni) was applied to test differences in the proportions of categorical variables. The Wilcoxon rank-sum test compared costs between communities. Multiple logistic regression explored the association between catastrophic expenditures (10% and 20% thresholds) and socio-economic characteristics. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Ethics Ethical approval was obtained from the Sierra Leone Ethics and Scientific Review Committee (SLESRC: 026/04/2023) and the Liverpool School of Tropical Medicine Research Ethics Committee (21-007). Informed consent was obtained before each interview. Results Participants characteristics Among 4,871 households, 2,575 (53%) reported healthcare utilisation within and/or outside the informal settlement, the final sample of this study. Most respondents were women (n=1,761, 68%), aged 26-49 (n=1,787, 70%) and married (n= 1,655 64%). Most participants were long-term community residents (> six years, n=1,695, 66%). Most were engaged in income-generating activities (n= 1,976, 77%), mainly employed in the informal market (n=1,660, 64%). The overall median monthly income across the communities was about 1,080 New Leones (Le) (US$47.5), with Cockle Bay reporting the highest median income (Le1,250, US$55). The average number of people in a household was five, with Cockle Bay presenting the lowest average number of residents at 4.6. The main structure of the houses in Cockle Bay was corrugated iron houses (55%), whereas in Dwarzark and Moyiba, mud houses were more common (43% and 46%). More than half (58%) of households reported having food insecurity meaning that sometimes or often in the past month, they and their household members could not eat the food they preferred. In Dwarzark (41%), more participants reported facing food insecurity often (>10 times) than in Cockle Bay (15%) and Moyiba (29%) (Table 1). Healthcare utilisation characteristics Malaria was the most common illness reported by respondents for which healthcare was sought (73%), followed by cold/flu (55%). For all illnesses, households were more likely to use formal providers than informal providers, both public (56%) and private (46%). Within the communities, private formal healthcare services were most used in Cockle Bay (58%) and Dwarzark (52%), whereas in Moyiba (73%), most reported using public formal healthcare. Outside the community, public formal healthcare providers were used by the majority in all the settlements, averaging 61% across the research settings. The majority of people in Cockle Bay (71%) and 42% of those in Dwarzark travelled fewer than 30 minutes on average to reach healthcare within their community, while in Moyiba, the majority of people (52%) spent between 30 minutes to 1 hour to reach healthcare in the community. Residents took longer to reach healthcare outside the community, with 43% of people in Cockle Bay and Dwarzark spending between 30 minutes and 1 hour, while most Moyiba residents spent more than 1 hour to reach healthcare services (38%) (Table 2 and Figure 1A). Healthcare costs Results for healthcare costs within the community reveal Dwarzark and Moyiba as the communities with the highest costs. Dwarzark presented higher median direct medical costs (consultation fees plus medicines plus charges for investigations) than Moyiba (Le157, US$ 6.9 vs Le 120, US$5.3, p<0.001) and Cockle Bay (Le157, US$6.9 vs Le115, US$5.1, p<0.001) and higher median total costs (direct medical plus non-medical costs) than Cockle Bay (Le175 vs Le125, p<0.001). On the other hand, median direct non-medical costs (transportation costs and the cost of food during healthcare visits) were higher in Moyiba than in Cockle Bay (Le25, US$1.1 vs Le0, US$0, p<0.001) and Dwarzark (Le25, US$1.1 vs Le10, US$0.44, p<0.001). Looking at the healthcare costs outside the communities, median direct medical, non-medical, and total costs were similar for Cockle Bay and Dwarzark residents. However, Moyiba presented higher median direct non-medical costs than Dwarzark (Le40, US$1.8 vs Le35, US$1.5, p=0.029) and Cockle Bay (Le40, US$1.8 vs Le35, US$1.5, p<0.001). Comparing costs within versus outside the communities, informal dwellers incurred almost three times higher total direct costs when utilising healthcare outside the communities (Le582, US$25.6 vs Le203, US$8.9) (Table 3 and Figure 1B). Catastrophic expenditures The pooled incidence of catastrophic expenditures was 61% and 41% for healthcare within the communities, and 76% and 57% for healthcare outside the communities, at 10% and 20% thresholds, respectively. For healthcare within the communities, catastrophic expenditure incidence was similar between Moyiba and Dwarzark (10% threshold= 64% vs 66%, p=1; 20% threshold= 42% vs 45%, p=0.855). A higher proportion of households in both communities incurred higher catastrophic expenditures than in Cockle Bay at the 10% and 20% thresholds (all p<0.001). In the pooled sample, the incidence of catastrophic expenditures was 91 percentage points lower in the wealthiest households at a 10% threshold (WQ1=91%, WQ5=8%) and 89 percentage points lower at a 20% threshold (WQ1=81%, WQ5=2%). Regarding healthcare outside the communities, we found similar incidences of catastrophic expenditures at 10% and 20% thresholds across the communities. In the pooled sample, catastrophic expenditures incidence was also substantially lower in the wealthiest households at the 10% (WQ1= 94%, WQ5= 34%) and 20% thresholds (WQ1= 89%, WQ5= 12%). Compared to healthcare within the communities, the overall catastrophic expenditures in the pooled sample outside the communities was 25 percentage points higher at the 10% threshold (61% to 76%) and 39 percentage points higher at the 20% threshold (41% to 57%) (Table 4 and Figure 1A). For healthcare within the community, households whose respondents were +35 years old (10% threshold: OR=1.53 [95%CI: 1.17-2.01]; 20% threshold: OR=1.57 [95% CI: 1.19-2.05]) and lived in Dwarzark (10% threshold: OR= 2.34 [95%CI: 1.68-3.26]; 20% threshold: OR=1.63 [95% CI: 1.16-2.31]) or Moyiba (10% threshold: OR=2.48 [95%CI: 1.69-3.62]; 20% threshold: OR=1.45 [95%CI: 0.98-2.14]) were more likely to incur catastrophic expenditures. Also, attending informal health providers[1] had a protective effect (10% threshold: OR=0.34 [95%CI: 0.21-0.55]; 20% threshold: OR= 0.23 [95% CI: 0.13-0.45]). For healthcare outside the community, length of residence +4 years was associated with catastrophic expenditures (10% threshold: OR=1.48 [95%CI: 1.13-1.94]; 20% threshold: OR=1.65 [95% CI: 1.30-2.09]) (Table 5). Concentration curves and index Healthcare expenditure within and outside the communities was similar across all wealth quintiles, with the concentration indices not statistically significant in Cockle Bay, Moyiba and overall. In Dwarzark, the concentration curves and indices indicated a progressive pattern with expenditures concentrated amongst the wealthiest households within (concentration index: 0.0467, p<0.05) and outside the community (concentration index: 0.083, p<0.1) (Figure 2). Discussion Costs and catastrophic expenditures The overall incidence of catastrophic expenditures in our study was higher than in informal settlements in Kenya (10% threshold: 23%) 25 and post-conflict Sierra Leone as reported by a representative national survey (10% threshold: 32%) 7 . However, our figures were similar to a study on emergency surgery in informal settlements in Nigeria (10% threshold: 71%) 26 . The incidence across wealth quintiles was higher amongst the poorest in our study, which also differs from a scoping review that showed similar incidences across wealth quintiles in informal settlements in LMICs (10% threshold: ~19%) 9 . Divergencies in the literature may be related to the methods used to estimate catastrophic expenditures. Studies in informal settlements in Kenya, Pakistan, Bangladesh and Nigeria found significant disparities in the incidence of catastrophic expenditures when using different methodological approaches (e.g., expenditure or income approaches) 27 . Regarding healthcare utilisation within the communities, residents of Cockle Bay were less likely to incur catastrophic expenditures, possibly because they mainly rely on informal health services, which our study indicated as a protective factor. On the other hand, residents of Moyiba and Dwarzark and participants +35 years were more likely to incur catastrophic expenditures. Outside the communities, the longer length of residence was associated with catastrophic expenditures in both thresholds. This could be linked to prolonged exposure to the environmental and health hazards experienced by long-term residents 28 . Other studies found that longer residences in informal settlements and older age groups are linked to a higher risk of illness, which can lead to higher use of healthcare and higher risk of catastrophic expenditures for these social groups, as our study has highlighted 29,30 . According to our study, 61% of households (N=1,580) choose to use healthcare services outside their communities. This preference for external healthcare can be potentially attributed to the perceived higher quality of services provided outside the communities, as noted in a study of informal settlements in Kenya and Nigeria. Households are willing to endure higher costs and longer travel distances to access these facilities due to the perceived better quality 31 . The qualitative study conducted prior to this survey examined the exclusion experienced in healthcare systems within community health facilities. The findings from this study also explain preferences for seeking care outside of local communities. Households, particularly in Moyiba, reported experiencing discrimination based on factors such as poverty, disability, and chronic conditions. These factors are often more prevalent in local healthcare settings, leading patients and their families to seek care elsewhere 32 . Furthermore, the majority of individuals in our study work in the informal sector and often have long working hours, which makes it difficult for them to use healthcare facilities with limited opening hours within their communities 5 .The qualitative studies conducted during the exploratory phase in the same study sites also identified opening hours as a significant barrier to accessing healthcare in the communities, especially for pregnant women who lack medical assistance at night 32 . Also, only 9% of respondents in our survey reported that opening hours posed a challenge for accessing healthcare outside the communities 18 . Comparing costs across the communities, residents of Dwarzark incurred the highest direct medical and total direct costs, whereas Moyiba had the highest direct non-medical costs. Cockle Bay presented the lowest direct costs across the communities. These findings indicated different scenarios regarding healthcare availability, socioeconomic status, ability to pay for health services and service access. In Cockle Bay, the lack of formal healthcare led households to utilise cheaper informal services more frequently (49% in Cockle Bay vs 25% in Dwarzark vs 34% in Moyiba). Also, the community is more centrally located, facilitating access to healthcare outside the community. On the other hand, Dwarzark and Moyiba share similar geography, both hilly settlements, which makes accessing healthcare outside the community more challenging, particularly in Moyiba, as this community is not centrally located. Moyiba presented a higher percentage of households spending +1 hour to reach healthcare (69%) than other communities (Cockle Bay: 40%; Dwarzark: 44%), which explains the higher direct non-medical costs compared to other communities. Inequalities in healthcare access Our findings indicated that Dwarzark was the only community presenting a progressive pattern of healthcare expenditure. This might be because higher-income people seek better and more costly healthcare. Also, this community is more centrally located, facilitating access to various health services outside the community. On the other hand, the similar distribution of OOPE across wealth quantiles in Cockle Bay and Moyiba suggests that people with higher incomes have good social connections with healthcare providers, which could lower the costs, bringing them similar to the costs of the poorest. A qualitative study conducted in informal settlements in Freetown found that access to healthcare is heavily mediated by people's social positions and status, especially their ability to draw on support from social networks 16 . However, no investigation has explored if these social connections have the potential to reduce the costs of accessing healthcare. We suggest further studies examining this topic in the context of the urban poor. Another study using data from the Sierra Leone Integrated Household Survey (2018) also brings insights into the progressivity and regressivity of the health financing system in Sierra Leone. The study found that primary healthcare is pro-poor (progressive), but when OOPE health expenditures are included in the analysis, the overall health financing in Sierra Leone becomes regressive due to the regressivity of OOPE 33 . More studies should explore inequalities in healthcare across urban informal settlements in Freetown to better understand the main drivers of these inequalities. The levels of regressivity and progressivity in healthcare spending are important factors in achieving universal health coverage. In Sierra Leone, the main sources of health financing are government general revenues, donor funding, and OOPE. However, in 2020, the government's contributions from these sources combined only accounted for 15%, while OOPE makes up a significant portion of health financing in the country, at around 55% 34 . Depending heavily OOPE can lead to greater disparities in healthcare spending, worsening the health outcomes for the most vulnerable individuals living in informal settlements. Implications of this study and policies to mitigate the economic burden This is the first study focusing on the economic burden of healthcare utilisation on urban informal settlements in Freetown. It provides reference material for decision-making policies to address healthcare challenges informal settlement dwellers are grappling with, particularly regarding the affordability of high-quality services within and outside the communities. We found that utilising informal healthcare providers can reduce the likelihood of incurring catastrophic expenditures, which indicates the significant role they play in communities, not only in delivering care in challenging situations where formal healthcare is limited but also in terms of affordability. However, unregulated healthcare providers can also threaten citizens' health security due to the poor quality of their services 35 . This highlights the need to explore ways to incorporate informal providers into the formal healthcare system to enhance the quality of care and make healthcare more accessible for vulnerable populations living in informal settlements. Stakeholders in Nigeria have seen the connections between informal and formal healthcare sectors in informal settlements as a positive step, arguing that it could enhance service delivery. The study suggested that collaboration with the informal sector can be achieved through regulatory and financial measures, improvement of clinical guidelines, and engagement with the communities 36 . Another study in Sierra Leone demonstrated that regulating the informal sector could help manage non-communicable diseases. Community health workers suggested collaboration with traditional healers to identify and refer hypertensive patients 37 . Despite these positive findings, evidence also indicates the challenges and risks of integrating informal providers into the formal health system. In India, a study on integrating informal providers into the National Tuberculosis (TB) Programme raised concerns about the low quality of the services provided and the lack of appropriate knowledge to treat TB. The study suggests that the formal health system must closely monitor informal practitioners to ensure they implement government guidelines to treat TB 38 . In China, seeking treatment from informal providers often resulted in missed or delayed diagnoses, which could have serious clinical consequences. The study also highlighted that these informal providers might spread misleading information or even cause adverse medical events, such as side effects or harmful treatment interactions 39 . A Consensus Study Report indicates that while it is challenging to create generalised recommendations for improving the quality of informal healthcare providers, addressing critical issues—such as enhancing their knowledge and practices—must be a top priority 40 . Additionally, a study conducted in Nigeria focused on advancing Universal Health Coverage by connecting formal and informal health providers. It recommended a comprehensive implementation strategy that includes adequate resources, active community participation, flexibility from policymakers, ongoing evaluation and feedback mechanisms, and a commitment to long-term sustainability and adaptability to evolving healthcare needs and community dynamics 41 . Another reflection is on the progressivity and regressivity in healthcare expenditures. Although a progressive expenditure can indicate fairness in health system financing as higher-income groups bear a proportionally larger share of costs relative to their income, it can also suggest a paradox. In several LMICs, the poorest contribute less to the health system in terms of OOPE because they cannot afford high-quality and more expensive healthcare. Thus, their payment for healthcare is reduced, resulting in a progressive health system. In this scenario, better-off households use expensive and usually better quality health services than the poorest, also leading to a progressive OOPE pattern in the health financing system when considering OOPE 27,42 . On the other hand, our study found that the poorest wealth quintiles experience a higher proportion of catastrophic expenditures compared to wealthier groups, even when accessing cheaper services, such as those provided by informal health providers. Given this limitation, we must investigate whether progressivity in Dwarzark is driven by the concentration of OOPE amongst the better-off or the lack of ability to pay for better-quality health services amongst the poorest. A final thought is about the affordability of high-quality services. Our survey