Exploring Self-Reported Morbidity, Health-Seeking Behavior and Associated Factors in Ethiopia: Evidence from National Health Equity Survey 2022/2023

Exploring Self-Reported Morbidity, Health-Seeking Behavior and Associated Factors in Ethiopia: Evidence from National Health Equity Survey 2022/2023 | 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 Exploring Self-Reported Morbidity, Health-Seeking Behavior and Associated Factors in Ethiopia: Evidence from National Health Equity Survey 2022/2023 Desalew Zelalem, Aderajew Mekonnen Girmay, Hiwot Achamyeleh, Tsegaye Getachew, and 20 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8280763/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Introduction Self-report is one of the easiest, cheapest and most widely used methods of collecting data about individuals’ health and risk factor status. Many health studies use self-reported data to assess the prevalence of given risk factors or health behaviors in the community. The objective of this study was to determine the level of perceived morbidity, treatment seeking behavior and associated factors using nationally representative self-reported morbidity data. Methods This study was embedded from a community based, national representative survey which was conducted from September 27 and December 20, 2022 in ten regions and two city administrations. Data collection in the eleventh region, i.e., Tigray region, was carried out separately from December 28, 2023 to February 14, 2024, due to contextual constraints. The survey covered 441 enumeration areas within 11 regional states and two city administrations. A two-stage stratified cluster sampling was employed to select the eligible households and a total of 9,157 household were selected. Data were collected through face-to-face interview with structured questionnaires. Descriptive statistics such as frequency with percentages and mean with standard deviations were employed to describe participants’ characteristics. Bivariate analysis was conducted to assess the association between treatment seeking behavior and independent variables. Mixed effects logistic regression was employed to determine predictors of treatment seeking behavior. Results A total of 2030 (18.02%) household heads experienced at least one perceived morbidity in the past 12 months prior to the survey date. Of these, 776(16.21%) were urban and 1254(18.71%) were rural residents. About 1793(89.4% with 95%CI: 3.76, 3.80) sought treatment to their perceived morbidity. In the multivariable analysis, Afar (AOR=0.47; 95%CI: 0.35, 0.64), Amhara(AOR=0.45; 95%CI: 0.33, 0.61), Oromia(AOR=0.26; 95%CI:0.18, 0.38), Ethiopia Somali(AOR=0.31; 95%CI: 0.21, 0.46), Benishangul-Gumuz (AOR=0.13; 95%CI: 0.09, 0.19), SNNPR(AOR=0.51; 95%CI: 0.37, 0.70), Sidama(AOR=0.59; 95%CI: 0.40, 0.87), South west-Ethiopia(AOR=0.23; 95%CI: 15, 35), Harari(AOR=0.29; 95%CI: 19, 45), and Dire Dawa(AOR=0.80; 95%CI: 0.53, 1.00) were found to be less likely to seek treatment to their perceived morbidity compared to Tigray regional state while Gambela was 2.7 (95%CI:2.07, 3.63) times more likely to seek treatment compared to Tigray regional state. Other factors associated with treatment seeking behavior were being male (AOR, 1.2; 95%CI: 1.00, 1.37), own agricultural land (AOR=1.6; 95%CI: 1.37, 1.80), safety net beneficiaries (AOR=1.5; 95%CI: 1.27, 1.86), self-rated health status (very poor, AOR=2.4; 95%CI: 1.53, 3.90; poor, AOR=5.6; 95%CI: 4.28, 7.44; Neutral, AOR=2.9; 95%CI: 2.21, 3.68; Good, AOR=1.9; 95%CI: 1.55, 2.40) showed statistically significant association. Conclusion This study revealed that majority of the participants sought treatment from health facility for their perceived illness. However, there were significant disparities across the regions and participant characteristics. Thus, the study finding underscores the need for targeted interventions to address inequalities and identified barriers to enhance equitable health care utilization across the regions. perceived morbidity treatment seeking National Health Equity Survey Figures Figure 1 1. Introduction Health promotion programs have long been proposed on the idea that providing knowledge about causes of ill health and choices available will promote a change in individual behavior leading towards better health seeking behavior. It has been thought that it positively influences progressive behaviors that seek to advance health potential, to continuously improve one’s life style (1, 2). However, it has been recognized that providing education and knowledge at the individual level is not sufficient in itself to promote a change in behavior. A number of studies on health seeking behavior demonstrated that multitudes of factors influence an individual’s behavior at a given time and place (3, 4). There is a growing concern that factors promoting ‘good’ health seeking behaviors are not rooted solely in the individual, they also have a more dynamic, collective and interactive element (5-8). Assessing both individuals’ and populations’ health risk status and behaviors is important in health promotion. Reliable, valid and appropriate information are prerequisites to accurately assess the prevalence of a target behavior, to identify and describe the characteristics of those individuals at greater risk, or to assess the efficacy of interventions aimed at reducing risk factors. Self-report is one of the easiest, cheapest and most widely used methods of collecting data about individuals’ health and risk factor status. Many health studies use self-reported data to assess the prevalence of given risk factors or health behaviors in the community or to evaluate the success or failure of health promotion interventions (9). Early health care utilization and adherence to effective treatment can reduce morbidity, disability and mortality (10). However, there are growing evidences in inequity and inequality to access health care services (11). Previous studies showed that inequalities in health care utilization and health outcomes between the different socio-economic and demographic characteristics are pervasive (12). The problem of partiality in health care utilization is getting sever in Sub-Saharan Africa including Ethiopia (13). Although both infectious and non-infectious diseases are becoming common in Ethiopia, the health care seeking behavior, utilization, and accessibility and availability is uneven among the different socio-economic and demographic groups of Ethiopians ((14). Thus healthcare-seeking behavior is a complex process that involves a number of factors and hence requiring contextual exploration among the various socio-economic and demographic characteristics of the populations so as to frame recommendations that will help with the design of health care policies and programs (15). Therefore, in this study we explored self-reported morbidity, health seeking behavior and factors associated to health seeking behavior of the household heads of Ethiopian population using nationally representative data. 2. Methods 2.1. Study Area Description Ethiopia is a country located in Northeastern part of Africa with latitudes between 3.30 to 15.00N and longitudes between 33.00 to 48.00E. The surface area of the country is approximately 1.1 million square kilometers. The altitude of the country ranges from the lowlands below 500 meters above the sea level and the highlands with peaks reaching up to Ras Dashen at 4,550 meters above sea level ( 16 ). The country consists of 13 administrative regions including two city administrations. There are more than 353 hospitals, 3706 health centers and more than 17,561 health posts in the country ( 17 ). Although the socio-demographic index and life expectancies improved and age standardized all-cause death rates declined in the country over a period of three decades (between 1990 to 2019), regional disparities still remain high. Life expectancy has increased from 46.91 years in 1990 to 68.84 years in 2019. The highest death rate was in Afar, at 1353.38 per 100,000 while the lowest was in Addis Ababa compared to other regions ( 18 ). The burden of both communicable and non-communicable diseases is high in the country ( 19 ). Study Design and Sampling This study was based on community-based cross-sectional design and took advantage of national household data that were representative of the country. The survey was conducted across ten regions and two city administrations between September 27 and December 20, 2022. Data collection in the eleventh region, i.e., Tigray region was carried out separately from December 28, 2023 to February 14, 2024 due to the security problem in the region. A two-stage stratified cluster sampling method was employed to select the households, and a total of 147,602 enumeration areas (EAs) obtained from the Ethiopian Central Statistical Service (CSS) were accounted for selecting the study enumeration areas. Proportional allocation to size was used to select study enumeration areas, considering the Urban and rural proportions in each region. Consequently, a total of 442 enumeration areas (172 urban and 270 rural areas). Logistical constraints prevented access to one enumeration area, and 441 enumeration areas ended up being included in the survey. The Tigray region, which was initially excluded due to security reasons, was later included when the situation was restored to normalcy, and 55 additional enumeration areas were identified. From each enumeration area, a total of 25 households were randomly selected. In the second phase, the simple random sample of each enumeration area was obtained by drawing 22 households, except in Tigray, where the number of households per enumeration area was between 16 and 26, depending on the accessibility of the field. The sample finally had 9,157 households with complete interview in 11 regions and two city administrations. The sampling weight was calculated to balance the selection probabilities, non-response, and post-stratification, which, in turn, allowed making an inference about the national, regional, and urban-rural strata. The detailed calculations and methodology of the sampling procedures are thoroughly explained in the National Health Equity Survey (NHES) report (ephi.gov.et/wp-content/uploads/2025/04/NHES2022_23_ETHfinalreport_I_azHSRDEPHI.pdf). 2.3 Data Sources The NHES database includes geo-referenced, household-level data that describes socio-demographic factors; health services use, and access and equity perceptions. The sample of analysis comprised 9,157 households, which had sufficient statistical power to conduct a multilevel analysis. The area of representativeness was maintained through the implementation of the sampling weight, which was adjusted to the chosen selection probabilities, non-response, and post-strata adjustments. 2.4 Data Collection Procedures Data were collected through a face-to-face interview by trained data collectors with an expert of the health office, nursing, and laboratory professionals. Pretested structured questionnaires, were used to collect the socio-demographic and health-seeking behavioral characteristics of the participants. All the questionnaires were adapted from the Ethiopian Demographic and Health Survey (EDHS) and the World Health Organization equity modules (ephi.gov.et/wp-content/uploads/2025/04/NHES2022_23_ETHfinalreport_I_azHSRDEPHI.pdf). Source population All household heads in Ethiopia who were aged 18 years and above, permanent residents and with women in the ages of 15 to 49 years in the household. Study population All household heads in the country who were aged 18 years and above, permanent residents and with women in the ages of 15 to 49 years in the households and included in the study. Inclusion and exclusion criteria : Inclusion criteria : The questions used to determine eligibility of participants included household heads or their spouses who satisfied the following criteria: 18 years of age and above, permanent residents; women between the ages of 15 and 49 years. Households that had incomplete interview data or were missing GPS coordinates, or left out important variables were not included in the analytic sample. Exclusion criteria All household heads in the country who were aged 18 years and above, who were not permanent residents and have no women in the ages of 15 to 49 years in the household and who were not able to respond to the questions as the result of serious illness during the survey. 2.5. Variables and Measurements The main outcome variable of this study was the health seeking behavior which has been defined as any action performed by individuals to search for a remedy due to the manifestation of symptoms for self-perceived health problems or illness ( 20 , 21 ). Thus, the dependent variable was treatment seeking behavior coded as 1 if the household head claims sought treatment to her/his recent perceived morbidity or 0 otherwise. Exposure variables include the different socio-economic and demographic variables such as region, age, gender, marital status, religion, education, occupation, residence, wealth quintile, family size, ownership of agricultural land, ownership of bank account, safety net beneficence, enrollment in community-based health insurance and ownership of dwelling house. The level of education was categorized as No education, Primary (1-8grades), Secondary (9-12grades), Technical/vocational training, and Higher education. Age of the heads was categorized as 18–24 years, 25–35 years, 36–49 years, 50–60 years and above sixty years. Marital status of household heads was also categorized as single, co-habituating, married, widowed, divorced/separated. 2.6. Data Quality Assurance The questionnaires were initially prepared in English and translated into five local languages, such as Amharic, Afaan Oromo, Tigrinya, and Somali. The data collectors used the translated tool for data collection, and the CSPro software was used for data collection purposes. Eight days of training were provided for data collectors and supervisors, and a pilot test was conducted before the actual data collection period. Regular supervision, spot checking, and daily feedback and back-checks were conducted by the supervisors, regional and central coordinators. In addition, reconciled duplicate household entries and promoted the safe transmission of data, which was done using the Internet File Streaming System (IFSS). The encrypted surveys were sent to the server of the Ethiopian Public Health Institute (EPHI), enhancing the internal validity of the data on health-seeking behavior and predictors. 2.7. Data Management and analysis Survey weights were applied to ensure nationally representative estimates. The descriptive statistics, such as frequency with percentages and mean with standard deviation, were used to describe the household characteristics, perceived morbidity, and treatment seeking behavior. Multi-stage sampling and unequal probabilities of selection to fit the complicated survey design used sampling weights in all analyses and determined weighted frequencies and weighted means to provide nationally representative estimates and correct design-induced variance inflation. Bi-variable logistic regression analyses were conducted to see the association between dependent variable and independent variables and determine variables to be included in the multivariable analysis. The variables with a p-value < 0.25 in the bi-variable analysis were considered for building the final model. Mixed effects logistic regression is used to model binary outcomes (like yes/no or success/failure) when the data is clustered or hierarchically structured. Since the outcome variable in our study is binary, i.e., sought treatment or not to their perceived morbidity and the data is clustered or hierarchically structured in which zone is nested in region and woreda is nested in zone we fitted mixed effects logistic regression to determine predictors of household heads treatment seeking behavior. Model diagnostics were included as the likelihood ratio tests of a nested model comparison and the analysis of the extracted residuals to identify the goodness-of-fit testing. Multicollinearity was checked through the Variance inflation factor and the pairwise correlation matrix, using the ordinary least squares method. Consequently, variables with VIF > 10 and the pairwise correlation > 0.8 were excluded. The final optimal mode was selected based on the lower value of AIC and BIC, and variables with a p-value < 0.05 in the final model were considered as significant predictors. The estimated population parameters were reported and interpreted as adjusted odds ratios (AORs) with 95% confidence intervals (CIs). All the analysis were done using Stata version 14. Ethical considerations The study was conducted according to the principles of the Declaration of Helsinki. Ethical and scientific clearance was obtained from Ethiopian Public Health Institutional Review Board (IRB). And then copy of the ethical clearance certificate was sent to each region, and letter of cooperation was also sent and communicated to regions, city administrations, Zones, Woredas and Kebeles up on which successful cooperation and support had been obtained from the respective bodies. The basic ethical principles of autonomy, confidentiality, benefits and no harms were thoroughly examined. To safeguard the autonomy of the study