explored poor healthcare quality and high costs as barriers to access to health services. The final survey report brings a more detailed analysis of this indicator, but in summary, participants reported that the quality of care is better in services outside the communities than within, and this is the reason respondents with sustainable and higher income-generating activities sought healthcare providers outside the community 18 . This reinforces the importance of investing in good quality and affordable health services within communities to reduce household costs of seeking care and treatment for their health conditions. Strengths and limitations This study team worked closely with the communities through community-based participatory research. This approach established bottom-up perspectives on the boundaries of the settlements and determined the key variables for the questionnaire. The survey findings were validated during two events: the City Learning Platform event in March 2024 and a Validation Workshop in May 20204. The City Learning event was attended by 51 participants, including community chiefs, health workers, representatives from community learning platforms, researchers, co-researchers, personnel from the Ministry of Health, members of the Freetown City Council, non-governmental organisations, and external consortium partners 43 . The Validation Workshop had 70 attendees from the study sites, including community chiefs, youth leaders, community mobilisers who participated in the survey, survey respondents, health workers, co-researchers, and researchers 44 . These events aimed to gather feedback from community residents and other stakeholders on the survey findings and incorporate their insights into the survey report. Participants reflected on the accuracy of the findings and concluded that they accurately represent the local situation and can be utilised by the government and other organisations to explore ways to enhance service provision for the community. Our study also has some limitations. Local community mobilisers and co-researchers were essential for improving the accuracy of the survey responses. However, some of these mobilisers had limited educational backgrounds and digital skills. As a result, we needed to recruit additional community members who had not participated in the earlier phases of the study, such as the qualitative research, to assist with data collection. The research team in Sierra Leone also provided more training sessions and content on the study context for those new to the study. We estimated catastrophic expenditures based on the payer’s household budget. In a country with a strong informal economy like Sierra Leone, this approach could overestimate the incidence of catastrophic costs. However, the income of informal settlement dwellers in Sierra Leone reported in this study is aligned with the figures provided by The World Salaries 45 . So, our approach may not have affected our estimates. Still, our analysis relied on self-reported health data, which can be subject to reporting bias, particularly regarding costing data. To minimise bias, a short time horizon to report costs and trained co-researchers residents in the studied communities monitored the data collection. This approach facilitated household engagement and trust. Given the lack of a sampling frame, multi-stage cluster sampling was unfeasible. However, to improve the generalisability of the obtained results, we used a design effect of 10 and established landmarks in the community, which led to an increase in sampled households. Therefore, the sample was large enough to allow generalisability as if the sampled households were obtained using probability sampling. Finally, a short timeframe may also risk minimising the costs associated with lengthy pathways to care. Conclusion Our study revealed a significant and unequal economic impact of healthcare utilisation, with residents of Moyiba and Dwarzark, respondents aged +35 and living in the communities longer than 4 years facing a higher risk of catastrophic expenses. The regulation of informal health providers and their integration into the formal health system should be tested, as they were found to protect against catastrophic expenses. Addressing the economic implications of healthcare utilisation, improving access to quality and affordable healthcare within the communities, and promoting an equitable health system should be the primary focus of Sierra Leone's health financing strategy. Box 1. Characteristics of the study sites Cockle Bay It lies along the western coast of Freetown. Established in the 1940s, it is home to over 20,000 people. The community lacks public or private formal health facilities, prompting residents to travel about 2-5 kilometres to seek care in facilities outside the community 46 . Moyiba Situated in a hill area on the eastern side, 5 km from the Central Business District (CBD), with an estimated population of 37,000. There is one formal health facility, but medical personnel are not always available. Private facilities and informal services such as pharmacies and nurses provide home care. Dwarzark Situated in the central area of Freetown, also in a hilly area, with an estimated population of 21,120. There is one formal health facility, but no medical personnel is available. Private facilities and informal services such as pharmacies and nurses provide home care. Box 2. Survey tool Themes Insights Summary of the main findings Service delivery This section examines several aspects of service delivery, including water sources, accessibility, sanitation facilities, waste management, and associated challenges. It also analyses drinking water sources, such as sachet water and community wells, domestic water usage patterns, and distances to water points. Most respondents rely on sachet water and community wells for drinking water. The sanitation system is poor across the three communities: flush toilets are mainly in Cockle Bay, while Moyiba and Dwarzark primarily use pit latrines. Healthcare landscape This section examines healthcare access and utilisation patterns, and challenges in accessing healthcare services across the three communities, such as distance, cost, and quality of care. Barriers like distance, cost, and quality of care are significant for healthcare services, and community responses vary across different areas. Risks This section examines common disasters that affected respondents, such as flooding, fire, building collapse, and falling boulders. Natural disasters like flooding, fires, and building collapses have affected respondents. Safety This section examines the occurrence of theft/robbery, physical violence, road accidents, evictions, and sexual and gender-based violence. Respondents reported common issues such as theft, physical violence, road accidents, evictions, and sexual and gender-based violence, primarily impacting vulnerable and marginalised groups. Perception of health and well-being, challenges and barriers This section examines the factors determining physical well-being among the community residents, such as good health, a clean and safe environment, financial stability, safety/security, and a support network. In Cockle Bay and Moyiba, physical well-being is influenced by good health and a clean, safe environment. In contrast, Dwazack has different factors. However, both Cockle Bay and Dwazarck prioritise social and mental well-being through financial stability, safety, and support networks. Source: Health and wellbeing survey of informal settlements in Freetown, Sierra Leone, May 2023. Declarations Acknowledgement The GCRF Accountability for Informal Urban Equity Hub (‘ARISE’) is a UKRI Collective Fund award with award reference (ES/S00811X/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data sharing The data used in this study include sensitive category household-level data. To prevent disclosure these data are not publicly available but are available for research purposes through successful application to data holders (Liverpool School of Tropical Medicine, College of Medicine and Allied Health Sciences (COMAHS) - University of Sierra Leone, Sierra Leone Urban Research Centre (SLURC), and Centre of Dialogue on Human Settlement and Poverty Alleviation (CODOHSAPA)-Sierra Leone). Author contributions NTSF, IG and HE conceived the idea for the study. IG and NTSF drafted the analysis plan. S Saidu, IJS, IG, S Sesay, AC, BK, NTSF, EK, RL, BM, LW, MN and NWG contributed to the survey planning and implementation. NTSF, SF and DV conducted data analysis. SF, DV, SM, BK and NTSF drafted the original manuscript. All authors contributed to the critical revision and approved the final manuscript. References Nijman J, Wei YD. Urban inequalities in the 21st century economy. Applied Geography. 2020;117(February):102188. 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Characteristics Cockle Bay N= 734 Dwarzark N=848 Moyiba N=993 All N=2,575 Gender, N (%) Female 514 (70) 624 (74) 623 (63) 1,761 (68) Age, N (%) 18-25 116 (16) 128 (15) 181 (18) 425 (16) 26-35 292 (40) 318 (37) 361 (36) 971 (38) 36-49 240 (33) 261 (31) 315 (32) 816 (32) 50 + 86 (12) 141 (16) 136 (14) 363(14) Marital status, N (%) Single 202 (27) 191 (22) 200 (20) 593 (23) Married, co-habiting, engaged 461 (63) 252 (62) 669 (67) 1,655 (64) Separated, divorced 27 (4) 49 (6) 35 (3) 111 (4) Widowed 44 (6) 83 (10) 89 (9) 216 (8) Length of residence, N (%) Less than 1 year 58 (8) 65 (7) 56 (6) 179 (7) 1-5 years 244 (33) 178 (21) 279 (28) 701 (27) 6-10 years 154 (21) 138 (16) 213 (21) 505 (20) Over 10 years 278 (38) 467 (55) 445 (45) 1,190 (46) Level of Education, N (%) * No education 213 (29) 221 (26) 348 (35) 782 (30) Primary 63 (9) 89 (10) 76 (8) 228 (9) Secondary 344 (47) 384 (45) 438 (44) 1,166 (45) Tertiary 65 (9) 102 (12) 71 (7) 238 (9) Quranic education 27 (4) 8 (1) 33(3) 68 (3) Technical/vocational 17 (2) 44 (5) 26 (3) 87 (3) Income activity type, N (%) Informal occupation 475 (65) 504 (59) 681 (69) 1,660 (64) Formal occupation 91 (12) 116 (14) 90 (9) 297 (12) Formal and informal occupation 7 (1) 9 (1) 3 (0.3) 19 (1) Unemployed 161 (22) 219 (26) 219 (22) 599 (23) Frequency of Income, N (%) Daily 461 (63) 500 (59) 710 (72) 1,671 (65) Weekly 63 (9) 123 (15) 91 (9) 277 (11) Monthly 173 (24) 186 (22) 97 (10) 456 (18) No income 37 (5) 39 (5) 95 (10) 171 (7) Median monthly income, Le (IQR) Overall ** 1,350 (800-2,700) 1,000 (540-1,890) 1,200 (600-2,160) 1,080 (600-2,160) Wealth quintiles, N (%) 1 (poorest) 113 (16) 210 (26) 249 (28) 572 (24) 2 121 (17) 126 (16) 205 (23) 452 (19) 3 118 (17) 109 (14) 180 (20) 407 (17) 4 150 (22) 160 (20) 156 (17) 466 (19) 5 (wealthier) 193 (28) 200 (25) 107 (12) 500 (21) Tenure status, N (%) Tenant 484 (66) 495 (58) 540 (54) 1,519 (59) Landlord 187 (25) 245 (29) 317 (32) 752 (29) Free-living 1 40 (5) 89 (10) 116 (12) 245 (10) Others 2 23 (3) 19 (2) 20 (2) 59 (2) Average (95%CI) number of people in the household 4.6 (4.5-4.8) 5.4 (5.3-5.7) 5.6 (5.5-5.8) 5.3 (5.2-5.4) House structure, N (%) Pan Body/Corrugated Iron Houses 438 (59) 216 (25) 69 (7) 723 (28) Concrete 263 (36) 248 (29) 409 (41) 920 (36) Mudhouse 21 (3) 379 (45) 484 (49) 884 (34) Others 3 12 (2) 5 (1) 31 (3) 48 (2) Food insecurity, N (%) No 205 (28) 118 (14) 158 (16) 481 (19) Rarely (once or twice) 154 (21) 139 (16) 292 (29) 585 (23) Sometimes (3-10 times) 264 (36) 246 (29) 250 (25) 760 (29) Often (> 10 times) 111 (15) 345 (41) 293 (29) 749 (29) * Missing data: Cokle Bay=5; Moyiba=34; ** Cokle Bay=20; Dwarzark=25, Moyiba=83. 1 People who neither pay rent nor own the house 2 Caretaker, lease, temporal 3 Wooden, mixed (e.g., concrete and PanBody) Table 2. Characteristics of healthcare utilisation within and outside the informal settlements. Sierra Leone, Freetown, 2023. Variables Within the community Outside the community All (within and/or outside) N=2,575 Cockle Bay N=287 Dwarzark N=658 Moyiba N=530 Total N=1,475 Cockle Bay N= 641 Dwarzark N= 369 Moyiba N= 568 Total N=1,580 Type of illness , N (%) 1 Malaria 212 (74) 428 (65) 375 (71) 1,015 (69) 509 (79) 193 (52) 408 (71) 1,110 (70) 1,887 (73) Cold, flu 167 (58) 283 (43) 291 (55) 741 (50) 399 (62) 121 (33) 313 (55) 833 (53) 1,414 (55) Typhoid 75 (26) 179 (27) 199 (38) 453 (31) 298 (46) 101 (27) 239 (42) 638 (40) 997 (39) High blood pressure 12 (4) 58 (9) 61 (12) 131 (9) 58 (9) 41 (11) 96 (17) 195 (12) 295 (11) Routine check-ups 9 (3) 17 (3) 48 (9) 74 (5) 51 (8) 26 (7) 76 (13) 153 (10) 217 (8) Injury 6 (2) 32 (5) 29 (5) 67 (4) 15 (2) 25 (3) 70 (7) 110 (4) 161 (6) Ulcer 19 (6) 34 (5) 22 (4) 75 (5) 40 (6) 24 (7) 78 (14) 142 (9) 193 (7) Skin rash 9 (3) 34 (5) 27 (5) 70 (5) 18 (3) 9 (2) 37 (6) 64 (4) 125 (5) Cholera, diarrhoea 7 (2) 22 (3) 27 (5) 56 (4) 18 (3) 9 (2) 32 (6) 59 (4) 114 (4) Type of healthcare used , N (%) 2 Public Formal NA 191 (29) 386 (73) 589 (40) 359 (56) 245 (66) 367 (64) 971 (61) 1,432 (56) Private Formal NA 340 (52) 55 (12) 574 (39) 303 (47) 122 (33) 276 (48) 701 (44) 1,181 (46) Drug Peddlers 91 (32) 49 (7) 93(17) 233 (16) 23 (4) 2 (1) 66 (12) 91 (6) 311 (12) Private Nurse 44 (15) 113 (17) 81 (15) 238 (16) 11 (2) 7 (2) 43 (8) 61 (4) 295 (11) Traditional healers 6 (2) 8 (1) 12 (2) 26 (2) 5 (1) 7 (2) 23 (4) 35 (2) 59 (2) Average time to reach healthcare , N (%) Less than 30 minutes 203 (71) 273 (42) 183 (35) 659 (45) 74 (12) 30 (8) 31 (5) 135 (9) NA Between 30min -1 hour 69 (24) 225 (35) 274 (52) 568 (39) 277 (43) 158 (43) 141 (25) 576 (37) NA 1-2hours 8 (3) 97 (15) 50 (9) 155 (11) 150 (23) 81 (22) 218 (38) 449 (28) NA Over 2 hours 4 (1) 37 (6) 17 (3) 58 (4) 111 (17) 82 (22) 176 (31) 369 (23) NA Do not know 1 (0.3) 19 (3) 3 (1) 23 (2) 27 (4) 16 (4) 1 (0.2) 44 (3) NA 1 Multiple choice question. Tuberculosis, convulsion and diabetes were reported by ≤ 3% of the participants; 2 Multiple choice question. 180 missing data in Cockle Bay, within the community. NA= not applicable Table 3. Average cost (Leone, Le [95% CI]) of healthcare utilisation within and outside the informal settlements. Sierra Leone, Freetown, 2023. Within the community Cockle Bay N=287 Dwarzark N=658 Moyiba N=530 Total N=1,475 Average (CI) Median (IQR) Average (CI) Median (IQR) Average (CI) Median (IQR) Average (CI) Median (IQR) Direct medical costs 154 (136-171) 115 (50-200) 200 (185-214) 157 (90-250) 173 (158-187) 120 (80-205) 181 (172-190 140 (80-227) Direct non-medical costs 10 (8-13) 0 (0-10) 16 (15-18) 10 (0-21) 35 (32-37) 25 (12-50) 22 (20-23) 13 (0-30) Total direct costs 164 (145-183) 125 (60-200) 216 (101-231) 175 (100-266) 207 (192-223) 162 (103-240) 203 (192-212) 160 (93-255) Outside the community Cockle Bay N= 641 Dwarzack N= 369 Moyiba N=568 Total N=1580 Average (CI) Median (IQR) Average (CI) Median (IQR) Average (CI) Median (IQR) Average (CI) Median (IQR) Direct medical costs 437 (385-488) 290 (190-450) 623 (517-728) 320 (150-320) 563 (316-810) 253 (159-430) 526 (431-620) 280 (160-500) Direct non-medical costs 48 (43-53) 35 (20-50) 54 (47-62) 35 (20-55) 68 (60-76) 40 (25-70) 57 (53-61) 35 (22-60) Total direct costs 485 (430-539) 323 (220-510) 677 (571-784) 362 (178-735) 631 (384-878) 300 (186-515) 582 (487-678) 320 (198-550) 1SLE=0.044 USD P-values, Wilcoxon rank-sum test, within the community Communities Cockle Bay (a) Dwarzark (b) Medical Non-medical Total Medical Non-medical Total Dwarzack (b) <0.001 0.003 <0.001 Moyiba (c) 0.041 <0.001 <0.001 <0.001 <0.001 0.291 P-values, Wilcoxon rank-sum test, outside the community Communities Cockle Bay Dwarzack Medical Non-medical Total Medical Non-medical Total Dwarzack 0.205 0.829 0.145 Moyiba 0.039 <0.001 0.300 <0.001 0.029 0.048 Table 4. Incidence of catastrophic expenditures with 10% and 20% thresholds by wealth quintile within and outside the informal settlements. Sierra Leone, Freetown, 2023. W ithin the community Cockle Bay N= 283 % (95%CI) Dwarzark N= 636 % (95%CI) Moyiba N= 483 % (95%CI) Pooled N= 1,402 % (95%CI) 10% 20% 10% 20% 10% 20% 10% 20% WQ 1 84 (73-92) 73 (60-83) 90 (85-94) 82 (76-87) 95 (91-98) 85 (78-90) 91 (88-94) 81 (77-85) WQ 2 58 (42-73) 39 (25-56) 87 (78-92) 63 (53-72) 90 (81-96) 66 (54-78) 82 (76-87) 59 (77-85) WQ 3 45 (32-57) 21 (12-33) 71 (62-78) 32 (24-41) 71 (62-80) 28 (20-38) 65 (60-71) 28 (23-34) WQ 4 17 (8-29) 7 (2-17) 45 (34-54) 11 (5-18) 33 (24-43) 8 (3-15) 34 (28-40) 8 (5-13) WQ 5 5 (1-15) 2 (0-9) 10 (5-19) 3 (1-9) 7 (2-16) 1 (0-7) 8 (5-12) 2 (1-5) Overall* 42 (36-48) 29 (24-35) 66 (63-70) 45 (42-49) 64 (60-69) 42 (38-47) 61 (58-64) 41 (38-44) Outside the community Cockle Bay N= 625 % (95%CI) Dwarzack N= 362 % (95%CI) Moyiba N= 519 % (95%CI ) Pooled N= 1,506 % (95%CI) 10% 20% 10% 20% 10% 20% 10% 20% WQ 1 96 (90-99) 95 (89-98) 89 (82-94) 83 (74-89) 97 (91-99) 90 (82-95) 94 (90-96) 89 (85-92) WQ 2 90 (85-94) 81 (74-86) 84 (73-91) 79 (68-87) 95 (89-98) 78 (68-85) 90 (87-93) 79 (75-84) WQ 3 88 (81-94) 65 (55-74) 87 (75-95) 60 (46-73) 89 (82-94) 61 (52-70) 89 (84-92) 63 (57-69 WQ 4 68 (59-76) 30 (22-39) 82 (71-90) 54 (42-66) 67 (58-75) 31 (23-40) 70 (65-75) 36 (30-41) WQ 5 28 (21-37) 9 (5-16) 44 (31-59) 17 (8-29) 35 (24-46) 12 (5-21) 34 (28-40) 12 (8-16) Overall* 73 (70-77) 55 (52-60) 79 (75-83) 63 (58-68) 79 (75-82) 56 (51-60) 76 (74-79) 57 (55-60) WQ=wealth quintile *P-values, ANOVA Bonferroni, Overall Community Cockle Bay Dwarzark Within, 10% Within, 20% Outside, 10% Outside, 20% Within, 10% Within, 20% Outside, 10% Outside, 20% Dwarzark <0.001 <0.001 0.1 0.069 Moyiba <0.001 <0.001 0.182 1 1 0.855 1 0.076 Table 5. Association between catastrophic expenditures (10% and 20% thresholds) and socio-economic characteristics within and outside the communities. Sierra Leone, Freetown, 2023. Variables Within the community Outside the community 10% Threshold 20% Threshold 10% Threshold 20% Threshold Crude OR (95% CI) Adjusted OR (95% CI) Crude OR (95% CI) Adjusted OR (95% CI) Crude OR (95% CI) Adjusted OR (95% CI) Crude OR (95% CI) Adjusted OR (95% CI) Age 18-35 1 1 1 1 1 1 1 1 >35 1.59 (1.28-1.97)**** 1.53 (1.17-2.01)*** 1.51 (1.22-1.87)**** 1.57 (1.19-2.05)**** 1.47 (1.14-1.87)*** 1.39 (1.03-1.87)** 1.12 (0.91-1.38) 1.08 (0.85-1.39) Marital status Single 1 1 1 1 1 1 1 1 Married, co-habiting, engaged 1.02 (0.78-1.32) 0.89 (0.65-1.21) 0.87 (0.67-1.13) 0.76 (0.57-1.03)* 0.92 (0.68-1.23) 0.86 (0.61-1.89) 0.80 (0.62-1.02)* 0.83 (0.63-1.10) Divorced, separated 2.35 (1.24.45)*** 1.70 (0.84-3.40) 1.26 (0.72-2.18) 0.96 (0.52-1.80) 0.99 (0.53-1.86) 1.00 (0.50-2.02) 0.88 (0.51-1.50) 1.03 (0.57-1.86) Widowed 1.90 (1.21-3.01)*** 1.38 (0.78-2.42) 1.71 (1.13-2.62)** 1.38 (0.82-2.31) 1.20 (0.70-2.06) 0.97 (0.52-1.82) 1.00 (0.64-1.57) 1.04 (0.62-1.75) Education Secondary 1 1 1 1 1 1 1 1 No education or primary 1.03 (0.83-1.31) 0.97 (0.70-1.19) 0.87 (0.69-1.09) 0.73 (0.56-0.96)** 1.06 (0.82-1.37) 0.85 (0.63-1.14) 0.87 (0.70-1.08) 0.73 (0.57-0.94)** Tertiary or technical 1.11 (0.79-1.55) 1.03 (0.69-1.46) 0.97 (0.69-1.35) 0.79 (0.55-1.14) 1.81 (1.18-2.78)*** 1.57 (0.99-2.48)* 1.36 (0.98-1.90)* 1.16 (0.81-1.66) Community Cockle Bay 1 1 1 1 1 1 1 1 Dwarzack 2.75 (2.07-3.67)**** 2.34 (1.68-3.26)**** 2.05 (1.51-2.77)**** 1.63 (1.16-2.31)*** 1.40 (1.02-1.90)*** 1.24 (0.88-1.76) 1.37 (1.04-1.78)** 1.22 (0.90-1.63) Moyiba 2.46 (1.82-3.31)**** 2.48 (1.69-3.62)**** 1.81 (1.32-2.47)**** 1.45 (0.98-2.14)* 1.29 (0.98-1.71)* 1.15 (0.84-1.60) 0.99 (0.79-1.26) 0.94 (0.72-1.23) Length of residence in the community 4 years 1.42 (1.13-1.79)*** 1.12 (0.85-1.46) 1.29 (1.02-1.63)** 1.08 (0.83-1.40) 1.59 (1.24-2.03)**** 1.48 (1.13-1.94)*** 1.63 (1.32-2.02)**** 1.65 (1.30-2.09)**** Number of people in the households 5 people 1.2 (0.96-1.50) 0.95 (0.73-1.22) 1.16 (0.93-1.43) 0.92 (0.72-1.18) 1.16 (0.90-1.49) 1.08 (0.81-1.44) 1.30 (1.04-1.61)** 1.30 (1.02-1.65)** House structure Concrete 1 1 1 1 1 1 1 1 Pan Body, mudhouse, woodhouse 1.09 (0.87-1.37) 1.15 (0.90-1.49) 0.91 (0.73-1.14) 0.95(0.74-1.22) 0.99 (0.77-1.28) 1.08 (0.82-1.44) 0.99 (0.80-1.22) 1.04 (0.82-1.32) Food insecurity No/rarely/sometimes 1 1 1 1 1 1 1 1 Often 1.42 (1.12-1.81)*** 1.31 (0.99-1.73)* 1.24 (0.98-1.56)* 1.22 (0.94-1.59) 1.47 (1.11-1.94)*** 1.29 (0.94-1.78) 1.05 (0.84-1.31) 0.97 (0.75-1.25) Healthcare provider Only public formal 1 1 1 1 1 1 1 1 Only private formal 1.04 (0.80-1.36) 1.32 (0.95-1.83)* 0.85 (0.66-1.11) 0.88 (0.63-1.20) 1.27 (0.97-1.68)* 1.31 (0.99-1.74)* 1.18 (0.94-1.49) 1.21 (0.95-1.53) Only informal (traditional healers, drug paddlers) 0.26 (0.17-0.41)**** 0.34 (0.21-0.55)**** 0.21 (0.12-0.36)**** 0.23 (0.13-0.45)**** 0.79 (0.30-2.06) 0.81 (0.30-2.19) 0.97 (0.40-2.37) 1.08 (0.43-2.68) Only private nurses 1.23 (0.82-1.85) 1.46 (0.94-2.26)* 0.84 (0.57-1.23) 0.86 (0.57-1.30) 0.81 (0.28-2.34) 0.91 (0.31-2.67) 0.89 (0.34-2.34) 0.92 (0.34-2.46) Formal and informal 1.10 (0.73-1.67) 1.40 (0.90-2.16) 0.91 (0.61-1.35) 1.01 (0.66-1.51) 1.81 (1.05-3.13)** 1.79 (1.00-3.20)* 1.16 (0.76-1.74) 1.25 (0.81-1.94) * P<0.1, **P<0.05, ***P<0.01, ****P<0.001 Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2025 Read the published version in Journal of Urban Health → Version 1 posted Editorial decision: Accept as is 18 Dec, 2024 Editor assigned by journal 17 Dec, 2024 First submitted to journal 16 Dec, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Settlement profile: Access to health services and economic burden within and outside the communities. The Y axis shows the frequency in terms of the percentage of each indicator, the X axis shows the incidence of catastrophic expenditures (CE) at 10% and 20% thresholds, the type of health services most frequently accessed and the average time to reach the health service.\u003c/p\u003e\n\u003cp\u003eB. Settlement profile: Total average costs (Leone, Le) within and outside the communities. The Y axis shows the costs.\u003c/p\u003e","description":"","filename":"1a.png","url":"https://assets-eu.researchsquare.com/files/rs-5131613/v1/369d094679dd416f948d0c3a.png"},{"id":71939115,"identity":"d86c5856-236f-4dab-b7e1-a743723a8363","added_by":"auto","created_at":"2024-12-20 01:02:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":559976,"visible":true,"origin":"","legend":"\u003cp\u003eInequalities in healthcare utilisation within and outside the community\u003c/p\u003e\n\u003cp\u003e* P\u0026lt;0.1, **P\u0026lt;0.05, ***P\u0026lt;0.01, ****P\u0026lt;0.001\u003c/p\u003e","description":"","filename":"2a.png","url":"https://assets-eu.researchsquare.com/files/rs-5131613/v1/98e0b4d78a1fae3b26711d18.png"},{"id":78689411,"identity":"f6dc380a-6349-438f-b835-711499be91c7","added_by":"auto","created_at":"2025-03-17 16:12:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2865682,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5131613/v1/5dc56e2c-4ce8-4395-bb4f-1e24b038bc86.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe Economic Burden of Healthcare Utilisation: Findings from a Health and Well-being Survey in Informal Settlements of Freetown, Sierra Leone\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe rapid urbanisation has been coupled with the worsening of income inequalities, as the gap between rich and poor is widening consistently across cities in low- and middle-income countries (LMICs)\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Within these urban areas in LMICs, many people reside in informal settlements characterised by inadequate housing, insecurity, overcrowding and limited access to basic social amenities and services\u003csup\u003e2\u003c/sup\u003e. In West Africa, Sierra Leone has experienced significant urban population growth. The percentage of the national population residing in urban areas has increased from 21% in 1976 to \u0026nbsp;43% in 2021, with more than half of these city dwellers (60%) living in informal\u0026nbsp;settlements\u003csup\u003e3\u003c/sup\u003e. Like most cities in LMICs, Freetown lacks coordinated development for healthy urbanisation with insufficient planning and implementation of environmental, housing and transport policies\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn addition to the complexities of demographics, urbanisation can be seen as a determinant of health, leading to widening health and well-being inequalities\u003csup\u003e5\u003c/sup\u003e. In an analysis of urban health systems in Ghana, Nigeria, Bangladesh and Nepal, Elsey and colleagues reflected on the fragile health system in these countries and how it can present significant challenges to effective health-seeking behaviour. In this scenario, limited access to quality public services and reliance on the private or informal sector could result in high healthcare costs and catastrophic expenditures for vulnerable urban dwellers\u003csup\u003e5\u003c/sup\u003e. In Sierra Leone, the recently implemented National Emergency Medical Service, aiming to provide a free-of-charge and good quality prehospital service, has improved healthcare access, however, the positive impact has been observed mainly in rural areas\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDespite the significant challenges of providing healthcare in the context of rapid urbanisation in LMICs, there needs to be more evidence to support policy and planning to address these challenges, particularly on the extent and nature of healthcare expenditure in informal settlements. In the context of Sierra Leone, the current evidence focuses on the financial burden of surgical care in Freetown and the changes in catastrophic costs in the pre and post-conflict period\u0026nbsp;between 2003 and 2011, a national-level analysis\u003csup\u003e7,8\u003c/sup\u003e. A recent scoping review on the economics of healthcare access for urban informal settlement dwellers in LMICs found a high incidence of catastrophic expenditures (~19%) across wealth quintiles; however, no evidence from Sierra Leone was found\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTo address the gap in evidence on healthcare costs to informal settlement dwellers, this study aims to assess the economic burden and inequalities in healthcare utilisation in three informal settlements in Freetown, Sierra Leone.\u0026nbsp;\u003c/p\u003e"},{"header":"Methodology ","content":"\u003ch2\u003eStudy setting\u003c/h2\u003e\n\u003cp\u003eSierra Leone is a low-income country in West Africa with a Gross Domestic Product (GDP) per capita of $1,931 in 2022\u003csup\u003e10\u003c/sup\u003eAccording to the latest estimate from the World Bank, 26% of the country\u0026apos;s population lived below the poverty line (defined as $2.15 a day in terms of purchasing power parity) in 2018\u003csup\u003e11\u003c/sup\u003e. In Freetown, the capital city, estimates indicate that average monthly expenses for an individual range from US$185 to US$500\u003csup\u003e12\u003c/sup\u003e. However, these figures vary significantly across different areas of the city, depending on location, lifestyle, and personal needs. In addition, in 2015, 35% of Freetown\u0026apos;s population was living below the multidimensional poverty line. Only 22% of residents have access to improved private sanitation facilities, and 3% of urban households have access to piped indoor drinking water. Additionally, 39% of households rely on public taps, and only 40% of the city\u0026rsquo;s waste is collected\u003csup\u003e13\u003c/sup\u003e. The community profiling and enumeration research in Freetown indicated the existence of 68 informal settlements,\u0026nbsp;36% of all settlements in the city, and high population density in these settings, which increased from 1,360 people per square kilometre in 2004 to 2,154 in 2015. The study also noted that the population growth occurred mainly in settlements on the coast and hillsides where residents are exposed to water and sanitation-related diseases, coastal floods,\u0026nbsp;fire and landslides\u003csup\u003e14\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe health and well-being survey reported in this article\u0026nbsp; occurred in three urban informal settlements in Freetown: Cockle Bay, Moyiba and Dwarzark. Box 1 shows the main characteristics of the study sites.\u003c/p\u003e\n\u003ch2\u003eStudy design and data collection procedures\u003c/h2\u003e\n\u003cp\u003eThe content and design of this study drew on findings from qualitative studies conducted\u0026nbsp;in the same informal settlements investigating\u0026nbsp;the community members\u0026rsquo; perspectives on health and well-being. During the qualitative study, community residents in the study areas revealed the vulnerability to health risks such as the poor WASH facilities, lack of health centres in Cockle Bay and the underserved peripheral health units in \u0026nbsp;Dwarzark and Moyiba, precarious livelihoods, exposure to disasters, high costs to access healthcare and lack of safety compounded the health risks and wellbeing of residents\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e15\u0026ndash;17\u003c/span\u003e\u003c/sup\u003e. Having understood the intersection of health risks in these settlements, we wanted to quantify the qualitative findings, which informed the development of survey tools to ascertain a wider perspective of the issues that emerged from the qualitative study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional survey from April to May 2023 to investigate service delivery, healthcare utilisation, environmental risks, and well-being priorities in those informal settlements. The survey questions were developed based on the priorities identified during the qualitative research across the study sites. These were access and barriers to services (water, sanitation, and healthcare), environmental health risks/vulnerabilities (disasters, safety and security, livelihoods), and well-being priorities. We collected data on household income, out-of-pocket expenditure (OOPE, direct medical costs: medicines, consultation fees and tests; direct non-medical costs: transport and food) to utilise healthcare within and outside the informal settlements\u0026apos; boundaries, and the type of healthcare utilised. \u0026nbsp;The survey sections are indicated in Box 2. All findings have been published in the Survey report\u003csup\u003e18\u003c/sup\u003e. The RedCap tool was applied to collect data online and offline.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survey team was recruited based on their familiarity with the communities\u0026apos; geography and landscape and understanding of the local context. Data was collected face-to-face by co-researchers and community mobilisers in the informal settlements included in this study. Co-researchers were residents in the study sites, recruited since the project\u0026apos;s inception. They were actively engaged in the research to ensure the full participation of communities throughout the various phases of the research process. Community mobilisers were recruited purposely to facilitate the data collection due to the huge volume of the sample size. They were responsible for community engagement, data collection and dissemination of the study findings to promote local utilisation/application of project components/outputs.The survey team underwent a 4-day training program covering using the participant information sheet and consent form and selecting households based on the survey\u0026apos;s sampling framework. They were also trained to familiarise themselves with the survey tool, use the redcap, and troubleshoot if they faced any problems.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survey tool was tested in a pilot survey of 150 households across the three communities in March 2023. The research team held a workshop in Sierra Leone, attended by all community mobilisers and co-researchers, to discuss the challenges faced during the pilot survey and the necessary improvements in the tool to enhance its accuracy.We collected data on the last visit to healthcare by any household member in the last month before the interview. Due to the strong informality in the job market in Freetown, the participants were asked to provide their income data daily, weekly, or monthly. Costs were collected in the local currency, Sierra Leone Leones and converted to US$ (1 SLE=0.044 USD), applying the average exchange rate from OANDA website (www.oanda.com) during the data collection period (April-May, 2023).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eSample size calculation and sampling\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe informal settlements were selected purposively to ensure maximum variation in context and to understand their spatial and social diversities.\u0026nbsp;The sample size was determined based on the proportion of households facing barriers to accessing health services, estimated to be 0.47 from a pilot survey conducted before the survey. A margin of error of 0.03, a design effect of 10 to account for convenience sampling, a critical value of 0.05 (95% confidence interval), and a non-response rate of 10% were applied in the sample size calculation. The final sample was determined to be 4,884 households, considered large enough to estimate other health and well-being indicators within the desired precision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe following formula was used to calculate the sample size:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1734587479.png\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;n\u003c/em\u003e = required sample size\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;p\u003c/em\u003e = proportion of households facing barriers to accessing health services (0.47)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003edeff\u003c/em\u003e = design effect (10)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003ed\u003c/em\u003e = margin of error (0.03)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ez21\u0026minus;\u0026alpha;2 = critical value for the standard normal distribution corresponding to a Type 1 error rate of a two-tailed test (1.96).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNR\u003c/em\u003e = Non-response rate (0.10)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA hybrid sampling technique comprising probability and non-probability approaches was employed in household selection due to the lack of a sample frame of all households in the study sites. Probability sampling was employed proportionally to allocate the number of households to each informal settlement based on estimated populations from 2018\u003csup\u003e13\u003c/sup\u003e. This approach resulted in a sample of 1,251 households in Cockle Bay, 2,312 in Moyiba, and 1,321 in Dwarzark. Within each settlement, the number of households was equally allocated to different settlement zones (Cockle Bay: 313 households per zone x 4 zones, Moyiba: 232 households per zone x 10 zones and Dwarzark: 111 households per zone x 12 zones). In each zone, a random household along the chosen direction pointing outwards from an identified landmark was selected as a starting point for interviews. Landmarks used (e.g., mosques, cinemas, community centres and water points) and settlement boundaries were identified during a GIS mapping study\u003csup\u003e19\u003c/sup\u003e. The next step involved selecting the closest household to the one randomly chosen and interviewed if inclusion criteria requirements were met. The process was repeated interactively until the boundary of the zone was reached. This ensured that the households sampled were representative of the community population. Data was collected by interviewing every \u003cem\u003ei\u003c/em\u003eth household in each direction from the landmark, with \u003cem\u003ek\u003c/em\u003eth value determined by dividing the number of sampled households in each zone by the number of landmarks. One consenting adult (18 years and older), either the head of the household or the most senior household member, was selected for the interview.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData analysis\u003c/h2\u003e\n\u003cp\u003eMean with 95% confidence intervals (CIs) and median costs with interquartile ranges (IQR) of healthcare utilisation were estimated by cost type (direct medical, direct non-medical) per informal settlement and healthcare location (within and outside the community). The incidence (%) of catastrophic expenditures was also estimated using the payer\u0026rsquo;s household budget. We converted the daily and weekly incomes into monthly income by multiplying them by 27 working days or four weeks. The number of working days a month (27) for daily income workers was established based on the reports from Women in Informal Employment Globalizing and Organizing (WIGO) and the International Labour Organization (ILO)\u003csup\u003e20\u0026ndash;22\u003c/sup\u003e. We adopted 10% and 20% threshold levels to estimate catastrophic expenditures within and outside the communities across wealth quintiles and communities. Wealth quintiles were calculated according to the monthly income reported by respondents.