participants, objectives of the research were clearly communicated and an informed, voluntary, written and signed consent were obtained prior to data collection. With regard to maintaining anonymity and confidentiality, names of the participants were not mentioned in the questionnaires and there was no way to identify any participant by name, except by research team. Privacy of study participants was maintained during the interview. No person had access to the information collected from the study participants except the research team. Furthermore, the participants were informed that they have the right to refuse taking part in the study or discontinue at any stage of the interview. The study participants involved in this study were offered valuable information on proper medical treatment seeking behavior. Those who were found seek during the survey referred to the nearby health facility. The study did no harm that should be declared, except for consuming the participants’ valuable time. 3. Results Socio-Economic and Demographic Characteristics of the Study Participants Of the total household heads (9157) included in the study, 2030 (18.02%) experienced at least one perceived morbidity in the past 12 months prior to the survey date. About 3621 (27.66%) study participants were urban dwellers while 5536 (72.34%) were rural residents. About 85.82% of household heads fall in the age category of 25 to 49 years with mean age of 36.85 years and SD ± 9.47 years. Majority of the respondents were males (88.6%) and married (94.8%). About 42.8% household heads were illiterate and 35.4% primary level educated while nearly half of household heads (51.6%) were employed in farmer/pastoralists and more than half (58.11%) of the household heads had family size four and more than four family members. About 4248(58.11%) had agricultural land, 4713(51.82%) had Bank Account, 872(6.11%) safety net beneficiary, 2813(50.50%) were enrolled to community-based health insurance, 6240(74.06%) had own dwelling house, 793(8.31%) free of charge/subsidized, 989(5.58%) rented from kebele/Agency, 1110(11.87%) rented from individuals and 25(0.18%) other types of dwelling houses (Table 1 ). Table 1 Socio-Economic and Demographic Characteristics of the household heads in Ethiopia 2022/23 Variables Frequency (n) Weighted proportion (%) Region Tigray 1080 0.97 Afar 633 0.98 Amhara 914 27.35 Oromia 955 40.51 Ethiopian Somali 424 3.19 Benishangul Gumuz 708 0.91 SNNPR 811 12.55 Sidama 724 3.38 South west-Ethiopia 701 4.22 Gambela 538 0.39 Harari 399 0.19 Addis Ababa 736 4.95 Dire Dawa 534 0.4 Age of Household Heads 18_24 404 4.35 25_35 4376 47.46 36_49 3476 38.36 50_60 707 7.86 60+ 193 1.96 Gender of Household Heads Male 7653 88.6 Female 1503 11.4 Marital Status of Household Heads Single 51 0.31 Co-habitation 10 0.18 Married 8570 94.8 Widowed 280 2.54 Divorced/Separated 245 2.17 Religion of Household Heads Orthodox 3924 47.44 Protestant 2173 17.76 Muslim 2989 34.03 Catholic 59 0.65 Other 11 0.12 Education of Household Heads No education 3365 42.80 Primary(1-8grades) 3123 35.40 Secondary(9-12grades) 1474 13.14 Technical/Vocational 403 2.95 Higher education 791 5.71 Occupation of Household Heads Government employee 863 6.09 Private employee 714 4.74 NGO employee 75 0.41 Merchant/Trader 672 5.38 Farmer/Pastoralist 3727 51.61 Homemaker/Housewife 2324 26.17 Student 60 0.52 Laborer 373 3.87 Unemployed 297 0.96 Other 51 0.25 Residence of Household Heads Urban 3621 27.66 Rural 5536 72.34 Wealth quintile Poorest 1833 26.64 Poor 1830 25.58 Moderate 1832 19.78 Rich 1834 14.80 Richest 1828 13.20 The household heads were asked whether they encountered perceived morbidity in the past 12 months prior the survey date. Accordingly, about 2030 (18.02% with 95%CI: 1.77, 1.79) household heads reported perceived morbidity in the last 12 months prior to the survey date. There was disparity in the level of reported perceived morbidity between urban and rural areas., i.e., 776 (16.21%) urban and 1254(18.71%) rural household heads reported experiencing at least one perceived morbidity in the last 12 months prior to the survey date. About 775(14.23%) household heads with less than four family members and 1255(20.99%) with four and above four family members (X 2 = 69.80, P-value = 0.000); 1052(19.88%) who own agricultural land and 978(15.44%) who had no agricultural land (X 2 = 29.73, P-value = 0.011); 1018(18.05%) who had Bank Account and 1012(17.98%) who had no Bank Account (X 2 = 0.01, P-value = 0.960); 576(20.05%) who enrolled to community based health insurance and 1454(15.94%) who were not enrolled to community based health insurance (X 2 = 26.22, P-value = 0.006); 305(35.52%) who were beneficiaries of safety net program and 1725(16.88%) who were not beneficiaries of safety net program (X 2 = 123.58, P-value = 0.000); 1443(19.29%) who had own dwelling houses, 158(12.40%) who own houses free of charge/subsidized, 250(17.81%) who own houses rented from kebele/Agency, 170(13.81%) who own houses rented from individuals and 9(41.16%) who own other types of houses (X 2 = 42.41, P-value = 0.015); from those household heads who are less than two hours walking distance from nearest health facility 5978(19.05%), from those from two to five hours walking distance 394(37.60%), from those who at walking distance of above five hours 122(23.84%) and from those who don’t know distance to the nearest health facility 2663(10.71%) (X 2 = 265.90, P-value = 0.000) reported experienced perceived morbidity in the 12 months prior to the survey date (Table 2 ). Table 2 Self-Reported Perceived Morbidity by Background Characteristics of Household Heads in Ethiopia 2022/23 Variable Experienced perceived morbidity in the last 12 months prior to the survey date Chi-square(X 2 ) P-value Yes, n (weighted%) No, n (weighted%) Total, n (weighted%) Age of Household Heads 18_24 91(21.27) 313(78.73) 404(100) 20.02 0.134 25_35 854(15.42) 3523(84.58) 4377(100) 36_49 823(19.29) 2653(80.71) 3476(100) 50_60 198(24.14) 509(75.86) 707(100) 60+ 64(24.35) 129(75.65) 193(100) Gender of Household Heads Male 1666(17.05) 5987(82.95) 7653(100) 12.74 0.020 Female 363(25.52) 1140(74.48) 1503(100) Marital Status of Household Heads Single 13(38.26) 38(61.74) 51(100) 6.62 0.520 Co-habitation 1(19.75) 9(80.25) 10(100) Married 1875(18.01) 6695(81.99) 8570(100) Widowed 84(16.52) 196(83.48) 280(100) Divorced/Separated 56(17.13) 189(82.87) 245(100) Religion of Household Heads Orthodox 886(18.23) 3038(81.77) 3924(100) 14.74 0.257 Protestant 577(19.69) 1596(80.31) 2173(100) Muslim 554(16.93) 2435(83.07) 2989(100) Catholic 8(7.93) 51(92.07) 59(100) Other 4(51.09) 7(48.91) 11(100) Education of Household Heads No education 797(19.06) 2568(80.94) 3365(100) 18.14 0.152 Primary (1-8grades) 683(18.08) 2440(81.92) 3123(100) Secondary(9-12grades) 306(15.80) 1168(84.20) 1474(100) Technical/vocational 74(12.60) 329(87.40) 403(100) Higher education 169(17.76) 622(82.24) 791(100) Occupation of Household Heads Government employee 164(13.16) 699(86.84) 863(100) 29.13 0.012 Private employee 169(25.72) 545(74.28) 714(100) NGO employee 21(18.08) 54(81.92) 75(100) Merchant/Trader 145(16.99) 527(83.01) 672(100) Farmer/Pastoralist 892(19.35) 2835(80.65) 3727(100) Homemaker/Housewife 443(15.99) 1881(84.01) 2324(100) Student 15(25.24) 45(74. 76) 60(100) Laborer 100(11.07) 273(88.93) 373(100) Unemployed 69(23.55) 228(76.45) 297(100) Other 11(20.42) 40(79.58) 51(100) Region Tigray 376(35.76) 704(64.24) 1080(100) 100.90 0.000 Afar 117(18.24) 516(81.76) 633(100) Amhara 194(23.22) 720(76.78) 914(100) Oromia 117(11.85) 838(88.15) 955(100) Ethiopia Somali 113(28.00) 311(72.00) 424(100) Benishangul Gumuz 48(7.22) 660(92.78) 708(100) SNNPR 157(18.91) 654(81.09) 811(100) Sidama 185(26.59) 539(73.41) 724(100) South west-Ethiopia 108(14.76) 593(85.24) 701(100) Gambela 281(49.98) 257(50.02) 538(100) Harari 38(11.22) 361(88.78) 399(100) Addis Ababa 171(23.96) 565(76.04) 736(100) Dire Dawa 125(20.87) 409(79.13) 534(100) Wealth quintile Poorest 437(17.81) 1396(82.19) 1833(100) 1.152 0.979 Poor 480(20.72) 1350(79.28) 1830(100) Moderate 376(16.95) 1456(83.05) 1832(100) Rich 380(15.12) 1454(84.88) 1834(100) Richest 357(18.06) 1471(81.94) 1828(100) Residence of Household Heads Urban 776(16.21) 2845(83.79) 3621(100) 0.201 0.807 Rural 1254(18.71) 4282(81.29) 5536(100) Health Care Seeking Behaviors of the Household Heads by Background Characteristics Of the total 2030 household heads who reported perceived morbidity in the last 12 months prior to the survey date, 1793 (89.4%) (95%CI: 3.76, 3.80) sought treatment to their recent perceived morbidity while 237(10.6%) household heads did not seek treatment to their recent perceived morbidity. About 688(88.75%) household heads with family size less than four members and 1105 (89.82%) with family members four and above four (X 2 = 0.560, P-value = 0.650); 952 (90.80%) household heads who own agricultural land and 841(87.02%) household heads with no agricultural land (X 2 = 7.084, P-value = 0.157); 935(91.95%) household heads with Bank Account and 858(86.74%) household heads with no Bank Account (X 2 = 14.576, P-value = 0.035); 259(85.95%) household heads who were beneficiaries of safety net and 1534(89.93%) household heads with no Bank Account (X 2 = 3.599, P-value = 0.327); 527(92.64%) household heads who enrolled to community based health insurance and 1266(85.35%) HH heads with no community based health insurance (X 2 = 28.071, P-value = 0.000); 1299(90.13%) household heads with own dwelling house, 131(86.91%) household heads owning Subsidized/Free of charge house, 217(86.80%) household heads owning houses rented from Kebele/Agency, 140(87.09%) household heads owned house rented from individuals, 6(81.15%) household heads owned other types of houses (X 2 = 4.082, P-value = 0.732); household heads who rated their health condition as very poor 36(82.18%), poor 305(81.37%), Neutral 290(89.39%), Good 1040(91.81%), Very Good 122(94.55%) (X 2 = 41.202, P-value = 0.021); household heads who are at walking distance of less than two hours from the nearest health facility 1379(91.08%), those who are at walking distance from two to five hours 114(84.46%), who are at walking distance of above five hours 39(90.44%) and those who don’t know the distance from nearest health facility 261(87.15%) (X 2 = 13.681, P-value = 0.201) sought treatment to their recent perceived morbidity (Table 3 ). Table 3 Treatment Seeking Behavior of Household Heads to their Perceived Morbidity by Background Characteristics in Ethiopia 2022/23 Variable Treatment seeking of household heads to the recent perceived morbidity Chi-square (X 2 ) P-value Yes, n (weighted%) No, n (weighted%) Total, n (weighted%) Age of Household Heads 18_24 83(93.63) 8(6.37) 91(100) 20.02 0.134 25_35 769(91.70) 85(8.30) 854(100) 36_49 713(85.97) 110(14.03) 823(100) 50_60 173(90.56) 25(9.44) 198(100) 60+ 55(96.30) 9(3.70) 64(100) Gender of Household Heads Male 1488(90.52) 178(9.48) 1666(100) 12.74 0.020 Female 305(83.90) 58(16.10) 363(100) Marital Status of Household Heads Single 10(97.81) 3(2.19) 13(100) 6.62 0.520 Co-habitation 1(100.00) 0(0.00) 1(100) Married 1662(89.42) 213(10.58) 1875(100) Widowed 73(81.50) 11(18.50) 84(100) Divorced/Separated 47(96.17) 9(3.83) 56(100) Religion of Household Heads Orthodox 774(88.76) 112(11.24) 886(100) 14.74 0.256 Protestant 543(93.44) 34(6.56) 577(100) Muslim 467(88.23) 87(11.77) 554(100) Catholic 5(58.73) 3(41.27) 8(100) Other 4(100.00) 0(0.00) 4(100) Educational Status of Household Heads No education 682(86.33) 115(13.67) 797(100) 18.14 0.152 Primary(1-8grades) 614(92.54) 69(7.46) 683(100) Secondary(9-12grades) 273(91.72) 33(8.28) 306(100) Technical/Vocational Training 71(90.71) 3(9.29) 74(100) Higher education 153(89.98) 16(10.02) 169(100) Occupation of Household Heads Gov’t employee 152(95.78) 12(4.22) 164(100) 29.13 0.012 Private employee 145(89.04) 24(10.96) 169(100) NGO employee 17(81.40) 4(18.60) 21(100) Merchant/Trader 136(95.25) 9(4.75) 145(100) Farmer/Pastoralist 812(90.49) 80(9.51) 892(100) Homemaker/Housewife 371(84.48) 72(15.52) 443(100) Student 13(96.39) 2(3.61) 15(100) Laborer 86(96.53) 14(3.47) 100(100) Unemployed 53(77.16) 16(22.84) 69(100) Other 8(89.54) 3(10.46) 11(100) Region Tigray 310(81.84) 66(18.16) 376(100) 100.90 0.000 Afar 114(97.29) 3(2.71) 117(100) Amhara 182(92.60) 12(7.40) 194(100) Oromia 105(89.06) 12(10.94) 117(100) Ethiopia Somali 72(62.59) 41(37.41) 113(100) Benishangul-Gumuz 46(95.80) 2(4.20) 48(100) SNNPR 143(91.69) 14(8.31) 157(100) Sidama 177(95.82) 8(4.18) 185(100) South west-Ethiopia 101(92.79) 7(7.21) 108(100) Gambela 268(93.97) 13(6.03) 281(100) Harari 31(83.03) 7(16.97) 38(100) Addis Ababa 144(83.97) 27(16.03) 171(100) Dire Dawa 100(80.37) 25(19.63) 125(100) Wealth quintile Poorest 385(88.38) 52(11.62) 437(100) 1.152 0.979 Poor 426(90.15) 54(9.85) 480(100) Moderate 332(89.64) 44(10.36) 376(100) Rich 337(90.17) 43(9.83) 380(100) Richest 313(89.04) 44(10.96) 357(100) Residence of Household Heads Urban 683(88.92) 93(11.08) 776(100) 0.201 0.807 Rural 1110(89.62) 144(10.38) 1254(100) Respondents were asked to rate their health status and tell how they feel about their health situation. As the result, 144(1.87%) replayed their health situation was very poor, 773(10.26%) poor, 1202 (11.82%) neutral, 5872(61.23%) good and 1166(14.83%) very good. From a total of 1768 household heads who get treatment for their recent illness, 39(0.88%) from home-based care, 61(1.46%) from local drug venders/pharmacy, eight (0.22%) from traditional healers and 1656(97.43%) get treatment from modern health facilities (i.e., private health facility 445 (21.61%), government hospital 374(16.30%), government health center 741(57.90%), government health post 81(1.28%), NGO health facilities 15(0.34%)) and the remaining four (0.01%) from other sources. The respondents were also asked about the quality of care they received from the health facility where they received treatment to the recent perceived morbidity. Accordingly, 28(2.09%) perceived to be very poor, 212(12.51%) as poor, 278(10.47%) neutral, 1035(66.51%) perceived as good and 107(8.42%) perceived to be very good. Further the respondents were asked the health professionals who checked their perceived morbidity and as the result 523(22.87%) Doctor, 620(24.55%) Nurse, 15(1.42%) midwife, 218(18.26%) health officer, 21(0.53%) HEW, 3(0.18%) other and 260(32.34%) they do not know the health professional who checked their perceived morbidity. The question on the nearest health facility to the household was also asked and as the result 2612 (25.07%) government health post, 4978 (64.50%) government health center, 938 (5.53%) government hospital, 30 (0.43%) NGO health facilities and 599 (4.47%) private health facilities. Those household heads who reported did not seek treatment to their perceived morbidity were further asked their reasons for not seeking treatment. As the result majority 109 (46.19%) lack of finance and about eight (3.39%) reported health facility far as the reasons for not seeking treatment to their perceived morbidity (Fig. 1 ). Factors Associated with Household heads’ health seeking behaviors In the bivariate analysis, sex of household head, region, family size, ownership of agricultural land, safety net beneficence, enrollment to community-based health insurance, and self-rated health status were associated with health seeking behavior at P-value < 0.25 and entered into multivariable analysis. Model fitness to the data was assessed using log likelihood ratio test, AIC and BIC. As the result a good model with log likelihood ratio of chi2 = 76.33 with P-value = 0.000; AIC = 8222.092 and BIC = 8393.016 was fitted. In the final model, self-rated health status of household head, safety net utilization, ownership of agricultural land, sex of household head and region were found to be significantly associated with household heads’ treatment seeking to the recent perceived morbidity. As can be seen in the final model the zonal variance is 0.08 while woreda level variance is 0.69 (Table 4 ). Intraclass correlation (ICC) for Zone was 0.0194955 with standard error (0.0154332) and confidence interval (95%CI: 0.0040689, 0.0882278) and for Woreda it was 0.1891751 with standard error 0.0272165 and confidence interval (95%CI: 0.1414685, 0.2483164) which is indicating the proportion of variance accounted by Zone was about two percent while this proportion for Woreda was 18.92%. Table 4 Multilevel Mixed Effects Logistic Regression Model Predicting Treatment Seeking Behavior of Household Heads in Ethiopia 2022/23 Variable AOR Std.Err P-value 95%CI Region Tigray (RC) 1 Afar 0.47 0.074 0.000 0.35, 0.64 Amhara 0.45 0.069 0.000 0.33, 0.61 Oromia 0.26 0.049 0.000 0.18, 0.38 Ethiopia Somali 0.31 0.062 0.000 0.21, 0.46 Benishangul-Gumuz 0.13 0.025 0.000 0.09, 0.19 SNNPR 0.51 0.082 0.000 0.37, 0.70 Sidama 0.59 0.118 0.008 0.40, 0.87 South west-Ethiopia 0.23 0.051 0.000 0.15, 0.35 Gambela 2.74 0.393 0.000 2.07, 3.63 Harari 0.29 0.065 0.000 0.19, 0.45 Addis Ababa 0.80 0.125 0.159 0.59, 1.09 Dire-Dawa 0.80 0.118 0.050 0.53, 1.00 Gender of Household Heads Female (RC) 1 Male 1.17 0.096 0.052 1.00, 1.37 Family size of Household Heads Less than four members (RC) 1 Four & above four members 1.12 0.069 0.076 0.99, 1.26 Ownership of Agricultural land Have no agricultural land (RC) 1 Have agricultural land 1.57 0.111 0.000 1.37, 1.80 Safety Net