\u003c/p\u003e\n\u003cp\u003eInequalities in healthcare expenditures were computed by determining concentration curves and indices for healthcare utilisation. The concentration curve displayed the share of healthcare costs by the cumulative population ranked in wealth quintiles. A concentration curve placed below the line of equity indicates higher costs amongst the wealthier (progressivity), whilst curves above the equity line indicate higher costs amongst the poorest (regressivity). The concentration indices were calculated to measure the magnitude of inequities in healthcare expenditures. The indices vary from -1 to 1, with negative values indicating healthcare expenditures concentrated amongst the poorest and positive values indicating expenditures concentrated amongst the wealthiest\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eData analysis was performed using Stata version 15. Frequency distributions and descriptive statistics were calculated. Chained multiple imputation (Royston, 2005) estimated missing cost data. Ten multiple imputed data sets with five iterations were generated and defined according to the percentage of missing data in healthcare utilisation\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e24\u003c/span\u003e\u003c/sup\u003e. ANOVA (Bonferroni) was applied to test differences in the proportions of categorical variables. The Wilcoxon rank-sum test compared costs between communities. Multiple logistic regression explored the association between catastrophic expenditures (10% and 20% thresholds) and socio-economic characteristics. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Sierra Leone Ethics and Scientific Review Committee (SLESRC: 026/04/2023) and the Liverpool School of Tropical Medicine Research Ethics Committee (21-007). Informed consent was obtained before each interview.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eParticipants characteristics\u003c/p\u003e\n\u003cp\u003eAmong 4,871 households, 2,575 (53%) reported healthcare utilisation within and/or outside the informal settlement, the final sample of this study. Most respondents were women (n=1,761, 68%), aged 26-49 (n=1,787, 70%) and married (n= 1,655 64%). Most participants were long-term community residents (\u0026gt; six years, n=1,695, 66%). Most were engaged in income-generating activities (n= 1,976, 77%), mainly employed in the informal market (n=1,660, 64%). The overall median monthly income across the communities was about 1,080 New Leones (Le) (US$47.5), with Cockle Bay reporting the highest median income (Le1,250, US$55). The average number of people in a household was five, with Cockle Bay presenting the lowest average number of residents at 4.6. The main structure of the houses in Cockle Bay was corrugated iron houses (55%), whereas in Dwarzark and Moyiba, mud houses were more common (43% and 46%). More than half (58%) of households reported having food insecurity meaning that sometimes or often in the past month, they and their household members could not eat the food they preferred. \u0026nbsp;In Dwarzark (41%), more participants reported facing food insecurity often (\u0026gt;10 times) than in Cockle Bay (15%) and Moyiba (29%) (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealthcare utilisation characteristics\u003c/p\u003e\n\u003cp\u003eMalaria was the most common illness reported by respondents for which healthcare was sought (73%), followed by cold/flu (55%). For all illnesses, households were more likely to use formal providers than informal providers, both public (56%) and private (46%). Within the communities, private formal healthcare services were most used in Cockle Bay (58%) and Dwarzark (52%), whereas in Moyiba (73%), most reported using public formal healthcare. Outside the community, public formal healthcare providers were used by the majority in all the settlements, averaging 61% across the research settings. The majority of people in Cockle Bay (71%) and 42% of those in Dwarzark travelled fewer than 30 minutes on average to reach healthcare within their community, while in Moyiba, the majority of people (52%) spent between 30 minutes to 1 hour to reach healthcare in the community. Residents took longer to reach healthcare outside the community, with 43% of people in Cockle Bay and Dwarzark spending between 30 minutes and 1 hour, while most Moyiba residents spent more than 1 hour to reach healthcare services (38%) (Table 2 and Figure 1A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealthcare costs\u003c/p\u003e\n\u003cp\u003eResults for healthcare costs within the community reveal Dwarzark and Moyiba as the communities with the highest costs. Dwarzark presented higher median direct medical costs (consultation fees plus medicines plus charges for investigations) than Moyiba (Le157, US$ 6.9 vs Le 120, US$5.3, p\u0026lt;0.001) and Cockle Bay (Le157, US$6.9 vs Le115, US$5.1, p\u0026lt;0.001) and higher median total costs (direct medical plus non-medical costs) than Cockle Bay (Le175 vs Le125, p\u0026lt;0.001). On the other hand, median direct non-medical costs (transportation costs and the cost of food during healthcare visits) were higher in Moyiba than in Cockle Bay (Le25, US$1.1 vs Le0, US$0, p\u0026lt;0.001) and Dwarzark \u0026nbsp;(Le25, US$1.1 vs Le10, US$0.44, p\u0026lt;0.001). Looking at the healthcare costs outside the communities, median direct medical, non-medical, and total costs were similar for Cockle Bay and Dwarzark residents. However, Moyiba presented higher median direct non-medical costs than Dwarzark (Le40, US$1.8 vs Le35, US$1.5, p=0.029) and Cockle Bay (Le40, US$1.8 vs Le35, US$1.5, p\u0026lt;0.001). Comparing costs within versus outside the communities, informal dwellers incurred almost three times higher total direct costs when utilising healthcare outside the communities (Le582, US$25.6 vs Le203, US$8.9) (Table 3 and Figure 1B).\u003c/p\u003e\n\u003cp\u003eCatastrophic expenditures\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe pooled incidence of catastrophic expenditures was 61% and 41% for healthcare within the communities, \u0026nbsp;and 76% and 57% for healthcare outside the communities, at 10% and 20% thresholds, respectively. For healthcare within the communities, catastrophic expenditure incidence was similar between Moyiba and Dwarzark (10% threshold= 64% vs 66%, p=1; 20% threshold= 42% vs 45%, p=0.855). A higher proportion of households in both communities incurred higher catastrophic expenditures than in Cockle Bay at the 10% and 20% thresholds (all p\u0026lt;0.001). In the pooled sample, the incidence of catastrophic expenditures was 91 percentage points lower in the wealthiest households at a 10% threshold (WQ1=91%, WQ5=8%) and 89 percentage points lower at a 20% threshold (WQ1=81%, WQ5=2%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding healthcare outside the communities, we found similar incidences of catastrophic expenditures at 10% and 20% thresholds across the communities. In the pooled sample, catastrophic expenditures incidence was also substantially lower in the wealthiest households at the 10% (WQ1= 94%, WQ5= 34%) and 20% thresholds (WQ1= 89%, WQ5= 12%). Compared to healthcare within the communities, the overall catastrophic expenditures in the pooled sample outside the communities was 25 percentage points higher at the 10% threshold (61% to 76%) and 39 percentage points higher at the 20% threshold (41% to 57%) (Table 4 and\u0026nbsp;Figure 1A).\u003c/p\u003e\n\u003cp\u003eFor healthcare within the community, households whose respondents were +35 years old (10% threshold: OR=1.53 [95%CI: 1.17-2.01]; 20% threshold: OR=1.57 [95% CI: 1.19-2.05]) and lived in Dwarzark (10% threshold: OR= 2.34 [95%CI: 1.68-3.26]; 20% threshold: OR=1.63 [95% CI: 1.16-2.31]) or Moyiba (10% threshold: OR=2.48 [95%CI: 1.69-3.62]; 20% threshold: OR=1.45 [95%CI: 0.98-2.14]) were more likely to incur catastrophic expenditures. Also, attending informal health providers[1] had a protective effect (10% threshold: OR=0.34 [95%CI: 0.21-0.55]; 20% threshold: OR= 0.23 [95% CI: 0.13-0.45]). For healthcare outside the community, length of residence +4 years was associated with catastrophic expenditures (10% threshold: OR=1.48 [95%CI: 1.13-1.94]; 20% threshold: OR=1.65 [95% CI: 1.30-2.09]) (Table 5).\u003c/p\u003e\n\u003cp\u003eConcentration curves and index\u003c/p\u003e\n\u003cp\u003eHealthcare expenditure within and outside the communities was similar across all wealth quintiles, with the concentration indices not statistically significant in Cockle Bay, Moyiba and overall. In Dwarzark, the concentration curves and indices indicated a progressive pattern with expenditures concentrated amongst the wealthiest households within (concentration index: 0.0467, p\u0026lt;0.05) and outside the community (concentration index: 0.083, p\u0026lt;0.1) \u0026nbsp;(Figure 2).\u003c/p\u003e\n"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eCosts and catastrophic expenditures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall incidence of catastrophic expenditures in our study was higher than in informal settlements in Kenya (10% threshold: 23%)\u003csup\u003e25\u0026nbsp;\u003c/sup\u003eand post-conflict Sierra Leone as reported by a representative national survey (10% threshold: 32%)\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, our figures were similar to a study on emergency surgery in informal settlements in Nigeria (10% threshold: 71%) \u003csup\u003e\u003cspan lang=\"EN-US\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The incidence across wealth quintiles was higher amongst the poorest in our study, which also differs from a scoping review that showed similar incidences across wealth quintiles in informal settlements in LMICs (10% threshold: ~19%)\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Divergencies in the literature may be related to the methods used to estimate catastrophic expenditures. Studies in informal settlements in Kenya, Pakistan, Bangladesh and Nigeria found significant disparities in the incidence of catastrophic expenditures when using different methodological approaches (e.g., expenditure or income approaches)\u003csup\u003e27\u003c/sup\u003e. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding healthcare utilisation within the communities, residents of Cockle Bay were less likely to incur catastrophic expenditures, possibly because they mainly rely on informal health services, which our study indicated as a protective factor. On the other hand, residents of Moyiba and Dwarzark and participants +35 years were more likely to incur catastrophic expenditures. Outside the communities, the longer length of residence was associated with catastrophic expenditures in both thresholds. This could be linked to prolonged exposure to the environmental and health hazards experienced by long-term residents\u003csup\u003e28\u003c/sup\u003e. Other studies found that longer residences in informal settlements and older age groups are linked to a higher risk of illness, which can lead to higher use of healthcare and higher risk of catastrophic expenditures for these social groups, as our study\u0026nbsp;has highlighted\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e29,30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAccording to our study, 61% of households (N=1,580) choose to use healthcare services outside their communities. This preference for external healthcare can be potentially attributed to the perceived higher quality of services provided outside the communities, as noted in a study of informal settlements in Kenya and Nigeria. Households are willing to endure higher costs and longer travel distances to access these facilities due to the perceived better quality\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The qualitative study conducted prior to this survey examined the exclusion experienced in healthcare systems within community health facilities. The findings from this study also explain preferences for seeking care outside of local communities. Households, particularly in Moyiba, reported experiencing discrimination based on factors such as poverty, disability, and chronic conditions. These factors are often more prevalent in local healthcare settings, leading patients and their families to seek care elsewhere\u003csup\u003e32\u003c/sup\u003e.\u0026nbsp;Furthermore, the majority of individuals in our study work in the informal sector and often have long working hours, which makes it difficult for them to use healthcare facilities with limited opening hours within their communities\u003csup\u003e5\u003c/sup\u003e.The qualitative studies conducted during the exploratory phase in the same study sites also identified opening hours as a significant barrier to accessing healthcare in the communities, especially for pregnant women who lack medical assistance at night\u003csup\u003e32\u003c/sup\u003e. Also, only 9% of respondents in our survey reported that opening hours posed a challenge for accessing healthcare outside the communities\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eComparing costs across the communities, residents of Dwarzark incurred the highest direct medical and total direct costs, whereas Moyiba had the highest direct non-medical costs. Cockle Bay presented the lowest direct costs across the communities. These findings indicated different scenarios regarding healthcare availability, socioeconomic status, ability to pay for health services and service access. In Cockle Bay, the lack of formal healthcare led households to utilise cheaper informal services more frequently (49% in Cockle Bay vs 25% in Dwarzark vs 34% in Moyiba). Also, the community is more centrally located, facilitating access to healthcare outside the community. On the other hand, Dwarzark and Moyiba share similar geography, both hilly settlements, which makes accessing healthcare outside the community more challenging, particularly in Moyiba, as this community is not centrally located. Moyiba presented a higher percentage of households spending +1 hour to reach healthcare (69%) than other communities (Cockle Bay: 40%; Dwarzark: 44%), which explains the higher direct non-medical costs compared to other communities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInequalities in healthcare access\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings indicated that Dwarzark was the only community presenting a progressive pattern of healthcare expenditure. This might be because higher-income people seek better and more costly healthcare. Also, this community is more centrally located, facilitating access to various health services outside the community. On the other hand, the similar distribution of OOPE across wealth quantiles in Cockle Bay and Moyiba suggests that people with higher incomes have good social connections with healthcare providers, which could lower the costs, bringing them similar to the costs of the poorest. A qualitative study conducted in informal settlements in Freetown found\u0026nbsp;that access to healthcare is heavily mediated by people\u0026apos;s social positions and status, especially their ability to draw on support from social networks\u003csup\u003e16\u003c/sup\u003e. However, no investigation has explored if these social connections have the potential to reduce the costs of accessing healthcare. We suggest further studies examining this topic in the context of the urban poor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother study using data from the Sierra Leone Integrated Household Survey (2018) also brings insights into the progressivity and regressivity of the health financing system in Sierra Leone. The study found that primary healthcare is pro-poor (progressive), but when OOPE health expenditures are included in the analysis, the overall health financing in Sierra Leone becomes regressive due to the regressivity of OOPE\u003csup\u003e33\u003c/sup\u003e. More studies should explore inequalities in healthcare across urban informal settlements in Freetown to better understand the main drivers of these inequalities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe levels of regressivity and progressivity in healthcare spending are important factors in achieving universal health coverage. In Sierra Leone, the main sources of health financing are government general revenues, donor funding, and OOPE. However, in 2020, the government\u0026apos;s contributions from these sources combined only accounted for 15%, while \u0026nbsp;OOPE makes up a significant portion of health financing in the country, at around 55%\u003csup\u003e\u003cspan lang=\"EN-US\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u0026nbsp;Depending heavily OOPE can lead to greater disparities in healthcare spending, worsening the health outcomes for the most vulnerable individuals living in informal settlements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications of this study and policies to mitigate the economic burden\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the first study focusing on the economic burden of healthcare utilisation on urban informal settlements in Freetown. It provides reference material for decision-making policies to address healthcare challenges informal settlement dwellers are grappling with, particularly regarding the affordability of high-quality services within and outside the communities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found that utilising informal healthcare providers can reduce the likelihood of incurring catastrophic expenditures, which indicates the significant role they play in communities, not only in delivering care in challenging situations where formal healthcare is limited but also in terms of affordability. However, unregulated healthcare providers can also threaten citizens\u0026apos; health security due to the poor quality of their services\u003csup\u003e35\u003c/sup\u003e. This highlights the need to explore ways to incorporate informal providers into the formal healthcare system to enhance the quality of care and make healthcare more accessible for vulnerable populations living in informal settlements. Stakeholders in Nigeria have seen the connections between informal and formal healthcare sectors in informal settlements as a positive step, arguing that it could enhance service delivery. The study suggested that collaboration with the informal sector can be achieved through regulatory and financial measures, improvement of clinical guidelines, and engagement with the communities\u003csup\u003e36\u003c/sup\u003e. Another study in Sierra Leone demonstrated that regulating the informal sector could help manage non-communicable diseases. Community health workers suggested collaboration with traditional healers to identify and refer hypertensive patients\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDespite these positive findings, evidence also indicates the challenges and risks of integrating informal providers into the formal health system. In India, a study on integrating informal providers into the National Tuberculosis (TB) Programme raised concerns about the low quality of the services provided and the lack of appropriate knowledge to treat TB. The study suggests that the formal health system must closely monitor informal practitioners to ensure they implement government guidelines to treat TB\u003csup\u003e38\u003c/sup\u003e.\u0026nbsp;In China, seeking treatment from informal providers often resulted in missed or delayed diagnoses, which could have serious clinical consequences. The study also highlighted that these informal providers might spread misleading information or even cause adverse medical events, such as side effects or harmful treatment interactions\u003csup\u003e39\u003c/sup\u003e. A Consensus Study Report indicates that while it is challenging to create generalised recommendations for improving the quality of informal healthcare providers, addressing critical issues\u0026mdash;such as enhancing their knowledge and practices\u0026mdash;must be a top priority\u003csup\u003e40\u003c/sup\u003e. Additionally, a study conducted in Nigeria focused on advancing Universal Health Coverage by connecting formal and informal health providers. It recommended a comprehensive implementation strategy that includes adequate resources, active community participation, flexibility from policymakers, ongoing evaluation and feedback mechanisms, and a commitment to long-term sustainability and adaptability to evolving healthcare needs and community dynamics\u003csup\u003e41\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAnother reflection is on the progressivity and regressivity in healthcare expenditures. Although a progressive expenditure can indicate fairness in health system financing as\u0026nbsp;higher-income groups bear a proportionally larger share of costs relative to their income, it can also suggest a paradox. In several LMICs, the poorest contribute less to the health system in terms of OOPE because they cannot afford high-quality and more expensive healthcare. Thus, their payment for healthcare is reduced, resulting in a progressive health system. In this scenario, better-off households use expensive and usually better quality health services than the poorest, also leading to a progressive OOPE pattern in the health financing system when considering OOPE\u003csup\u003e27,42\u003c/sup\u003e. On the other hand, our study found that the poorest wealth quintiles experience a higher proportion of catastrophic expenditures compared to wealthier groups, even when accessing cheaper services, such as those provided by informal health providers. Given this limitation, we must investigate whether progressivity in Dwarzark is driven by the concentration of OOPE amongst the better-off or the lack of ability to pay for better-quality\u0026nbsp;health services amongst the poorest.\u003c/p\u003e\n\u003cp\u003eA final thought is about the affordability of high-quality services. Our survey explored poor healthcare quality and high costs as barriers to access to health services. The final survey report brings a more detailed analysis of this indicator, but in summary,\u0026nbsp;participants reported that the quality of care is better in services outside the communities than within, and this is the reason respondents with sustainable and higher income-generating activities sought healthcare providers outside the community\u003csup\u003e18\u003c/sup\u003e. This reinforces the importance of investing in good quality and affordable health services within communities to reduce household costs of seeking care and treatment for their health conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study team worked closely with the communities through community-based participatory research. This approach established bottom-up perspectives on the boundaries of the settlements and determined the key variables for the questionnaire.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survey findings were validated during two events: the City Learning Platform event in March 2024 and a Validation Workshop in May 20204. The City Learning event was attended by 51 participants, including community chiefs, health workers, representatives from community learning platforms, researchers, co-researchers, personnel from the Ministry of Health, members of the Freetown City Council, non-governmental organisations, and external consortium partners\u003csup\u003e43\u003c/sup\u003e. The Validation Workshop had 70 attendees from the study sites, including community chiefs, youth leaders, community mobilisers who participated in the survey, survey respondents, health workers, co-researchers, and researchers\u003csup\u003e44\u003c/sup\u003e. These events aimed to gather feedback from community residents and other stakeholders on the survey findings and incorporate their insights into the survey report. Participants reflected on the accuracy of the findings and concluded that they accurately represent the local situation and can be utilised by the government and other organisations to explore ways to enhance service provision for the community.\u003c/p\u003e\n\u003cp\u003eOur study also has some limitations. Local community mobilisers and co-researchers were essential for improving the accuracy of the survey responses. However, some of these mobilisers had limited educational backgrounds and digital skills. As a result, we needed to recruit additional community members who had not participated in the earlier phases of the study, such as the qualitative research, to assist with data collection. The research team in Sierra Leone also provided more training sessions and content on the study context for those new to the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe estimated catastrophic expenditures based on the payer\u0026rsquo;s household budget. In a country with a strong informal economy like Sierra Leone, this approach could overestimate the incidence of catastrophic costs. However, the income of informal settlement dwellers in Sierra Leone reported in this study is aligned with the figures provided by The World Salaries\u003csup\u003e45\u003c/sup\u003e. So, our approach may not have affected our estimates. Still, our analysis relied on self-reported health data, which can be subject to reporting bias, particularly regarding costing data. To minimise bias, a short time horizon to report costs and trained co-researchers residents in the studied communities monitored the data collection. This approach facilitated household engagement and trust.\u003c/p\u003e\n\u003cp\u003eGiven the lack of a sampling frame, multi-stage cluster sampling was unfeasible. However, to improve the generalisability of the obtained results, we used a design effect of 10 and established landmarks in the community, which led to an increase in sampled households. Therefore, the sample was large enough to allow generalisability as if the sampled households were obtained using probability sampling. Finally, a short timeframe may also risk minimising the costs associated with lengthy pathways to care.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study revealed a significant and unequal economic impact of healthcare utilisation, with residents of Moyiba and Dwarzark, respondents aged +35 and living in the communities longer than 4 years facing a higher risk of catastrophic expenses. The regulation of informal health providers and their integration into the formal health system should be tested, as they were found to protect against catastrophic expenses. Addressing the economic implications of healthcare utilisation, improving access to quality and affordable healthcare within the communities, and promoting an equitable health system should be the primary focus of Sierra Leone\u0026apos;s health financing strategy.\u003c/p\u003e\n\u003cp\u003eBox 1. Characteristics of the study sites\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.138%;\"\u003e\n \u003cp\u003eCockle Bay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.862%;\"\u003e\n \u003cp\u003eIt lies along the western coast of Freetown. Established in the 1940s, it is home to over 20,000 people. The community lacks public or private formal health facilities, prompting residents to travel about 2-5 kilometres to seek care in facilities outside the community\u003csup\u003e46\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.138%;\"\u003e\n \u003cp\u003eMoyiba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.862%;\"\u003e\n \u003cp\u003eSituated in a hill area on the eastern side, 5 km from the Central Business District (CBD), with an estimated population of 37,000. There is one formal health facility, but medical personnel are not always available. Private facilities and informal services such as pharmacies and nurses provide home care.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.138%;\"\u003e\n \u003cp\u003eDwarzark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.862%;\"\u003e\n \u003cp\u003eSituated in the central area of Freetown, also in a hilly area, with an estimated population of 21,120. There is one formal health facility, but no medical personnel is available.\u0026nbsp;Private facilities and informal services such as pharmacies and nurses provide home care.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Box 2. Survey tool\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003eThemes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eInsights\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eSummary of the main findings\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003eService delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eThis section examines several aspects of service delivery, including water sources, accessibility, sanitation facilities, waste management, and associated challenges. It also analyses drinking water sources, such as sachet water and community wells, domestic water usage patterns, and distances to water points. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eMost respondents rely on sachet water and community wells for drinking water. The sanitation system is poor across the three communities: flush toilets are mainly in Cockle Bay, while Moyiba and Dwarzark primarily use pit latrines.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003eHealthcare landscape\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eThis section examines healthcare access and utilisation patterns, and challenges in accessing healthcare services across the three communities, such as distance, cost, and quality of care.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eBarriers like distance, cost, and quality of care are significant for healthcare services, and community responses vary across different areas.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003eRisks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eThis section examines common disasters that affected respondents, such as flooding, fire, building collapse, and falling boulders.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eNatural disasters like flooding, fires, and building collapses have affected respondents.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003eSafety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eThis section examines the occurrence of theft/robbery, physical violence, road accidents, evictions, and sexual and gender-based violence.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eRespondents reported common issues such as theft, physical violence, road accidents, evictions, and sexual and gender-based violence, primarily impacting vulnerable and marginalised groups.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.2013%;\"\u003e\n \u003cp\u003ePerception of health and well-being, challenges and barriers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eThis section examines the factors determining physical well-being among the community residents, such as good health, a clean and safe environment, financial stability, safety/security, and a support network.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.3993%;\"\u003e\n \u003cp\u003eIn Cockle Bay and Moyiba, physical well-being is influenced by good health and a clean, safe environment. In contrast, Dwazack has different factors. However, both Cockle Bay and Dwazarck prioritise social and mental well-being through financial stability, safety, and support networks.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Health and wellbeing survey of informal settlements in Freetown, Sierra Leone, May 2023.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GCRF Accountability for Informal Urban Equity Hub (\u0026lsquo;ARISE\u0026rsquo;) is a UKRI Collective Fund award\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ewith award reference (ES/S00811X/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study include sensitive category household-level data. To prevent disclosure these data are not publicly available but are available for research purposes through successful application to data holders (Liverpool School of Tropical Medicine, College of Medicine and Allied Health Sciences (COMAHS) - University of Sierra Leone, Sierra Leone Urban Research Centre (SLURC), and Centre of Dialogue on Human Settlement and Poverty Alleviation (CODOHSAPA)-Sierra Leone).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNTSF, IG and HE conceived the idea for the study. IG and NTSF drafted the analysis plan. S Saidu, IJS, IG, S Sesay, AC, BK, NTSF, EK, RL, BM, LW, MN and NWG contributed to the survey planning and implementation. NTSF, SF and DV conducted data analysis. SF, DV, SM, BK and NTSF drafted the original manuscript. All authors contributed to the critical revision and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNijman J, Wei YD. Urban inequalities in the 21st century economy. Applied Geography. 2020;117(February):102188. \u003c/li\u003e\n\u003cli\u003eAbascal A, Rothwell N, Shonowo A, Thomson DR, Elias P, Elsey H, et al. \u0026ldquo;Domains of deprivation framework\u0026rdquo; for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review. Vol. 93, Computers, Environment and Urban Systems. Elsevier Ltd; 2022. \u003c/li\u003e\n\u003cli\u003eUN Environment Programme. 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Sierra Leone Public Expenditure Review 2021. 2021. \u003c/li\u003e\n\u003cli\u003eAgwu P, Etiaba E, Onwujekwe O. Ungoverned Spaces Among Informal Health Providers in Nigeria and Health Security Implications. J Soc Serv Res [Internet]. 2024 Aug 29;1\u0026ndash;13. Available from: https://www.tandfonline.com/doi/full/10.1080/01488376.2024.2395929\u003c/li\u003e\n\u003cli\u003eOnwujekwe O, Mbachu C, Onyebueke V, Ogbozor P, Arize I, Okeke C, et al. Stakeholders\u0026rsquo; perspectives and willingness to institutionalize linkages between the formal health system and informal healthcare providers in urban slums in southeast, Nigeria. BMC Health Serv Res. 2022 Dec 1;22(1). \u003c/li\u003e\n\u003cli\u003eWitter S, Zou G, Diaconu K, Senesi RGB, Idriss A, Walley J, et al. Opportunities and challenges for delivering non-communicable disease management and services in fragile and post-conflict settings: Perceptions of policy-makers and health providers in Sierra Leone. Confl Health. 2020 Jan 6;14(1). \u003c/li\u003e\n\u003cli\u003eThapa P, Narasimhan P, Jayasuriya R, Hall JJ, Mukherjee PS, Das DK, et al. Barriers and facilitators to informal healthcare provider engagement in the national tuberculosis elimination program of India: An exploratory study from West Bengal. PLOS Global Public Health. 2023 Oct 1;3(10 October). \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO traditional medicine strategy. 2014-2023 [Internet]. World Health Organization; 2013 [cited 2024 Nov 20]. Available from: https://iris.who.int/bitstream/handle/10665/92455/9789241506090_eng.pdf?sequence=1\u003c/li\u003e\n\u003cli\u003eNational Academies of Sciences Engineering and Medicine; Crossing the Global Quality Chasm. In Washington, D.C.: National Academies Press; 2018. Available from: https://www.nap.edu/catalog/25152\u003c/li\u003e\n\u003cli\u003eChristian BIN, Christian NG, Keshinro MI, Olutade-Babatunde O. How to build bridges for Universal Health Coverage in Nigeria by linking formal and informal health providers. Vol. 8, BMJ Global Health. BMJ Publishing Group; 2023. \u003c/li\u003e\n\u003cli\u003eBayati M, Mehrolhassani MH, Yazdi-Feyzabadi V. A paradoxical situation in regressivity or progressivity of out of pocket payment for health care: Which one is a matter of the health policy maker\u0026rsquo;s decision to intervention? Vol. 17, Cost Effectiveness and Resource Allocation. BioMed Central Ltd.; 2019. \u003c/li\u003e\n\u003cli\u003eSierra Leone Urban Research Centre. ARISE Sierra Leone City Learning Platform Report [Internet]. Freetown; 2024 [cited 2024 Dec 3]. Available from: Unpublished\u003c/li\u003e\n\u003cli\u003eSierra Leone Urban Research Centre. Validation workshop quantitative survey [Internet]. Freetown; 2024 [cited 2024 Dec 3]. Available from: Unpublished\u003c/li\u003e\n\u003cli\u003eWorld Salaries. Average Salary in Sierra Leone for 2024. https://worldsalaries.com/average-salary-in-sierra-leone/. 2024. \u003c/li\u003e\n\u003cli\u003eMacarthy J, Conteh A, Sellu SA, Doughty T. Issue Brief: The State of healthcare access in Freetown\u0026rsquo;s informal settlements [Internet]. 2018 [cited 2024 Apr 26]. Available from: file:///C:/Users/ns1451/OneDrive%20-%20University%20of%20York/references%20informal%20settlements,%20engagement,%20KT/\u003cbr\u003ehealthcare%20access%20freetown.pdf\u003c/li\u003e\n\u003cli\u003eBloom G, Standing H, Lucas H, Bhuiya A, Oladepo O, Peters DH. Making health markets work better for poor people: The case of informal providers. Health Policy Plan. 2011 Jul;26(SUPPL. 1). \u003c/li\u003e\n\u003cli\u003eKumah E. The informal healthcare providers and universal health coverage in low and middle-income countries. Vol. 18, Globalization and Health. BioMed Central Ltd; 2022. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Participants\u0026apos; socioeconomic and demographic characteristics.