Utilization Not utilizers (RC) 1 Utilizers 1.54 0.149 0.000 1.27, 1.86 Enrollment to CBHI Not Enrolled to CBHI (RC) 1 Enrolled to CBHI 1.10 0.085 0.211 0.95, 1.28 Self-rated Health Status of Household Heads Very poor 2.44 0.582 0.000 1.53, 3.90 Poor 5.65 0.795 0.000 4.28, 7.44 Neutral 2.85 0.372 0.000 2.21, 3.68 Good 1.93 0.216 0.000 1.55, 2.40 Very good (RC) 1 _cons 0.10 0.017 0.000 0.07, 0.14 zone var(_cons) 0.08 0.064 0.02, 0.38 zone > woreda var(_cons) 0.69 0.127 0.48, 0.99 LR test vs. logistic model: chi2( 2 ) = 76.33 Prob > chi2 = 0.0000 RC = Reference Category; AOR = Adjusted Odds Ratio; CBHI = Community Based Health Insurance; Std.Err = Standard Error; SNNP = Southern Nations, Nationalities and Peoples Regional State 4. Discussion Less than twenty percent (18.02%) of household heads included in the study reported suffered from some recent perceived morbidity. This observed burden of self-perceived morbidity was comparable with previously reported value in Addis Zemen, North-Western Ethiopia in which 18% of study participants reported illness with recall period of four weeks ( 22 ). The current finding is also comparable to the findings by Dodd et al., 2016 in India in which 22.3% of study participants reported suffered from self-reported morbidity ( 23 ). A study in Malaysia done on adults using national data also corroborates our finding with16.1% reported perceived morbidity ( 24 ). However, the finding of the current study is lower than the finding by Feyisa et al., 2020 in which 75% of the study participants reported they experienced morbidity at least once in the year before the interview ( 5 ). This difference could be due to the difference in the study population included in the two studies. In a study by Feyisa et al., 2020 the study participants were elderly aged 60 years and above while the study participants to the current study were adults aged 18 years and above. Another study in Esera District, SNNPR of Ethiopia indicated that 85.6% household heads reported at least one family member experienced perceived morbidity at least once in two months prior to the survey date which is higher than the current finding ( 6 ). This difference could be due to the fact that in our study the information was collected about the household heads while in the study of Begashaw et al., 2016 the information was collected about the family members. Higher proportion of women reported self-perceived morbidity than men, the finding which is consistent with previous findings ( 22 , 25 – 27 ). Other study conducted in Southern Brazil also showed that women were more likely to report morbidity than men ( 28 ). A study by Paul and Singh, 2017 in India using longitudinal data showed that self-reported morbidity was persistently higher among the female population compared to the male population irrespective of the types of morbidities reported ( 29 ). The proportion of household heads who suffered from perceived morbidity was higher for rural residents (18.71%) compared to urban dwellers (16.21%), the finding which corroborates with the findings in other studies ( 6 , 24 ). The current finding is different from the findings by Paul and Singh, 2017 in India in which urban residents reported higher prevalence of self-reported morbidity as compared to their rural counterparts for most of the morbidities ( 29 ). We have assessed health seeking behavior of household heads for their perceived morbidity and found that 89.4% sought treatment to their recent perceived morbidity. This finding is higher than the findings of other studies ( 5 , 6 ). This could be due to the fact that our current study covers the whole country and the study was conducted recently compared to the two studies and hence recent service expansions and changes to treatment seeking behaviors could account for the variation. However, the current finding is more or less comparable to the findings of systematic review by Haridoss et al., 2025 in which 72.72% ( 8 ) and a study by Belachew et al., 2025 in Bahir Dar, Ethiopia in 79.3% study participants ( 30 ) sought treatment for their existing health conditions. Our finding is also comparable to the findings of Kabir et al., 2025 in Bangladesh in which 80% study participants sought treatment to their recent perceived morbidity ( 31 ). There was gender disparity in treatment seeking for their perceived morbidity. Higher proportion of men (89.3%) reported sought treatment to their recent perceived morbidity compared to women (84%) counterparts. In multilevel analysis too, men were found to be 1.2 times more likely to seek treatment to their perceived morbidity compared to their counterpart women. This finding is comparable to the finding of a study by Belachew et al., 2025 in older adult men were found higher treatment seekers compared to their counterpart older adult women ( 30 ). This could be due to the fact that in the case of Ethiopia, men are usually bread winners and hence they could have better opportunity to get access to financial resource to seek treatment to their perceived morbidity. Our finding is in contrary to the findings by Wang et al., 2008 in which women were found more likely to seek treatment to their illness compared to men ( 32 ). The current finding is also contrary to the findings of Altameemi et al., 2024 in which women were found to be 1.3 times more likely to sought treatment compared to men ( 33 ). In our study majority of respondents (93.67%) sought treatment to their recent perceived morbidity from modern health facilities, mostly from government health facilities which is contrary to the findings by Haridoss et al., 2025 in India in which private health facilities were preferred over government facilities ( 8 ). This could be due to the fact that cost of treatment to illnesses would be lower in government health facilities compared to private health facilities in the case of Ethiopia. In the current study, financial constraints and illness not considered serious (together constituted 76.69%) were the major barriers for household heads who reported experienced perceived morbidity in the past year prior to the survey date but didn’t seek treatment to their perceived morbidity which is consistent with the findings by Haridoss et al., 2025 in India ( 8 ). Our finding is also consistent with the finding by Rahman et al., 2017 in Jorhat district of India in which for 43.25% of study participants who didn’t seek treatment to their illness the major impediment was financial constraint ( 34 ). A study in Bahir Dar, Ethiopia also corroborates our finding indicating that financial independence of study participants was associated with higher treatment seeking behavior ( 30 ). In the multilevel analysis region was significantly associated with treatment seeking behavior of household heads to their recent perceived morbidity. Afar, Amhara, Oromia, Ethiopia Somali, Benishangu-Gumuz, SNNPR, Sidama, South west-Ethiopia, Harari, and Dire Dawa were found to be less likely to seek treatment compared to Tigray Regional state which was taken as reference category. However, Gambela Regional State was 2.7 times more likely to seek treatment to recent perceived morbidity compared to Tigray Regional State. This variation could be due to the variations in health services coverage and quality of services and the variation in the level of health literacy among the regions. This finding is in line with the finding in India in which health care treatment seeking behavior varied across various regions of the country, particularly in eastern, north-eastern and western regions of the nation ( 35 ). Our finding is also concurrent to the finding by Kamal et al., 2025 in Pakistan in which the health seeking behavior of mothers varied across the regions of the country ( 36 ). Supporting prior evidences ( 5 , 34 ) our study specified that ownership of agricultural land was significantly associated with treatment seeking to their recent perceived morbidity in which household heads who own agricultural land were 1.6 times more likely to seek treatment to their recent perceived morbidity compared to household heads who had no agricultural land. Those household heads who were beneficiary of safety net were 1.5 times more likely to seek treatment to their recent perceived morbidity compared to household heads who were not beneficiary of safety net. This finding is comparable with other findings in which social protection schemes (both productive safety net program and the community-based health insurance scheme) enhanced the use of modern healthcare ( 37 – 39 ). A study by Tossou, 2025 in Togo also indicated the positive indirect effect of social safety net on beneficiary households with respect to healthcare utilization ( 40 ). Self-rated health status of household heads was significantly associated with treatment seeking behavior of household heads. Those household heads who rated their health status as very poor were 2.4 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health condition as very good which was reference category. Those household heads who rated their health condition as poor were 5.6 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health status as very good. Those household heads who rated their health condition as good were 1.9 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health condition as very good. These finding is comparable to the study by Mohan et al., 2025 in Malaysia in which study participants who rated their health status from poor to very poor were 3 times more likely to seek care to their morbidity compared to their counterparts who rated their health status from good to excellent ( 41 ). Similarly, a study by Noh et al., 2022 in Malaysia also indicated that the study participants who rated their health as poor to very poor were 2.9 times more likely to seek treatment than those who rated their health from good to excellent ( 24 ). A study in Bahir Dar, Ethiopia also substantiates our finding in which study participants who rate their health status as poor were higher in seeking treatment to their recent illness compared to those study participants who rated their health status as good ( 30 ). Limitations of the study This study has certain limitations which are inherent to the study design. It was a cross-sectional self-reported study with recall period of 12 months in which the study participants could forget some morbidities and treatment seeking behavior which may underestimate the level of morbidity in the population. Another limitation inherent to cross-sectional surveys is the difficulty to establish causal relationship. Data on perceived morbidity and treatment seeking behavior was collected only for the household heads and information about family members was not collected which might have again underestimated the prevalence of perceived morbidity in the population. 5. Conclusion The study revealed that majority of the participants sought treatment from health facility for their perceived morbidity. However, there were significant socio-economic and demographic and regional disparities in health seeking behavior. The factors that influence the health seeking behavior of population are unique for each socio-economic and demographic and regional category. Thus, the study findings underscore the importance of targeted interventions to address inequalities and identified barriers to enhance equitable health care utilization across the study participants’ characteristics and regions. Governmental and non-governmental organizations working on the wellbeing of the population could work on addressing regional and socio-economic disparities, empowering women, strengthening social protection schemes (Community Based Health Insurance and Productive Safety Net) and focusing on the rural and vulnerable population especially regarding improving access to healthcare services as well as their knowledge and literacy on seeking proper medical care through mass media approach. Declarations Data Sharing Statement Data analyzed and materials used for this article are available with the corresponding author and can be obtained on request. Ethical Approval and Consent Ethical approval was secured from Institutional Review Board (IRB) of Ethiopian Public Health Institute. Informed, voluntary, written and signed consent was obtained from the study participants. Acknowledgments We would like to acknowledge Ministry of Health for the financial and technical support in all phases of the survey. We would like to thank regional state Health Bureaus/Regional Health Institutes for their follow up for the success of the survey process. Our thanks also extend to the study participants, supervisors and data collectors for their kind cooperation. Competing interests The authors declared that they have no conflicts of interest for this work. Funding This research has been funded by Ministry of Health. Author Contributions Desalew Z, Aderajew MG, Hiwot A, Tsegaye G, Desallegn A, Arega Z, Girum T, Yitayh L, Weldemariam B, Kelem BA, Akberet L, Afewerk A, Ashenif T, Gebeyaw M, Wogayehu T, Tesfaye D, Senait A, Hanim T, Fikreselassie G, Daniel AC, Seboka A, Tefera T, Mesay H and Getachew T, all these authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising and critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work References Sanjiv Kumar PG. Health Promotion: An Effective Tool for Global Health. Indian Journal of Community Medicine. 2012;Vol 37/Issue 1/. Chi-Horng LiaoID SB. Success factors of health promotion: Evaluation by DEMATEL and M-DEMATEL methods—A case study in a non-profit organization. PLoS ONE 2021;16(12): e0260801. Nilanjana Ghosh IC, Manasi Chakraborty, Romy Biswas. Factors affecting the healthcare-seeking behavior of mothers regarding their children in a rural community of Darjeeling district, West Bengal. International Journal of Medicine and Public Health | Jan-Mar 2013 2013;Vol 3 (Issue 1). Asm Shahabuddin CNs, The´rèse Delvaux, Malabika Sarker, Alexandre Delamou, Azucena Bardajı, Jacqueline E. W. Broerse, Vincent De Brouwere. Exploring Maternal Health Care-Seeking Behavior of Married Adolescent Girls in Bangladesh: A Social-Ecological Approach. PLoS ONE. 2017;12(1): e0169109. Beshadu Bedada Feyisa SFD, Gosaye Mekonen Tefera,. Self-Reported Morbidity and Health-Seeking Behavior and its Predictors Among a Geriatric Population in Western Ethiopia: Community-Based Cross-Sectional Study. International Journal of General Medicine. 2020;13 1381–93. Bayu Begashaw FT, Hailay Abrha Gesesew. Health Care Seeking Behavior in Southwest Ethiopia. PLoS ONE. 2016;11(9). Shahinur Akter TA, Md. Habibur Rahman, Md. Firoz Raihan. Morbidity Patterns and Determinants of Healthcare‑Seeking Behavior Among Older Women in Selected Rural Areas of Bangladesh. Dr Sulaiman Al Habib Medical Journa. 2023;5:70–79. Madhumitha Haridoss DN, Shiny P. John, V. V. Anantharaman, Raji Rajesh Lenin, Rajiv Janardhanan. Health-seeking behavior and its determinants for non-communicable diseases in India - a systematic review and meta-analysis. Front Public Health 2025;13:1580824. Johanna NSGAS-FRWSN. The accuracy of self-reported health behaviours and risk factors relating to cancer and cardiovascular disease in the general population: a critical review. American Journal of Preventive Medicine. 1999;17(3):211–29. Bhutto AQ NN. Health-seeking behavior of people living with HIV/AIDS and their satisfaction with health services provided at a tertiary care hospital, Karachi, Pakistan. Eastern Mediterranean Health Journal. 2017;Vol. 23, No. 1. Gwatkin DR. Health inequalities and the health of the poor: What do we know? What can we do? Bulletin of the World Health Organization 2000;78 (1). Whitehead M. THE CONCEPTS AND PRINCIPLES OF EQUITY AND HEALTH. International Journal of Health Services. 1992;Vol. 22, No. 3:429-45. SRINIVAS GOLI DN, ANU RAMMOHAN, T. V. SEKHER, DEEPSHIKHA SINGH. DECOMPOSING THE SOCIOECONOMIC INEQUALITY IN UTILIZATION OF MATERNAL HEALTH CARE SERVICES IN SELECTED COUNTRIES OF SOUTH ASIA AND SUB-SAHARAN AFRICA. J Biosoc Sci, . 2017;50,:749–69. Solomon Yimer CH-H, Tilahun Yimaldu, Gunnar Bjune. Health care seeking among pulmonary tuberculosis suspects and patients in rural Ethiopia: a community-based study. BMC Public Health. 2009;9:454. Marinka van der Hoeven AK, Minrie Greeff. Differences in health care seeking behaviour between rural and urban communities in South Africa. International Journal for Equity in Health 2012;11:31. Aychiluhm SB, Gelaye, K. A., Angaw, D. A., Dagne, G. A., Tadesse, A. W., Abera, A., & Dillu, D. . Determinants of malaria among under-five children in Ethiopia: Bayesian multilevel analysis. BMC Public Health. 2020;20(1), 1468. Ashenif Tadele TT, Shegaw Mulu, Tamrat Awel, Tsedeke Mathewos, Dessalegn Melesse. National and subnational coverage and other service statistics for reproductive, maternal, newborn and child health using health facility data and surveys ETHIOPIA: Brief synthesis of the analyses. Countdown to 2030 / GFF / UNICEF / WHO workshop, Nairobi, Kenya. 2022. Misganaw A. Progress in health among regions of Ethiopia, 1990–2019: a subnational country analysis for the Global Burden of Disease Study 2019. Lancet 2022;399: :1322–35. WHO AR. Country Disease Outlook of Ethiopia. 2023. Tesfaye Falaha AW, Mengistu Meskele, Wolde Facha. Health Care Seeking Behaviour of Elderly People in Rural Part of Wolaita Zone, Southern Ethiopia. Health Science Journal. 