\u0026nbsp;Sierra Leone, Freetown, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 734\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzark\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=848\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=993\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=2,575\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, N (%)\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e514 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e624 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e623 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,761 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e18-25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e116 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e128 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e181 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e425 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e26-35\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e292 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e318 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e361 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e971 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e36-49\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e240 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e261 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e315 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e816 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e50\u0026nbsp;+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e86 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e141 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e136 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e363(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSingle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e202 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e191 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e200 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e593 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eMarried, co-habiting, engaged\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e461 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e252 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e669 (67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,655 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSeparated, divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e27 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e49 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e35 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e111 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e44 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e83 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e89 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e216 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of residence, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eLess than 1 year\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e58 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e65 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e56 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e179 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1-5 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e244 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e178 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e279 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e701 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e6-10 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e154 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e138 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e213 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e505 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eOver 10 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e278 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e467 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e445 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,190 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel of Education, N (%)\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e213 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e221 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e348 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e782 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePrimary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e63 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e89 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e76 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e228 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSecondary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e344 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e384 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e438 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,166 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eTertiary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e65 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e102 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e71 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e238 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eQuranic education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e27 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e33(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e68 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eTechnical/vocational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e17 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e44 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e26 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e87 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome activity type, N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eInformal occupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e475 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e504 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e681 (69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,660 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eFormal occupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e91 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e116 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e90 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e297 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eFormal and informal occupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e7 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e9 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e19 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e161 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e219 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e219 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e599 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency of Income, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eDaily\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e461 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e500 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e710 (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,671 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eWeekly\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e63 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e123 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e91 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e277 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eMonthly\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e173 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e186 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e97 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e456 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eNo income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e37 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e39 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e95 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e171 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian monthly income, Le (IQR)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eOverall\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1,350 (800-2,700)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1,000 (540-1,890)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1,200 (600-2,160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e1,080 (600-2,160)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth quintiles, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e1 (poorest)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e113 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e210 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e249 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e572 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e121 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e126 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e205 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e452 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e118 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e109 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e180 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e407 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e150 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e160 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e156 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e466 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e5 (wealthier)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e193 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e200 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e107 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e500 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTenure status, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eTenant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e484 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e495 (58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e540 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1,519 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eLandlord\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e187 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e245 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e317 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e752 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eFree-living\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e40 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e89 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e116 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e245 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eOthers\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e23 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e19 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e20 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e59 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage (95%CI) number of people in the household\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.6 (4.5-4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.4 (5.3-5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.6 (5.5-5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e5.3 (5.2-5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHouse structure, N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePan Body/Corrugated Iron Houses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e438 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e216 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e69 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e723 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eConcrete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e263 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e248 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e409 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e920 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eMudhouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e21 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e379 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e484 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e884 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eOthers\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e12 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e31 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e48 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood insecurity, N (%)\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e205 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e118 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e158 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e481 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eRarely (once or twice)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e154 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e139 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e292 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e585 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSometimes (3-10 times)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e264 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e246 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e250 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e760 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eOften (\u0026gt; 10 times)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e111 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e345 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e293 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e749 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u0026nbsp;\u003c/sup\u003eMissing data: Cokle Bay=5; Moyiba=34; \u003csup\u003e**\u003c/sup\u003e Cokle Bay=20; Dwarzark=25, Moyiba=83.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e People who neither pay rent nor own the house\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eCaretaker, lease, temporal\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Wooden, mixed (e.g., concrete and PanBody)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Characteristics of healthcare utilisation within and outside the informal settlements. Sierra Leone, Freetown, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 250px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithin the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 241px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutside the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(within and/or outside)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=2,575\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=287\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzark\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u003cstrong\u003eN=658\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=530\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=1,475\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 641\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzark\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 369\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 568\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=1,580\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of illness\u003c/strong\u003e\u003cstrong\u003e, N (%)\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMalaria\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e212 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e428 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e375 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1,015 (69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e509 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e193 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e408 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1,110 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1,887 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCold, flu\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e167 (58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e283 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e291 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e741 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e399 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e121 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e313 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e833 (53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1,414 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eTyphoid\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e75 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e179 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e199 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e453 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e298 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e101 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e239 (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e638 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e997 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eHigh blood pressure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e12 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e58 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e61 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e131 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e58 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e41 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e96 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e195 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e295 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eRoutine check-ups\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e17 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e48 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e74 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e51 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e26 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e76 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e153 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e217 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eInjury\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e6 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e32 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e29 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e67 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e15 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e25 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e70 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e110 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e161 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eUlcer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e19 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e34 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e22 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e75 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e40 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e24 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e78 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e142 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e193 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSkin rash\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e34 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e27 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e70 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e18 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e9 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e37 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e64 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e125 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCholera, diarrhoea\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e7 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e22 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e27 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e56 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e18 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e9 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e32 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e59 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e114 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of healthcare used\u003c/strong\u003e\u003cstrong\u003e, N (%)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePublic Formal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e191 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e386 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e589 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e359 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e245 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e367 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e971 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1,432 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePrivate Formal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e340 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e55 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e574 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e303 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e122 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e276 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e701 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1,181 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDrug Peddlers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e91 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e49 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e93(17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e233 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e23 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e66 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e91 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e311 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ePrivate Nurse\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e44 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e113 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e81 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e238 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e11 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e43 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e61 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e295 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eTraditional healers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e6 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e8 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e12 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e26 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e23 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e35 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e59 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage time to reach\u0026nbsp;healthcare\u003c/strong\u003e\u003cstrong\u003e, N (%)\u003c/strong\u003e \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eLess than 30 minutes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e203 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e273 (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e183 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e659 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e74 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e30 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e31 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e135 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eBetween 30min -1 hour\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e69 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e225 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e274 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e568 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e277 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e158 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e141 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e576 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1-2hours \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e8 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e97 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e50 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e155 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e150 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e81 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e218 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e449 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eOver 2 hours \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e4 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e37 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e17 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e58 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e111 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e82 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e176 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e369 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDo not know\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e19 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e23 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e27 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e16 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e44 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003eMultiple choice question. Tuberculosis, convulsion and diabetes were reported by \u0026le; 3% of the participants; \u003csup\u003e2\u003c/sup\u003e Multiple choice question. 180 missing data in Cockle Bay, within the community.\u003c/p\u003e\n\u003cp\u003eNA= not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Average cost (Leone, Le [95% CI]) of healthcare utilisation within and outside the informal settlements. Sierra Leone, Freetown, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithin the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=287\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzark\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=658\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=530\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=1,475\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDirect medical costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e154 (136-171)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e115 (50-200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e200 (185-214)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e157 (90-250)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e173 (158-187)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e120 (80-205)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e181 (172-190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e140 (80-227)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDirect non-medical costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e10 (8-13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0 (0-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e16 (15-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e10 (0-21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (32-37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e25 (12-50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e22 (20-23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e13 (0-30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eTotal direct costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e164 (145-183)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e125 (60-200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e216 (101-231)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e175 (100-266)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e207 (192-223)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e162 (103-240)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e203 (192-212)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e160 (93-255)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutside the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 641\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzack \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 369\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=568\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=1580\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eAverage (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDirect medical costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e437 (385-488)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e290 (190-450)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e623 (517-728)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e320 (150-320)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e563 (316-810)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e253 (159-430)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e526 (431-620)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e280 (160-500)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDirect non-medical costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e48 (43-53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (20-50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e54 (47-62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (20-55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e68 (60-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e40 (25-70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e57 (53-61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (22-60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eTotal direct costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e485 (430-539)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e323 (220-510)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e677 (571-784)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e362 (178-735)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e631 (384-878)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e300 (186-515)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e582 (487-678)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e320 (198-550)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e1SLE=0.044 USD\u003c/p\u003e\n\u003cp\u003eP-values, Wilcoxon rank-sum test, within the community\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eCommunities\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eCockle Bay (a)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eDwarzark \u0026nbsp;(b)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eNon-medical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eNon-medical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eDwarzack (b) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eMoyiba (c)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-values, Wilcoxon rank-sum test, outside the community\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eCommunities\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eCockle Bay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eDwarzack \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eNon-medical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eMedical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eNon-medical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eDwarzack \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eMoyiba\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4.\u0026nbsp;Incidence of catastrophic expenditures with 10% and 20% thresholds\u0026nbsp;by wealth quintile\u0026nbsp;within and outside the informal settlements. Sierra Leone, Freetown, 2023.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eW\u003c/strong\u003e\u003cstrong\u003eithin the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 283\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzark\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 636\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 483\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePooled\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN=\u0026nbsp;1,402\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e84 (73-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e73 (60-83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e90 (85-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e82 (76-87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e95 (91-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e85 (78-90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e91 (88-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e81 (77-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e58 (42-73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e39 (25-56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e87 (78-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e63 (53-72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e90 (81-96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e66 (54-78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e82 (76-87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e59 (77-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e45 (32-57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e21 (12-33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e71 (62-78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e32 (24-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e71 (62-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e28 (20-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e65 (60-71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e28 (23-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17 (8-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e7 (2-17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e45 (34-54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e11 (5-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e33 (24-43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e8 (3-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e34 (28-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e8 (5-13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e5 (1-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2 (0-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e10 (5-19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e3 (1-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e7 (2-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1 (0-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e8 (5-12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2 (1-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cem\u003eOverall*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e42 (36-48)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e29 (24-35)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e66 (63-70)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e45 (42-49)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e64 (60-69)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e42 (38-47)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e61 (58-64)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e41 (38-44)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutside the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCockle Bay\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= \u0026nbsp;625\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwarzack\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 362\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoyiba\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 519\u003c/p\u003e\n \u003cp\u003e% (95%CI\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePooled\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN= 1,506\u003c/p\u003e\n \u003cp\u003e% (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e96 (90-99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e95 (89-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e89 (82-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e83 (74-89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e97 (91-99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e90 (82-95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e94 (90-96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e89 (85-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e90 (85-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e81 (74-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e84 (73-91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e79 (68-87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e95 (89-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e78 (68-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e90 (87-93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e79 (75-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e88 (81-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e65 (55-74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e87 (75-95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e60 (46-73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e89 (82-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e61 (52-70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e89 (84-92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e63 (57-69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e68 (59-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e30 (22-39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e82 (71-90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e54 (42-66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e67 (58-75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e31 (23-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e70 (65-75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e36 (30-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eWQ 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e28 (21-37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e9 (5-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e44 (31-59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17 (8-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e35 (24-46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e12 (5-21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e34 (28-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e12 (8-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cem\u003eOverall*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e73 (70-77)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e55 (52-60)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e79 (75-83)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e63 (58-68)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e79 (75-82)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e56 (51-60)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e76 (74-79)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cem\u003e57 (55-60)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWQ=wealth quintile\u003c/p\u003e\n\u003cp\u003e*P-values, \u0026nbsp;ANOVA Bonferroni, Overall\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCommunity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 274px;\"\u003e\n \u003cp\u003eCockle Bay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 274px;\"\u003e\n \u003cp\u003eDwarzark\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eWithin, 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eWithin, 20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eOutside, 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eOutside, 20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eWithin, 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eWithin, 20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eOutside, 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eOutside, 20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDwarzark \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMoyiba\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eTable 5. Association between catastrophic expenditures (10% and 20% thresholds) and socio-economic characteristics within and outside the communities. Sierra Leone, Freetown, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"869\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 104px;\"\u003e\u003cbr\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 383px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithin the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 383px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutside the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10% Threshold\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20% Threshold\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10% Threshold\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20% Threshold\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e18-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.59 (1.28-1.97)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.53 (1.17-2.01)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.51 (1.22-1.87)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.57 (1.19-2.05)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.47 (1.14-1.87)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.39 (1.03-1.87)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.12 (0.91-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.08 (0.85-1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eMarried, co-habiting, engaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.02 (0.78-1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.89 (0.65-1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.87 (0.67-1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.76 (0.57-1.03)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.92 (0.68-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.86 (0.61-1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.80 (0.62-1.02)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.83 (0.63-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eDivorced, separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.35 (1.24.45)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.70 (0.84-3.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.26 (0.72-2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.96 (0.52-1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.99 (0.53-1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.00 (0.50-2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.88 (0.51-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.03 (0.57-1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.90 (1.21-3.01)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.38 (0.78-2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.71 (1.13-2.62)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.38 (0.82-2.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.20 (0.70-2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.97 (0.52-1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.00 (0.64-1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.04 (0.62-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eNo education or primary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.03 (0.83-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.97 (0.70-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.87 (0.69-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.73 (0.56-0.96)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.06 (0.82-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.85 (0.63-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.87 (0.70-1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.73 (0.57-0.94)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eTertiary or technical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.11 (0.79-1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.03 (0.69-1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.97 (0.69-1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.79 (0.55-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.81 (1.18-2.78)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.57 (0.99-2.48)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.36 (0.98-1.90)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.16 (0.81-1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCockle Bay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eDwarzack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.75 (2.07-3.67)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.34 (1.68-3.26)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.05 (1.51-2.77)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.63 (1.16-2.31)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.40 (1.02-1.90)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.24 (0.88-1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.37 (1.04-1.78)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.22 (0.90-1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eMoyiba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.46 (1.82-3.31)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.48 (1.69-3.62)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.81 (1.32-2.47)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.45 (0.98-2.14)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.29 (0.98-1.71)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.15 (0.84-1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.99 (0.79-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.94 (0.72-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of residence in the community\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt;4 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026gt;4 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.42 (1.13-1.79)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.12 (0.85-1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.29 (1.02-1.63)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.08 (0.83-1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.59 (1.24-2.03)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.48 (1.13-1.94)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.63 (1.32-2.02)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.65 (1.30-2.09)****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of people in the households\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026lt; 5 people\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026gt; 5 people\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.2 (0.96-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.95 (0.73-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.16 (0.93-1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.92 (0.72-1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.16 (0.90-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.08 (0.81-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.30 (1.04-1.61)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.30 (1.02-1.65)**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHouse structure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eConcrete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003ePan Body, mudhouse, woodhouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.09 (0.87-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.15 (0.90-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.91 (0.73-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.95(0.74-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.99 (0.77-1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.08 (0.82-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.99 (0.80-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.04 (0.82-1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood insecurity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eNo/rarely/sometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eOften\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.42 (1.12-1.81)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.31 (0.99-1.73)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.24 (0.98-1.56)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.22 (0.94-1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.47 (1.11-1.94)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.29 (0.94-1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.05 (0.84-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.97 (0.75-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare provider\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eOnly public formal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eOnly private formal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.04 (0.80-1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.32 (0.95-1.83)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.85 (0.66-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.88 (0.63-1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.27 (0.97-1.68)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.31 (0.99-1.74)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.18 (0.94-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.21 (0.95-1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eOnly informal (traditional healers, drug paddlers)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.26 (0.17-0.41)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.34 (0.21-0.55)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.21 (0.12-0.36)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.23 (0.13-0.45)****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.79 (0.30-2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.81 (0.30-2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.97 (0.40-2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.08 (0.43-2.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eOnly private nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.23 (0.82-1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.46 (0.94-2.26)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.84 (0.57-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.86 (0.57-1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.81 (0.28-2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.91 (0.31-2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.89 (0.34-2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.92 (0.34-2.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eFormal and informal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.10 (0.73-1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.40 \u0026nbsp;(0.90-2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.91 (0.61-1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.01 (0.66-1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.81 (1.05-3.13)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.79 (1.00-3.20)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.16 (0.76-1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.25 (0.81-1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* P\u0026lt;0.1, **P\u0026lt;0.05, ***P\u0026lt;0.01, ****P\u0026lt;0.001\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-urban-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jurh","sideBox":"Learn more about [Journal of Urban Health](https://www.springer.com/journal/11524)","snPcode":"11524","submissionUrl":"https://www.editorialmanager.com/jurh","title":"Journal of Urban Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"healthcare utilisation, informal settlements, inequalities, catastrophic expenditures, costs","lastPublishedDoi":"10.21203/rs.3.rs-5131613/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5131613/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The fragile health system in Sierra Leone undermines healthcare, leading to substantial patient costs. We aimed to estimate the economic burden and inequalities in healthcare in urban informal settlements in Freetown, Sierra Leone. A cross-sectional survey was conducted in three informal settlements in Freetown in April and May 2023 to collect data on healthcare usage within and outside the boundaries of the informal settlements. Catastrophic expenditures were estimated using the payer’s household budget. Logistic regression explored socio-economic characteristics associated with catastrophic expenditures. Inequalities in healthcare expenditures were assessed through concentration curves and indices. 2,575 participants reported healthcare utilisation. Dwarzark (US$6.9) and Moyiba (US$7.1) had higher costs than Cockle Bay (US$5.5) when utilising healthcare within the communities. Households incurred higher costs when seeking healthcare outside their informal settlements than within (US$14 vs US$ 7). Over half of the households across the settlements incurred catastrophic expenditures when seeking care outside the communities (57%), with the poorest wealth quintile (poorest: 89%; wealthier: 12%) incurring in higher incidence. Attending informal healthcare had a protective effect against catastrophic expenditure for healthcare within the communities. Age +35, residence in Dwarzark and Moyiba and length of residence +4 years were associated with catastrophic expenditures. Healthcare expenditure was progressive in Dwarzark and equally distributed across wealth quintiles in the other communities. Our findings indicate the need to provide accessible, affordable and good-quality healthcare within communities to alleviate the catastrophic costs of healthcare utilisation. The regulation of informal health providers and their integration into the formal health system should be considered.","manuscriptTitle":"The Economic Burden of Healthcare Utilisation: Findings from a Health and Well-being Survey in Informal Settlements of Freetown, Sierra Leone","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-20 00:45:56","doi":"10.21203/rs.3.rs-5131613/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept as is","date":"2024-12-18T11:37:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-17T19:40:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Urban Health","date":"2024-12-16T06:21:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-urban-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jurh","sideBox":"Learn more about [Journal of Urban Health](https://www.springer.com/journal/11524)","snPcode":"11524","submissionUrl":"https://www.editorialmanager.com/jurh","title":"Journal of Urban Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c057e4d8-e03b-4b89-a3b3-53f659a5eaa1","owner":[],"postedDate":"December 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:08:15+00:00","versionOfRecord":{"articleIdentity":"rs-5131613","link":"https://doi.org/10.1007/s11524-025-00960-5","journal":{"identity":"journal-of-urban-health","isVorOnly":false,"title":"Journal of Urban Health"},"publishedOn":"2025-03-10 15:58:23","publishedOnDateReadable":"March 10th, 2025"},"versionCreatedAt":"2024-12-20 00:45:56","video":"","vorDoi":"10.1007/s11524-025-00960-5","vorDoiUrl":"https://doi.org/10.1007/s11524-025-00960-5","workflowStages":[]},"version":"v1","identity":"rs-5131613","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5131613","identity":"rs-5131613","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}