2016;Vol. 10 No. 4: 14. Vineeta Shukla KR, Sinjita Dutta , Mausumi Basu. Self-Medication Practices and Health Seeking Behaviour among Residents of Selected Villages in A Block of West Bengal: A Mixed-Methods Study. Healthline Journal 2022;Volume 13 (Issue 1). Zein Ahmed Zein MF, Sirak Petras, Shimellis Alemayehu, Shumi Tala, Shiferaw Ayalew, Siyaum Tafese. PREVALENCE OF PERCEIVED MORBIDITY IN ADDIS ZEMEN TOWN, ETHOPIA. Ethiopian Journal of Health Development. 2017;2(1). Warren Dodd NK, Sally Humphries, Matthew Little. Self-reported morbidity and health services utilization in rural TamilNadu, India. Social Science & Medicine. 2016;161:118-25. Sarah Nurain Mohd Noh SJ, Ee Hong Tan, Yeung R’ong Tan, Iqbal Ab Rahim The Health-Seeking Behavior among Malaysian Adults in Urban and Rural Areas Who Reported Sickness: Findings from the National Health and Morbidity Survey (NHMS) 2019. Int J Environ Res Public Health 2022;19. 3193. ERVIN TOCI GB, NAIM JERLIU, KRISTINE SØRENSEN, NASER RAMADANI, BAJRAMHYSA, HELMUTBRAND. Health literacy, self-perceived health and self-reported chronic morbidity among older people in Kosovo. Health Promotion International. 2014;Vol. 30 No. 3. Suman Kanungo KB, Tanmay Mahapatra, Sanchita Mahapatra, Uchhal K. Bhadra, Kamalesh Sarkar. Perceived Morbidity, Healthcare-Seeking Behavior and Their Determinants in a PoorResource Setting: Observation from India. PLoS ONE 2015;10(5): e0125865. Mélusine Boon-Falleur BD, Coralie Chevallier. Does higher perceived risk of morbidity and mortality decrease risk-taking? R Soc Open Sci 2022;9: 220486. Raúl A. Mendoza-Sassi JUB. Gender differences in self-reported morbidity: evidence from a population-based study in southern Brazil. Cad Saúde Pública, Rio de Janeiro. 2007;23(2):341-6. Kalosona Paul JS. Emerging trends and patterns of selfreported morbidity in India: Evidence from three rounds of national sample survey. Journal of Health, Population and Nutrition 2017;36:32. Amare Belachew NC, Nasser Bagheri, Richard Burns. Identifying the Factors That Drive Health Service Utilization Among Healthy and Non‐Healthy Agers in a Sample of Older Ethiopians: A Cross‐Sectional Study. Health Science Reports. 2025;8:e70351. Ashraful Kabir MNK, Baki Billah. Self- reported health complaints and healthcare- seeking behaviour among adult people in rural Bangladesh: results from a cross- sectional study. BMJ Open. 2025;15:e086324. Jianming Wang YF, Hongbing Shen, Biao Xu. Gender difference in knowledge of tuberculosis and associated health-care seeking behaviors: a cross-sectional study in a rural area of China. MC Public Health. 2008;8:354. Mohammed Mkhailef Hawi Al-tameemi KB, Yousef Moradi, Ghobad Moradi, Amjad Mohamadi-Bolbanabad. Insights into determinants of health-seeking behavior: a cross-sectional investigation in the Iraqi context. Front Public Health 2024;12:1367088. Syeda Jesmin Rahman BRD, Gunjan Nath. Health seeking behavior of farming community in rural area of Titabor block in Jorhat district. nternational Journal of Community Medicine and Public Health. 2017;4(10):3854-8. Swaroop VKKSKYVKTPGSMS. Socioeconomic and Geographical Inequities in Burden and Treatment seeking Behavior for Hypertension among Women in the Reproductive Age (15–45 years) Group in India: Findings from a Nationally Representative Survey. Indian Journal of Public Health 2024;68(2):208-13. Asifa Kamal GHS, Afrah Hafeez, Maryam Siddiqa, Charles Owens. Mapping Geographic Disparities in Healthcare Access Barriers Among Married Women in Pakistan: Evidence from a Nationally Representative Survey. Healthcare. 2025;13. 2448. Hiwot Tilahun DDA, Geta Asrade, Amare Minyihun, Yihun Mulugeta Alemu. Factors for healthcare utilization and effect of mutual health insurance on healthcare utilization in rural communities of South Achefer Woreda, North West, Ethiopia. Health Economics Review. 2018;8:15. Essa Chanie Mussa TP, Gustavo Angeles, Martha Kibur, Frank Otchere, Amhara ISNP Evaluation Team. Impact of community-based health insurance on health services utilisation among vulnerable households in Amhara region, Ethiopia. BMC Health Services Research. 2023;23:55. Tadele Fentabil Anagaw EMM, Eyob Ketema Bogale , Eneyew Talie Fenta , Habitu Birhan Eshetu4, Natnael Kebede , Sintayehu Shiferaw Gelaw, Amare Zewdie, Tadele Derbew Kassie. Health-seeking behavior among noncommunicable disease patients globally, systematic review and meta-analysis. SAGE Open Medicine. 2023;11: 1 –10. Tossou Y. Evaluation of the impact of social safety net program on health care utilization in Togo. Health Economics Review. 2025;15:19. Devi Shantini Rata Mohan SJ, Adilius Manual, Nur Elina Abdul Mutalib, Sarah Nurain Mohd Noh, Iqbal Ab Rahim, Jabrullah Ab Hamid, Awatef Amer Nordin. Gender differences in health-seeking behaviour: insights from the National Health and Morbidity Survey 2019. BMC Health Services Research. 2025;25:900. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 02 Jan, 2026 Editor invited by journal 11 Dec, 2025 Editor assigned by journal 09 Dec, 2025 Submission checks completed at journal 09 Dec, 2025 First submitted to journal 04 Dec, 2025 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":15542,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReasons for Absence of Health Seeking Behaviors 2022/23\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8280763/v1/dc56c1e94ff061624723d616.png"},{"id":99802856,"identity":"4265235b-95e8-49be-a118-6f58e5180c8b","added_by":"auto","created_at":"2026-01-08 14:08:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2219752,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8280763/v1/db81b302-e8b5-401f-8090-9309be258b10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Self-Reported Morbidity, Health-Seeking Behavior and Associated Factors in Ethiopia: Evidence from National Health Equity Survey 2022/2023","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHealth promotion programs have long been proposed on the idea that providing knowledge about causes of ill health and choices available will promote a change in individual behavior leading towards better health seeking behavior. It has been thought that it positively influences progressive behaviors that seek to advance health potential, to continuously improve one’s life style (1, 2). However, it has been recognized that providing education and knowledge at the individual level is not sufficient in itself to promote a change in behavior. A number of studies on health seeking behavior demonstrated that multitudes of factors influence an individual’s behavior at a given time and place (3, 4). There is a growing concern that factors promoting ‘good’ health seeking behaviors are not rooted solely in the individual, they also have a more dynamic, collective and interactive element (5-8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAssessing both individuals’ and populations’ health risk status and behaviors is important in health promotion. Reliable, valid and appropriate information are prerequisites to accurately assess the prevalence of a target behavior, to identify and describe the characteristics of those individuals at greater risk, or to assess the efficacy of interventions aimed at reducing risk factors. Self-report is one of the easiest, cheapest and most widely used methods of collecting data about individuals’ health and risk factor status. Many health studies use self-reported data to assess the prevalence of given risk factors or health behaviors in the community or to evaluate the success or failure of health promotion interventions (9). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEarly health care utilization and adherence to effective treatment can reduce morbidity, disability and mortality (10). However, there are growing evidences in inequity and inequality to access health care services (11). Previous studies showed that inequalities in health care utilization and health outcomes between the different socio-economic and demographic characteristics are pervasive (12).\u0026nbsp;The problem of partiality in health care utilization is getting sever in Sub-Saharan Africa including Ethiopia\u0026nbsp;(13).\u003c/p\u003e\n\u003cp\u003eAlthough both infectious and non-infectious diseases are becoming common in Ethiopia, the health care seeking behavior, utilization, and accessibility and availability is uneven among the different socio-economic and demographic groups of Ethiopians ((14). Thus healthcare-seeking behavior is a complex process that involves a number of factors and hence requiring contextual exploration among the various socio-economic and demographic characteristics of the populations so as to frame recommendations that will help with the design of health care policies and programs (15). Therefore, in this study we explored self-reported morbidity, health seeking behavior and factors associated to health seeking behavior of the household heads of Ethiopian population using nationally representative data.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area Description\u003c/h2\u003e \u003cp\u003eEthiopia is a country located in Northeastern part of Africa with latitudes between 3.30 to 15.00N and longitudes between 33.00 to 48.00E. The surface area of the country is approximately 1.1\u0026nbsp;million square kilometers. The altitude of the country ranges from the lowlands below 500 meters above the sea level and the highlands with peaks reaching up to Ras Dashen at 4,550 meters above sea level (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The country consists of 13 administrative regions including two city administrations. There are more than 353 hospitals, 3706 health centers and more than 17,561 health posts in the country (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Although the socio-demographic index and life expectancies improved and age standardized all-cause death rates declined in the country over a period of three decades (between 1990 to 2019), regional disparities still remain high. Life expectancy has increased from 46.91 years in 1990 to 68.84 years in 2019. The highest death rate was in Afar, at 1353.38 per 100,000 while the lowest was in Addis Ababa compared to other regions (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The burden of both communicable and non-communicable diseases is high in the country (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Design and Sampling\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study was based on community-based cross-sectional design and took advantage of national household data that were representative of the country. The survey was conducted across ten regions and two city administrations between September 27 and December 20, 2022. Data collection in the eleventh region, i.e., Tigray region was carried out separately from December 28, 2023 to February 14, 2024 due to the security problem in the region. A two-stage stratified cluster sampling method was employed to select the households, and a total of 147,602 enumeration areas (EAs) obtained from the Ethiopian Central Statistical Service (CSS) were accounted for selecting the study enumeration areas. Proportional allocation to size was used to select study enumeration areas, considering the Urban and rural proportions in each region. Consequently, a total of 442 enumeration areas (172 urban and 270 rural areas). Logistical constraints prevented access to one enumeration area, and 441 enumeration areas ended up being included in the survey. The Tigray region, which was initially excluded due to security reasons, was later included when the situation was restored to normalcy, and 55 additional enumeration areas were identified. From each enumeration area, a total of 25 households were randomly selected.\u003c/p\u003e \u003cp\u003eIn the second phase, the simple random sample of each enumeration area was obtained by drawing 22 households, except in Tigray, where the number of households per enumeration area was between 16 and 26, depending on the accessibility of the field. The sample finally had 9,157 households with complete interview in 11 regions and two city administrations. The sampling weight was calculated to balance the selection probabilities, non-response, and post-stratification, which, in turn, allowed making an inference about the national, regional, and urban-rural strata. The detailed calculations and methodology of the sampling procedures are thoroughly explained in the National Health Equity Survey (NHES) report (ephi.gov.et/wp-content/uploads/2025/04/NHES2022_23_ETHfinalreport_I_azHSRDEPHI.pdf).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Sources\u003c/h2\u003e \u003cp\u003eThe NHES database includes geo-referenced, household-level data that describes socio-demographic factors; health services use, and access and equity perceptions. The sample of analysis comprised 9,157 households, which had sufficient statistical power to conduct a multilevel analysis. The area of representativeness was maintained through the implementation of the sampling weight, which was adjusted to the chosen selection probabilities, non-response, and post-strata adjustments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Collection Procedures\u003c/h2\u003e \u003cp\u003eData were collected through a face-to-face interview by trained data collectors with an expert of the health office, nursing, and laboratory professionals. Pretested structured questionnaires, were used to collect the socio-demographic and health-seeking behavioral characteristics of the participants. All the questionnaires were adapted from the Ethiopian Demographic and Health Survey (EDHS) and the World Health Organization equity modules (ephi.gov.et/wp-content/uploads/2025/04/NHES2022_23_ETHfinalreport_I_azHSRDEPHI.pdf).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSource population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll household heads in Ethiopia who were aged 18 years and above, permanent residents and with women in the ages of 15 to 49 years in the household.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll household heads in the country who were aged 18 years and above, permanent residents and with women in the ages of 15 to 49 years in the households and included in the study.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInclusion and exclusion criteria\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cb\u003eInclusion criteria\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eThe questions used to determine eligibility of participants included household heads or their spouses who satisfied the following criteria: 18 years of age and above, permanent residents; women between the ages of 15 and 49 years. Households that had incomplete interview data or were missing GPS coordinates, or left out important variables were not included in the analytic sample.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll household heads in the country who were aged 18 years and above, who were not permanent residents and have no women in the ages of 15 to 49 years in the household and who were not able to respond to the questions as the result of serious illness during the survey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Variables and Measurements\u003c/h2\u003e \u003cp\u003eThe main outcome variable of this study was the health seeking behavior which has been defined as any action performed by individuals to search for a remedy due to the manifestation of symptoms for self-perceived health problems or illness (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Thus, the dependent variable was treatment seeking behavior coded as 1 if the household head claims sought treatment to her/his recent perceived morbidity or 0 otherwise. Exposure variables include the different socio-economic and demographic variables such as region, age, gender, marital status, religion, education, occupation, residence, wealth quintile, family size, ownership of agricultural land, ownership of bank account, safety net beneficence, enrollment in community-based health insurance and ownership of dwelling house. The level of education was categorized as No education, Primary (1-8grades), Secondary (9-12grades), Technical/vocational training, and Higher education. Age of the heads was categorized as 18\u0026ndash;24 years, 25\u0026ndash;35 years, 36\u0026ndash;49 years, 50\u0026ndash;60 years and above sixty years. Marital status of household heads was also categorized as single, co-habituating, married, widowed, divorced/separated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Data Quality Assurance\u003c/h2\u003e \u003cp\u003eThe questionnaires were initially prepared in English and translated into five local languages, such as Amharic, Afaan Oromo, Tigrinya, and Somali. The data collectors used the translated tool for data collection, and the CSPro software was used for data collection purposes. Eight days of training were provided for data collectors and supervisors, and a pilot test was conducted before the actual data collection period. Regular supervision, spot checking, and daily feedback and back-checks were conducted by the supervisors, regional and central coordinators. In addition, reconciled duplicate household entries and promoted the safe transmission of data, which was done using the Internet File Streaming System (IFSS). The encrypted surveys were sent to the server of the Ethiopian Public Health Institute (EPHI), enhancing the internal validity of the data on health-seeking behavior and predictors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Data Management and analysis\u003c/h2\u003e \u003cp\u003eSurvey weights were applied to ensure nationally representative estimates. The descriptive statistics, such as frequency with percentages and mean with standard deviation, were used to describe the household characteristics, perceived morbidity, and treatment seeking behavior. Multi-stage sampling and unequal probabilities of selection to fit the complicated survey design used sampling weights in all analyses and determined weighted frequencies and weighted means to provide nationally representative estimates and correct design-induced variance inflation.\u003c/p\u003e \u003cp\u003eBi-variable logistic regression analyses were conducted to see the association between dependent variable and independent variables and determine variables to be included in the multivariable analysis. The variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in the bi-variable analysis were considered for building the final model. Mixed effects logistic regression is used to model binary outcomes (like yes/no or success/failure) when the data is clustered or hierarchically structured. Since the outcome variable in our study is binary, i.e., sought treatment or not to their perceived morbidity and the data is clustered or hierarchically structured in which zone is nested in region and woreda is nested in zone we fitted mixed effects logistic regression to determine predictors of household heads treatment seeking behavior. Model diagnostics were included as the likelihood ratio tests of a nested model comparison and the analysis of the extracted residuals to identify the goodness-of-fit testing. Multicollinearity was checked through the Variance inflation factor and the pairwise correlation matrix, using the ordinary least squares method. Consequently, variables with VIF\u0026thinsp;\u0026gt;\u0026thinsp;10 and the pairwise correlation\u0026thinsp;\u0026gt;\u0026thinsp;0.8 were excluded. The final optimal mode was selected based on the lower value of AIC and BIC, and variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the final model were considered as significant predictors. The estimated population parameters were reported and interpreted as adjusted odds ratios (AORs) with 95% confidence intervals (CIs). All the analysis were done using Stata version 14.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEthical considerations\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The study was conducted according to the principles of the Declaration of Helsinki. Ethical and scientific clearance was obtained from Ethiopian Public Health Institutional Review Board (IRB). And then copy of the ethical clearance certificate was sent to each region, and letter of cooperation was also sent and communicated to regions, city administrations, Zones, Woredas and Kebeles up on which successful cooperation and support had been obtained from the respective bodies. The basic ethical principles of autonomy, confidentiality, benefits and no harms were thoroughly examined. To safeguard the autonomy of the study participants, objectives of the research were clearly communicated and an informed, voluntary, written and signed consent were obtained prior to data collection. With regard to maintaining anonymity and confidentiality, names of the participants were not mentioned in the questionnaires and there was no way to identify any participant by name, except by research team. Privacy of study participants was maintained during the interview. No person had access to the information collected from the study participants except the research team. Furthermore, the participants were informed that they have the right to refuse taking part in the study or discontinue at any stage of the interview. The study participants involved in this study were offered valuable information on proper medical treatment seeking behavior. Those who were found seek during the survey referred to the nearby health facility. The study did no harm that should be declared, except for consuming the participants\u0026rsquo; valuable time.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003eSocio-Economic and Demographic Characteristics of the Study Participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOf the total household heads (9157) included in the study, 2030 (18.02%) experienced at least one perceived morbidity in the past 12 months prior to the survey date. About 3621 (27.66%) study participants were urban dwellers while 5536 (72.34%) were rural residents. About 85.82% of household heads fall in the age category of 25 to 49 years with mean age of 36.85 years and SD\u0026thinsp;\u0026plusmn;\u0026thinsp;9.47 years. Majority of the respondents were males (88.6%) and married (94.8%). About 42.8% household heads were illiterate and 35.4% primary level educated while nearly half of household heads (51.6%) were employed in farmer/pastoralists and more than half (58.11%) of the household heads had family size four and more than four family members. About 4248(58.11%) had agricultural land, 4713(51.82%) had Bank Account, 872(6.11%) safety net beneficiary, 2813(50.50%) were enrolled to community-based health insurance, 6240(74.06%) had own dwelling house, 793(8.31%) free of charge/subsidized, 989(5.58%) rented from kebele/Agency, 1110(11.87%) rented from individuals and 25(0.18%) other types of dwelling houses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-Economic and Demographic Characteristics of the household heads in Ethiopia 2022/23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted proportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthiopian Somali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenishangul Gumuz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth west-Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGambela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHarari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAddis Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDire Dawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18_24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25_35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36_49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50_60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-habitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary(1-8grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary(9-12grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical/Vocational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGO employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerchant/Trader\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer/Pastoralist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomemaker/Housewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaborer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe household heads were asked whether they encountered perceived morbidity in the past 12 months prior the survey date. Accordingly, about 2030 (18.02% with 95%CI: 1.77, 1.79) household heads reported perceived morbidity in the last 12 months prior to the survey date. There was disparity in the level of reported perceived morbidity between urban and rural areas., i.e., 776 (16.21%) urban and 1254(18.71%) rural household heads reported experiencing at least one perceived morbidity in the last 12 months prior to the survey date. About 775(14.23%) household heads with less than four family members and 1255(20.99%) with four and above four family members (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;69.80, P-value\u0026thinsp;=\u0026thinsp;0.000); 1052(19.88%) who own agricultural land and 978(15.44%) who had no agricultural land (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;29.73, P-value\u0026thinsp;=\u0026thinsp;0.011); 1018(18.05%) who had Bank Account and 1012(17.98%) who had no Bank Account (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.01, P-value\u0026thinsp;=\u0026thinsp;0.960); 576(20.05%) who enrolled to community based health insurance and 1454(15.94%) who were not enrolled to community based health insurance (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;26.22, P-value\u0026thinsp;=\u0026thinsp;0.006); 305(35.52%) who were beneficiaries of safety net program and 1725(16.88%) who were not beneficiaries of safety net program (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;123.58, P-value\u0026thinsp;=\u0026thinsp;0.000); 1443(19.29%) who had own dwelling houses, 158(12.40%) who own houses free of charge/subsidized, 250(17.81%) who own houses rented from kebele/Agency, 170(13.81%) who own houses rented from individuals and 9(41.16%) who own other types of houses (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;42.41, P-value\u0026thinsp;=\u0026thinsp;0.015); from those household heads who are less than two hours walking distance from nearest health facility 5978(19.05%), from those from two to five hours walking distance 394(37.60%), from those who at walking distance of above five hours 122(23.84%) and from those who don\u0026rsquo;t know distance to the nearest health facility 2663(10.71%) (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;265.90, P-value\u0026thinsp;=\u0026thinsp;0.000) reported experienced perceived morbidity in the 12 months prior to the survey date (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelf-Reported Perceived Morbidity by Background Characteristics of Household Heads in Ethiopia 2022/23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eExperienced perceived morbidity in the last 12 months prior to the survey date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChi-square(X\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAge of Household Heads\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18_24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91(21.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e313(78.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e404(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e20.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25_35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e854(15.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3523(84.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4377(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36_49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e823(19.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2653(80.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3476(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50_60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198(24.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e509(75.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e707(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64(24.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129(75.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e193(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1666(17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5987(82.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7653(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e363(25.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1140(74.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1503(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(38.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(61.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e6.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-habitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(19.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(80.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1875(18.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6695(81.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8570(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(16.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196(83.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(17.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189(82.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e886(18.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3038(81.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3924(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e14.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e577(19.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1596(80.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2173(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e554(16.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2435(83.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2989(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(7.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51(92.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(51.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(48.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e797(19.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2568(80.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3365(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e18.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary (1-8grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e683(18.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2440(81.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3123(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary(9-12grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e306(15.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1168(84.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1474(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical/vocational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74(12.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e329(87.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e403(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169(17.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e622(82.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e791(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164(13.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e699(86.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e863(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e29.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169(25.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e545(74.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e714(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGO employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21(18.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(81.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerchant/Trader\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145(16.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e527(83.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e672(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer/Pastoralist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e892(19.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2835(80.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3727(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomemaker/Housewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e443(15.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1881(84.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2324(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(25.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(74. 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaborer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100(11.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e273(88.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e373(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69(23.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228(76.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(20.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(79.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e376(35.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e704(64.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1080(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e100.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117(18.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e516(81.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e633(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194(23.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e720(76.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e914(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117(11.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e838(88.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e955(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthiopia Somali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113(28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311(72.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e424(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenishangul Gumuz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48(7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e660(92.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e708(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157(18.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e654(81.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e811(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185(26.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e539(73.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e724(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth west-Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108(14.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e593(85.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e701(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGambela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281(49.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257(50.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e538(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHarari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38(11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e361(88.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAddis Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171(23.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e565(76.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e736(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDire Dawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125(20.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e409(79.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e534(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e437(17.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1396(82.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1833(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e1.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e480(20.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1350(79.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1830(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e376(16.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1456(83.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1832(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e380(15.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1454(84.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1834(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e357(18.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1471(81.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1828(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e776(16.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2845(83.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3621(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1254(18.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4282(81.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5536(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHealth Care Seeking Behaviors of the Household Heads by Background Characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOf the total 2030 household heads who reported perceived morbidity in the last 12 months prior to the survey date, 1793 (89.4%) (95%CI: 3.76, 3.80) sought treatment to their recent perceived morbidity while 237(10.6%) household heads did not seek treatment to their recent perceived morbidity. About 688(88.75%) household heads with family size less than four members and 1105 (89.82%) with family members four and above four (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.560, P-value\u0026thinsp;=\u0026thinsp;0.650); 952 (90.80%) household heads who own agricultural land and 841(87.02%) household heads with no agricultural land (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;7.084, P-value\u0026thinsp;=\u0026thinsp;0.157); 935(91.95%) household heads with Bank Account and 858(86.74%) household heads with no Bank Account (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;14.576, P-value\u0026thinsp;=\u0026thinsp;0.035); 259(85.95%) household heads who were beneficiaries of safety net and 1534(89.93%) household heads with no Bank Account (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;3.599, P-value\u0026thinsp;=\u0026thinsp;0.327); 527(92.64%) household heads who enrolled to community based health insurance and 1266(85.35%) HH heads with no community based health insurance (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;28.071, P-value\u0026thinsp;=\u0026thinsp;0.000); 1299(90.13%) household heads with own dwelling house, 131(86.91%) household heads owning Subsidized/Free of charge house, 217(86.80%) household heads owning houses rented from Kebele/Agency, 140(87.09%) household heads owned house rented from individuals, 6(81.15%) household heads owned other types of houses (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.082, P-value\u0026thinsp;=\u0026thinsp;0.732); household heads who rated their health condition as very poor 36(82.18%), poor 305(81.37%), Neutral 290(89.39%), Good 1040(91.81%), Very Good 122(94.55%) (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;41.202, P-value\u0026thinsp;=\u0026thinsp;0.021); household heads who are at walking distance of less than two hours from the nearest health facility 1379(91.08%), those who are at walking distance from two to five hours 114(84.46%), who are at walking distance of above five hours 39(90.44%) and those who don\u0026rsquo;t know the distance from nearest health facility 261(87.15%) (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;13.681, P-value\u0026thinsp;=\u0026thinsp;0.201) sought treatment to their recent perceived morbidity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment Seeking Behavior of Household Heads to their Perceived Morbidity by Background Characteristics in Ethiopia 2022/23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eTreatment seeking of household heads to the recent perceived morbidity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChi-square (X\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal, n (weighted%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAge of Household Heads\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18_24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83(93.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e20.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25_35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e769(91.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85(8.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e854(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36_49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e713(85.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110(14.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e823(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50_60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173(90.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(9.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e198(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55(96.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(3.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1488(90.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178(9.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1666(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305(83.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(16.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e363(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(97.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e6.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-habitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1662(89.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213(10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1875(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73(81.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(18.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47(96.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e774(88.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112(11.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e886(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e14.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e543(93.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(6.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e577(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e467(88.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(11.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e554(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(58.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(41.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Status of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e682(86.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115(13.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e797(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e18.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary(1-8grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e614(92.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69(7.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e683(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary(9-12grades)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e273(91.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(8.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e306(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical/Vocational Training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71(90.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(9.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153(89.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(10.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e169(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGov\u0026rsquo;t employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152(95.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(4.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e164(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e29.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145(89.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(10.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e169(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGO employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(81.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(18.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerchant/Trader\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136(95.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(4.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer/Pastoralist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e812(90.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(9.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e892(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomemaker/Housewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e371(84.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(15.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e443(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(96.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaborer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86(96.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(3.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(77.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(22.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(89.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(10.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310(81.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(18.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e376(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e100.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"12\" rowspan=\"13\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114(97.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182(92.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(7.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(89.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(10.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthiopia Somali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72(62.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(37.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenishangul-Gumuz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46(95.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143(91.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(8.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177(95.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(4.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth west-Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101(92.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(7.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGambela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268(93.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(6.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e281(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHarari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(83.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(16.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAddis Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144(83.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(16.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDire Dawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100(80.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(19.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e385(88.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(11.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e437(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e1.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e426(90.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(9.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e480(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e332(89.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e376(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e337(90.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(9.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e380(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313(89.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(10.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e357(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e683(88.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93(11.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e776(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1110(89.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144(10.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1254(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRespondents were asked to rate their health status and tell how they feel about their health situation. As the result, 144(1.87%) replayed their health situation was very poor, 773(10.26%) poor, 1202 (11.82%) neutral, 5872(61.23%) good and 1166(14.83%) very good. From a total of 1768 household heads who get treatment for their recent illness, 39(0.88%) from home-based care, 61(1.46%) from local drug venders/pharmacy, eight (0.22%) from traditional healers and 1656(97.43%) get treatment from modern health facilities (i.e., private health facility 445 (21.61%), government hospital 374(16.30%), government health center 741(57.90%), government health post 81(1.28%), NGO health facilities 15(0.34%)) and the remaining four (0.01%) from other sources.\u003c/p\u003e \u003cp\u003eThe respondents were also asked about the quality of care they received from the health facility where they received treatment to the recent perceived morbidity. Accordingly, 28(2.09%) perceived to be very poor, 212(12.51%) as poor, 278(10.47%) neutral, 1035(66.51%) perceived as good and 107(8.42%) perceived to be very good. Further the respondents were asked the health professionals who checked their perceived morbidity and as the result 523(22.87%) Doctor, 620(24.55%) Nurse, 15(1.42%) midwife, 218(18.26%) health officer, 21(0.53%) HEW, 3(0.18%) other and 260(32.34%) they do not know the health professional who checked their perceived morbidity.\u003c/p\u003e \u003cp\u003eThe question on the nearest health facility to the household was also asked and as the result 2612 (25.07%) government health post, 4978 (64.50%) government health center, 938 (5.53%) government hospital, 30 (0.43%) NGO health facilities and 599 (4.47%) private health facilities.\u003c/p\u003e \u003cp\u003eThose household heads who reported did not seek treatment to their perceived morbidity were further asked their reasons for not seeking treatment. As the result majority 109 (46.19%) lack of finance and about eight (3.39%) reported health facility far as the reasons for not seeking treatment to their perceived morbidity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors Associated with Household heads\u0026rsquo; health seeking behaviors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the bivariate analysis, sex of household head, region, family size, ownership of agricultural land, safety net beneficence, enrollment to community-based health insurance, and self-rated health status were associated with health seeking behavior at P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 and entered into multivariable analysis.\u003c/p\u003e \u003cp\u003eModel fitness to the data was assessed using log likelihood ratio test, AIC and BIC. As the result a good model with log likelihood ratio of chi2\u0026thinsp;=\u0026thinsp;76.33 with P-value\u0026thinsp;=\u0026thinsp;0.000; AIC\u0026thinsp;=\u0026thinsp;8222.092 and BIC\u0026thinsp;=\u0026thinsp;8393.016 was fitted.\u003c/p\u003e \u003cp\u003eIn the final model, self-rated health status of household head, safety net utilization, ownership of agricultural land, sex of household head and region were found to be significantly associated with household heads\u0026rsquo; treatment seeking to the recent perceived morbidity. As can be seen in the final model the zonal variance is 0.08 while woreda level variance is 0.69 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Intraclass correlation (ICC) for Zone was 0.0194955 with standard error (0.0154332) and confidence interval (95%CI: 0.0040689, 0.0882278) and for Woreda it was 0.1891751 with standard error 0.0272165 and confidence interval (95%CI: 0.1414685, 0.2483164) which is indicating the proportion of variance accounted by Zone was about two percent while this proportion for Woreda was 18.92%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultilevel Mixed Effects Logistic Regression Model Predicting Treatment Seeking Behavior of Household Heads in Ethiopia 2022/23\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd.Err\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTigray (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35, 0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33, 0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18, 0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthiopia Somali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21, 0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenishangul-Gumuz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09, 0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37, 0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40, 0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth west-Ethiopia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15, 0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGambela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.07, 3.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHarari\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19, 0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAddis Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59, 1.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDire-Dawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53, 1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00, 1.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily size of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than four members (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour \u0026amp; above four members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99, 1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOwnership of Agricultural land\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave no agricultural land (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave agricultural land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.37, 1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSafety Net Utilization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot utilizers (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtilizers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27, 1.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnrollment to CBHI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Enrolled to CBHI (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnrolled to CBHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95, 1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated Health Status of Household Heads\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.53, 3.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.28, 7.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.21, 3.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.55, 2.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good (RC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07, 0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ezone var(_cons)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02, 0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ezone\u0026thinsp;\u0026gt;\u0026thinsp;woreda var(_cons)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48, 0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eLR test vs. logistic model: chi2(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;76.33 Prob\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u0026thinsp;=\u0026thinsp;0.0000\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRC\u0026thinsp;=\u0026thinsp;Reference Category; AOR\u0026thinsp;=\u0026thinsp;Adjusted Odds Ratio; CBHI\u0026thinsp;=\u0026thinsp;Community Based Health Insurance; Std.Err\u0026thinsp;=\u0026thinsp;Standard Error; SNNP\u0026thinsp;=\u0026thinsp;Southern Nations, Nationalities and Peoples Regional State\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eLess than twenty percent (18.02%) of household heads included in the study reported suffered from some recent perceived morbidity. This observed burden of self-perceived morbidity was comparable with previously reported value in Addis Zemen, North-Western Ethiopia in which 18% of study participants reported illness with recall period of four weeks (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The current finding is also comparable to the findings by Dodd et al., 2016 in India in which 22.3% of study participants reported suffered from self-reported morbidity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A study in Malaysia done on adults using national data also corroborates our finding with16.1% reported perceived morbidity (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). However, the finding of the current study is lower than the finding by Feyisa et al., 2020 in which 75% of the study participants reported they experienced morbidity at least once in the year before the interview (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). This difference could be due to the difference in the study population included in the two studies. In a study by Feyisa et al., 2020 the study participants were elderly aged 60 years and above while the study participants to the current study were adults aged 18 years and above. Another study in Esera District, SNNPR of Ethiopia indicated that 85.6% household heads reported at least one family member experienced perceived morbidity at least once in two months prior to the survey date which is higher than the current finding (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This difference could be due to the fact that in our study the information was collected about the household heads while in the study of Begashaw et al., 2016 the information was collected about the family members.\u003c/p\u003e \u003cp\u003eHigher proportion of women reported self-perceived morbidity than men, the finding which is consistent with previous findings (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Other study conducted in Southern Brazil also showed that women were more likely to report morbidity than men (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). A study by Paul and Singh, 2017 in India using longitudinal data showed that self-reported morbidity was persistently higher among the female population compared to the male population irrespective of the types of morbidities reported (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe proportion of household heads who suffered from perceived morbidity was higher for rural residents (18.71%) compared to urban dwellers (16.21%), the finding which corroborates with the findings in other studies (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The current finding is different from the findings by Paul and Singh, 2017 in India in which urban residents reported higher prevalence of self-reported morbidity as compared to their rural counterparts for most of the morbidities (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe have assessed health seeking behavior of household heads for their perceived morbidity and found that 89.4% sought treatment to their recent perceived morbidity. This finding is higher than the findings of other studies (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This could be due to the fact that our current study covers the whole country and the study was conducted recently compared to the two studies and hence recent service expansions and changes to treatment seeking behaviors could account for the variation. However, the current finding is more or less comparable to the findings of systematic review by Haridoss et al., 2025 in which 72.72% (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) and a study by Belachew et al., 2025 in Bahir Dar, Ethiopia in 79.3% study participants (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) sought treatment for their existing health conditions. Our finding is also comparable to the findings of Kabir et al., 2025 in Bangladesh in which 80% study participants sought treatment to their recent perceived morbidity (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere was gender disparity in treatment seeking for their perceived morbidity. Higher proportion of men (89.3%) reported sought treatment to their recent perceived morbidity compared to women (84%) counterparts. In multilevel analysis too, men were found to be 1.2 times more likely to seek treatment to their perceived morbidity compared to their counterpart women. This finding is comparable to the finding of a study by Belachew et al., 2025 in older adult men were found higher treatment seekers compared to their counterpart older adult women (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This could be due to the fact that in the case of Ethiopia, men are usually bread winners and hence they could have better opportunity to get access to financial resource to seek treatment to their perceived morbidity. Our finding is in contrary to the findings by Wang et al., 2008 in which women were found more likely to seek treatment to their illness compared to men (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The current finding is also contrary to the findings of Altameemi et al., 2024 in which women were found to be 1.3 times more likely to sought treatment compared to men (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study majority of respondents (93.67%) sought treatment to their recent perceived morbidity from modern health facilities, mostly from government health facilities which is contrary to the findings by Haridoss et al., 2025 in India in which private health facilities were preferred over government facilities (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This could be due to the fact that cost of treatment to illnesses would be lower in government health facilities compared to private health facilities in the case of Ethiopia. In the current study, financial constraints and illness not considered serious (together constituted 76.69%) were the major barriers for household heads who reported experienced perceived morbidity in the past year prior to the survey date but didn\u0026rsquo;t seek treatment to their perceived morbidity which is consistent with the findings by Haridoss et al., 2025 in India (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Our finding is also consistent with the finding by Rahman et al., 2017 in Jorhat district of India in which for 43.25% of study participants who didn\u0026rsquo;t seek treatment to their illness the major impediment was financial constraint (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). A study in Bahir Dar, Ethiopia also corroborates our finding indicating that financial independence of study participants was associated with higher treatment seeking behavior (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the multilevel analysis region was significantly associated with treatment seeking behavior of household heads to their recent perceived morbidity. Afar, Amhara, Oromia, Ethiopia Somali, Benishangu-Gumuz, SNNPR, Sidama, South west-Ethiopia, Harari, and Dire Dawa were found to be less likely to seek treatment compared to Tigray Regional state which was taken as reference category. However, Gambela Regional State was 2.7 times more likely to seek treatment to recent perceived morbidity compared to Tigray Regional State. This variation could be due to the variations in health services coverage and quality of services and the variation in the level of health literacy among the regions. This finding is in line with the finding in India in which health care treatment seeking behavior varied across various regions of the country, particularly in eastern, north-eastern and western regions of the nation (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Our finding is also concurrent to the finding by Kamal et al., 2025 in Pakistan in which the health seeking behavior of mothers varied across the regions of the country (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSupporting prior evidences (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) our study specified that ownership of agricultural land was significantly associated with treatment seeking to their recent perceived morbidity in which household heads who own agricultural land were 1.6 times more likely to seek treatment to their recent perceived morbidity compared to household heads who had no agricultural land.\u003c/p\u003e \u003cp\u003eThose household heads who were beneficiary of safety net were 1.5 times more likely to seek treatment to their recent perceived morbidity compared to household heads who were not beneficiary of safety net. This finding is comparable with other findings in which social protection schemes (both productive safety net program and the community-based health insurance scheme) enhanced the use of modern healthcare (\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). A study by Tossou, 2025 in Togo also indicated the positive indirect effect of social safety net on beneficiary households with respect to healthcare utilization (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSelf-rated health status of household heads was significantly associated with treatment seeking behavior of household heads. Those household heads who rated their health status as very poor were 2.4 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health condition as very good which was reference category. Those household heads who rated their health condition as poor were 5.6 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health status as very good. Those household heads who rated their health condition as good were 1.9 times more likely to seek treatment to their perceived morbidity compared to their counterparts who rated their health condition as very good. These finding is comparable to the study by Mohan et al., 2025 in Malaysia in which study participants who rated their health status from poor to very poor were 3 times more likely to seek care to their morbidity compared to their counterparts who rated their health status from good to excellent (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Similarly, a study by Noh et al., 2022 in Malaysia also indicated that the study participants who rated their health as poor to very poor were 2.9 times more likely to seek treatment than those who rated their health from good to excellent (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). A study in Bahir Dar, Ethiopia also substantiates our finding in which study participants who rate their health status as poor were higher in seeking treatment to their recent illness compared to those study participants who rated their health status as good (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations of the study\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study has certain limitations which are inherent to the study design. It was a cross-sectional self-reported study with recall period of 12 months in which the study participants could forget some morbidities and treatment seeking behavior which may underestimate the level of morbidity in the population. Another limitation inherent to cross-sectional surveys is the difficulty to establish causal relationship. Data on perceived morbidity and treatment seeking behavior was collected only for the household heads and information about family members was not collected which might have again underestimated the prevalence of perceived morbidity in the population.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe study revealed that majority of the participants sought treatment from health facility for their perceived morbidity. However, there were significant socio-economic and demographic and regional disparities in health seeking behavior. The factors that influence the health seeking behavior of population are unique for each socio-economic and demographic and regional category. Thus, the study findings underscore the importance of targeted interventions to address inequalities and identified barriers to enhance equitable health care utilization across the study participants’ characteristics and regions. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGovernmental and non-governmental organizations working on the wellbeing of the population could work on addressing regional and socio-economic disparities, empowering women, strengthening social protection schemes (Community Based Health Insurance and Productive Safety Net) and focusing on the rural and vulnerable population especially regarding improving access to healthcare services as well as their knowledge and literacy on seeking proper medical care through mass media approach.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData Sharing Statement\u003c/p\u003e\n\u003cp\u003eData analyzed and materials used for this article are available with the corresponding author and can be obtained on request.\u003c/p\u003e\n\u003cp\u003eEthical Approval and Consent\u003c/p\u003e\n\u003cp\u003eEthical approval was secured from Institutional Review Board (IRB) of Ethiopian Public Health Institute. Informed, voluntary, written and signed consent was obtained from the study participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge Ministry of Health for the financial and technical support in all phases of the survey. We would like to thank regional state Health Bureaus/Regional Health Institutes for their follow up for the success of the survey process. Our thanks also extend to the study participants, supervisors and data collectors for their kind cooperation.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declared that they have no conflicts of interest for this work.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research has been funded by Ministry of Health.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eDesalew Z, Aderajew MG, Hiwot A, Tsegaye G, Desallegn A, Arega Z, Girum T, Yitayh L, Weldemariam B, Kelem BA, Akberet L, Afewerk A, Ashenif T, Gebeyaw M, Wogayehu T, Tesfaye D, Senait A, Hanim T, Fikreselassie G, Daniel AC, Seboka A, Tefera T, Mesay H and Getachew T, all these authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising and critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSanjiv Kumar PG. Health Promotion: An Effective Tool for Global Health. Indian Journal of Community Medicine. 2012;Vol 37/Issue 1/.\u003c/li\u003e\n \u003cli\u003eChi-Horng LiaoID SB. Success factors of health promotion: Evaluation by DEMATEL and M-DEMATEL methods\u0026mdash;A case study in a non-profit organization. PLoS ONE 2021;16(12): e0260801.\u003c/li\u003e\n \u003cli\u003eNilanjana Ghosh IC, Manasi Chakraborty, Romy Biswas. Factors affecting the healthcare-seeking behavior of mothers regarding their children in a rural community of Darjeeling district, West Bengal. International Journal of Medicine and Public Health | Jan-Mar 2013 2013;Vol 3 (Issue 1).\u003c/li\u003e\n \u003cli\u003eAsm Shahabuddin CNs, The\u0026acute;r\u0026egrave;se Delvaux, Malabika Sarker, Alexandre Delamou, Azucena Bardajı, Jacqueline E. W. Broerse, Vincent De Brouwere. Exploring Maternal Health Care-Seeking Behavior of Married Adolescent Girls in Bangladesh: A Social-Ecological Approach. PLoS ONE. 2017;12(1): e0169109.\u003c/li\u003e\n \u003cli\u003eBeshadu Bedada Feyisa SFD, Gosaye Mekonen Tefera,. Self-Reported Morbidity and Health-Seeking Behavior and its Predictors Among a Geriatric Population in Western Ethiopia: Community-Based Cross-Sectional Study. International Journal of General Medicine. 2020;13 1381\u0026ndash;93.\u003c/li\u003e\n \u003cli\u003eBayu Begashaw FT, Hailay Abrha Gesesew. Health Care Seeking Behavior in Southwest Ethiopia. PLoS ONE. 2016;11(9).\u003c/li\u003e\n \u003cli\u003eShahinur Akter TA, Md. Habibur Rahman, Md. Firoz Raihan. Morbidity Patterns and Determinants of Healthcare‑Seeking Behavior Among Older Women in Selected Rural Areas of Bangladesh. Dr Sulaiman Al Habib Medical Journa. 2023;5:70\u0026ndash;79.\u003c/li\u003e\n \u003cli\u003eMadhumitha Haridoss DN, Shiny P. John, V. V. Anantharaman, Raji Rajesh Lenin, Rajiv Janardhanan. Health-seeking behavior and its determinants for non-communicable diseases in India - a systematic review and meta-analysis. Front Public Health 2025;13:1580824.\u003c/li\u003e\n \u003cli\u003eJohanna NSGAS-FRWSN. The accuracy of self-reported health behaviours and risk factors relating to cancer and cardiovascular disease in the general population: a critical review. American Journal of Preventive Medicine. 1999;17(3):211\u0026ndash;29.\u003c/li\u003e\n \u003cli\u003eBhutto AQ NN. Health-seeking behavior of people living with HIV/AIDS and their satisfaction with health services provided at a tertiary care hospital, Karachi, Pakistan. Eastern Mediterranean Health Journal. 2017;Vol. 23, No. 1.\u003c/li\u003e\n \u003cli\u003eGwatkin DR. Health inequalities and the health of the poor: What do we know? What can we do? Bulletin of the World Health Organization 2000;78 (1).\u003c/li\u003e\n \u003cli\u003eWhitehead M. THE CONCEPTS AND PRINCIPLES OF EQUITY AND HEALTH. International Journal of Health Services. 1992;Vol. 22, No. 3:429-45.\u003c/li\u003e\n \u003cli\u003eSRINIVAS GOLI DN, ANU RAMMOHAN, T. V. SEKHER, DEEPSHIKHA SINGH. DECOMPOSING THE SOCIOECONOMIC INEQUALITY IN UTILIZATION OF MATERNAL HEALTH CARE SERVICES IN SELECTED COUNTRIES OF SOUTH ASIA AND SUB-SAHARAN AFRICA. J Biosoc Sci, . 2017;50,:749\u0026ndash;69.\u003c/li\u003e\n \u003cli\u003eSolomon Yimer CH-H, Tilahun Yimaldu, Gunnar Bjune. Health care seeking among pulmonary tuberculosis suspects and patients in rural Ethiopia: a community-based study. BMC Public Health. 2009;9:454.\u003c/li\u003e\n \u003cli\u003eMarinka van der Hoeven AK, Minrie Greeff. Differences in health care seeking behaviour between rural and urban communities in South Africa. International Journal for Equity in Health 2012;11:31.\u003c/li\u003e\n \u003cli\u003eAychiluhm SB, Gelaye, K. A., Angaw, D. A., Dagne, G. A., Tadesse, A. W., Abera, A., \u0026amp; Dillu, D. . Determinants of malaria among under-five children in Ethiopia: Bayesian multilevel analysis. BMC Public Health. 2020;20(1), 1468.\u003c/li\u003e\n \u003cli\u003eAshenif Tadele TT, Shegaw Mulu, Tamrat Awel, Tsedeke Mathewos, Dessalegn Melesse. National and subnational coverage and other service statistics for reproductive, maternal, newborn and child health using health facility data and surveys ETHIOPIA: Brief synthesis of the analyses. Countdown to 2030 / GFF / UNICEF / WHO workshop, Nairobi, Kenya. 2022.\u003c/li\u003e\n \u003cli\u003eMisganaw A. Progress in health among regions of Ethiopia, 1990\u0026ndash;2019: a subnational country analysis for the Global Burden of Disease Study 2019. Lancet 2022;399: :1322\u0026ndash;35.\u003c/li\u003e\n \u003cli\u003eWHO AR. Country Disease Outlook of Ethiopia. 2023.\u003c/li\u003e\n \u003cli\u003eTesfaye Falaha AW, Mengistu Meskele, Wolde Facha. Health Care Seeking Behaviour of Elderly People in Rural Part of Wolaita Zone, Southern Ethiopia. Health Science Journal. 2016;Vol. 10 No. 4: 14.\u003c/li\u003e\n \u003cli\u003eVineeta Shukla KR, Sinjita Dutta , Mausumi Basu. Self-Medication Practices and Health Seeking Behaviour among Residents of Selected Villages in A Block of West Bengal: A Mixed-Methods Study. Healthline Journal 2022;Volume 13 (Issue 1).\u003c/li\u003e\n \u003cli\u003eZein Ahmed Zein MF, Sirak Petras, Shimellis Alemayehu, Shumi Tala, Shiferaw Ayalew, Siyaum Tafese. PREVALENCE OF PERCEIVED MORBIDITY IN ADDIS ZEMEN TOWN, ETHOPIA. Ethiopian Journal of Health Development. 2017;2(1).\u003c/li\u003e\n \u003cli\u003eWarren Dodd NK, Sally Humphries, Matthew Little. Self-reported morbidity and health services utilization in rural TamilNadu, India. Social Science \u0026amp; Medicine. 2016;161:118-25.\u003c/li\u003e\n \u003cli\u003eSarah Nurain Mohd Noh SJ, Ee Hong Tan, Yeung R\u0026rsquo;ong Tan, Iqbal Ab Rahim The Health-Seeking Behavior among Malaysian Adults in Urban and Rural Areas Who Reported Sickness: Findings from the National Health and Morbidity Survey (NHMS) 2019. Int J Environ Res Public Health 2022;19. 3193.\u003c/li\u003e\n \u003cli\u003eERVIN TOCI GB, NAIM JERLIU, KRISTINE S\u0026Oslash;RENSEN, NASER RAMADANI, BAJRAMHYSA, HELMUTBRAND. Health literacy, self-perceived health and self-reported chronic morbidity among older people in Kosovo. Health Promotion International. 2014;Vol. 30 No. 3.\u003c/li\u003e\n \u003cli\u003eSuman Kanungo KB, Tanmay Mahapatra, Sanchita Mahapatra, Uchhal K. Bhadra, Kamalesh Sarkar. Perceived Morbidity, Healthcare-Seeking Behavior and Their Determinants in a PoorResource Setting: Observation from India. PLoS ONE 2015;10(5): e0125865.\u003c/li\u003e\n \u003cli\u003eM\u0026eacute;lusine Boon-Falleur BD, Coralie Chevallier. Does higher perceived risk of morbidity and mortality decrease risk-taking? R Soc Open Sci 2022;9: 220486.\u003c/li\u003e\n \u003cli\u003eRa\u0026uacute;l A. Mendoza-Sassi JUB. Gender differences in self-reported morbidity: evidence from a population-based study in southern Brazil. Cad Sa\u0026uacute;de P\u0026uacute;blica, Rio de Janeiro. 2007;23(2):341-6.\u003c/li\u003e\n \u003cli\u003eKalosona Paul JS. Emerging trends and patterns of selfreported morbidity in India: Evidence from three rounds of national sample survey. Journal of Health, Population and Nutrition 2017;36:32.\u003c/li\u003e\n \u003cli\u003eAmare Belachew NC, Nasser Bagheri, Richard Burns. Identifying the Factors That Drive Health Service Utilization Among Healthy and Non‐Healthy Agers in a Sample of Older Ethiopians: A Cross‐Sectional Study. Health Science Reports. 2025;8:e70351.\u003c/li\u003e\n \u003cli\u003eAshraful Kabir MNK, Baki Billah. Self- reported health complaints and healthcare- seeking behaviour among adult people in rural Bangladesh: results from a cross- sectional study. BMJ Open. 2025;15:e086324.\u003c/li\u003e\n \u003cli\u003eJianming Wang YF, Hongbing Shen, Biao Xu. Gender difference in knowledge of tuberculosis and associated health-care seeking behaviors: a cross-sectional study in a rural area of China. MC Public Health. 2008;8:354.\u003c/li\u003e\n \u003cli\u003eMohammed Mkhailef Hawi Al-tameemi KB, Yousef Moradi, Ghobad Moradi, Amjad Mohamadi-Bolbanabad. Insights into determinants of health-seeking behavior: a cross-sectional investigation in the Iraqi context. Front Public Health 2024;12:1367088.\u003c/li\u003e\n \u003cli\u003eSyeda Jesmin Rahman BRD, Gunjan Nath. Health seeking behavior of farming community in rural area of Titabor block in Jorhat district. nternational Journal of Community Medicine and Public Health. 2017;4(10):3854-8.\u003c/li\u003e\n \u003cli\u003eSwaroop VKKSKYVKTPGSMS. Socioeconomic and Geographical Inequities in Burden and Treatment seeking Behavior for Hypertension among Women in the Reproductive Age (15\u0026ndash;45 years) Group in India: Findings from a Nationally Representative Survey. Indian Journal of Public Health 2024;68(2):208-13.\u003c/li\u003e\n \u003cli\u003eAsifa Kamal GHS, Afrah Hafeez, Maryam Siddiqa, Charles Owens. Mapping Geographic Disparities in Healthcare Access Barriers Among Married Women in Pakistan: Evidence from a Nationally Representative Survey. Healthcare. 2025;13. 2448.\u003c/li\u003e\n \u003cli\u003eHiwot Tilahun DDA, Geta Asrade, Amare Minyihun, Yihun Mulugeta Alemu. Factors for healthcare utilization and effect of mutual health insurance on healthcare utilization in rural communities of South Achefer Woreda, North West, Ethiopia. Health Economics Review. 2018;8:15.\u003c/li\u003e\n \u003cli\u003eEssa Chanie Mussa TP, Gustavo Angeles, Martha Kibur, Frank Otchere, Amhara ISNP Evaluation Team. Impact of community-based health insurance on health services utilisation among vulnerable households in Amhara region, Ethiopia. BMC Health Services Research. 2023;23:55.\u003c/li\u003e\n \u003cli\u003eTadele Fentabil Anagaw EMM, Eyob Ketema Bogale , Eneyew Talie Fenta , Habitu Birhan Eshetu4, Natnael Kebede , Sintayehu Shiferaw Gelaw, Amare Zewdie, Tadele Derbew Kassie. Health-seeking behavior among noncommunicable disease patients globally, systematic review and meta-analysis. SAGE Open Medicine. 2023;11: 1 \u0026ndash;10.\u003c/li\u003e\n \u003cli\u003eTossou Y. Evaluation of the impact of social safety net program on health care utilization in Togo. Health Economics Review. 2025;15:19.\u003c/li\u003e\n \u003cli\u003eDevi Shantini Rata Mohan SJ, Adilius Manual, Nur Elina Abdul Mutalib, Sarah Nurain Mohd Noh, Iqbal Ab Rahim, Jabrullah Ab Hamid, Awatef Amer Nordin. Gender differences in health-seeking behaviour: insights from the National Health and Morbidity Survey 2019. BMC Health Services Research. 2025;25:900.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"perceived morbidity, treatment seeking, National Health Equity Survey ","lastPublishedDoi":"10.21203/rs.3.rs-8280763/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8280763/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-report is one of the easiest, cheapest and most widely used methods of collecting data about individuals’ health and risk factor status. Many health studies use self-reported data to assess the prevalence of given risk factors or health behaviors in the community. The objective of this study was to determine the level of perceived morbidity, treatment seeking behavior and associated factors using nationally representative self-reported morbidity data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was embedded from a community based, national representative survey which was conducted from September 27 and December 20, 2022 in ten regions and two city administrations. Data collection in the eleventh region, i.e., Tigray region, was carried out separately from December 28, 2023 to February 14, 2024, due to contextual constraints. \u0026nbsp;The survey covered 441 enumeration areas within 11 regional states and two city administrations. A two-stage stratified cluster sampling was employed to select the eligible households and a total of 9,157 household were selected. Data were collected through face-to-face interview with structured questionnaires. Descriptive statistics such as frequency with percentages and mean with standard deviations were employed to describe participants’ characteristics. Bivariate analysis was conducted to assess the association between treatment seeking behavior and independent variables. Mixed effects logistic regression was employed to determine predictors of treatment seeking behavior.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 2030 (18.02%) household heads experienced at least one perceived morbidity in the past 12 months prior to the survey date. Of these, 776(16.21%) were urban and 1254(18.71%) were rural residents. About 1793(89.4% with 95%CI: 3.76, 3.80) sought treatment to their perceived morbidity. In the multivariable analysis, Afar (AOR=0.47; 95%CI: 0.35, 0.64), Amhara(AOR=0.45; 95%CI: 0.33, 0.61), Oromia(AOR=0.26; 95%CI:0.18, 0.38), Ethiopia Somali(AOR=0.31; 95%CI: 0.21, 0.46), Benishangul-Gumuz (AOR=0.13; 95%CI: 0.09, 0.19), SNNPR(AOR=0.51; 95%CI: 0.37, 0.70), Sidama(AOR=0.59; 95%CI: 0.40, 0.87), South west-Ethiopia(AOR=0.23; 95%CI: 15, 35), Harari(AOR=0.29; 95%CI: 19, 45), and Dire Dawa(AOR=0.80; 95%CI: 0.53, 1.00) were found to be less likely to seek treatment to their perceived morbidity compared to Tigray regional state while Gambela was 2.7 (95%CI:2.07, 3.63) times more likely to seek treatment compared to Tigray regional state. Other factors associated with treatment seeking behavior were being male (AOR, 1.2; 95%CI: 1.00, 1.37), own agricultural land (AOR=1.6; 95%CI: 1.37, 1.80), safety net beneficiaries (AOR=1.5; 95%CI: 1.27, 1.86), self-rated health status (very poor, AOR=2.4; 95%CI: 1.53, 3.90; poor, AOR=5.6; 95%CI: 4.28, 7.44; Neutral, AOR=2.9; 95%CI: 2.21, 3.68; Good, AOR=1.9; 95%CI: 1.55, 2.40) showed statistically significant association.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study revealed that majority of the participants sought treatment from health facility for their perceived illness. However, there were significant disparities across the regions and participant characteristics. Thus, the study finding underscores the need for targeted interventions to address inequalities and identified barriers to enhance equitable health care utilization across the regions.\u003c/p\u003e","manuscriptTitle":"Exploring Self-Reported Morbidity, Health-Seeking Behavior and Associated Factors in Ethiopia: Evidence from National Health Equity Survey 2022/2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-05 09:34:40","doi":"10.21203/rs.3.rs-8280763/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-01-02T10:06:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-11T08:42:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T04:23:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-10T04:23:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-12-04T15:00:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ef35325-051b-474f-982a-25bd78a61e67","owner":[],"postedDate":"January 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T09:34:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-05 09:34:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8280763","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8280763","identity":"rs-8280763","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}